• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.803-812
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• 2009

The application of extreme value theory to financial data is a fairly recent innovation. The classical annual maximum method is to fit the generalized extreme value distribution to the annual maxima of a data series. An alterative modern method, the so-called threshold method, is to fit the generalized Pareto distribution to the excesses over a high threshold from the data series. A more substantial variant is to take the point-process viewpoint of high-level exceedances. That is, the exceedance times and excess values of a high threshold are viewed as a two-dimensional point process whose limiting form is a non-homogeneous Poisson process. In this paper, we apply the two-dimensional non-homogeneous Poisson process model to daily losses, daily negative log-returns, in the data series of KBW/USD exchange rate, collected from January 4th, 1982 until December 31 st, 2008. The main question is how to estimate extreme quantiles of losses such as the 10-year or 50-year return level.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• Fashion & Textile Research Journal
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• v.13 no.4
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• pp.461-471
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• 2011

Jewelry has recognized as a part of independent formative arts of fashion with the change modern man's cognition for the fashion. It is a great important section to express fashion image. So, many corporations design and develop the jewelry by themselves to maxmize their fashion image. Among the so many kinds of jewelry, especially the necklace is located beneath the face and linked as a part of fashion, so it frequently has showed in Fashion Collection. Like this Fashion and jewelry enact each other and share their esthetic features but, it is insufficient the study of fashion linked with the jewelry. In this study, we defined the words which is using confusedly according to jewelry forms what researched by others. In addition, we tend to study the effect of that the form, hue and character of materials of necklace that is expressed in fashion collection influence fashion image. The method of this study is comprised with precedent studies and analysis of necklace photos in fashion collection. For the analysis of data, we implement content analysis and statistical analysis using SPAW Statistics 18(frequency analysis, percentage, cross-tabulations, $X^2$-test). Because the hue and the form of necklace take a great role to make fashion image with the sense of its eyesight, its effective coordination go up the delicate feelings with the form, hue and quality of the fashion. Especially, the hue is the essential element of formative characteristics to express visual image. The necklace had coordinated more frequently in S/S than F/W, it means that more light and simple fashion let ornamental beauty could express by the necklace. So, it is very effective things that we predict the trend of fashion, then, coordinate with well-matched necklace.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.9
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• pp.1133-1140
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• 2013

A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.

• Korean Institute of Interior Design Journal
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• v.17 no.5
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• pp.91-98
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• 2008

The cafeteria is one of the welfare facilities in the college and crowed with students during lunchtime because of the various menu, saying time and cheap price. In designing the cafeteria, we have to consider the users' needs and the factors which effect on their satisfaction and behavior under the pleasant environment. The purpose of this study is to draw the environmental improvement factors by Post Occupancy Evaluation. A survey about the users' actual condition and environmental satisfaction level and a behavior observation in the field were utilized as the study methode. The 150 copies of questionnaire were completed by students who ate at the cafeteria of W college in Daejeon city. The SPSS 15.0 for Windows was used for a statistical analysis. The results are listed below; two factors were drawn as the improvement elements through the combination of the unsatisfactory items obtained by the descriptive statistics and the influential items by the multi-regression analysis. They are images and approach. In the 'image' category, there us a statistical difference between the present image and prefer image. The users prefer much brighter, warmer, newer, more gorgeous, more cheerful, more clear, more active, more comfortable, and more modern image of cafeteria. In the 'approach', the location of ail existing cafeteria is inaccessible from the classrooms in spite of an important relationship between classrooms and cafeteria. Therefore the complementary plan for convenient approach is demanded for improvement of users' satisfaction.

• Fire Science and Engineering
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• v.15 no.2
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• pp.80-90
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• 2001

It is expected that hotel buildings will be large-scale, luxurious and multiplex according to the needs of modern functions. In addition, building users, who are many and unspecified persons, are short of information on the buildings, so that they may be injured or killed at the occurrence of fire accident. Therefore, in order to overcome such problems, hotel buildings need systematic fire protection facilities concerning particulars to pay attention to the safety on a fire and an evacuation. This study has investigated the following matters. First, it examined hotel use records, statistics relevant to fire accidents, a case investigation related to fire accidents, survey on actual performance of fire protection awareness. Second, it investigated the design planning matters of hotel buildings. Third, it demand to amend the law and regulations related to physical Protection after analyzing them. The purpose of the study is to protect human being and properties at the occurrence of fire accident, and to present basic material for design of hotel buildings to minimize damages and losses.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.33-40
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• 2020

The purpose of the study was to examine the effects of fathers' sex-role attitude and parenting involvement on mothers' parenting stress. The subjects were 383 parents with young children aged 3-5 in Metropolitan area, South Korea. We measured the study variables using the questionnaires. The collected data were analyzed with descriptive statistics, Pearson's correlation analyses, and the analyses of multiple regression using SPSS 21.0. The results showed that both fathers' sex-role attitude and fathers' parenting involvement had the statistically significant negative correlations with mothers' parenting stress. Second, fathers' sex-role attitude and parenting involvement showed the statistically significant negative effects on mothers' parenting stress. We suggest that it is necessary to promote the fathers modern and desirable sex-role attitude and to support fathers' participation in parenting in order to alleviate the parenting stress of mothers with young children.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1295-1303
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• 2015

In a mixture experiment, one may be interested in estimating not only main effects but also some interactions. Main effects and interactions may be estimated through appropriate designs such as simplex-centroid designs. However, the estimability problems, implied by the sum to one functional relationship among the factors, have strong consequences on the confounding and identifiability of models for such designs. To handle these problems, we address homogeneous polynomial model based on the computational commutative algebra (CCA) instead of using $Scheff{\acute{e}}s$ canonical model which is typically used. The problem posed here is to give how to choose estimable main effects and also some low-degree interactions. The theory is tested using a fraction of simplex-centroid designs aided by a modern computational algebra package CoCoA.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.147-156
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• 2013

Each field of modern society, industrialization and the development of science and technology are rapidly changing. However, as a side effect of rapid social change has caused various problems. Crime of the side effects of rapid social change is a big problem. In this paper, a model for predicting crime and Markov chains applied to the crime, predictive modeling is proposed. Markov chain modeling of the existing one with the overall status of the case determined the probability of predicting the future, but this paper predict the events to increase the probability of occurrence probability of the prediction and the recent state of the entire state was divided by the probability of the prediction. And the whole state and the probability of the prediction and the recent state by applying the average of the prediction probability and the probability of the prediction model were implemented. Data was applied to the incidence of crime. As a result, the entire state applies only when the probability of the prediction than the entire state and the last state is calculated by dividing the probability value. And that means when applied to predict the probability, close to the crime was concluded that prediction.