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These analyses were based upon Latin Hypercube Sampling (LHS), a sampling technique that enables us to make predictions using a range of parameter values for each parameter.
Figure 6 Comparison between the predicted APAR by Maestra and predictions using (a) Equation 7 (or 1) in Stand 5, (b) Equation 12 in Stand 4, (c) Equation 12 at the total stand level in Stand 5 and (d) Equation 12 at the species level in Stand 5.
The parameters were obtained by comparing experimental values with theoretical predictions using a constrained nonlinear least squares approach.
We will empirically test discrete-state and continuous model predictions using a task similar to eyewitness ID.
The historic wildfire hazards are plotted against model predictions using a scatter plot, and a linear regression curve is fitted.
We tested these predictions using a small mammal dataset recorded in 100 transects in a savanna region of Brazil.
Numerical model predictions using a three-layer electrical conductivity/moisture content profile agreed qualitatively with the observed acetate distribution.
Region dependent crack growth resistance was measured on SEVNB specimens and compared to theoretical predictions using a fracture mechanics model.
We test that and other predictions using a modification of the application folders design used in double standards research.
Model predictions using a quadratic surface for water content and % charred pieces were validated with an additional experiment.
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The thermal-model predictions using A-values obyainedifferenterent groups are compared in Fig. 4 along with the observed band ratios of all the C60 sources.
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