• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.12
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• pp.2051-2061
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• 2010

Extreme sports refers to sports activities with a high level of inherent danger, such as extreme skiing, snow-boarding, mountain biking, motocross bicycling, aggressive in-line skating, wake-boarding, and paragliding. This study investigates the characteristics of extreme sports participants as group identities through an examination of the differences between extreme sports participants and traditional sports groups in lifestyle and sportswear benefits sought. We composed a total 108-item lifestyle profiles characterized by six lifestyle dimensions (dress, diet, home, recreation, consumption, and sense of values); in addition, we developed 32 items for sportswear benefits sought. The surveys targeted 422 sports participants living in Korea (216 men and 206 women, aged 15-23): 119 extreme sports participants and 303 traditional sports participants. All items were evaluated on a 5-point Likert scale, and SPSS 17.0. was used for data analysis. Exploratory factor analysis was conducted to confirm the substructure of each lifestyle dimension and sportswear benefits sought. The results of the factor analysis on each lifestyle dimension are as follows: 5 factors in dress dimension, 4 in diet, 3 in home, 6 in recreation, 5 in consumption, and 6 in sense of values. Six factors of sportswear benefit sought were identified. A t-test revealed that there were significant differences between the two groups in lifestyle dimensions and sportswear benefits sought. This study reveals that the lifestyle characteristics of extreme sports participants are more likely than traditional sports group to be more self-expressive, more distinctive, more fashion-oriented, more conspicuous, and more brand-oriented, while preferring more active sports, more dynamic leisure, and a more sensible life. Another finding is that extreme sports participants seek the distinctive, conspicuous, and latest sportswear benefits.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.523-529
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• 2010

In this paper, we obtain some recurrence relations for the quotient moments of the lower record values from the generalized extereme value(GEV) distribution. We also deduce some recurrence relations for the negative moments from the GEV distribution.

• Journal of Ocean Engineering and Technology
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• v.34 no.1
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• pp.26-36
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• 2020

An extreme value analysis of metocean data which include wave, wind, and current data is a prerequisite for the operation and survival of offshore structures. The purpose of this study was to provide information about the return wave, wind, and current values for the Barents Sea using extreme value analysis. Hindcast datasets of the Global Reanalysis of Ocean Waves 2012 (GROW2012) for a waves, winds and currents were obtained from the Oceanweather Inc. The Gumbel distribution, 2 and 3 parameters Weibull distributions and log-normal distribution were used for the extreme value analysis. The least square method was used to estimate the parameters for the extreme value distribution. The return values, including the significant wave height, spectral peak wave period, wind speed and current speed at surface, were calculated and it will be utilized to design offshore structures to be operated in the Barents Sea.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.159-166
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• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

• Journal of applied mathematics & informatics
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• v.1 no.1
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• pp.43-48
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• 1994

There are some difficulties in applying the Pearson's Chi-Square Test for the continuous distribution. The problems include how to form class intervals for the test of fit how to employ in the test when the estimators of parameters are obtained from the ungrouped sample so on. In order to solve these problems we use the generalized minimum Chi-Square technique which is a test free of the complications associated with the Peason's Chi-Square test. This paper show how to apply the goodness of fit tests based on generalized minimum Chi-Square technique to the extreme values.

• Wind and Structures
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• v.13 no.1
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• pp.83-94
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• 2010

Wind tunnel measurements on T-shaped free-standing walls and inclined free-standing walls have been carried out. Mean net pressure coefficients have been derived and compared with previous research. It was observed that the high loads at the free ends are differently distributed than those derived from the pressure coefficients for free-standing walls in EN 1991-1-4. In addition net pressure coefficients based on extreme value analysis have been obtained. The lack of correlation of the wind induced pressures at windward and leeward side result in lower values for the net pressure coefficients when based on extreme value analysis. The results of this wind tunnel study have been included in Dutch guidelines for noise barriers.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.291-311
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• 2007

With a series of unexpected huge losses in the financial markets around the world recently, especially in the insurance market with extreme loss cases such as catastrophes, there is an increasing demand for risk management for extreme loss exposures due to high unpredictability of those risks. For extreme risk management, to make a maximum use of the information concerning the tail part of a loss distribution, EVT(Extreme Value Theory) modelling nay be the best to analyze extreme values. The Extreme Value Theory is widely used in practice and, especially in financal markets, EVT modelling is getting popular to analyBe the effects of extreme risks. This study is to review the significance of the Extreme Value Theory in risk management and, focusing on analyzing insurer's risk capital, extreme risk is measured using the real fire loss data and insurer's specific amount of risk capital is figured out to buffer the extreme risk.

• 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.

• Korean Management Science Review
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• v.24 no.2
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• pp.115-126
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• 2007

Weekly minima of daily log returns of Korean composite stock price index 200 and its five industry-based business divisions over the period from January 1990 to December 2005 are fitted using two block-based extreme distributions: Generalized Extreme Value(GEV) and Generalized Logistic(GLO). Parameters are estimated using the probability weighted moments. Applicability of two distributions is investigated using the Monte Carlo simulation based empirical p-values of Anderson Darling test. Our empirical results indicate that both the GLO and GEV models seem to be comparably applicable to the weekly minima. These findings are against the evidences in Gettinby et al.[7], who claimed that the GEV model was not valid in many cases, and supported the significant superiority of the GLO model.

• Smart Structures and Systems
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• v.21 no.5
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• pp.549-559
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• 2018

The dynamic behaviors of the bridge structures have great effects on the comfortability and safety of running high-speed trains, which can also reflect the structural degradation. This paper aims to reveal the characteristics of the dynamic behaviors induced by train loadings for a combined highway and railway bridge. Monitoring-based analysis of the acceleration and dynamic displacement of the bridge girder is carried out. The effects of train loadings on the vertical acceleration of the bridge girder are analyzed; the spatial variability of the train-induced lateral girder displacement is studied; and statistical analysis has been performed for the daily extreme values of the train-induced girder deflections. It is revealed that there are great time and spatial variabilities for the acceleration induced by train loadings for the combined highway and railway cable-stayed bridge. The daily extreme values of the train-induced girder deflections can be well fitted by the general extreme value distribution.