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Comparison Semiparametric Bayesian Method with Classical Method for Estimating Systems Reliability using Simulation Procedure
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               In this research, the semiparametric Bayesian method is compared with the classical  method to  estimate reliability function of three  systems :  k-out of-n system, series system, and parallel system. Each system consists of three components, the first one represents the composite parametric in which failure times distributed as exponential, whereas the second and the third components are nonparametric ones in which reliability estimations depend on Kernel method using two methods to estimate bandwidth parameter h method and Kaplan-Meier method. To indicate a better method for system reliability function estimation, it has been used simulation procedure for comparison and different sample sizes of size (14,30,60 and 100) using standard comparison Integral Mean Square Error (IMSE). For k-out of-n system, the results indicate that it is better to use Bayesian method for samples of size (30,60 and 100), and to use the classical method for samples of size (14), whereas for series system the best method to use is Bayesian method for samples of size (14,60 and 100) , and  to use the classical method for sample of size (30). for parallel system, it is better to use Bayesian method for all sample sizes.                                                                                                

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Utilization of Geographic Information System for hydrological analyses: A case study of Karbala province, Iraq
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    Analyses are the power point of GIS because GIS can process and analyze different spatial and attribute data, leading to new results for supporting decision makers. The research aims to study advanced hydrologic analyses for the western part of Karbala province, Iraq. The hydrologic analysis is done based on where that DEM creates from the field survey method. This analysis gives digital maps and tables showing the region's main and minor hydrological properties, such as flow direction, flow accumulation, stream order, stream to feature, basin, and watershed maps. Also, it can be calculated as area, perimeter, lengths of streams, and numbers of stream orders for the main watersheds that are effective in the study area. These analy

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Sat May 08 2021
Journal Name
Iraqi Journal Of Science
Some Results on the Norm Attainment Set for Bounded Linear Operators on Smooth Banach Spaces
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In this paper, we give new results and proofs that include the notion of norm attainment set of bounded linear operators on a smooth Banach spaces and using these results to characterize a bounded linear operators on smooth Banach spaces that preserve of approximate - -orthogonality. Noting that this work takes brief sidetrack in terms of approximate - -orthogonality relations characterizations of a smooth Banach spaces. 

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Formulation and Characterization of Nimodipine Nanoparticles for the Enhancement of solubility and dissolution rate
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Nimodipine (NMD) is a dihydropyridine calcium channel blocker useful for the prevention and treatment of delayed ischemic effects. It belongs to class ? drugs, which is characterized by low solubility and high permeability. This research aimed to prepare Nimodipine nanoparticles (NMD NPs) for the enhancement of solubility and dissolution rate. The formulation of nanoparticles was done by the solvent anti-solvent technique using either magnetic stirrer or bath sonicator for maintaining the motion of the antisolvent phase. Five different stabilizers were used to prepare NMD NPs( TPGS, Soluplus®, HPMC E5, PVP K90, and poloxamer 407). The selected formula F2, in which  Soluplus 

has been utilized as a stabilizer, has a par

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Publication Date
Wed Jan 01 2020
Journal Name
Aip Conference Proceedings
Effect of BaTio3 mixture on the structural, electrical properties and morphology for PET/ BaTiO3 composite
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In the present work, the focusing was on the study of the x-ray diffraction, dielectric constant, loses dielectric coefficient, tangent angle, alter- natively conductivity and morphology of PET/BaTio3. The PET/BaTio3 composite was prepared for polyethylene terephthalate PET polymer composite containing 0, 10, 20, 30, 40, 50, and 60 wt. % from Barium titanate BaTi03 powder. The composite of two materials leads to form mixing solution and hot-pressing method. The effect of BaTio3 on the structure and dielectric properties with morphology was studied on PET matrix polymer using XRD, LCR meter and SEM.

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Publication Date
Wed Feb 01 2023
Journal Name
Optik
Synthesis and characterization of PVDF/PMMA/ZnO hybrid nanocomposite thin films for humidity sensor application
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Publication Date
Wed May 10 2023
Journal Name
Biomass Conversion And Biorefinery
Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Wed Sep 01 2021
Journal Name
Acta Pharmaceutica Sinica B
Discovery of a potent and dual-selective bisubstrate inhibitor for protein arginine methyltransferase 4/5
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Publication Date
Thu Oct 13 2022
Journal Name
Computation
A Pattern-Recognizer Artificial Neural Network for the Prediction of New Crescent Visibility in Iraq
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Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

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Publication Date
Sun Jan 01 2023
Journal Name
International Conference On Scientific Research & Innovation (icsri 2022)
Investigating the capability of MCM-41 nanoparticle for COD removal from Iraqi petroleum refinery wastewater
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