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The DVC-MCFI codec is rather similar to the DISCOVER DVC codec: the only differences regard the LDPC syndrome codec [27] adopted in the DVC-MCFI codec and the sub-pel motion vector accuracy adopted in the DISCOVER DVC codec.
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Fig. 5 Radial basis kernel function experiment result Figure 5 shows that using the RBF radial basis as kernel function to obtain the SVM model results in 48 iterative calculations, made up of 62 support vectors; the accuracy of using the file tr1.model to classify the 63 test samples was higher than the polynomial kernel function, with the classification accuracy of about 87.3016%%.
With the availability of additional samples and inclusion of more clinical and topological feature vectors, the accuracy of this prediction model may be enhanced.
By use of a support vector machine, diagnostic accuracy of 74% was achieved with Raman, while the same classifier showed 93.3% accuracy for ATR-IR spectra of blood plasma, demonstrating the enhanced sensitivity and specificity of the ATR-FT-IR technique.
It allows to decide an estimation problem of state vector with given accuracy by finite gains.
Subpixel motion estimation finds the optimal motion vector with subpixel accuracy around the integer motion vector.
Fig. 6 Relation between the composition of the feature vector and classification accuracy.
Results reveal the relation between the feature vector and classification accuracy.
In the following, we start with the feature vector solution, the accuracy measure and then we give details on the three local search methods for feature selection.
DNA sequencing of the recombinant vector confirmed the accuracy of the reading frame of IL-25.
8 The method of analysing the eye rotation vector and its accuracy have already been described elsewhere.
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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