• Korean Journal of Fisheries and Aquatic Sciences
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• v.22 no.1
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• pp.41-47
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• 1989

Using computer simulated irregular waves, variations of ocean wave statistics according to sea state are analyzed, and the reasonable conditions that transform the energy spectrum to individual wave statistics are discussed. Ocean wave statistics varying with sea state are found to respond linearly to the spectral peakedness parameter $Q_p$ and spectrum moments $m_n$ (n = 0, 1, 2${\cdots}{\cdots}\;\infty$ ). It is clarified that the 2nd-order spectrum moment is a reasonable parameter which represents the wave statistics including wave periods, and that the spectrum analysis should be carried out under the conditions of minimum data length of 10 times of peak period $T_p$ with time lag of $7T_p$ to satisfy the stable condition of wave statistics.

• Journal of Ocean Engineering and Technology
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• v.15 no.3
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• pp.20-27
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• 2001

After using the filtering method, wave parameters are calculated by the spectral analysis and wave by wave analysis. Extreme environments and higher wave characteristics int he Chujeon Sea are analyzed using the observed wave data. Higher wave has been intensely emphasized as an important environmental force parameter in several recent research works. The aims of this study are to summarize the distribution of extreme environment for wind waves, and to find occurrence probability of higher wave in Chujeon Sea. Ocean wave statistics varying with sea state are found to respond linearly to the spectral peakedness parameter Qp, mean run-length and Ursell number. Although the spreading of the field results is large, it may be concluded that the tendency of wave group formation depends on the spectral peakedness parameter Qp. Extreme wave is estimated to apply various model distribution functions by using the monthly maximum significant wave parameters which can be used to the design and analysis of coastal structures.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.411-422
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• 2014

A classification ensemble method aggregates different classifiers obtained from training data to classify new data points. Voting algorithms are typical tools to summarize the outputs of each classifier in an ensemble. WAVE, proposed by Kim et al. (2011), is a new weight-adjusted voting algorithm for ensembles of classifiers with an optimal weight vector. In this study, when constructing an ensemble, we applied the WAVE algorithm on the double-bagging method (Hothorn and Lausen, 2003) to observe if any significant improvement can be achieved on performance. The results showed that double-bagging using WAVE algorithm performs better than other ensemble methods that employ plurality voting. In addition, double-bagging with WAVE algorithm is comparable with the random forest ensemble method when the ensemble size is large.

• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.252-258
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• 2019

In this paper, the time history of the surface elevation measured at the Draupner platform in the North Sea in 1995 is used to examine the statistical characteristics of the wave data. The wave statistics for 48 surface measurements, which contain three freak wave occurrences, are summarized. The quartiles, boxplots, correlations, and pair plots of 15 variables, along with the abnormality index, are presented. The kurtosis and skewness of the surface elevation are two variables that are highly correlated with the abnormality index, which defines freak waves. Principal coordinate analysis showed that the direction of the changes in the abnormality index agreed with the changes in the kurtosis and skewness. In addition, various wave heights, except the maximum wave height, showed a similar direction for the height changes, and various wave periods showed a similar direction for the period changes. Based on the correlations and PCA analysis, the kurtosis and skewness of the surface profiles are the two most important variables to predict the abnormality index.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.16 no.3
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• pp.1-10
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• 2012

Objectives: The purpose of this study is to observe clinically the anti-cholesterol effects on the prescription of red onion. Materials and methods: The subject of study were middle-aged people. We measured clinically physiological index, body composition, radial arterial pulse wave after 2 month by taking medicine (the prescription of red onion) Results: The study results were as follows. 1. Systolic and diastolic blood pressure of subjects were decreased significantly in the statistics. 2. Total cholesterol and low-density lipoprotein were decreased significantly after 2 month taking medicine. Triglyceride was decreased after 2 month but there was no significant difference and high density lipoprotein was increased after 2 month but there was no significant difference. 3. Waist-Hip ratio, body mass index and body fat percentage were decreased significantly in the statistics, after 2 month taking medicine. 4. HR was increased significantly in the statistics after 2 month but ESV and ECO were decreased signficantly in the statistics after 2 month taking medicine. 5. Pulse wave energy was increased after 2 month but there was no significant difference in the statistics. 6. RAI was decreased significantly in the statistics after 2 month taking medicine. Conclusion: The prescription of purple onion was showed significant change in physiological index, character of body composition, blood circulation index, pulse wave energy and RAI. Therefore it was showed the effect of anti-cholesterol blood circulation clinically. In the future, with diversified study on effect of prescription of purple onion, Oriental medicinal herbs will be used extensively.

