• Journal of the Ergonomics Society of Korea
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• v.29 no.2
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• pp.183-188
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• 2010

The purpose of this study is to investigate the stationarity of the electromyographic signal in various flexion angles, loads, and window sizes, which influence the result of the mean power frequency (MPF) and median frequency (MNF) analysis. Six healthy subjects participated in the experiment. They were tested in the combination of 3-level flexion angles (0 degree, 22.5 degree, 45 degree) and 3-level loads (0Nm, 30Nm, 60Nm). Electromyographic data were collected for 20 seconds during isometric contraction. The stationarity of collected data were analyzed with four different window sizes including 250, 500, 1000 and 2000ms. Two test methods for stationarity such as Reverse Arrangements Test and Modified Reverse Arrangements Test were used. In order to show the effect of nonstationarity, the increasing/decreasing trend of MPF and MNF trend were discussed. In results, the stationarity of the electromyographic signal decreased as flexion angle increased and load decreased while window size decreased based on Reverse Arrangements Test. The highest stationarity was shown at 500 ms window in Modified Reverse Arrangements Test. The inclination of MNF and MPF indicated 3.6-6.3%, 3.8-5.1% discrepancy compared to the result from stationary data.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.65-73
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• 2013

In the simulation output analysis, bootstrap method is an applicable resampling technique to insufficient data which are not significant statistically. The moving block bootstrap, the stationary bootstrap, and the threshold bootstrap are typical bootstrap methods to be used for autocorrelated time series data. They are nonparametric methods for stationary time series data, which correctly describe the original data. In the simulation output analysis, however, we may not use them because of the non-stationarity in the data set caused by the trend such as increasing or decreasing. In these cases, we can get rid of the trend by differencing the data, which guarantees the stationarity. We can get the bootstrapped data from the differenced stationary data. Taking a reverse transform to the bootstrapped data, finally, we get the pseudo-samples for the original data. In this paper, we introduce the applicability of bootstrap methods to the time series data having trend, and then verify it through the statistical analyses.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.79-88
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• 2007

This study evaluated the statistical stationarity of rainfall quantiles as well as the rainfall itself. The conventional methodologies like the Cox-Stuart test for trend and Dickey-Fuller test for a unit root used for testing the stationarity of a time series were applied and evaluated their application to the rainfall quantiles. As results, first, no obvious increasing or decreasing trend was found for the rainfall in Seoul, which was also found to be a stationary time series based on the Dickey-Fuller test. However, the Cox-Stuart test for the rainfall quantiles show some trends but not in consistent ways of increasing or decreasing. Also, the Dickey-Fuller test for a unit root shows that the rainfall quantiles are non-stationary. This result is mainly due to the difference between the rainfall data and rainfall quantiles. That is, the rainfall is a random variable without any trend or non-stationarity. On the other hand, the rainfall quantiles are estimated by considering all the data to result in high correlation between their consecutive estimates. That is, as the rainfall quantiles are estimated by adding a stationary rainfall data continuously, it becomes possible for their consecutive estimates to become highly correlated. Thus, it is natural for the rainfall quantiles to be decided non-stationary if considering the methodology used in this study.

• Wind and Structures
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• v.24 no.1
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• pp.59-78
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• 2017

Non-stationarity and non-Gaussian property are two of the most important characteristics of wind. These two features are studied in this study based on wind speed records measured at different heights from a 325 m high meteorological tower during the synoptic wind storms. By using the time-frequency analysis tools, it is found that after removing the low frequency trend of the longitudinal wind, the retained fluctuating wind speeds remain to be asymmetrically non-Gaussian distributed. Results show that such non-Gaussianity is due to the weak-stationarity of the detrended fluctuating wind speed. The low frequency components of the fluctuating wind speeds mainly contribute to the non-zero skewness, while distribution of the high frequency component is found to have high kurtosis values. By further studying the decomposed wind speed, the mechanisms of the non-Gaussian distribution are examined from the phase, turbulence energy point of view.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.241-253
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• 2010

As standard unit root tests are empirically proved to fail to reject the null hypothesis of a unit root for many economic and business time series, it is doubtful that most of those series are informative about the existence of a unit root or that those tests are powerful against relevant alternative hypotheses. This study attempts to perform tests of the null hypothesis of stationarity as well as tests of the null hypothesis of a unit root using the time series data of housing prices in the major metropolitan areas. The results of the additional analyses such as lead-lag, cross-correlation and impulse response for testing the statistical interrelationships between the prices are generally found to be consistent.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.355-362
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• 2006

