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A model for kernel migration based on vapor transport by CO was used to semi-quantitatively assess the effect of controlling oxygen potential with SiC or ZrC and demonstrate the potential dramatic effect of the addition of these phases on carbon transport.
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Mathematical models for kernel drying predict grain air mass and heat transfer rates, and the faster and more accurately they can do this the better, especially in simulation-based design and control.
In this paper we give an overview of already available kernels, establish a performance model for each kernel, and show a comparison of implementations and recent architectures.
Bartel et al. proposed a method for equating emphysema measurements using a mathematical model to convert values between different kernels, requiring the construction of a model for every kernel separately [ 17].
We used the estimated propensity scores from the resulting model for the kernel and local linear matching estimators and for IPW.
A major part of the work is the development of an efficient search procedure for computing stable models for this kernel language.
In this paper, we describe the reversibility of our previously reported descriptor, the vector space model molecular descriptor (VSMMD) based on a vector space model that is suitable for kernel studies in QSAR modeling.
VSMMD is based on a vector space model that is suitable for kernel studies in QSAR modeling.
Using the Hα and CaII 8542 Å line profiles and the non-LTE calculation, we obtain the semi-empirical atmospheric model for the bright kernel of the MF.
Toward this goal, we introduce a systematic methodology to derive reliable time and power models for algebraic kernels employing a bottom-up approach.
For a successful SVM model, the kernel parameters for SVM and feature subset selection are the most important factors affecting prediction accuracy.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com