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Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing different MCDM approaches has been raised based on different perspectives; however, the latest one, namely, the fuzzy decision by opinion score method that was produced in 2020, has efficiently been able to solve some existing issues that other methods could not manage to solve. because of the multiple criteria decision-making problem and because some criteria have a conflict problem. The methodology of this research was divided into two main stages. The first stage related to identifying the decision matrix used eight different ML methods on chest X-ray (CXR) images and extracted a new decision matrix so as to assess the ML methods.  The second stage related to FDOSM was utilized to solve the multiple criteria decision-making problems. The results of this research are as follows: (1) The individual benchmarking results of three decision makers are nearly identical; however, among all the used ML methods, neural networks (NN) achieved the best results. (2) The results of the benchmarking group are comparable, and the neural network machine learning method is the best among the used methods. (3) The final rank is more logical and closest to the decision-makers' opinion. (4) Significant differences among groups' scores are shown by our validation results, which indicate the authenticity of our results. Finally, this research presents many benefits, especially for hospitals and medical clinics, with a view to speeding up the diagnosis of patients suffering from COVID-19 using the best machine learning method.

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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Modeling Extreme COVID-19 Data in Iraq
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     This paper considers the maximum number of weekly cases and deaths caused by the COVID-19 pandemic in Iraq from its outbreak in February 2020 until the first of July 2022. Some probability distributions were fitted to the data. Maximum likelihood estimates were obtained and the goodness of fit tests were performed. Results revealed that the maximum weekly cases were best fitted by the Dagum distribution, which was accepted by three goodness of fit tests. The generalized Pareto distribution best fitted the maximum weekly deaths, which was also accepted by the goodness of fit tests. The statistical analysis was carried out using the Easy-Fit software and Microsoft Excel 2019.

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Publication Date
Fri Jan 27 2023
Journal Name
Research Journal Of Pharmacy And Technology
Physical human Activity, Immunity and COVID-19
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Background: The global threat of COVID-19 outbreak and on the 11 March 2020, WHO acknowledged that the virus would likely spread to all countries across the globe and declared the coronavirus outbreak a pandemic which is the fifth pandemic since 20 century and this has brought human lives to a sudden and complete lockdown and the confirmed cases of this disease and deaths continue to rise in spite of people around the world are taking important actions to mitigate and decrease transmission and save lives. Objectives: To assess the effect of exercise and physical activity on the immunity against COVID-19. Methods: Collected electronic databases including (Medline, EMBASE, Google Scholar, PubMed and Web of Science) were searched with

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Publication Date
Thu Sep 16 2021
Journal Name
International Journal Of Clinical Practice
An overview of post‐COVID‐19 complications
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Publication Date
Fri Dec 01 2023
Journal Name
Slas Discovery
Role Of Vaccines Against COVID-19 Pandemic
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Publication Date
Sun Aug 06 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Approximation Solutions for System of Linear Fredhom Integral Equations by Using Decomposition Method
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In this paper, the Decomposition method was used to find approximation solutions for a system of linear Fredholm integral equations of the second kind. In this method the solution of a functional equations is considered as the sum of an infinite series usually converging to the solution, and Adomian decomposition method for solving linear and nonlinear integral equations. Finally, numerical examples are prepared to illustrate these considerations.

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Estimate missing value by use analyses of covariance method for split block-design
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The research aims to estimate missing values using covariance analysis method Coons way to the variable response or dependent variable that represents the main character studied in a type of multi-factor designs experiments called split block-design (SBED) so as to increase the accuracy of the analysis results and the accuracy of statistical tests based on this type of designs. as it was noted in the theoretical aspect to the design of dissident sectors and statistical analysis have to analyze the variation in the experience of experiment )SBED) and the use of covariance way coons analysis according to two methods to estimate the missing value, either in the practical side of it has been implemented field experiment wheat crop in

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Computational Science
Novel approximate solution for fractional differential equations by the optimal variational iteration method
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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Determination of some characteristics of comet’s gases by photometry method for comet Hyakutake
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The present paper focuses on the study of some characteristics of
comets ions by photometry method which represent by CCD camera
which it provide seeing these images in a graded light. From 0-255
when Zero (low a light intensity) and 255 (highlight intensity). These
differences of photonic intensity can be giving us a curve which
appear from any line of this image.
From these equations the focus is concentrating on determine the
temperature distribution, velocity distribution, and intensity number
distribution which is give number of particles per unit volume.
The results explained the interaction near the cometary nucleus
which is mainly affected by the new ions added to the density of the
solar wind, th

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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Computational Science
Novel approximate solution for fractional differential equations by the optimal variational iteration method
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