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The method is based on representing the scene as a set of 2D views and predicting the appearances of novel views by linear combinations of the model views.
This method, being less time consuming and hence more practical, employs only a small number of all the possible combinations of the model parameters to estimate the main effects and some interactions.
Fig. 4 Distribution of reduced (chi^{2}) with respect to the viscoelastic structure parameters: the colored star, triangles, and circles indicate the distribution of combinations of the model parameters, and their color indicates the value of the reduced (chi^{2}).
It has been shown that there are certain combinations of the model parameters depicting a remarkable dynamic behavior, in which the second to first resonance frequencies ratio is close to three.
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The metamodel type determines the design of the simulation experiment, which determines the input combinations of the simulation model.
We applied the Reversible-jump (RJ) Discrete Markov chain model [31] to the trait data to integrate the results over all possible combinations of the models.
We have combined the models by the very simple strategy of exhaustively looking for all the possible 2-model combinations of the models built from each of the pools of descriptors.
The naïve model combination of the Model 1 and Model 2 results improves recall at the expense of precision, the heuristic combination in provides the highest f-measure, and our high recall combination provides the highest recall.
The model with B = 0.09 year was obtained as the optimum, and this combination of the model parameters is also acceptable with respect to the best-fitted viscoelastic model according to a Chi-squared test.
The dynamic thermodynamic combination of the model gives the opportunity to instantly calculate a precise open-loop response, which is the essential part of designing proper load controllers for inherently unstable Stirling engines.
Furthermore, the combination of the model with the cloud-based WBAN allows performing a query processing algorithm that uses the error tolerance and the probabilistic confidence interval as query execution criterions.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com