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The paper extends weighted essentially non-oscillatory (WENO) methods to three dimensional mixed-element unstructured meshes, comprising tetrahedral, hexahedral, prismatic and pyramidal elements.
After applying the code bias correction methods to three types of BDS satellites, the systematic variations are not obvious and the resulting MW time series become much more stable and closer to the zero.
We introduce the applications of hybrid intelligent methods to three common problems that arise in bioinformatics, that is, feature selection, parameter estimation, and molecular network/pathway reconstruction.
The applicability of these methods to three sampling strategies commonly deployed in marine population genetic studies is summarized in Box 2. Below, we briefly describe their broad properties rather than providing an exhaustive catalog, highlighting why both types of dispersal inference methods may be limited in their application for many marine species.
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Figure 8 Applications of the proposed and Bresson et al.'s methods to four infrared images.
Finally, we apply the proposed methods to two real sequencing datasets to demonstrate their utilities.
We applied our methods to two sets of mouse QTL identified from a public database.
We applied classification, clustering, and feature selection methods to eight datasets in this work (Table 1).
Additionally, we applied these three methods to two datasets using protein-level alignments which we inferred using BLAST+/tblastx.
To further demonstrate the utility of the proposed method, we applied the methods to two datasets: pine and maize.
In this section we apply our methods to two contrasting examples and we discuss the results that we obtain.
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