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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
Tue Apr 30 2024
Journal Name
International Journal On Technical And Physical Problems Of Engineering
Deep Learning Techniques For Skull Stripping of Brain MR Images
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Deep Learning Techniques For Skull Stripping of Brain MR Images

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials & Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Studying the Effect of Curcumin (Standard & Supplements) and Zinc on the Concentrations of Glucose, Insulin, HOMA-IR, and Anti-Mullerian Hormone in PCOS-Model Rats
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The goal of the current study was to investigate the effects of curcumin in both formulas (supplement and standard), zinc, and then use them together to show their effect on the levels of glucose, insulin, insulin resistance (IR), and anti-mullerian hormone (AMH) in the model of female rats with induced polycystic ovary syndrome (PCOS) using 1mg/kg/day of letrozole for 21 days followed by a treatment period of 14 days including different treatments of zinc 30 mg/kg, curcumin standard 200 mg/kg, curcumin supplement 200 mg/kg, (curcumin standard plus zinc), (curcumin Supplement plus zinc) and metformin as a standard treatment. After the treatment, all female rats were sacrificed, and blood samples were collected from the inferior vena cava

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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
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Numerical Solution for Linear Fredholm Integro-Differential Equation Using Touchard Polynomials
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A new method based on the Touchard polynomials (TPs) was presented for the numerical solution of the linear Fredholm integro-differential equation (FIDE) of the first order and second kind with condition. The derivative and integration of the (TPs) were simply obtained. The convergence analysis of the presented method was given and the applicability was proved by some numerical examples. The results obtained in this method are compared with other known results.

 

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Solving Fractional Damped Burgers' Equation Approximately by Using The Sumudu Transform (ST) Method
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       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Kinetic Study of the Leaching of Iraqi Akashat Phosphate Ore Using Lactic Acid
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     In the present work, a kinetic study was performed to the extraction of phosphate from Iraqi Akashat phosphate ore using organic acid. Leaching was studied using lactic acid for the separation of calcareous materials (mainly calcite). Reaction conditions were 2% by weight acid concentration and 5ml/gm of acid volume to ore weight ratio. Reaction time was taken in the range 2 to 30 minutes (step 2 minutes) to determine the reaction rate constant k based on the change in calcite concentration. To determine value of activation energy when reaction temperature is varied from 25 to 65 , another investigation was accomplished. Through the kinetic data, it was found that selective leaching was controlled by

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Variable Selection Using aModified Gibbs Sampler Algorithm with Application on Rock Strength Dataset
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Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

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