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By sheer size, Microsoft's model considers both the highly probable and the exceedingly unlikely to account for attributes, sub-contexts and relationships.
Our model considers both scenarios.
The model considers both transportation and kinetics phenomena.
The proposed model considers both the saturation traffic and the non-saturation traffic.
Finally, the third model considers both connection and disconnection durations separately for periodic connections.
The corresponding state-space model considers both polytopic and norm-bounded uncertainties.
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The model considered both material nonlinearity and geometrical nonlinearity.
In this paper, we present a haze image model considering both sensor blur and noise.
So, the regression model considering both of them will be more reasonable.
First, the formal model considering both loaded and empty flows is given.
Association analysis was performed with the MLM model, considering both kinship (K) and population structure (Q), implemented in TASSEL software.
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