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weighted-averaging-based classification of laser-induced breakdown spectroscopy measurements using most informative spectral lines

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Plasma Science and Technology 2020年第1期22卷 58-73页

作者： Ekta SRIVASTAVA Hyemin JANG Sungho SHIN Janghee CHOI Sungho JEONG Euiseok HWANG School of Mechanical Engineering Gwangju Institute of Science and Technology(GIST)123 Cheomdangwagi-roBuk-guGwangju 61005Republic of Korea LGCNS LG Sciencepark El371Magokjungang 8-roGangseo-guSeoul 07795Republic of Korea Smart Manufacturing Technology Group Korea Institute of Industrial Technology89 Yangdaegiro-gilSeobuk-guCheonan-siChungcheongnam-do 31056Republic of Korea

In this study,efficient spectral line selection and wcightcd-avcraging-bascd processing schemes are proposed for the classification of laser-induced breakdown spectroscopy(UBS)*** fast on-line classification,a set of representative spectral lines arc selected ami processed relying on the information metric,instead of the time consuming full spectrum based analysis.I he most informative spectral line sets arc investigated by the joint mutual information estimation(MIR)evaluated with the Gaussian kernel density,where dominant intensity peaks associated with the concentrated components arc not necessarily most valuable for *** order to further distinguish the characteristic patterns of die LIBS measured spectrum,two-dimensional spectral images are synthesized through column-wise concatenation of the peaks along with their *** fast classification while preserv ing die effect of distinctive peak patterns,column-wise Gaussian weighted averaging is applied to die synthesized images,yielding a favorable trade off between classification performance and computational *** explore the applicability of the proposed schemes,two applications of alloy classification and skin cancer detection arc investigated with the multi-class and binary support vector machines classifiers,*** MIE measures associated with selected spectral lines in bodi applications show a strong correlation to the actual classification or detection accuracy,which enables to find out meaningful combinations of spectral *** addition,the peak patterns of the selected lines and their Gaussian weighted averaging with nciehbors of the selected peaks efficiently distineuish different classes of LIBS measured spectrum.

关键词： laser-induced breakdown spectroscopy mutual information weighted averaging alloy classification skin cancer detection

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Someweighted averaging Methods for Gradient Recovery

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Advances in Applied Mathematics and Mechanics 2012年第2期4卷 131-155页

作者： Yunqing Huang Kai Jiang Nianyu Yi Hunan Key Laboratory for Computation and Simulation in Science and Engineering School of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105HunanChina

We propose some new weighted averaging methods for gradient recovery,and present analytical and numerical investigation on the performance of these weighted averaging *** is shown analytically that the harmonic averaging yields a superconvergent gradient for any mesh in one-dimension and the rectangular mesh in *** results indicate that these new weighted averaging methods are better recovered gradient approaches than the simple averaging and geometry averaging methods under triangular mesh.

关键词： Finite element method weighted averaging gradient recovery

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