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Journal ArticleDOI

Parameter estimation from multiresponse data

TLDR
Methods for modeling such data are described, emphasizing parameter estimation strategy and available software, and experiences in multiresponse modeling are reviewed for several chemical engineering problems.
Abstract
Multiresponse data are familiar outputs of experiments and processes involving multicomponent mixtures, multiple streams or multiple methods of observation. The resulting arrays of data exhibit various structures, including rectangular (no missing values), block-rectangular, and irregular (missing values with no simple pattern). Methods for modeling such data are described, emphasizing parameter estimation strategy and available software. Experiences in multiresponse modeling are then reviewed for several chemical engineering problems.

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Journal ArticleDOI

A review of Maillard reaction in food and implications to kinetic modelling

TL;DR: A review of the research designed to lead to an increased understanding of the chemistry of the Maillard reaction, based on recent developments, and its influence on food properties like color, flavour and nutritional value is given in this paper.
Journal ArticleDOI

On the mechanism of low-temperature water gas shift reaction on copper.

TL;DR: Periodic, self-consistent density functional theory (DFT-GGA) calculations are used to investigate the water gas shift reaction (WGSR) mechanism on Cu(111) and identify carboxyl, a new reactive intermediate, which plays a central role in WGSR.
Journal ArticleDOI

An efficient method for parametric uncertainty analysis of numerical geophysical models

TL;DR: In this article, a new method for parametric uncertainty analysis of numerical geophysical models is presented, which approximates model response surfaces, which are functions of model input parameters, using orthogonal polynomials, whose weighting functions are the probabilistic density functions of the input uncertain parameters.
Journal ArticleDOI

Statistical aspects of kinetic modeling for food science problems.

TL;DR: In this article, the authors used extended least-squares to obtain information about experimental uncertainties of data and compared non-linear and linear regression with multiresponse modeling and the Arrhenius equation.
Journal ArticleDOI

Thermal degradation of glucosinolates in red cabbage

TL;DR: In this paper, the degradation of individual glucosinolates within the plant matrix was studied and the degree of thermal degradation at standardized heating conditions (blanching, cooking and canning) was simulated.
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