LFDA model for the assessment of water quality through Microtox® using excitation-emission matrices

Oscar Martinez, Ranga Dabarera, Kamal Premaratne, Miroslav Kubat, James Douglas Englehardt

Research output: Contribution to journalArticle

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)181-203
Number of pages23
JournalIntelligent Data Analysis
Volume21
Issue number1
DOIs
StatePublished - 2017

Keywords

  • fluorescence spectroscopy
  • Latent Dirichlet allocation
  • nonparametric estimation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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