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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
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
تقويم اسئلة كتاب الكيمياء للصف الرابع العلمي وفقا لتصنيف جالاجر وآشنر
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The research aims to evaluate the current book chemistry fourth grade scientific questions on the classification according to Gallagher And Aschner levels of its four reflexion A cognitive thinking, thinking Convergent , Divergent thinking and osteopathic thinking and evaluating those questions in terms of standards of honesty, inclusiveness and objectivity . The research sample included a book of chemistry for fourth grade scientific for the academic year  (2016 - 2017), the same research community and the number of sub - prime questions amounted to (354) Question distributed to the chapters of the book adult (6) chapters, the researchers ends of chapters by classification questions by finding the relative weight of the are

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The level of Mental Mindfulness of College of Education Students at Umm Al-Qura University in the light of Corona Pandemic
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The aim of this research is to identify the level of mental mindfulness among female students of the College of Education at Umm Al-Qura University, as well as to identify the statistically significant differences in the level of mental mindfulness according to academic level, specialization, and academic achievement. A mental mindfulness scale was designed to cover five dimensions. The study employed the analytic descriptive approach applied to a random sample of (217) female students from various academic specializations. The findings indicated that the level of mental mindfulness was average among female students. Statistically significant differences were attributable to the academic level, academic specializations, and academic achi

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Publication Date
Fri Jan 01 2016
Journal Name
Machine Learning And Data Mining In Pattern Recognition
A New Strategy for Case-Based Reasoning Retrieval Using Classification Based on Association
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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Study of (Zn0.7 Mn0.3-x Ag0.3 Fe2O4) ferrite nanoparticles synthesized by auto combustion method for NO2 gas sensing
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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
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of The Effect of The Administration of Communications Towers in The Selling Prices of Residential Real estate )New University Village Model(
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Abstract                          

 Should be the goal of Government controls, including environmental controls and safety laws to protect citizens from the harmful effects of negative secreted by human's additions and changes in the environment. and perhaps the protection aspects of the protection of citizens from the adverse effects of communications towers, including those produced by towers of health effects. The people the right to choose the nature of the physical environment, which should not be imposed on them by others. Communications towers are one of the main problems that have been

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparative Study for Risk Criteria of Al-Qudus Plant between the Present and Planning of MOE
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The main function of a power system is to supply the customer load demands as economically as possible. Risk criterion is the probability of not meeting the load. This paper presents a methodology to assess probabilistic risk criteria of Al-Qudus plant before and after expansion; as this plant consists of ten generating units presently and the Ministry Of Electricity (MOE) is intending to compact four units to it in order to improve the performance of Iraqi power system especially at Baghdad region. The assessment is calculated by a program using Matlab programming language; version 7.6. Results show that the planned risk is (0.003095) that is (35 times) less than that in the present plant risk; (0.1091); which represents respectable imp

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Structure dependence of gamma ray irradiation effects on polyurethane and epoxy resin studied by PAL technique
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Positron annihilation lifetime (PAL) technique has been employed to
study the microstructural changes of polyurethane (PU), EUXIT 101
and epoxy risen (EP), EUXIT 60 by Gamma-ray irradiation with the
dose range (95.76 - 957.6) kGy. The size of the free volume hole and
their fraction in PU and EP were determined from ortho-positronium
lifetime component and its intensity in the measured lifetime spectra.
The results show that the irradiation causes significant changes in the
free volume hole size (Vh) and the fractional free volume (Fh), and
thereby the microstructure of PU and EP. The results indicate that
the γ-dose increases the crystallinity in the amorphous regions of PU
and increas

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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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