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We have introduced a network based method to perform partial correlation analysis of multivariate data.
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Particle filter is a kind of powerful and effective simulation-based method to perform optimal state estimation in nonlinear non-Gaussian state-space models.
Therefore, we propose to use a GA-based method to perform load balancing and a sliding window technique to initialize a population of tasks on which the GA will be applied [6].
Although there have been a lot of work on using vision-based method to perform registration for indoor AR system, it is very difficult to apply such registration method for outdoor AR system due to the inability to modify the objects in outdoor environment and the huge range of working area.
We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell.
In this paper, we extend the original Kohonen SOM network to include a contiguity-constrained clustering method to perform clustering based on the output map generated by the network.
A practical method to perform these corrections based on the theoretical models is developed.
This paper presents a gap metric based method which aims to perform the operating range decomposition and the minimum linear model bank determination of a nonlinear system when multilinear model approach is employed to design a controller for this nonlinear system.
Comparisons between the proposed framework and Edgeworth expansions based method are also performed to illustrate the advantage of the proposed framework.
Figure 2 is in linear scale for the y-axis, and a log scale is used for the y-axis in Figure 3 to see the difference clearly in the low SNR regime, It is observed that the selection based methods perform similarly to the optimal (exhaustive) method.
The results reveal that the proposed rule-based ST and AdaBoost based method performs better than the other methods viz., SVM and Decision Tree (DT), under varied noise conditions as well as under varied amount of data used for training.
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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