Rather than looking at mortality rates directly, a number of recent academic studies have looked modeling improvement in when making projections. Although relatively new the literature, use has long-standing tradition actuarial practice allowing for improvements from standard tables. However, are difficult to estimate robustly, and models them subject high levels parameter uncertainty, because ...

This study compares two techniques for uncertainty quantification in chemistry computations, one based on sensitivity analysis and error-propagation, and the other on stochastic analysis using polynomial chaos techniques. The two constructions are studied in the context of H2-O2 ignition under supercritical-water conditions. They are compared in terms of their prediction of uncertainty in speci...

In the modeling of exible structures, there is generally uncertainty in both the frequencies and damping constants , and it is thus important that the control methods for such systems be robust to these uncertainties. Input shapers have been shown to yield good performance while being insensitive to modeling errors. Most previous input shaping studies, however, have addressed only frequency mod...

The S-System formalism provides a popular, versatile and mathematically tractable representation of metabolic pathways. At steady-state, after a logarithmic transformation, the S-System representation reduces into a system of linear equations. Thus, the maximization of a particular metabolite concentration or a flux subject to physiological constraints can be expressed as a linear programming (...

Simulation models are increasingly used to gain insights regarding the long-term effect of both direct and indirect anthropogenic impacts on natural resources and to devise and evaluate policies that aim to minimize these effects. If the uncertainty from simulation model projections is not adequately quantified and reported, modeling results might be misleading, with potentially serious implica...

the environmental rules of reverse logistic networks have caused important economic growth in the past decades. to integrate forward logistic networks with reverse logistics networks a helpful method is to design both networks simultaneously. considering more retrieval choices in modeling reverse logistic systems can be very critical. this article contains a mixed integer linear programming mod...