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The surface heat and moisture transfer from the human body are normally characterized by the thermal insulation and moisture vapor resistance, which are important parameters in environmental engineering.
Yang and Koziel (2011) provided a detailed description of application of GA for various engineering problems such as estimation of input parameters in environmental emergency modeling, simulation of behavior of concrete materials, and network optimization.
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Probabilistic uncertainty and imprecision in structural parameters and in environmental conditions and loads are challenging phenomena in engineering analyses.
Soil hydraulic parameters needed in environmental, hydrological or land-surface modelling vary according to the model used.
We then tested relationships between key demographic features and functional traits given the environment by predicting demographic rates from parameters in different environmental contexts.
Many QTL (with P ≤ 0.2) were identified for both the growth parameters in different environmental conditions (Table 1, Figure S1).
Preliminary studies quantifying various SAM parameters in diverse environmental conditions show intriguing plasticity at the level of cell cycle activity, core regulators and SAM size (Geier et al., 2008).
Results indicate that an extrapolation is feasible for selected parameters when changes in environmental conditions are small.
In yet another example, Bayesian methods including Markov chain Monte Carlo (MCMC) simulation and the Kalman filter are common approaches to calibrating model parameters for predictions in environmental systems.
Land surface temperature (LST), which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis.
Land surface temperature (LST) is a crucial parameter in investigating environmental, ecological processes and climate change at various scales, and is also valuable in the studies of evapotranspiration, soil moisture conditions, surface energy balance, and urban heat islands.
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