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In part I of this two-part study, we introduced a new optimal Bayesian classification methodology that utilizes the same modeling framework proposed in Bayesian minimum-mean-square error (MMSE) error estimation.
We hope the modeling framework proposed will be useful in testing chemical perturbations from HTS data to generalized networks on signaling events assessed at the tissue level.
The integrated patch-prediction modeling framework proposed in this paper constitutes a parsimonious but useful risk assessment tool for species decline with respect to more accurate metapopulation models.
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An alternative modeling framework is proposed, integrating simulation models and optimization strategies that take into account double-parking derived vehicle obstruction.
For this purpose, a two-equation modeling framework is proposed to investigate the effect of built environment on both pedestrian activity and vehicle pedestrian collision frequency at signalized intersections.
In this article, a modeling framework is proposed for two-time-scale chemical processes modeled by nonlinear ordinary differential equations (ODEs) with large parameters of the form 1ε, to obtain a standard singularly perturbed representation where the slow and fast variables are explicitly separated.
To prevent models from predicting such unrealistic metabolic modes, extensions of the modeling framework were proposed that directly enforce these laws (Beard et al., 2002).
A three dimension modeling framework is proposed.
A modeling framework is proposed for complex chemical process networks.
Furthermore, a modeling framework is proposed to describe flow-induced crystallization of isotactic polypropylene.
In this study, a two-scale modeling framework is proposed to simulate the capillary pore network in hydrated cement paste.
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