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The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in order to select the best features that affect the prediction of the proposed model. These are the Recursive Feature Elimination (RFE) as wrapper feature selection and the Extra Tree Classifier (ETC) as embedded feature selection. Two classification methods are applied for classifying the features vectors which include the Naïve Bayesian method and Restricted Boltzmann Machine (RBM) method. The results were 56.181%, 97.906% respectively when classifying all features and 66.329%, 99.924% respectively when classifying the best ten features using features selection techniques.</p>
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Publication Date
Thu Jan 01 2026
Journal Name
Chalcogenide Letters
Structural and Optical Properties of Cu&lt;sub&gt;2&lt;/sub&gt;ZnSn(S&lt;sub&gt;1−x&lt;/sub&gt;Se&lt;sub&gt;x&lt;/sub&gt;)&lt;sub&gt;4&lt;/sub&gt; Nanostructures Thin Film for Photovoltaic Applications
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Copper zinc tin sulfide selenide, Cu2 ZnSn(S1−x Se x)4 , absorbers are promising earth-abundant and environmentally benign materials for low-cost photovoltaic applications. This study investigates the structural and optical properties of Cu 2 ZnSn(S1−x Se x)4 nanostructured thin films prepared by pulsed laser deposition using melt-quenched targets with selenium compositions x = 0.0–1.0. X-ray diffraction revealed that films with low selenium content remained amorphous, whereas higher selenium incorporation promoted the formation of polycrystalline kesterite–stannite phases with preferred orientations along (112), (200), (220), and (312). The crystallite size increased from 12.3 to 17.9 nm as selenium reached x = 1.0, indicating enha

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Publication Date
Wed Jan 11 2017
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Characterization of some Metal Complexes with (3Z ,5Z, 8Z)-2-azido-8-[azido(3Z,5Z)-2-azido-2,6- bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide(L-AZ) .
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The reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5- dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2- azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III) ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and Hg(II)] has been i

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