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Comparative Analysis of MFO, GWO and GSO for Classification of Covid-19 Chest X-Ray Images
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Medical images play a crucial role in the classification of various diseases and conditions. One of the imaging modalities is X-rays which provide valuable visual information that helps in the identification and characterization of various medical conditions. Chest radiograph (CXR) images have long been used to examine and monitor numerous lung disorders, such as tuberculosis, pneumonia, atelectasis, and hernia. COVID-19 detection can be accomplished using CXR images as well. COVID-19, a virus that causes infections in the lungs and the airways of the upper respiratory tract, was first discovered in 2019 in Wuhan Province, China, and has since been thought to cause substantial airway damage, badly impacting the lungs of affected persons. The virus was swiftly gone viral around the world and a lot of fatalities and cases growing were recorded on a daily basis. CXR can be used to monitor the effects of COVID-19 on lung tissue. This study examines a comparison analysis of k-nearest neighbors (KNN), Extreme Gradient Boosting (XGboost), and Support-Vector Machine (SVM) are some classification approaches for feature selection in this domain using The Moth-Flame Optimization algorithm (MFO), The Grey Wolf Optimizer algorithm (GWO), and The Glowworm Swarm Optimization algorithm (GSO). For this study, researchers employed a data set consisting of two sets as follows: 9,544 2D X-ray images, which were classified into two sets utilizing validated tests: 5,500 images of healthy lungs and 4,044 images of lungs with COVID-19. The second set includes 800 images, 400 of healthy lungs and 400 of lungs affected with COVID-19. Each image has been resized to 200x200 pixels. Precision, recall, and the F1-score were among the quantitative evaluation criteria used in this study.

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Publication Date
Thu Apr 01 2010
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
The Invariant Moments Based With Wavelet Used To Decide the Authintication and Originality of Images
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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Applied Science & Technology
The Use of Cubic Bezier Interpolation, Biorthogonal Wavelet and Quadtree Coding to Compress Color Images
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In this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e

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Publication Date
Fri Nov 28 2025
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Comparative Efficacy of Biologics vs. Conventional Therapies in Psoriasis: A Meta-Analysis of a Decade of Progress From 2015 to 2025
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Background: The treatment of moderate-to-severe psoriasis has advanced significantly with the use of biologic treatments. Objective: To compare the effectiveness, safety, and impact on quality of life of biologic therapies versus conventional systemic therapies for moderate-to-severe psoriasis, using evidence from 2015 to 2025, focusing on the implications for understudied regions such as Iraq and the Middle East. Methods: Data was collected using "Embase," "MEDLINE," "PubMed," and "Cochrane Central Register." The study includes 45 randomized controlled trials. Additionally, 25 key real-world evidence studies were included for qualitative synthesis to provide context on long-term drug survival, quality of life, and regional applicab

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Sat Aug 01 2020
Journal Name
Key Engineering Materials
Irradiation Duration Effect of Gamma Ray on the Compressive Strength of Reactive Powder Concrete
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Reactive Powder Concrete (RPC) could be considered as the furthermost significant modern high compressive strength concrete. In this study, an experimental investigation on the impact of micro steel fiber volume fraction ratio and gamma ray irradiation duration influence upon the compressive strength of RPC is presented. Three volume fraction ratios (0.0, 1.0 and 1.5) % was implemented. For each percentage of the adopted fiber ratios, six different irradiation duration was considered; these are (1, 2, 3, 4, 5 and 6) days. Gamma source (Cs-137) of energy (0.662) MeV and activity (6) mci was used. In a case of zero volume fraction ratio, the experimental results showed that gamma ray had a significant influence on the reducing of the

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Publication Date
Sat Aug 01 2020
Journal Name
Key Engineering Materials
Irradiation Duration Effect of Gamma Ray on the Compressive Strength of Reactive Powder Concrete
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Reactive Powder Concrete (RPC) could be considered as the furthermost significant modern high compressive strength concrete. In this study, an experimental investigation on the impact of micro steel fiber volume fraction ratio and gamma ray irradiation duration influence upon the compressive strength of RPC is presented. Three volume fraction ratios (0.0, 1.0 and 1.5) % was implemented. For each percentage of the adopted fiber ratios, six different irradiation duration was considered; these are (1, 2, 3, 4, 5 and 6) days. Gamma source (Cs-137) of energy (0.662) MeV and activity (6) mci was used. In a case of zero volume fraction ratio, the experimental results showed that gamma ray had a significant influence on the reducing of the

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Publication Date
Sat May 30 2020
Journal Name
Neuroquantology
Comparative Study for Optoelectronic Properties of Zn (Te, Se) Solar Cells
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Isolation and Classification of Green Alga Stigeoclonium attenuatum and Evaluation of its Ability to Prepare Zinc Oxide Nanoflakes for Methylene Blue Photodegradation by Sunlight
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           Algae have been used in different applications in various fields such as the pharmaceutical industry, environmental treatments, and biotechnology. Studies show that the preparation of nanoparticles by a green synthesis method is a promising solution to many medical and environmental issues. In the current study, the green alga Stigeoclonium attenuatum (Hazen) F.S. Collins 1909 was isolated and identified from the Al-Hillah River (Governorate of Babylon) in the middle of Iraq. The green synthesis by the aqueous extract of algae was used to prepare the nanoflakes of ZnO. Nanoflakes of ZnO are characterized by X-Ray diffraction (XRD) and scanning electron microscope (SEM) with flakes shape and dimensions ranging be

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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
Studying Audio Capacity as Carrier of Secret Images in Steganographic System
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Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other.  In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect

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