• Journal of The Korean Astronomical Society
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• v.52 no.4
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• pp.133-144
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• 2019

We develop forecast models of daily probabilities of major flares (M- and X-class) based on empirical relationships between photospheric magnetic parameters and daily flaring rates from May 2010 to April 2018. In this study, we consider ten magnetic parameters characterizing size, distribution, and non-potentiality of vector magnetic fields from Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) and Geostationary Operational Environmental Satellites (GOES) X-ray flare data. The magnetic parameters are classified into three types: the total unsigned parameters, the total signed parameters, and the mean parameters. We divide the data into two sets chronologically: 70% for training and 30% for testing. The empirical relationships between the parameters and flaring rates are used to predict flare occurrence probabilities for a given magnetic parameter value. Major results of this study are as follows. First, major flare occurrence rates are well correlated with ten parameters having correlation coefficients above 0.85. Second, logarithmic values of flaring rates are well approximated by linear equations. Third, using total unsigned and signed parameters achieved better performance for predicting flares than the mean parameters in terms of verification measures of probabilistic and converted binary forecasts. We conclude that the total quantity of non-potentiality of magnetic fields is crucial for flare forecasting among the magnetic parameters considered in this study. When this model is applied for operational use, it can be used using the data of 21:00 TAI with a slight underestimation of 2-6.3%.

• Journal of Korea Water Resources Association
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• v.43 no.9
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• pp.813-822
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• 2010

An important problem in frequency analysis is the estimation of the quantile for a certain return period. In frequency analysis an assumed probability distribution is fitted to the observed sample data to estimate the quantile at the upper tail corresponding to return periods which are usually much larger than the record length. In most cases, the selection of an appropriate probability distribution is based on goodness of fit tests. The goodness of fit test method can be described as a method for examining how well sample data agrees with an assumed probability distribution as its population. However it gives generally equal weight to differences between empirical and theoretical distribution functions corresponding to all the observations. In this study, the modified Anderson-Darling (AD) test statistics are provided using simulation and the power study are performed to compare the efficiency of other goodness of fit tests. The power test results indicate that the modified AD test has better rejection performances than the traditional tests. In addition, the applications to real world data are discussed and shows that the modified AD test may be a powerful test for selecting an appropriate distribution for frequency analysis when extreme cases are considered.

• Journal of Distribution Science
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• v.14 no.4
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• pp.117-125
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• 2016

Purpose - As consumers' needs for purchasing fresh and safe food have been bigger in Korea, their interest in local food is also growing recently. So, the number of local food stores has been increased from 3 in 2012 to 103 in 2015. Local food stores should operate a business responding consumers' needs in order that local food stores are not to be a one-time fad. Therefore, the purpose of this study is to analyze the characteristics of consumers who use a local food store and provide helpful implications to design a strategy for sustainable growth of local food store. Research design, data, and methodology - In this study, Probit model was used for empirical analysis in order to examine the effect of purchase choice attributes of agricultural products, consumer's satisfaction, and their demographic factors upon the intention to use a local food store. After estimating coefficients of the probit model, marginal effects were calculated as a standard normal, and cumulative distribution is differentiated with respect to explanatory variables. To collect the data, questionnaire survey was carried out with the consumers using the local food store (Youngjin Nonghyup near to Jeonju city located in Jeollabuk-do). Result - The data analysis found that the more consumers are satisfied with local food store, the higher intention they have to use the local food store. In addition, it was known that the factors related to quality of agricultural products and shopping convenience among the purchase choice attributes have a considerable impact on the purchase intention of a local food store. In demographic factors, income was turned out to be an important factor affecting purchase intention of local food. Such a result supports the hypothesis that high income consumers are likely to purchase local food, which is based on the inference that consumers who have a high income tend to pursue wellbeing life. Futhermore, information delivery, through a reputable media source among general factors, was known to play an important role in forming an intention to purchase local food. According to the analysis of marginal effects, probability of purchase intention of a local food store is increased by 11.4%, if a monthly average income of a household is above 4.5 million Won(Korean currency). If purchasing satisfaction with local food stores is high, the probability of purchase intention would be increased by 24.1%. Likewise, such a probability goes up by 8.7%, 5.8%, respectively as an increasing one unit of quality of agricultural products and shopping convenience of local food stores, respectively. Conclusion - For attaining sustainable growth in a local food store, it is considered necessarily to establish a proper store operation system to meet consumers' needs, especially for quality and shopping convenience of local food. Moreover, as it was found that appropriate communication through media source has a positive effect on the intention to use local food store, PR activity seems to be necessary to expand the consumers' demands for local foods.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.5
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• pp.241-252
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• 2019

