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The model we described above provides excellent performance, yet its main advantage is also a weakness, and this forms the underlying idea of this paper.
Also, the Pareto-Search Algorithm component uses historical data of the already executed jobs in order to create the job's execution time estimation model we described in Section 4.2.
This estimation was performed by adjusting a parametric survival model to our data, using the survreg function [21] in R. The parametric model we used has the same fixed and random factors than the non-parametric model we described above.
The model we described here provides but one approach for estimating foodborne illness and quantifying estimate uncertainty.
In the framework of this model we described conditions that promote the production of superoxide taking into account the effects of transient changes in distances between the cofactors caused by the movement of the FeS cluster [11].
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In Section System model, we describe our system model.
In section "System model", we describe the relaying system.
In Section "System model", we describe the system model for our simulation studies.
In the section 'Reference model', we describe a reference model employing GMMs instead of NMF.
In Section "System model", we describe the distributed network scheme model.
In Section 'System model', we describe the model adopted for the analysis and the system components (transmitter, channel, receiver).
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