• Bulletin of the Korean Mathematical Society
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• v.52 no.6
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• pp.1945-1962
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• 2015

This paper is mainly concerned with the formation of delta standing wave for the scalar conservation law with a linear flux function involving discontinuous coefficients by using the self-similar viscosity vanishing method. More precisely, we use the self-similar viscosity to smooth out the discontinuous coefficient such that the existence of approximate viscous solutions to the delta standing wave for the Riemann problem is established and then the convergence to the delta standing wave solution is also obtained when the viscosity parameter tends to zero. In addition, the Riemann problem is also solved with the standard method and the instability of Riemann solutions with respect to the specific small perturbation of initial data is pointed out in some particular situations.

• Ocean Science Journal
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• v.41 no.4
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• pp.245-254
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• 2006

Long term wave climate of both extreme wave and operational wave height is essential for planning and designing coastal structures. Since the field wave data for the waters around Korean peninsula is not enough to provide reliable wave statistics, the wave climate information has been generated by means of long-term wave hindcasting using available meteorological data. Basic data base of hindcasted wave parameters such as significant wave height, peak period and direction has been established continuously for the period of 25 years starting from 1979 and for major 106 typhoons for the past 53 years since 1951 for each grid point of the North East Asia Regional Seas with grid size of 18 km. Wind field reanalyzed by European Center for Midrange Weather Forecasts (ECMWF) was used for the simulation of waves for the extra-tropical storms, while wind field calculated by typhoon wind model with typhoon parameters carefully analyzed using most of the available data was used for the simulation of typhoon waves. Design wave heights for the return period of 10, 20, 30, 50 and 100 years for 16 directions at each grid point have been estimated by means of extreme wave analysis using the wave simulation data. As in conventional methodsi of design criteria estimation, it is assumed that the climate is stationary and the statistics and extreme analysis using the long-term hindcasting data are used in the statistical prediction for the future. The method of extreme statistical analysis in handling the extreme vents like typhoon Maemi in 2003 was evaluated for more stable results of design wave height estimation for the return periods of 30-50 years for the cost effective construction of coastal structures.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.267-274
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• 2017

The natural disasters such as typhoon, earthquake, flood, heavy rain, drought, sweltering heat, wind wave, tsunami and so on, are difficult to estimate the scale of damage and spot. Also, these disasters were being damaged to human life. However, if based on the disaster statistics the past damage cases are analyzed and the estimated damages can be calculated, the initial damage action can be taken immediately and based on the estimated damage scale the damage can be mitigated. In the present study, therefore, we proposed the functions of wind wave damage estimation for the southern coast. The functions are developed based on Disaster Report('91~'14) for wind wave and typhoon disaster statistics, regional characteristics and observed sea weather.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.469-482
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• 2002

This paper suggests a new method of compensating for wave nonresponse in panel survey, which combines weighting adjustment and imputation. By deleting less frequent nonresponse patterns, we can get simplicity. A new mean estimator under the new combining method is provided and a limited simulation study employing a real data is conducted.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.899-907
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• 2010

Several non-response imputation methods are suggested, however, mainly cross-sectional imputations are studied and applied to this analysis. A simple and common imputation method for panel data is the cross-wave regression imputation or carry-over imputation as a special case of cross-wave regression imputation. This study suggests a multiple imputation method combined time series analysis and cross-sectional multiple imputation method. We compare this method and the cross-wave regression imputation method using MSE, MAE, and Bias. The 2008 monthly labor survey data is used for this study.