• Title/Summary/Keyword: conditional sampling

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Application of Indicator Geostatistics for Probabilistic Uncertainty and Risk Analyses of Geochemical Data (지화학 자료의 확률론적 불확실성 및 위험성 분석을 위한 지시자 지구통계학의 응용)

  • Park, No-Wook
    • Journal of the Korean earth science society
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    • v.31 no.4
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    • pp.301-312
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    • 2010
  • Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.

BENZENE AND LEUKEMIA An Epidemiologic Risk Assessment

  • Rinsky Robert A.;Smith Alexander B.;Hornung Richard;Filloon Thomas G.;Young Ronald J.;Okun Andrea H.;Landrigan Philip J.
    • 대한예방의학회:학술대회논문집
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    • 1994.02a
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    • pp.651-657
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    • 1994
  • To assess quantitatively the association between benzene exposure and leukemia, we examined the mortality rate of a cohort with occupational exposure to benzene. Cumulative exposure for each cohort member was estimated from historical air-sampling data and, when no sampling data existed, from interpolation on the basis of existing data. The overall standardized mortality ratio (a measure of relative risk multiplied by 100) for leukemia was 337 (95 percent confidence interval, 154 to 641), and that for multiple myeloma was 409 (95 percent confidence interval, 110 to 1047). With stratification according to levels of cumulative exposure, the standardized mortality ratios for leukemia increased from 109 to 322, 1186, and 6637 with increases in cumulative benzene exposure from less than 40 parts per million-years (ppm-years), to 40 to 199, 200 to 399, and 400 or more. respectively. A cumulative benzene exposure of 400 ppm years is equivalent to a mean annual exposure of 10 ppm over a 40-year working lifetime; 10 ppm is the currently enforceable standard in the United States for occupational exposure to benzene. To examine the shape of the exposure-response relation, we performed a conditional logistic-regression analysis, in which 10 controls were matched to each cohort member with leukemia. From this model, it can be calculated that protection from benzene induced leukemia would increase exponentially with any reduction in the permissible exposure limit.

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Three-stage Sampling Inspection Plans (삼단계(三段階) 샘플링 검사방식(檢査方式))

  • Ryu, Mun-Chan;Bae, Do-Seon
    • Journal of Korean Institute of Industrial Engineers
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    • v.6 no.2
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    • pp.37-47
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    • 1980
  • A system of conditional sampling plans composed of three stages is developed. In the first stage, the decision to accept or reject the lot is based on the information obtained from the current lot. When a decision is not made in the first stage, a second stage is introduced and the information from the immediately preceding lot as well as the information from the current lot is used for the decision. When a decision is not made in the first stage, a second stage is introduced and the information from the immediately preceding lot as well as the information from the current lot is used for the decision. When a decision is not made in the second stage either, the decision is deferred until the information from the immediately following lot is obtained. Existing tables for constructing double sampling plans with $_2$=$2n_1$ can be used to find the parameters of these plans. These sampling plans can bring sizable savings in the amount of inspection when the process is relatively stable. The response delay to the change in process quality and the deferred events may be considered as shortcomings of these plans. However, these are not serious in practical applications, and the reduction in sample size may more than offset these shortcomings.

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Modelling and Simulating the Spatio-Temporal Correlations of Clustered Wind Power Using Copula

  • Zhang, Ning;Kang, Chongqing;Xu, Qianyao;Jiang, Changming;Chen, Zhixu;Liu, Jun
    • Journal of Electrical Engineering and Technology
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    • v.8 no.6
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    • pp.1615-1625
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    • 2013
  • Modelling and simulating the wind power intermittent behaviour are the basis of the planning and scheduling studies concerning wind power integration. The wind power outputs are evidently correlated in space and time and bring challenges in characterizing their behaviour. This paper provides a methodology to model and simulate the clustered wind power considering its spatio-temporal correlations using the theory of copula. The sampling approach captures the complex spatio-temporal connections among the wind farms by employing a conditional density function calculated using multidimensional copula function. The empirical study of real wind power measurement shows how the wind power outputs are correlated and how these correlations affect the overall uncertainty of clustered wind power output. The case study validates the simulation technique by comparing the simulated results with the real measurements.

Prediction of Wall Shear Stresses in Transitional Boundary Layers Using Near-Wall Mean Velocity Profiles

  • Jeon, Woo-Pyung;Shin, Sung-Ho;Kang, Shin-Hyoung
    • Journal of Mechanical Science and Technology
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    • v.14 no.11
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    • pp.1305-1318
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    • 2000
  • The local wall shear stress in transitional boundary layer was estimated from the near-wall mean velocity data using the principle of Computational Preston Tube Method(CPM). The previous DNS and experimental databases of transitional boundary layers were used to demonstrate the accuracy of the method and to provide the applicable range of wall unit y(sup)+. The skin friction coefficients predicted by the CPM agreed well with those from previous studies. To reexamine the applicability of CPM, near-wall hot-wire measurement were conducted in developing transitional boundary layers on a flat plate with different freestream turbulence intensities. The intermittency profiles across the transitional boundary layers were reasonably obtained from the conditional sampling technique. An empirical correlation between the representative intermittency near the wall and free parameter K$_1$of the extended wall function of CPM has been newly proposed using the present and other experimental data. The CPM has been verified as a useful tool to measure the wall shear stress in transitional boundary layer with reasonable accuracy.

