Preferred Language
Articles
/
lRfgPo8BVTCNdQwCGGXF
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
...Show More Authors

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
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
...Show More Authors

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

... Show More
View Publication Preview PDF
Scopus (37)
Crossref (25)
Scopus Crossref
Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sat Dec 03 2022
Journal Name
Al-kut University College Of Humanities
Deep understanding skills in chemistry among middle school students
...Show More Authors

Preview PDF
Publication Date
Wed Nov 06 2024
Journal Name
2024 17th International Conference On Development In Esystem Engineering (dese)
Speech Enhancement Algorithm using Deep Learning and Hahn Polynomials
...Show More Authors

View Publication
Scopus (1)
Scopus Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
...Show More Authors

View Publication
Scopus (40)
Crossref (28)
Scopus Clarivate Crossref
Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Effect of sowing Dates of some bread wheat cultivars on Disease response toward the fungal pathogen Wheat leaf rust
...Show More Authors

Disease responses of eight wheat cultivars , Saber Beg. , Abu-Ghraib 3, Mexipak , Tamoz 2,Tamoz 3 , IPA 95 ,IPA 99 and Tahadi which were grown in four different sowing date , 25 th October , 19th September , 14th December and 8 January , to leaf rust disease caused by Puccinia recondita were investigated under natural infection conditions at the experimental farm , College of Agriculture , Abu-Ghraib, during the growing season of 1997-1998.Results of this study revealed that IPA 95, IPA 99 and Tahadi showed moderate resistant reaction, while Tamuz 3 was moderateley susceptable . Abu-Ghraib , Saber Beg, Tamuz 2 and Mexipak showed susceptible yeaction to the causal agent . The first sowing date was not suitable for disease progress in compars

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 31 2019
Journal Name
Journal Of Pure And Applied Microbiology
Determination of Level of 25-Hydroxy Vitamin D3 in Patients with Multiple Sclerosis and Its Effect on Disease Activity
...Show More Authors

View Publication Preview PDF
Scopus (2)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Effect of laser energy and pulses on size and concentration of gold nanoparticles in DDDW by LALP method
...Show More Authors

The size and the concentration of the gold nanoparticles (GNPs)
synthesized in double distilled deionized water (DDDW) have been
found to be affected by the laser energy and the number of pulses.
The absorption spectra of the nanoparticles DDDW, and the
surface plasmon resonance (SPR) peaks were measured, and found to
be located between (509 and 524)nm using the UV- Vis
spectrophotometer. SPR calculations, images of transmission
electron microscope, and dynamic light scattering (DLS) method
were used to determine the size of GNPs, which found to be ranged
between (3.5 and 27) nm. The concentrations of GNPs in colloidal
solutions found to be ranged between (37 and 142) ppm, and
measured by atomic absorptio

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Mon Apr 01 2013
Journal Name
International Journal Of Electrical, Electronics And Telecommunication Engineering
Performance Analysis of xPON Network for Different Queuing Models
...Show More Authors

Passive optical network (PON) is a point to multipoint, bidirectional, high rate optical network for data communication. Different standards of PONs are being implemented, first of all PON was ATM PON (APON) which evolved in Broadband PON (BPON). The two major types are Ethernet PON (EPON) and Gigabit passive optical network (GPON). PON with these different standards is called xPON. To have an efficient performance for the last two standards of PON, some important issues will considered. In our work we will integrate a network with different queuing models such M/M/1 and M/M/m model. After analyzing IPACT as a DBA scheme for this integrated network, we modulate cycle time, traffic load, throughput, utilization and overall delay

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
...Show More Authors

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

... Show More
View Publication