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Progressive sampling distances across the BS were used, i.e. from the top to the base of the BS by using proportional distances, i.e. 20 100% for large BS and 50 100% for the smallest BS, and these were compared with two types of control soil, 120% or 150% in the case of large and small BS, respectively, and soil sampled 1 m away from the BS.
Progressive sampling, on the other hand, focuses more on minimizing the amount of computation for a given performance target.
For instance, Provost et al. proposed progressive sampling using a geometric progression-based sampling schedule [ 31].
Other forms of sampling, including clustered and nested sampling as well as progressive sampling including spatially adaptive sampling, are described.
We then empirically show that the adaptive approach is faster and produces accurate models for circuit simulators as compared to other techniques such as progressive sampling and Artificial Neural Networks.
These strategies included reducing the size of the population during the evolution process of the genetic algorithm, reducing the fitness computation time of individuals in the genetic algorithm using progressive sampling for finding the (near) optimal sample size of the training data, and parallelization of individual fitness computation in each generation.
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Additionally, to map the genetic alterations occurring during progression, we assessed CNAs within the progressive samples from each patient.
First, within the bundle adjustment, erroneous matches are usually discarded by the random sample consensus (RANSAC) [14] or its extensions, progressive sample consensus (PROSAC) [15], and preemptive RANSAC [16].
A median expression profile of progressive samples was computed from these differential genes.
We observed an average of 113, 61, 153 and 178 significant change calls (P < 0.001) in sequential progressive samples of mild (n = 4), moderate (n = 3), severe (n = 6) leukoplakia and OSCCs (n = 25), across all patients.
Other studies have identified large chromosomal regions and LOH events in dysplasias and OSCCs, but did not characterize such changes in sequential, progressive samples from same patients (12– 13, 43, 65).
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