• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.116-116
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• 2017

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.117-117
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• 2017

• Proceedings of KOSOMES biannual meeting
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• 2017.11a
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• pp.111-111
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• 2017

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1814-1819
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• 2010

Since 1987, when statistical analyzing guide for thermal life test of Accelerated Life Test(ALT) was proposed as ANSI/IEEE Std 101, this guide has been used widely for many experiment data. Shim(2004) had done Monte Carlo simulation to compare life of two different systems or materials, based on statistic values obtained from ANSI/IEEE Std 101 data. In this study, a profile analysis is proposed for comparing life of two different systems or materials, and some examples using pre-existing data are given.

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.1
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• pp.27-38
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• 1994

Accumulation analysis is difficult to analyze the ordered categorical data except smaller-the-better type problem. The purpose of this paper is to develop the statistic and method that can be easily applied to general type of problem, including nominal-the-best type problem. The experimental data of contact window process is analyzed and new procedure is compared with accumulation analysis.

• Bulletin of the Korean Mathematical Society
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• v.51 no.3
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• pp.701-716
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• 2014

The limiting distribution for the linear placement statistics under the null hypotheses has been provided by Orban and Wolfe [9] and Kim [5] when one of the sample sizes goes to infinity, and by Kim, Lee and Wang [6] when the sample sizes of each group go to infinity simultaneously. In this paper we establish the generalized Kruskal-Wallis one-way analysis of variance for the linear placement statistics.

• Research in Mathematical Education
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• v.14 no.2
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• pp.143-172
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• 2010

In this paper, we present an analysis of how students understand some statistical terms, mainly from inferential statistics, which are taught at the high school level. We focus our analysis on those terms that present more difficulties and are persistent in spite of having been studied until the college level. This analysis leads us to a hierarchical classification of responses at different levels of understanding using the SOLO theoretical framework.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.9-18
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• 2005

This study delivers the actual condition of investment for industrial accident prevention based on survey of 526 construction sites. The various research techniques were used such as technical statistic analysis for construction industry, construction and civil engineering works, cost comparison of industrial accident prevention and accident loss. A formula was deduced to calculate accident loss and accident frequency by accident prevention cost through regression analysis.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.727-735
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• 2010

The collapse of cut slope near national roads in Korea mostly occurs in every summer when typhoon or localized heavy rain comes. Such collapse brings about a loss of many lives and property and recently the damage is on rapidly increasing trend. Therefore, we may reduce the loss of many lives and property in great deals if we can predict and prepare for the collapse of cut slope. However, it is not easy to predict collapse because there are many factors causing collapse in combination and all they have different levels of contribution. Therefore, this study completed prediction formula by using a statistic technique for quantitative analysis on the interaction of those factors so as to predict the stability of slopes. Consequently, it is judged that effective slope management will be possible by selecting dangerous slopes quantitatively among cut slopes near national roads and by preparing for the collapse in advance.