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Evaluation the profitability of public commercial banks using liquidity indicators: A comparison of the Rafidain and Rasheed study
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The issue of liquidity, profitability, and money employment, and capital fullness is one of the most important issues that gained high consideration by other authors and researchers in their attempts to find out the real relationship and how can balance be achieved, which is the main goal of each deposits.

For the sake of comprising the study variables, the research has formed the problem of the study which refers to the bank capability to enlarge profits without dissipation in liquidity   of the bank which will negatively reflect on the bank's fame as well as the customers' trust. For all these matters, the researcher has proposed a set of aims, the important of which is the estimation of the bank profitability; liquidity, using the proper indexes belong to them, and also showing the effect of liquidity, on the profitability gained by the bank.

To achieve the above aims, a set of hypotheses have been introduced and verified according to the statistical index ANOVA that contains the Test F and the vector R2 .The time limits of the study stretches from 2003 to 2012.

The main conclusion of the study is that the percentage of the effect of liquidity for the both banks was weak and does not indicate the indexes of the profitability

.Finally, the main recommendation of this reseaech, one of which is the necessity of verifying the bank investment port folio for both banks which can be due to the decrease of the employment rate .

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
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

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