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COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings, and Pneumonia) classification tasks. Our model has achieved an accuracy value of 98.4% for binary and 93.8% for the multi-class classification. The number of parameters of our model is 11 Million parameters which are fewer than some state-of-the-art methods with achieving higher results.

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Building a High Accuracy Transfer Learning-Based Quality Inspection System at Low Costs
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      Products’ quality inspection is an important stage in every production route, in which the quality of the produced goods is estimated and compared with the desired specifications. With traditional inspection, the process rely on manual methods that generates various costs and large time consumption. On the contrary, today’s inspection systems that use modern techniques like computer vision, are more accurate and efficient. However, the amount of work needed to build a computer vision system based on classic techniques is relatively large, due to the issue of manually selecting and extracting features from digital images, which also produces labor costs for the system engineers.

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Use Dividend Discount Model , DDM in Stocks Valuation With Framework of Inflation: An Applied Study
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The theme of this Study presents analysis and discuss to the "Share the framework for assessing inflation," a practical study in a sample of joint stock companies listed on the Iraq Stock Exchange for the years (2009-2013). To determine the extent of the disparity between the nominal value of shares (Nominal Value) before deducting inflation and the real value (Real Value) per share, after deducting inflation in the case of zero growth. The study relied on annual reports of the companies of the research sample of the Iraq Stock Exchange, as well as the Iraqi Securities Commission. Besides the annual reports issued by the Ministry of Planning, as well as annual reports and statistical bulletin issued by the Central Bank of Iraq. It is fra

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS
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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Use aggregate slide estimate additive splines estimation for the diagnosis of non-linear composite model self-regression with practical application
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Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
apply Six Sigma in improving the quality of projects added expert system )Applied research(
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Construction projects need methods and techniques to ensure the level of quality and commensurate with the level required and documented in the project contract. The quality of the project is affected by the quality of the inputs and accompanying procedures in the construction of the project.

Al-Rumaitha residential project found that the quality of the concrete for the ceilings in the research sample (the roof of the third floor of buildings A25 and A26) and (roof of the second floor of buildings A27, A28, A29, A30, A31, A32 and A33) and roof of buildings A15 and A16 A19)) is not the required quality level.

The idea of the research came after the need to improve the performance o

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Prediction of the Scale Removal Rate in Heat Exchanger Piping System Using the Analogies between Mass and Momentum Transfer
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The possibility of predicting the mass transfer controlled CaCO3 scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sat Oct 01 2022
Journal Name
Colloids And Surfaces A: Physicochemical And Engineering Aspects
Application of natural deep eutectic solvents in bulk liquid membrane system for removal of free glycerol from crude fatty acid methyl ester
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Fatty Acid Methyl Ester (FAME) produced from biomass offers several advantages such as renewability and sustainability. The typical production process of FAME is accompanied by various impurities such as alcohol, soap, glycerol, and the spent catalyst. Therefore, the most challenging part of the FAME production is the purification process. In this work, a novel application of bulk liquid membrane (BLM) developed from conventional solvent extraction methods was investigated for the removal of glycerol from FAME. The extraction and stripping processes are combined into a single system, allowing for simultaneous solvent recovery whereby low-cost quaternary ammonium salt-glycerol-based deep eutectic solvent (DES) is used as the membrane phase.

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Building a Sustainable GARCH Model to Forecast Rubber Price: Modified Huber Weighting Function Approach
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The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
New Versions of Liu-type Estimator in Weighted and non-weighted Mixed Regression Model
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This paper considers and proposes new estimators that depend on the sample and on prior information in the case that they either are equally or are not equally important in the model. The prior information is described as linear stochastic restrictions. We study the properties and the performances of these estimators compared to other common estimators using the mean squared error as a criterion for the goodness of fit. A numerical example and a simulation study are proposed to explain the performance of the estimators.

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