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In this study, we developed and evaluated methodologies for quantifying aboveground carbon (AGC) stocks affected by mountain pine beetle using field observations, lidar data, and multispectral imagery.
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Evaluation results indicate that the evaluated methodology achieves a level of accuracy higher than 96% (with TPR above 0.95 and FPR approximately 0.1), which slightly improves the results in previous studies that use byte n-gram representation.
Here we followed previously evaluated methodology described in detail elsewhere (Mah et al., 2012), implemented in SPM8 (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) and custom MATLAB (http://www.mathworks.co.uk/products/matlab/) scripts.
Today, researchers are evaluating methodologies for determining which patients should receive generalized care vs. specialized care, while others continue to study further treatment adaptations for patients with complex dual diagnoses.
This review is part of a series of reviews on behalf of the Prevention of Falls Network Europe (ProFaNE) which evaluate methodology in RCTs of fall prevention interventions in older adults.
Our main objective was to propose and evaluate methodology that takes advantage of any potential sparsity in the inverse of A22 in order to reduce the computing time required for its inversion.
In the absence of evidence in adult populations, this study evaluated the methodologies from studies that targeted general physical activity in community settings, including workplaces.
We evaluated our methodology in different ranking and regression settings.
We proposed, applied, and evaluated a methodology based on graphic oracles to test a segmentation scheme used in [17].
We evaluated our methodology with three test cases: protein targets of pharmaceutical relevance with a variety of binding site characteristics.
Neither study evaluated their methodology compared with other administrative algorithms.
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