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However, the CN methods generated higher water yields to streams than the G&A method.
However, for both databases, the majority of the machine learning methods generated higher mean accuracies (with lower variance) than any of the semi-quantification approaches.
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In addition, old and inefficient farming methods generate higher need to groundwater.
However, as information technology improves, the informational advantage diminishes; the opportunity costs of managers' bargaining eventually dominate, and cost-based methods generate higher profits.
These methods generate high-level profiles from sequences to represent and determine protein catalytic functions.
However, it has been observed that the aggregation of different network inference methods generates high-quality robust results (Marbach et al., 2012).
The method generates high-quality layouts, showing mostly overlap-free solutions with molecules which are displayed as structure diagrams providing interaction information in atomic detail.
In addition, Kamae et al. (1998) proposed a new hybrid technique that combined the stochastic method generating high-frequency motions with the long-period motions calculated by the 3D finite-difference method to simulate the broadband near-fault ground motions.
Numerical examples show that the proposed method generates high quality meshes as measured both in terms of element characteristics and in terms of orthogonality at the boundary and overall smoothness, when compared to other known methods.
Since the presented interactive algorithm allows to control the distance between a pair of nodes depending on the curvature of the NURBS surface, the method generates high quality triangular mesh.
First, this method generates high quality multiple sequence alignments that can be used for phylogenetic reconstructions as well as for diversity measures such as the identification of OTUs.
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