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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
Fri Jul 26 2019
Journal Name
Dental Materials Journal
Semi-interpenetrating network composites reinforced with Kevlar fibers for dental post fabrication
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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Tue Aug 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Energy generation by crystalline silicon photovoltaic network per meter square in Iraq
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<span lang="EN-US">Iraqi people have been without energy for nearly two decades, even though their geographic position provides a high intensity of radiation appropriate for the construction of solar plants capable of producing significant quantities of electricity. Also, the annual sunny hours in Iraq are between 3,600 to 4,300 hours which makes it perfect to use the photovoltaics arrays to generate electricity with very high efficiency compared to many countries, especially in Europe. This paper shows the amount of electric energy generated by the meter square of crystalline silicon in the photovoltaic (PV) array that already installed in 18 states in Iraq for each month of the year. The results of the meter-square of PV arr

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Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Wed Jul 01 2020
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
Prothrombotic changes in patients with end-stage renal disease and its relation to thrombotic cardiovascular complication
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There is a great risk of cardiovascular disease (CVD) and vascular thrombosis in patients with End-Stage Renal Disease (ESRD). These patients exhibit numerous abnormalities in coagulation, fibrinolytic, inhibitory protein abnormalities in multiple levels. The study aimed to assess hypercoagulable changes by measuring the levels of antithrombin, plasma fibrinogen and FXII activity in patients with ESRD, and to find their correlation with Hemoglobin (Hb) level, WBC count, reticulocyte percentage and platelet count. This study was conducted at Al-Hayat center, Al Karama Teaching Hospital on 50 ESRD patients aged < 60 years of both genders. In addition, 20 apparently healthy individuals were included as a control group. The mean Hb level, total

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Scopus
Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
Social Exclusion of People Infected with Coronavirus and Its Relationship with the Length of Incubation of the Disease Fatin sabaa khamas
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The importance of social exclusion lies in the psychological problems that cause problems in social relations and mental-physical health. For this reason, the researcher set three goals for the current research: identifying the level of social exclusion among people infected with the Coronavirus. The incubation period of the virus. Social exclusion and its relationship to the duration of incubation of the disease among people infected with the Coronavirus. The result showed that the research sample does not suffer from social exclusion. The mean value for the period from

(8-14) days is the highest value followed by the period (1-7) days and the period

 (14 days or more) comes at the end. There is no statistically sig

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Publication Date
Sun Apr 27 2025
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
CD40 Gene Variants and Disease Susceptibility: A Comprehensive Review of Associations with Immune-Mediated Inflammatory Diseases, Cancer, and Infectious Diseases
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CD40 is a type 1 transmembrane protein composed of 277 amino acids, and it belongs to the tumor necrosis factor receptor (TNFR) superfamily. It is expressed in a variety of cell types, including normal B cells, macrophages, dendritic cells, and endothelial cells, as a costimulatory molecule. This study aims to summarize the CD40 polymorphism effect and its susceptibility to immune-related disorders. The CD40 gene polymorphisms showed a significant association with different immune-related disorders and act as a risk factor for increased susceptibility to these diseases.

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