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Originally presented in Ref. [1], where it was applied to implicit nonlinear structural-dynamics models, this method is further developed here and applied to the solution of a benchmark turbulent viscous flow problem.
When compared with other existing boundary models, this method involves a simpler algorithm and exhibits a comparable or even better accuracy in describing flow field and flow-structure interaction, as demonstrated by several test simulations.
In contrast to other parametric models, this method is based on meaningful and intuitive parameters like the detection limit, the dilution factor and the saturation level.
Instead in Grzegorczyk et al. (2008), an allocation sampler is used in combination with Bayesian Networks to assign each observation to a group, but unlike changepoint models, this method treats the observations as being exchangeable, ignoring the fact that the data are sequential.
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In relation to the system model, this method allows estimation of its parameters.
When combined with 4-gram de-lexicalized language model, this method achieved an accuracy of 80.1% on binary pitch accent classification and 89.6% on boundary detection.
Even though it restricts the problem model, this method is advantageous in that it finds an optimal solution in a reasonable computation time.
Based on reference models and knowledge modelling, this method requires the definition of a collaborative information system to assist design actors.
Given an object and a kinematic hand model, this method can easily be used to build a library of the corresponding object possible grasps.
Comparing to the previous method base on parametric fan model, this method has advantages of better accuracy, stronger robustness and higher efficiency under various conditions of fan characteristics and disturbances.
Due to the strong symmetry of the signal model, this method achieves linear phase filter banks with equal delay for all the derivative estimates, which are very useful in applications where synchronized derivative of a bandlimited signal are desired.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com