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Investigation of Biases for Variance Components on Multiple Traits with Varying Number of Categories in Threshold Models Using Bayesian Inferences

  • Lee, D.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.15 no.7
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    • pp.925-931
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    • 2002
  • Gibbs sampling algorithms were implemented to the multi-trait threshold animal models with any combinations of multiple binary, ordered categorical, and linear traits and investigate the amount of bias on these models with two kinds of parameterization and algorithms for generating underlying liabilities. Statistical models which included additive genetic and residual effects as random and contemporary group effects as fixed were considered on the models using simulated data. The fully conditional posterior means of heritabilities and genetic (residual) correlations were calculated from 1,000 samples retained every 10th samples after 15,000 samples discarded as "burn-in" period. Under the models considered, several combinations of three traits with binary, multiple ordered categories, and continuous were analyzed. Five replicates were carried out. Estimates for heritabilities and genetic (residual) correlations as the posterior means were unbiased when underlying liabilities for a categorical trait were generated given by underlying liabilities of the other traits and threshold estimates were rescaled. Otherwise, when parameterizing threshold of zero and residual variance of one for binary traits, heritability estimates were inflated 7-10% upward. Genetic correlation estimates were biased upward if positively correlated and downward if negatively correlated when underling liabilities were generated without accounting for correlated traits on prior information. Residual correlation estimates were, consequently, much biased downward if positively correlated and upward if negatively correlated in that case. The more categorical trait had categories, the better mixing rate was shown.

Testing Independence in Contingency Tables with Clustered Data (집락자료의 분할표에서 독립성검정)

  • 정광모;이현영
    • The Korean Journal of Applied Statistics
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    • v.17 no.2
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    • pp.337-346
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    • 2004
  • The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

Seismic Safety Assessment of Containment Building (격납건물의 내진안전성 평가)

  • Lee, Seong-Lo;Bae, Yong-Gwi
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.8 no.3
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    • pp.225-233
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    • 2004
  • In this study, the seismic safety of containment building is assessed using response surface method. The structural analyses considering random variables such as load, resistance and analysis by ABAQUS are performed to obtain the structural response. The structural response is represented by polynomial of random variables, and the reliability analysis is performed by Level II method. Drucker-Prager failure criterion is applied as limit state function to take bi-axial stress states into account in the concrete. The lifetime probability of failure is evaluated by considering the lifetime of containment building, the annual occurrence rate of earthquake and the conditional probability of failure. Also the sensitivity analysis on the selection of sampling points is performed to obtain the steady results from response surface method.

An Investigation of the Coherent Structures in Turbulent Wake Past a Stationary and Rotating Cylinder (정지 및 회전하는 원주에 의한 난류후류의 응집구조)

  • 부정숙;이종춘
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.18 no.5
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    • pp.1310-1321
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    • 1994
  • Turbulent coherent structures in the intermediate wake of a stationary and rotating cylinder, spin rate S=0.7, situated in a uniform were experimentally investigated using a conditionalphase average technique. Measurements were carried out at a section of 8.5 diameters downstream form the center of cylinder and a Reynolds number of $Re=6.5{\times}10^{3}.$/TEX> The phase averaged velocity and velocity vector fields, contours of vorticity, turbulent intermittency function and velocity fluctuation energy are presented and discussed in relation to the large scale coherent structures by Karman vortices that shed periodically from the cylinder. Coherent wake structures of the rotating cylinder is almost identical with stationary cylinder, but the lateral displacement and shrinkage of turbulent wake region is occured by rotation. Rotation of the cylinder result in that the deflection of wake center to deceleration region(Y/D${\simeq}-0.3)$ and the decrease of mean velocity defect(10%), vorticity strength of large scale structures(19%), total velocity fluctuation energy(12%).

A Study on the Identification of Risk Factors for unplanned Readmissions in a University Hospital (계획되지 않은 재입원에 대한 위험요인분석)

  • Hwang Jeong Hae;Rhee Seon Ja
    • Journal of Korean Public Health Nursing
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    • v.16 no.1
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    • pp.201-212
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    • 2002
  • This study was designed to identify the risk factors of unplanned readmission in a university hospital. The six-month discharge information from January to June, 2000 in a tertiary university hospital was used as a source of data through the medical record and hospital information system. To increase the effect of comparison. the data were collected by sampling 192 couples (384 patients) of unplanned readmission group through the matching by its disease groups, sex, and age. The accuracy of prediction for unplanned readmission was analyzed by constructing the predicted model of unplanned readmission through the logistic regression. The study results are as follows. The conditional logistic regression analysis was performed with nine variables at the significance level 0.05 through univariate analysis including residence, days after discharge, initial admission route, previous admission, transfer to special care unite, hospital stay days, medical care expenses, special cares, and laboratory and imaging services. As a result, the closer the patients live in Seoul and Gyeong-in area (Odds ratio=2.529, p=0.003), the shorter the days after discharge was (Odds ratio=0.600, p=0.000), and the more frequent admission rate was (Odds ratio=2.317, p=0.004), the more unplanned readmission was resulted. Also, the accuracy of prediction for data classification of this regression model showed $70.3\%$(032+83/306).

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