To choose appropriate countermeasures against potential coastal disaster damages caused by a storm surge, it is necessary to estimate the frequency of storm surge heights estimation. As the coastal populations size in the past was small, the tropical cyclone risk model (TCRM) was used to generate 176,689 synthetic typhoons. In simulation, historical paths and central pressures were incorporated as a probability density function. Moreover, to consider the typhoon characteristics that resurfaced or decayed after landfall on the southeast coast of China, incorporated the shift angle of the historical typhoon as a function of the probability density function and applied it as a damping parameter. Thus, the passing rate of typhoons moving from the southeast coast of China to the south coast has improved. The characteristics of the typhoon were analyzed from the historical typhoon information using correlations between the central pressure, maximum wind speed ($V_{max}$) and the maximum wind speed radius ($R_{max}$); it was then applied to synthetic typhoons. The storm surges were calculated using the ADCIRC model, considering both tidal and synthetic typhoons using automated Perl script. The storm surges caused by the probabilistic synthetic typhoons appear similar to the recorded storm surges, therefore this proposed scheme can be applied to the storm surge simulations. Based on these results, extreme values were calculated using the Generalized Extreme Value (GEV) method, and as a result, the 100-year return period storm surge was found to be satisfactory compared with the calculated empirical simulation value. The method proposed in this study can be applied to estimate the frequency of storm surges in coastal areas.

• Journal of the Earthquake Engineering Society of Korea
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• v.26 no.5
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• pp.191-202
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• 2022

Markov envelope as a theoretical solution of the parabolic wave equation with Markov approximation for the von Kármán type random medium is studied and approximated with the convolution of two probability density functions (pdf) of normal and gamma distributions considering the previous studies on the applications of Radiative Transfer Theory (RTT) and the analysis results of earthquake records. Through the approximation with gamma pdf, the constant shape parameter of 2 was determined regardless of the source distance r_o. This finding means that the scattering process has the property of an inhomogeneous single-scattering Poisson process, unlike the previous studies, which resulted in a homogeneous multiple-scattering Poisson process. Approximated Markov envelope can be treated as the normalized mean square (MS) envelope for ground acceleration because of the flat source Fourier spectrum. Based on such characteristics, the path duration is estimated from the approximated MS envelope and compared to the empirical formula derived by Boore and Thompson. The results clearly show that the path duration increases proportionately to r_o^1/2-r_o², and the peak value of the RMS envelope is attenuated by exp (-0.0033r_o), excluding the geometrical attenuation. The attenuation slope for r_o≤100 km is quite similar to that of effective attenuation for shallow crustal earthquakes, and it may be difficult to distinguish the contribution of intrinsic attenuation from effective attenuation. Slowly varying dispersive delay, also called the medium effect, represented by regular pdf, governs the path duration for the source distance shorter than 100 km. Moreover, the diffraction term, also called the distance effect because of scattering, fully controls the path duration beyond the source distance of 300 km and has a steep gradient compared to the medium effect. Source distance 100-300 km is a transition range of the path duration governing effect from random medium to distance. This means that the scattering may not be the prime cause of peak attenuation and envelope broadening for the source distance of less than 200 km. Furthermore, it is also shown that normal distribution is appropriate for the probability distribution of phase difference, as asserted in the previous studies.

