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This modelling approach enables to provide a predictive model involving very rapid calculation.
The level of detail provided by our modelling approach enables the definition of a new risk metric, the exposure count, which directly quantifies the threat to a population.
In addition, the empirical modelling approach enables confidence bounds on the predicted GWLs and SGI values to be estimated without the need for prior information about catchment or aquifer parameters.
However, the structural equation modelling approach enables me to consider the problem in a different way.
However, this modelling approach enables us to separate the real effect of temperature on plant traits by taking into account the effect of time as a random factor.
In conclusion, although further validation is necessary, the results clearly indicate that the present modelling approach enables design of a useful decision system for planning transfusion needs in patients after heart surgery.
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This tradeoff relationship, which is easily explored using the spatial resource allocation modeling approach, enables an MPA design to allow decision makers to select various non-inferior solutions to meet their decision preferences.
The main conclusion in the paper is that due to the low computation time, the convex modeling approach enables optimization of problems with two or more state variables, e.g. allowing for thermal models of the components; or to include more sizing variables, e.g. sizing of the engine and the electric machine simultaneously.
Additionally, modelling approaches enable eloquent exploration of large-scale and long-term datasets to test predictions and ultimately construct further hypotheses.
We chose to analyze the five probe means for each gene, rather than take an overall mean (or median), because our mixed-model approach enabled us to consider all this information in the model rather than discard the variation that may be present among different probes targeting the same gene.
This paper introduces a novel modelling approach to geometric skeleton computation enabling concurrent product engineering and assembly sequence planning.
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