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Simplified models were derived to estimate the transfer coefficients.
The stress strain curves at various strain rates were derived to investigate the strain rate sensitivity.
Semi-empirical equations were derived to describe the wall-jet performance.
Some mathematical relationships were derived to show the quantitative increase in irrigation efficiency under deficit irrigation.
Logistic regression models were derived to indicate the probability of entering the restaurant.
Polynomial models were derived to describe the relationships between properties and glass composition.
Models were derived to understand the impact of mix design on performance and for optimization.
Two simple parameters were derived to represent succession rate or change extent.
Probabilistic distribution functions and histograms were derived to assess GCM modelling uncertainty on future irrigation needs.
Subsequently, a 14-step and a 15-step ARMs were derived to account for NO formation.
Using the drive-response concept, the control laws were derived to achieve the synchronization of two identical chaotic neural networks.
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