scholarly journals Metamodel Defined Multidimensional Embedded Sequential Sampling Criteria

2004 ◽  
Author(s):  
Cameron J. Turner ◽  
Matthew I. Campbell ◽  
Richard H. Crawford
Keyword(s):  
Sequential Sampling ◽  
Sampling Techniques ◽  
Convergence Criteria ◽  
Preliminary Results ◽  
Planar Functions ◽  
Level Of Confidence ◽  
Higher Dimensional

Collecting data to characterize an unknown space presents a series of challenges. Where in the space should data be collected? What regions are more valuable than others to sample? When have sufficient samples been acquired to characterize the space with some level of confidence? Sequential sampling techniques offer an approach to answering these questions by intelligently sampling an unknown space. Sampling decisions are made with criteria intended to preferentially search the space for desirable features. However, N-dimensional applications need efficient and effective criteria. This paper discusses the evolution of several such criteria based on an understanding of the behaviors of existing criteria, and desired criteria properties. The resulting criteria are evaluated with a variety of planar functions, and preliminary results for higher dimensional applications are also presented. In addition, a set of convergence criteria, intended to evaluate the effectiveness of further sampling are implemented. Using these sampling criteria, an effective metamodel representation of the unknown space can be generated at reasonable sampling costs. Furthermore, the use of convergence criteria allows conclusions to be drawn about the level of confidence in the metamodel, and forms the basis for evaluating the adequacy of the original sampling budget.

scholarly journals Generic Sequential Sampling for Metamodel Approximations

2003 ◽  
Author(s):  
Cameron J. Turner ◽  
Matthew I. Campbell ◽  
Richard H. Crawford
Keyword(s):  
Sequential Sampling ◽  
Multivariate Data ◽  
Sampling Strategy ◽  
Sampling Techniques ◽  
Data Sets ◽  
B Spline ◽  
Intelligent Sampling ◽  
Kriging Metamodel ◽  
Data Search ◽  
New Type

Metamodels approximate complex multivariate data sets from simulations and experiments. These data sets often are not based on an explicitly defined function. The resulting metamodel represents a complex system’s behavior for subsequent analysis or optimization. Often an exhaustive data search to obtain the data for the metamodel is impossible, so an intelligent sampling strategy is necessary. While multiple approaches have been advocated, the majority of these approaches were developed in support of a particular class of metamodel, known as a Kriging. A more generic, commonsense approach to this problem allows sequential sampling techniques to be applied to other types of metamodels. This research compares recent search techniques for Kriging metamodels with a generic, multi-criteria approach combined with a new type of B-spline metamodel. This Bspline metamodel is competitive with prior results obtained with a Kriging metamodel. Furthermore, the results of this research highlight several important features necessary for these techniques to be extended to more complex domains.

“Sequential Sampling” Strategy Optimises the Use of Two Endoscopic Ultrasound (EUS)-Guided Tissue Sampling Techniques

2005 ◽  
Vol 61 (5) ◽  
pp. AB269
Author(s):  
George K. Anagnostopoulos ◽  
Steve P. Pereira ◽  
Abed M. Zaitoun ◽  
Krish Ragunath ◽  
Guruprasad P. Aithal
Keyword(s):  
Endoscopic Ultrasound ◽  
Sequential Sampling ◽  
Sampling Strategy ◽  
Sampling Techniques ◽  
Tissue Sampling

scholarly journals THE EFFECT OF KANGAROO METHOD ON IMPROVEMENT BODY WEIGHT ON LOW BIRTH WEIGHT

2021 ◽  
Vol 4 (3) ◽  
pp. 241
Author(s):  
Yeni Riskawati ◽  
Martono Tri Utomo ◽  
Pudji Lestari
Keyword(s):  
Body Weight ◽  
Sequential Sampling ◽  
Total Sample ◽  
Study Cohort ◽  
Sampling Techniques ◽  
Neonatal Mortality Rate ◽  
Kangaroo Care ◽  
Significant Difference ◽  
Measurement Results ◽  
Maintain Body Temperature

AbstractBackground: In Indonesia the Neonatal mortality rate was 15 infants per 1000 births and in Surabaya in 2018 LBW deaths were 50 per 1000 live births, while in Haji General Hospital the LBW deaths were 12 babies in 1 year. Kangaroo care was the most effective way to meet the basic needs of LBW. Babies with 1500-2500 grams body weight either due to prematurity or small pregnancy period will lose weight ranging from 10-15% in 7 days of life. To overcome the problem Kangaroo care method4 component aims to promote weight loss, maintain body temperature remains stable and facilitate breastfeeding Methods: The method of this study was observational analytic with the design of the study cohort. Total sample of 40 LBW with sampling techniques using Sequential Sampling in the period August-October period 2019. Variabel was free kangaroo care method  given 1-2 times a day with a duration of more than 120 minutes. The dependent variable was increased in body weight carried out 3x the measurement. Results: The results of the study using paired T test showed an increase in body weight, namely 1) the first measurement of 31.82 grams for 3 days with p = 0.037, 2) the second measurement increased by 227.15 for 7 days, with p = 0,000, 3) the third measurement was 258.97 with p = 0,000. The conclusion: of the studied, that there were a significant difference between the kangaroo method treatments for weight gain in LBW in the NICU Room Haji Hospital Surabaya

DEVELOPMENT OF SAMPLING TECHNIQUES FOR THE SPRUCE BUDMOTH, ZEIRAPHERA CANADENSIS MUT. AND FREE. (LEPIDOPTERA: TORTRICIDAE)

1987 ◽  
Vol 119 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Jean J. Turgeon ◽  
Jacques Régnière
Keyword(s):  
New Brunswick ◽  
Sequential Sampling ◽  
White Spruce ◽  
Sampling Techniques ◽  
Growth Reduction ◽  
Density Estimates ◽  
Sample Unit ◽  
Sequential Sampling Plan ◽  
Branch Segment ◽  
Eggs And Larvae

AbstractThe spatial and statistical distribution of Zeiraphera canadensis Mut. and Free. (spruce budmoth) within the crown of white spruce (< 4 m high) was investigated in northern New Brunswick. A 15-cm branch segment, measured distally from the scales of the branch’s apical growth and taken from the upper one-third of the crown, is considered an adequate sample unit for density estimates of spruce budmoth eggs and larvae. Sample sizes required to estimate spruce budmoth larval densities with given levels of precision and confidence were determined. A sequential sampling plan to classify spruce budmoth populations as low or high (potentially leading to growth reduction and deformed leaders in white spruce) was also developed.

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