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In our study, the cost modeling approach presented in [5] is extended to include the allocation of unused capacity.
The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states.
The nonlinear mixed-effects modeling approach presented here can be used to describe not only the overall population, but also the tumor dynamics of each individual patient.
The basic modeling approach presented here follows that of the latter paper.
The idea behind the control-oriented model of underwater snake robot locomotion is based on the simplified modeling approach presented in [6, 49] for a land-based snake robot.
The Q-2D modeling approach presented here is validated by comparing the predicted interlaminar stresses with corresponding 3D models and previously published data.
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The wave modeling approaches presented in [17, 18] rely on computationally intensive procedures that result in processing times that can range from several minutes to a couple of days [17, 18], resulting in low data throughput rates.
Using the geospatial modeling approaches presented here, we can provide preliminary assessments of the likely contributors that underlie the partitioning of chimpanzee population genetic diversity: Riverine barriers and environmental variation.
The predictive model approach presented in this study is quite satisfactory in predicting surface roughness results during hard turning of AISI 52100 steel.
Different degrees of modelling sophistication were employed: (A) the analytical calculations described in the Society of Fire Protection Engineers SFPEE) handbook, (B) an individual use of evacuation models and (C) a multi-model approach, presented in this paper for the first time.
In this paper, a neural network modeling approach is presented for the prediction of surface roughness (Ra) in CNC face milling.
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