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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 Dec 25 2021
Journal Name
Diyala Journal Of Medicine
Oxidative Stress in Multiple Sclerosis Disease (Review Article)
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Background: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system, in which the myelin sheaths got injured. The prevalence of MS is on grow, as well as, it affects the young ages. Females are most common to have MS compared to males. Oxidative stress is the situation of imbalance between oxidants (free radicals and reactive oxygen species (ROS)) and antioxidants in a living system, in which either the oxidants are elevated or antioxidants are reduced, or sometimes both. ROS and oxidative stress have been implicated in the progression of many degenerative diseases, which is important in cracking the unrevealed mysteries of MS. In this review article, some of the proposed mechanisms that link oxidative stres

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Publication Date
Thu Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Pattern of Congenital Heart Disease In Children Attending Central Teaching Pediatric Hospital, Baghdad
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Background: Congenital cardiac defects have a wide spectrum of severity in infants. About 30-40% of patients with congenital cardiac defects will be symptomatic in the 1st year of life, while the diagnosis was established in 60% of patients by the 1st month of age.

Objectives: To identify the occurrence of specific types of CHD among hospitalized patients and to evaluate of growth of patients by different congenital heart lesions.

Methods: A retrospective study, done on ninety-six patients (51 male and 45 female) with congenital heart disease (CHD) admitted to central teaching hospital of pediatrics, Baghdad from 1st September 2009 to 30

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition
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There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Intelligent Congestion Control of 5G Traffic in SDN using Dual-Spike Neural Network
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Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
On Bayesian Estimation of System Reliability in Stress – Strength Model Based on Generalized Inverse Rayleigh Distribution
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Abstract<p>The parameter and system reliability in stress-strength model are estimated in this paper when the system contains several parallel components that have strengths subjects to common stress in case when the stress and strengths follow Generalized Inverse Rayleigh distribution by using different Bayesian estimation methods. Monte Carlo simulation introduced to compare among the proposal methods based on the Mean squared Error criteria.</p>
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Publication Date
Tue Dec 10 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Development of Robust and Efficient Symmetric Random Keys Model based on the Latin Square Matrix
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Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

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Publication Date
Tue Feb 27 2024
Journal Name
Tem Journal
Supervised Classification Accuracy Assessment Using Remote Sensing and Geographic Information System
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Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

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Publication Date
Sun Dec 31 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
A Ranked-Aware GA with HoG Features for Infant Cry Classification
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Publication Date
Sun Dec 01 2013
Journal Name
Diyala Journal Of Engineering Sciences
Design and Simulation of parallel CDMA System Based on 3D-Hadamard Transform
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Future wireless systems aim to provide higher transmission data rates, improved spectral efficiency and greater capacity. In this paper a spectral efficient two dimensional (2-D) parallel code division multiple access (CDMA) system is proposed for generating and transmitting (2-D CDMA) symbols through 2-D Inter-Symbol Interference (ISI) channel to increase the transmission speed. The 3D-Hadamard matrix is used to generate the 2-D spreading codes required to spread the two-dimensional data for each user row wise and column wise. The quadrature amplitude modulation (QAM) is used as a data mapping technique due to the increased spectral efficiency offered. The new structure simulated using MATLAB and a comparison of performance for ser

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Estimation of Minimum Miscibility Pressure for 〖CO〗_2 Flood Based on EOS
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CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.  Many trials have been done to ma

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