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For the limitations above, in this paper, we proposed a strategy of dataset remodeling by transferring parameters of ResNet-101 layers trained on the ImageNet dataset to initialize learning model and adopt an augmented data variation approach to overcome the overfitting challenge of sample deficiency.
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This showed that our concern about transferring parameter sensitivity to the adaptation equation was not unfounded and that it has a natural geometric interpretation.
Liang, Z. X., Tsigos, I., Bouriotis, V. & Klinman, J. P. Impact of protein flexibility on hydride-transfer parameters in thermophilic and psychrophilic alcohol dehydrogenases.
First, a series of single-column experiments were performed to determine the mass-transfer parameters and to validate the adsorption isotherm and mass-transfer parameters at 30 °C.
Aerodynamic characteristics as well as heat transfer parameters such as wall heat transfer coefficients were investigated.
The model has two mass transfer parameters, estimated after injections of a tracer.
Currently, the uncertainty in these mass transfer parameters results in the addition of large safety factors.
Exergy efficiencies are derived as functions of heat and mass transfer parameters.
Mass transfer parameters were used to accurately predict IgG breakthrough in packed bed mode.
Effect of pressure and entrance temperature on heat transfer parameters is also considered.
Scaled sensitivity coefficients were calculated to assess simultaneously estimation of a number of mass transfer parameters.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com