Sentence examples for constrained sampling from inspiring English sources

Unlike many current methods, the proposed approach does not require feasible initial point and can handle hard constraints via a novel optimization-based constrained sampling scheme.

Constrained sampling optimization problems conform a class of problems where only a part of the solution space is available from any point at any time.

Researchers evaluating NTMRs: a) ignored habitat or described sites as broadly similar (28.7%); b) constrained sampling to similar habitats (43.9%); c) explicitly tested for habitat differences among sites (12.8%); d) used statistical methods to partition habitat and reserve effects (26.2%); and e) examined changes in habitat caused by reserve protection (17.1%).

Results for assignment to genus using random versus constrained sampling of sub-libraries were very close in terms of overall accuracy, with constrained having slightly lower overall accuracy across all completeness levels.

This paper deals with how to modify the general strategy of evolutionary algorithms to address these constraints in an efficient manner and proposes extending their application to other problems that, even though, they are not strictly constrained sampling problems, restricting their sampling capabilities reduces the cost of the optimization procedure without affecting its results.

Where departures from monotonicity are not pronounced, one can impose monotonicity constrained sampling by rejecting any iterations t where ( sum limits_{mathrm{i}}{mathrm{m}}_{mathrm{i}mathrm{t}}

In both stages, we included MOHCA-seq data to constrain sampling.

In the present work we employed this useful occurrence for gel-processing/drawing of i-PP, yielding material with Young's moduli of 35 GPa, tensile strengths of approximately 1 GPa and melting temperatures measured for constrained samples as high as 228 °C.

Yet, these results are difficult to generalise as the vast majority of such studies were reported on constrained samples, mainly university students [23, 33].

Our ability to answer questions is hampered by a lack of sufficient data for many taxonomic groups, which is constrained by sampling biases, life-history characteristics of target species, and the lack of trained taxonomists.

To make the SVM more specific for distinguishing between genuine miRNA hairpin structures and miRNA-like structures we constrained the sampled structures by requiring that their sequence/structure features be within specific quantiles of the distributions observed for known miRNAs (detailed in Methods).