• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.401-410
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• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.2 no.1
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• pp.41-51
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• 2004

The cost-effective reduction of occupational radiation dose (ORD) at a nuclear power plant could not be achieved without going through an extensive analysis of accumulated ORD data of existing plants. Through the data analysis, it is required to identify what are the jobs of repetitive high ORD at the nuclear power plant. In this study, Percentile Rank Sum Method (PRSM) is proposed to identify repetitive high ORD jobs, which is based on non-parametric statistical theory. As a case study, the method is applied to ORD data of maintenance and repair jobs at Kori units 3 and 4 that are pressurized water reactors with 950 MWe capacity and have been operated since 1986 and 1987, respectively in Korea. The results was verified and validated, and PRSM has been demonstrated to be an efficient method of analyzing the data.

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.651-658
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• 2005

The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.

• Journal of Periodontal and Implant Science
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• v.39 no.4
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• pp.399-405
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• 2009

Purpose: This article is purposed to present the correct statistic method by pointing out the statistical errors after analyzing the method of articles that were published in Korean Academy Journal of Periodontology and made statistic processes in them. Methods: 488 science papers which being put in Korean Academy Journal of Periodontology published from 2000 to 2006 was divided according to year. Results: In the 308 articles that applied statistic methods, 59 articles (50.0%), the largest portion of all, were included the case that applied incorrect parametric statistic method when needed to apply parametric statistics and 38 articles (32.2%) were included in the case that applied incorrect parametric statistic method when needed to apply non-parametric statistics. Conclusions: It is necessary to present the cases of inappropriate statistical methods in order to improve the quality of academic researches. Also, to apply adequate methods of statistics, it is suggested to report the articles periodically which are comparing and analyzing the statistical methods that are applied in the international articles in periodontal field.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1525-1528
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• 2011

The purpose of this study was to detect SNPs that were responsible for a carcass trait in Hanwoo populations. A non-parametric model applying a restricted partition method (RPM) was used, which exploited a partitioning algorithm considering statistical criteria for multiple comparison testing. Phenotypic and genotypic data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, in which the pedigree structure comprised 229 steers from 16 paternal half-sib proven sires that were born in Namwon or Daegwanryong livestock testing station between spring of 2002 and fall of 2003. A carcass trait, longissimus dorsi muscle area for each steer was measured after slaughter at approximately 722 days. Three SNPs (19_1, 18_4 and 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the quantitative trait loci (QTL) for meat quality were previously detected, were used in this study. The RPM analyses resulted in two significant interaction effects between SNPs (19_1 and 18_4) and (19_1 and 28_2) at ${\alpha}$ = 0.05 level. However, under a general linear (parametric) model no interaction effect between any pair of the three SNPs was detected, while only one main effect for SNP19_1 was found for the trait. Also, under another non-parametric model using a multifactor dimensionality reduction (MDR) method, only one interaction effect of the two SNPs (19_1 and 28_2) explained the trait significantly better than the parametric model with the main effect of SNP19_1. Our results suggest that RPM is a good alternative to model choices that can find associations of the interaction effects of multiple SNPs for quantitative traits in livestock species.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.825-833
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• 2013

An estimation of confidence intervals is essential to calculate uncertainty for greenhouse gases inventory. It is generally assumed that the population has a normal distribution for the confidence interval of parameters. However, in case data distribution is asymmetric, like nonnormal distribution or positively skewness distribution, the traditional estimation method of confidence intervals is not adequate. This study compares two estimation methods of confidence interval; parametric and non-parametric method for exponential distribution as an asymmetric distribution. In simulation study, coverage probability, confidence interval length, and relative bias for the evaluation of the computed confidence intervals. As a result, the chi-square method and the standardized t-bootstrap method are better methods in parametric methods and non-parametric methods respectively.

• Herbal Formula Science
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• v.17 no.1
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• pp.75-83
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• 2009

Objective : The purpose of this study is to indicate of problems in statistical analysis method of "The Korean Journal of oriental Medical Prescription" and we will be proposed the useful application of the statistical analysis method. Methods : In this paper, we were analysed statistical analysis methodology from published journal articles "The Korean Journal of Oriental Medical Prescription" December, year 2000 to December, year 2008. We were investigated of problems in application of structured analysis methods those journal articles that including statistical analysis techniques and analysis methods. Results : 1. A random allocation of the experimental group and control groups are important factors in the planning process of statistical analysis. However, there are less explanation those journal articles. 2. There are no consideration in specimen size that there will be considerate by the level of significance and statistical test. 3. Many article authors were confused between parametric methods and non-parametric methods that they were applied parametric statistical analysis methods although inapplicable sample size. 4. There were applied the parametric methods consists of t-test instead non-parametric methods in the comparison of average intergroup relations. 5. There were less understanding posterior analysis and were confused with t-test. Conclusion : Our goal was to outline the key methods with a brief discussion of problems(statistical analysis methods), avenues for solutions. we recommend authors to use an appropriate statistical analysis methods for obtaining a more cautions results.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.502-507
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• 2003

Toward the development of practical methods for observed data oriented bispectral estimation, an automatic means for determining the smoothing bandwidth of bispectral windows is proposed, that can also provide an associated optimum bispectral estimate of stationary non-Gaussian signals, systematically only from an observed time series datum of finite length. For the conventional non-parametric bispectral estimation, the MSE (mean squared error) of the normalized estimate is reviewed under a certain mixing condition and sufficient data length, mainly from the viewpoint of the inverse relation between its bias and variance with respect to the smoothing bandwidth. Based on the fundamental relation, a systematic method not only for determining the bandwidth, but also for obtaining the optimum bispectral estimate is presented by newly introducing a MSE evaluation index of the estimate only from an observed time series datum of finite length. The effectiveness and fundamental features of the proposed method are illustrated by the basic results of numerical experiments.

• Wind and Structures
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• v.2 no.2
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• pp.85-94
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• 1999

The EARPG(1)/UPS was first developed by Seong (1993) and has been tested for wind pressure time series simulations (Seong and Peterka 1993, 1997, 1998) to prove its excellent performance for generating non-Gaussian time series, in particular, with large amplitude sharp peaks. This paper presents a parametric study focused on simulation of extreme value statistics based on the synthetic realizations of the EARPG(1)/UPS. The method is shown to have a great capability to simulate a wide range of non-Gaussian statistic values and extreme value statistics with exact target sample power spectrum. The variation of skewed long tail in PDF and extreme value distribution are illustrated as function of relevant parameters.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.785-790
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• 2008

Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.