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The model is fed with some assumed data and the resulting output values of shear strength are studied.
The model is fed with the values of influencing parameters and resulting output values of shear strength are studied.
In the dereverberation stage, the well-trained DNN model is fed with the features of reverberant speech to generate dereverberated LPS features.
The T S fuzzy model is fed with its own states, which are indeed its past outputs, rather than the measurements from the plants.
The process model is fed with kinetic data of cyclooctene hydroformylation reaction kinetics (TU Eindhoven) and experimental data of OSN membrane permeation (Evonik Industries AG).
The link level-focused propagation model is fed with dedicated CIR measurements carried out in larger bandwidths than the system bandwidth, involving filtering and lower sampling rate processing to generate the adequate CIR model.
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The structures for the fragments and the initial seed model were fed into Modeller to generate 10 models, and the model with minimum energy was chosen as a refined model.
The estimates of volatility obtained by an EGARCH model are fed forward to a Neural Network.
Furthermore, to fairly compare the results, the channel model was fed with identical initial conditions (e.g., delays and mean power per path) for each evaluated interpolation factor.
The model was fed with real-world data and solved in order to check whether it actually reflects the planning problem.
The predictions of the energy model are fed into finite element simulations to provide the in-plane shear properties of two different macro-scale constitutive models implemented in the finite element codes.
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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