Results 161 to 170 of about 5,105 (201)

Examining the Compositional Selectivity of Hydrocarbon Oxidation Products Using Liquid-Liquid Extraction and Solid-Phase Extraction Techniques. [PDF]

Environ Sci Technol
Zito P, Ghannam R, Harsha ML, Bekins BA, Podgorski DC.   +4 more
europepmc   +1 more source

Stemflow Fluorescence Predicts Lignin Composition and Phenolic Monomer Yield for Trees. [PDF]

ACS Sustain Chem Eng
O'Halloran RC, Shapiro AJ, Gupta Y, Guerard JJ, Siple D, Sadula S, Epps TH, Vlachos DG, Levia DF.   +8 more
europepmc   +1 more source

Unambiguous Determination of Benzo[a]pyrene and Dibenzo[a,l]pyrene in HPLC Fractions via Room-Temperature Fluorescence Excitation-Emission Matrices. [PDF]

Molecules
Knecht GT, Nauth SD, Alvarado JCG, Santana AM, Goicoechea HC, Campiglia AD.   +5 more
europepmc   +1 more source

A prompt technique to identify fluoroquinolone antibiotics (FQs) residue in the environments. [PDF]

MethodsX
Niloy NM, Parvin F, Tareq SM.
europepmc   +1 more source

Low-Rank Tensor Decomposition for Cross-Bispectral Analysis of EEG Data

Kaziki D, Engel AK, Nolte G.
europepmc   +1 more source

A fully robust PARAFAC method for analyzing fluorescence data

Journal of Chemometrics, 2009
Parallel factor analysis (PARAFAC) is a widespread method for modeling fluorescence data by means of an alternating least squares procedure. Consequently, the PARAFAC estimates are highly influenced by outlying excitation–emission landscapes (EEM) and ...
Stina Frosch
exaly   +2 more sources

Characterization of cereal flours by fluorescence spectroscopy coupled with PARAFAC

Food Chemistry, 2017
This paper presents parallel factor analysis (PARAFAC) of fluorescence of cereal flours. Excitation emission matrices (EEMs) of different cereal flours (wheat, corn, rye, rice, oat, spelt, barley and buckwheat) were measured in a front-face configuration
Ivana Zeković, Bojana Milićević, Miroslav D. Dramicanin   +2 more
exaly   +2 more sources

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A comparison of algorithms for fitting the PARAFAC model

Computational Statistics and Data Analysis, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rasmus Bro, Giorgio Tomasi
exaly   +4 more sources

PARAFAC and missing values

Chemometrics and Intelligent Laboratory Systems, 2005
Abstract Missing values are a common occurrence in chemometrics data, and different approaches have been proposed to deal with them. In this work, two different concepts based on two algorithms are compared in their efficiency in dealing with incomplete data when fitting the PARAFAC model: single imputation (SI) combined with a standard PARAFAC ...
Rasmus Bro, Giorgio Tomasi
exaly   +2 more sources

PARAFAC algorithms for large-scale problems

Neurocomputing, 2011
Parallel factor analysis (PARAFAC) is a tensor (multiway array) factorization method which allows to find hidden factors (component matrices) from a multidimensional data. Most of the existing algorithms for the PARAFAC, especially the alternating least squares (ALS) algorithm need to compute Khatri-Rao products of tall factors and multiplication of ...
Anh-Huy Phan, Andrzej Cichocki
exaly   +3 more sources