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Previous study on improving the frame complexity measure is based on modifying the MAD prediction.
The computation of the target bits relies on the estimation of the frame complexity using a linear MAD prediction of the previous frames.
For example, we also used the same temporal Mean Absolute Difference MADD) prediction method as JVT-G012, which has the following drawbacks: (a) inaccurate MAD prediction for sudden changes; (b) inaccurate bit allocation since the header bits of the current basic unit are predicted from previous encoded basic units.
Since the prediction does not consider the complexity of the current frame to be encoded, the MAD prediction is not an accurate estimate of the frame complexity, especially in complex sequences containing a lot of motion.
An optimised Mean Absolute Difference (MAD) prediction model for the spatial enhancement layers that considers both the MAD from the spatial base layer in the same frame and the MAD from the corresponding macroblock in previous frames is also proposed.
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LH: It's funny we agree on this — I loathe Harry, but my "Mad Men" plot predictions are always guided by Peggy's line, "Every time something good happens, something bad happens".
These statistical measures provide a threshold (IQR, MAD and THR) and prediction (LR and LRR) for a host to be identified as overloaded.
To obtain high confidence functional targets for each of the miRNAs, we set a cutoff of two median absolute deviations (mad) from the median prediction score of all miRNA-mRNA interactions.
Predictable predictions?
In the previous section we have compared our proposed algorithm with both thresholds based (MAD, IQR and THR) and prediction based approaches (LR and LRR).
But as I said in this collection of predictions about where "Mad Men" will end up, my hope for the man is that, as he goes forward, he makes a better class of mistakes.
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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