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The reaction kinetics parameters were estimated based on the experimental data.
Model parameters were estimated based on potentiometric titration data and adsorption isotherms leading to satisfactory fitting for any considered strain.
Reasonable values for all mass transfer rate parameters were estimated based on the available surface science and membrane permeation literature.
CPA binary interaction parameters were estimated based on the experimental vapour liquid or liquid liquid equilibria data available in the literature.
By using the concentration-time curves, adsorption kinetic parameters were estimated based on a simplified model including reversible and irreversible adsorption states.
IUH parameters were estimated based on the "match test" between the autocorrelation function (ACFs) derived from the filtered base flow time series and from the IUH parameters, under the GLUE framework.
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Both parameters are estimated based on the observed data using the estimator introduced by Ephraim and Malah [56].
For the sequential Bayesian approach, the problem of multipath mitigation becomes one of sequential estimation of a hidden Markov process: the unknown channel parameters are estimated based on an evolving sequence of received noisy channel outputs.
The parameters are estimated based on stated choice data using a Bayesian D-efficient optimal design.
Bubbles sizes and kinetics parameters are estimated based on dedicated experiments.
With its immeasurable parameters being estimated based on experimental data, an approximate 1-DOF linear model is obtained neglecting the coupling terms.
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