• Journal of Distribution Science
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• v.18 no.5
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• pp.83-88
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• 2020

Purpose of the research: In response to the increasing number of selling centers, this paper examines factors that influence the voluntary participation in selling centers. The goal of this study is to enable organizations to meet changing market conditions, which require interdisciplinary collaboration during sales projects. This paper also discusses potential problems which may occure during the implementation of these factors in practice. Research design and methodology: The research method consists of a qualitative cross-sectional study with N=12 interviewees. All interviewees are current or former selling center participants. During the interview sessions, semi-structured face-to-face interviews were used, which were evaluated using a qualitative content analysis. In addition, a frequency analysis was applied to evaluate the number of mentions per factor. Research results: In total, five factors were raised in order to improve the framework conditions of voluntary participation. These factors are performance incentives, transparency, availability of resources, goal orientation, as well as collegiality and affiliation. Major conclusions: The identified factors are also under discussion in the existing literature. Knowing about factors that generate voluntary participation in selling centers pays off particularly in improving the probability of completion of sales projects in which buying centers and selling centers are working together.

• International Journal of Concrete Structures and Materials
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• v.19 no.1E
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• pp.11-16
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• 2007

Recently, probabilistic neural network (PNN) has been proposed to predict the compressive strength of concrete for the known effect of improvement on PNN by the iteration method. However, an empirical method has been incorporated in the PNN technique to specify its smoothing parameter, which causes significant uncertainty in predicting the compressive strength of concrete. In this study, a modified probabilistic neural network (MPNN) approach is hence proposed. The global probability density function (PDF) of variables is reflected by summing the heterogeneous local PDFs which are automatically determined by the individual standard deviation of each variable. The proposed MPNN is applied to predict the compressive strength of concrete using actual test data from a concrete company. The estimated results of MPNN are compared with those of the conventional PNN. MPNN showed better results than the conventional PNN in predicting the compressive strength of concrete and provided promising results for the probabilistic approach to predict the concrete strength by using the individual standard deviation of a variable.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1464-1470
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• 2009

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

• Wind and Structures
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• v.27 no.3
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• pp.149-161
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• 2018

A reliability analysis method is proposed in this paper based on the maximum entropy (MaxEnt) principle in which constraints are specified in terms of the fractional moments instead of integer moments. Then a multiplicative dimensional reduction method (M-DRM) is introduced to compute the fractional moments. The method is applicable for both explicit and implicit limit state functions of complex structures. After two examples illustrate the accuracy and efficiency of this method in comparison to the Monte Carlo simulation (MCS), the method is used to analyze the flutter reliability of suspension bridge. The results show that the empirical formula method in which the limit state function is explicitly represented as a function of variables is only a too conservative estimate for flutter reliability analysis but is not accurate adequately. So it is not suitable for reliability analysis of bridge flutter. The actual flutter reliability analysis should be conducted based on a finite element method in which limit state function is implicitly represented as a function of variables. The proposed M-DRM provide an alternate and efficient way to analyze a much more complicated flutter reliability of long span suspension bridge.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.629-644
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• 2013

This paper concerns about the raking damages on the ultimate residual hull girder strength of bulk carriers by applying the modified R-D diagram (advanced method). The limited raking damage scenarios, based on the IMO's probability density function of grounding accidents, were carried out by using sampling technique. Recently, innovative method for the evaluation of the structural condition assessment, which covers the residual strength and damage index diagram (R-D diagram), was proposed by Paik et al. (2012). This concept is applied in the present study and modified R-D diagram, which can be considered vessel size effect, is then proposed. Four different types of bulk carrier structures, i.e., Handysize (37K), Supramax (57K), Kamsarmax (82K) and Capesize (181K) by Common Structural Rule (CSR), were applied to draw the general tendency. The ALPS/HULL, intelligent supersize finite element method, was employed for the ultimate longitudinal strength analysis. The obtained empirical formulas will be useful for the condition assessment of bulk carrier structures. It can also cover different sizes of the bulk carriers in terms of ultimate longitudinal strength. Important insights and findings with useful guidelines developed in this study are summarized.