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Brain MR Images Classification for Alzheimer’s Disease
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    Alzheimer’s Disease (AD) is the most prevailing type of dementia. The prevalence of AD is estimated to be around 5% after 65 years old and is staggering 30% for more than 85 years old in developed countries. AD destroys brain cells causing people to lose their memory, mental functions and ability to continue daily activities. The findings of this study are likely to aid specialists in their decision-making process by using patients’ Magnetic Resonance Imaging (MRI) to distinguish patients with AD from Normal Control (NC). Performance evolution was applied to 346 Magnetic Resonance images from the Alzheimer's Neuroimaging Initiative (ADNI) collection. The Deep Belief Network (DBN) classifier was used to fulfill classification function. Weights were used to test the proposed method's recognition capacity, and the network was trained with a sample training set. As a result, this study offeres a new method for identifying Alzheimer's disease utilizing automated categorization. In tests, it performed admirably With 98.46% accuracy achieved for AD and NC studied classes when combining Gray Level Co-occurrence Matrix (GLCM) features with a DBN.

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Publication Date
Sat Jan 19 2019
Journal Name
Artificial Intelligence Review
Survey on supervised machine learning techniques for automatic text classification
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Publication Date
Mon Jan 01 2018
Journal Name
Lecture Notes Of The Institute For Computer Sciences, Social Informatics And Telecommunications Engineering
Sensor Data Classification for the Indication of Lameness in Sheep
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Publication Date
Tue Aug 02 2022
Journal Name
Dirasat: Human And Social Sciences
Denotation of Narrative Features in Television Advertising (A Semiotic Approach to Mr. President's Declaration)
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The research summarizes the knowledge of the dimensions and denotations of T.V advertisement; and its constituents for building it through the semiotic approach of an ad sample represented by the announcement of Zain Kuwait Telecom Company which carries the title "Mr. President" using Roland Barth's approach, starting with the designation, implicit, and linguistic reading to reach the narrative features and their denotations. That makes television advertising as a semiotic and pragmatic discourse in view of the still and motion picture with its efficiency and strength to inform and communicate. And what lies in it of aesthetic, artistic elements; informational and effective power in influencing the recipients by focusing on narratives and a

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
New vision of Mr. Abdul Mahdi Al-Muttafiqi in the light of unpublished documents
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New vision of Mr. Abdul Mahdi Al-Muttafiqi in the light of unpublished documents

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Publication Date
Sun Dec 01 2013
Journal Name
Political Sciences Journal
Mr. Hassan Ezzedine al-Ulum The social contract and popular power when Imam Ali
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حسن السيد عز الدين بحر العلوم العقد الاجتماعي والسلطة الشعبية عند الإمام علي (عليه السلام )

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Publication Date
Thu Sep 01 2016
Journal Name
2016 8th Computer Science And Electronic Engineering (ceec)
Class-specific pre-trained sparse autoencoders for learning effective features for document classification
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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fully Automated Magnetic Resonance Detection and Segmentation of Brain using Convolutional Neural Network
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     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

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Publication Date
Thu Jun 04 2020
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
User authentication system based specified brain waves
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A security system can be defined as a method of providing a form of protection to any type of data. A sequential process must be performed in most of the security systems in order to achieve good protection. Authentication can be defined as a part of such sequential processes, which is utilized in order to verify the user permission to entree and utilize the system. There are several kinds of methods utilized, including knowledge, and biometric features. The electroencephalograph (EEG) signal is one of the most widely signal used in the bioinformatics field. EEG has five major wave patterns, which are Delta, Theta, Alpha, Beta and Gamma. Every wave has five features which are amplitude, wavelength, period, speed and frequency. The linear

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Hybrid Techniques with Support Vector Machine for Improving Artifact Ultrasound Images
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     The most common artifacts in ultrasound (US) imaging are reverberation and comet-tail. These are multiple reflection echoing the interface that causing them, and result in ghost echoes in the ultrasound image. A method to reduce these unwanted artifacts using a Otsu thresholding to find region of interest (reflection echoes) and output applied to median filter to remove noise. The developed method significantly reduced the magnitude of the reverberation and comet-tail artifacts. Support Vector Machine (SVM) algorithm is most suitable for hyperplane differentiate. For that, we use image enhancement, extraction of feature, region of interest, Otsu thresholding, and finally classification image datasets to normal or abnormal image.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
New Class of Conjugate Gradient Methods for Removing Impulse Noise Images
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The conjugate coefficient optimal is the very establishment of a variety of  conjugate gradient methods. This paper proposes a new class coefficient of conjugate gradient (CG) methods for impulse noise removal, which is based on the quadratic model. Our proposed method ensures descent independent of the accuracy of the line search and it is globally convergent under some conditions, Numerical experiments are also presented for the impulse noise removal in images.

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