Near-infrared spectroscopy coupled with chemometrics and artificial neural network modeling for prediction of emulsion droplet diameters
There is increased interest in the food industry for emulsions as delivery systems to preserve
the stability of sensitive biocompounds with the aim of improving their bioavailability …
the stability of sensitive biocompounds with the aim of improving their bioavailability …
Unbiased prediction errors for partial least squares regression models: Choosing a representative error estimator for process monitoring
PB Skou, M Tonolini, CE Eskildsen… - Journal of Near …, 2023 - journals.sagepub.com
Partial least squares (PLS) regression is widely used to predict chemical analytes from
spectroscopic data, thus reducing the need for expensive and time-consuming wet chemical …
spectroscopic data, thus reducing the need for expensive and time-consuming wet chemical …
Machine learning algorithms in spatiotemporal gait analysis can identify patients with Parkinson's disease
PVR Fernando, M Pannu, P Natarajan, RD Fonseka… - medRxiv, 2023 - medrxiv.org
Abstract Changes to spatiotemporal gait metrics in gait-altering conditions are characteristic
of the pathology. This data can be interpreted by machine learning (ML) models which have …
of the pathology. This data can be interpreted by machine learning (ML) models which have …
Comparing Calibration Algorithms for the Rapid Characterization of Pretreated Corn Stover Using Near-Infrared Spectroscopy
Z Tillman, EJ Wolfrum - Frontiers in Energy Research, 2022 - frontiersin.org
Rapid characterization of biomass composition is a key enabling technology for biorefineries—
the ability to measure the chemical composition of biomass materials entering the …
the ability to measure the chemical composition of biomass materials entering the …
Diagnosing indirect relationships in multivariate calibration models
CE Eskildsen, SB Engelsen, KR Dankel… - Journal of …, 2021 - Wiley Online Library
Problems concerning covariance among independent variables are well understood and
dealt with by inverse regression methods like partial least squares regression. However …
dealt with by inverse regression methods like partial least squares regression. However …
[HTML][HTML] Orthogonality constrained inverse regression to improve model selectivity and analyte predictions from vibrational spectroscopic measurements
PB Skou, E Hosseini, JB Ghasemi, AK Smilde… - Analytica Chimica …, 2021 - Elsevier
In analytical chemistry spectroscopy is attractive for high-throughput quantification, which
often relies on inverse regression, like partial least squares regression. Due to a multivariate …
often relies on inverse regression, like partial least squares regression. Due to a multivariate …