• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.2
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• pp.1-8
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• 2019

Optimal path planning refers to find the safe route to the destination at a low cost, is a major problem with regard to autonomous navigation. Sampling Based Planning(SBP) approaches, such as Rapidly-exploring Random Tree Star($RRT^*$), are the most influential algorithm in path planning due to their relatively small calculations and scalability to high-dimensional problems. $RRT^*$-Smart introduced path optimization and biased sampling techniques into $RRT^*$ to increase convergent rate. This paper presents an improvement plan that has changed the biased sampling method to increase the initial convergent rate of the $RRT^*$-Smart, which is specified as m$RRT^*$-Smart. With comparison among $RRT^*$, $RRT^*$-Smart and m$RRT^*$-Smart in 2 & 3-D environments, m$RRT^*$-Smart showed similar or increased initial convergent rate than $RRT^*$ and $RRT^*$-Smart.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.103-129
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• 2019

The main goal of a case-control study is to learn the association between various risk factors and a primary outcome (e.g., disease status). Particularly recently, it is also quite common to perform secondary analyses of the case-control data in order to understand certain associations between the risk factors of the primary outcome. It has been repeatedly documented with case-control data, association studies of the risk factors that ignore the case-control sampling scheme can produce highly biased estimates of the population effects. In this article, we review the issues of the naive secondary analyses that do not account for the biased sampling scheme, and also the various methods that have been proposed to account for the case-control ascertainment. We additionally compare the results of many of the discussed methods in an example examining the association of a particular genetic variant with smoking behavior, where the data were obtained from a lung cancer case-control study.

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.683-688
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• 2006

We have developed a program for generating shotgun data sets from known genome sequences. Generation of synthetic data sets by computer program is a useful alternative to real data to which students and researchers have limited access. Uniformly-distributed-sampling clones that were adopted by previous programs cannot account for the real situation where sampled reads tend to come from particular regions of the target genome. To reflect such situation, a probabilistic model for biased sampling distribution was developed by using an experimental data set derived from a microbial genome project. Among the experimental parameters tested (varied fragment or read lengths, chimerism, and sequencing error), the extent of sequencing error was the most critical factor that hampered sequence assembly. We propose that an optimum sequencing strategy employing different insert lengths and redundancy can be established by performing a variety of simulations.

• Journal of Integrative Natural Science
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• v.9 no.1
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• pp.67-71
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• 2016

The university president direct election system in Korea had begun in 1987 as a movement of college democratization in the 1980s after 6.29 Declaration. Since then, many national/private universities had adopted the election system. However, it has posed many problems and it caused a sharp division of opinions between those who approve and disapprove the direct election system. Since 2005, the government has made official of the reformation and/or abolition of the university president direct election system, and has kept pushing for universities to give up the direct election system. Now, only 3 or 4 universities hold on to the system, and many universities have changed into the indirect election system. In the indirect election, a key is the composition of president nomination committee, which confirms the university members's variety. Many universities adopting the indirect election system have used simple random sampling, like drawing lots, to compose the president nomination committee. However, drawing lots has a problem that it has large possibility of composing a biased committee. This research suggests systematic sampling as an alternative to drawing lots. A numerical analysis was conducted using a data of a university in which the indirect election was implemented recently. The drawing lots gave the biased nomination committee. On the other hand, the systematic sample improves the problem and confirms more the variety of all members.

• Journal of the Korean Data and Information Science Society
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• v.4
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• pp.45-51
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• 1993

For studies in reliability, biometry and survival analysis, the length biased distribution is frequently appropriate for certain natural sampling plans. So, we shall convey the preservation of some partial orderings under life length biasd distributions and closures of ILR and NBU classes under life length biasd distributions.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1127-1135
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• 2014

Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.641-648
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• 2007

We propose the new sampling method, called modified ranked ordering set sampling (MROSS). Kim and Kim (2003) suggested the sign test using the ranked ordering set sampling (ROSS), and showed that the asymptotic relative efficiency (ARE) of ROSS against RSS for sign test increases as sample size does. We propose the estimator for the population mean using MROSS. The relative precision (RP) of estimator of the population mean using MROSS method with respect to the usual estimator using modified RSS is higher, and when the underlying distribution is skewed, the bias of the proposed estimator is smaller than that of several ranked set sampling estimators.

• Journal of Preventive Medicine and Public Health
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• v.46 no.2
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• pp.96-104
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• 2013

Objectives: The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures. Methods: This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010. Results: Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses. Conclusions: Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.

• The Korean Journal of Ecology
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• v.26 no.3
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• pp.123-127
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• 2003

Cubic-meter volumes estimated from two proxy taper functions were compared to observed volumes of Japanese red cedar trees (Cryptomeria japonica D. Don) to evaluate accuracy and precision in the centroid method. Centroid volume estimates were also compared to volume estimates from existing whole-tree volume equations developed for another geographic region. This study found that one proxy function produced unbiased volume estimates while the other was biased. Volume estimates from the whole-tree equations were also biased. However, the volume estimates from the whole-tree equations were more precise than those from the centroid method. These results support previous studies that the centroid method can produce reliable volumes of trees when no other reliable volume equations exist.

• Journal of agriculture & life science
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• v.43 no.1
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• pp.17-23
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• 2009

This study was conducted to compare volumes estimated from two taper functions and observed volumes of Chamaecyparis obtusa trees to evaluate accuracy and precision of centroid method. Centroid volume estimates were also compared with volume estimates from existing Forest Resources Evaluation and Prediction Program. The results of this study showed that Gregoire's simple taper function produced unbiased volume estimates while the others were biased. Volume estimates from the Forest Resources Evaluation and Prediction Program were also biased when applied in the Jangseong National Forest regions. These results suggested that the centroid method could produce reliable stem volumes of trees when no other reliable stem volume equations exist.