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Article type: Research Article
Authors: Martinez, Oscara; * | Dabarera, Rangaa | Premaratne, Kamala | Kubat, Miroslava | Englehardt, Jamesb
Affiliations: [a] Department of Electrical and Computer Engineering, University of Miami, FL, USA | [b] Department of Civil, Architectural and Environmental Engineering, University of Miami, FL, USA
Correspondence: [*] Corresponding author: Oscar Martinez, Department of Electrical and Computer Engineering, University of Miami, FL, USA. E-mail:[email protected]
Abstract: Fluorescence spectroscopic excitation-emission matrices (EEMs) can be used to characterize dissolved organic matter in water with high sensitivity. Our goal is to predict the standard biosensor-based measurement Microtox® utilizing EEMs, pH, turbidity and conductivity, among other variables. EEMs have been modeled using novel latent fluorescent Dirichlet allocation (LFDA) based probabilistic graphical model. We found that nonparametric techniques offer a better mapping from, LFDA based EEMs scores and other measurements, to Microtox® measurements. The final decision on Microtox® measurement is given using an evidence fusion mechanism. In general, the novel LFDA based graphical model can be utilized in analyzing two dimensional data.
Keywords: Latent Dirichlet allocation, nonparametric estimation, fluorescence spectroscopy
DOI: 10.3233/IDA-150291
Journal: Intelligent Data Analysis, vol. 21, no. 1, pp. 181-203, 2017
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