Xiaoping Wang
Zhejiang University
41 Papers
97 Citations
Xiaoping Wang is an academic researcher from Zhejiang University. The author has contributed to research in topics: Surface plasmon resonance & Surface plasmon. The author has an hindex of 10, co-authored 41 publications.
Chat about Author
Papers
Design of an ultra-broadband near-perfect bilayer grating metamaterial absorber based on genetic algorithm.
TL;DR: An ultra-broadband metamaterial absorber, consisting of 2D SiO2-Ti square bilayer grating onSiO2 film and Ti substrate, is proposed and designed by rigorous coupled wave analysis (RCWA) and genetic algorithm (GA) methods and is a promising candidate in solar applications.
68
Quantitative analysis of adulteration of extra virgin olive oil using Raman spectroscopy improved by Bayesian framework least squares support vector machines
TL;DR: In this article, a Bayesian framework is applied to find the best parameters for the least squares support vector machines (LS-SVM), and an adulteration prediction model is established by using the optimal parameters and the Raman spectral data of extra virgin olive oil (EVOO) for the training of LS -SVM without any classification process.
65
Review: advances and applications of surface plasmon resonance biosensing instrumentation
TL;DR: A review of surface plasmon resonance (SPSR) biosensors can be found in this paper, where the authors examine the last three years of literature on SRS instruments and present several studies that have practical significance for progress in the instrumentation.
49
Rapid prediction of fatty acid composition of vegetable oil by Raman spectroscopy coupled with least squares support vector machines
TL;DR: In this paper, a prediction model of fatty acid content based on least squares support vector machines (LS-SVM) was established for multivariate analysis between the Raman spectral eigenvalues and the fatty acid composition measured by gas chromatography (GC) method.
44
Identification of surface defects on glass by parallel spectral domain optical coherence tomography.
TL;DR: Preliminary results demonstrate the advantage of the proposed nondestructive method to identify glass surface defects using a parallel spectral domain OCT (SD-OCT) system to precisely demarcate surface defects and sensitively measure surface deformations.
31