The scheme we developed is based on two supports: well-balanced treatment of the variable updating at the new time-level and flux evaluation by three-wave approximations of the intercell Riemann-problem that, without any split, embody the effect of the non-conservative term.
In SNPs3D, the classification into in vivo functional impact categories of the SNP was based on two Support Vector Machine (SVM) models: protein sequence conservation profiling and protein structure stability.
Each of the 31,007 reference-inconsistent loci was assessed based on three support characteristics, each with a corresponding bit value: assembly support (+4), multi-source support (+2), and long-read force calling (+1).
Markers were then called as N. vitripennis (V), N. giraulti (G), or ambiguous (U) based on three parameters (supporting information, File S1).
In this paper, we extend our previous system with new functions based on our two supporting approaches.
This work proposes efficient scheme rainfall estimation based on two multiclass support vector machine (SVM) algorithms: SVM_D for daytime and SVM_N for night time rainfall estimations.
The agreement of age estimates based on two different methods supports the age models derived for Sites U1427 and U1424, and the inter-site correlation of JS sites.
To this end, we develop an experimental system based on two functionally different support cells differing in their ability to support the development of B-lineage cells from immature hematopoietic progenitor cells.
The association rules are evaluated based on two measures namely, support and confidence.
As a new strategy within the nervous system tissue engineering, multifunctional systems based on two different biomaterials to support axonal guidance in damaged connective tracts have been developed herein.