Several techniques of MK test, Spearman's Rho test, Linear Regression test, CUSUM test, Cumulative Deviation, Worsley Likelihood Ratio test, Rank Sum test, and Students' t test were applied to detect the trends of slope and shift which exist in hydrologic and climate time series. The time series of annual rainfall, inflow, tree ring index, and southern oscillation index (SOI) were used and the trends of these series were compared in the study. From the results, it can be found that the data could be classified into two categories such as linear trend and shift. 4 series data of 8 rainfall series which reveal the trend show the shift and 8 series data of 18 tree ring index and March and April series of monthly SOI data show shift. Moreover, ADF test and BDS test were used to test stationarity and non-linearity of the data. In conclusion, through the study, various trend analysis techniques were compared and 6 kinds of characteristics which can exist in hydrologic time series were identified.

• Atmosphere
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• v.23 no.3
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• pp.307-320
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• 2013

We performed comprehensive quality control for eddy-covariance measurements from 3 farmland sites and 1 industrial site adjacent to Nakdong river. The quality control program is based on Foken and Wichura (1996) and Vicker and Mahrt (1997) and we added criteria for trend and standard deviation for scalar variables and modified criteria for non-stationarity condition of Foken and Wichura (1996) to consider random error of fluxes. The classification of data quality is designed for the raw data and the processed flux data, separately. Use of added criteria efficiently reduces the number of outlier for water vapor and $CO_2$ fluxes and use of modified criteria for non-stationarity reduces the number of outlier for scalar fluxes and increases the number of data with accepted quality for further work. Energy balance ratio is higher in farmlands than industrial site, which is due to neglect of heat storage term in industrial site. Among farmland sites, C4 site shows higher energy balance ratio than other sites. This is due to more homogeneous surface of C4 site than other farmland sites. However, energy balance ratio is very low or even negative at night. Mismatch between the flux footprint and the other energy component footprint over the heterogeneous surface is main cause for energy imbalance at night. Other possible causes are also discussed.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.447-457
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• 2014

This research focuses on the changes of return period for nonstationary rainfall data in which exceedance or nonexceedance probability varies depending on time. We examined two definitions of return period under nonstationarity and also performed nonstationary frequency analysis using the nonstationary Gumbel model to investigate variations of return period in Korea. Seogwipo, Inje, Jecheon, Gumi, Mungyeong, and Geochang were selected as subject sites of application. These sites have a trend in rainfall data as well as having more than 30 years data. As the results of application, the return periods considering nonstationarity are different with those considering stationarity. The differences of return periods between nonstationarity and stationarity increase as growing return period increases. In addition, the return period using the expected waiting time method shows lower value than that using the expected number of event method.

• Wind and Structures
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• v.17 no.2
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• pp.135-162
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• 2013

The majority of experiments to characterize the turbulence in the surface layer have been performed in flat, open expanses. In order to characterize the turbulence in built-up terrain, two mobile towers were deployed during Hurricane Ike (2008) in close proximity, but downwind of different terrain conditions: suburban and open. Due to the significant non-stationarity of the data primarily caused by changes in wind direction, empirical mode decomposition was employed to de-trend the signal. Analysis of the data showed that the along-wind mean turbulence intensity of the suburban terrain was 37% higher than that of the open terrain. For the mean vertical turbulence intensity, the increase for the suburban terrain was as high as 74%, which may have important implications in structural engineering. The gust factor of the suburban terrain was also 16% higher than that of the open terrain. Compared to non-hurricane spectral models, the obtained spectra showed significantly higher energy in low frequencies especially for the open terrain.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.345-345
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• 2012

정상성 기반의 전통적 극한치 이론은 기후변화 및 변동에 의한 외부변화 요인을 반영하기에는 한계가 있음이 지적되어왔다. 따라서 강우의 빈도분석 시 매개변수의 시간에 따른 변화를 반영한 비정상성 빈도분석 방법이 필요하다. 본 연구에서는 미호천 유역의 강우관측소 중 기상청에서 관리하는 청주 관측소 및 국토해양부에서 관리하는 가덕, 병천, 증평, 진천 관측소의 24시간 연최대치 강우자료를 대상으로 시간에 따른 경향성 분석을 하였다. 또한 자료의 경향성을 고려하여 비정상성 빈도분석을 하였고 외부상관기상변수로써 ENSO(El Nino Southern Oscillation)를 이용하여 비정상성 빈도분석을 실시하였다.