This paper introduces a modification to genetic algorithms which provides computational support to creative designing by adaptively exploring design structure spaces. This modification is based on the re-interpretation of the GA's crossover as a random sampling of interpolations and its replacement with the random sampling of direct phenotype-phenotype interpolation and phenotypephenotype extra...

This article presents an application of the jackknifing re-sampling approach (Efron, 1982) to error variance estimation for ability distributions of groups of students, using a multidimensional discrete model for item response data. The data utilized to examine the approach came from the National Assessment of Educational Progress (NAEP). In contrast to the operational approach used in NAEP, wh...

Aim To utilize comprehensive geographical sampling and a new, multilocus dataset to re-examine the biogeography of spotted stream frogs (Hylarana signata complex) throughout Southeast Asia. To compare patterns of diversification among stream frog populations on land-bridge islands and oceanic islands and to re-evaluate a previous ‘dual-invasion’ hypothesis for the origins of endemic Philippine ...

To train accurate deep object detectors under the extreme foreground-background imbalance, heuristic sampling methods are always necessary, which either re-sample a subset of all training samples (hard methods, e.g. biased sampling, OHEM), or use but re-weight them discriminatively (soft Focal Loss, GHM). In this paper, we challenge necessity such hard/soft for detectors. While previous studies...

crop insurance is a main tool for coping up with different adversities in farming. the purpose followed in this study was to identify the major motivating and determinant factors of re-purchase of crop insurance by and among already insured farmers. survey research and multi sectional sampling procedures employed used to select farmers. the sample consisted of two groups of farmers: 1) currentl...

The eeects of randomly sampled training data on genetic programming performance is empirically investigated. Often the most natural, if not only, means of characterizing the target behaviour for a problem is to randomly sample training cases inherent to that problem. A natural question to raise about this strategy is, how deleterious is the randomly sampling of training data to evolution perfor...

Sampling is the process of collecting, analysing, and interpreting data in order to test hypotheses and provide needed information for intelligent decisions. Sampling is an attractive alternative to complete enumeration. Instead of measuring or recording all members of a population of interest, one concentrates on a representative proportion, objectively selected, to estimate desired characteri...