• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.2
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• pp.215-222
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• 2004

Drift design methods using resizing techniques have been presented as a practical drift control methods of high-rise buildings. Most drift design methods using the resizing techniques have adopted the cross-sectional area as the design variables for all structural members in a structure. However, the cross-sectional area is not always governing sectional property for the structural members, but the governing sectional property of each member is dependent on the characteristics of member forces. In this paper, a drift design method using the sectional property related to the governing displacement participation factor as the design variable of each member is presented and applied to the drift design of 20-story steel frame-shear wall system. It can be noted from example test that drift design method considering member characteristics shows similar or somewhat better results in the view point of structural weights and the accuracy of displacement estimation.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.407-415
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• 2015

$Na{\ddot{i}}ve$ Bayes Classification is based on input variables that are a conditionally independent given output variable. The $Na{\ddot{i}}ve$ Bayes assumption is unrealistic but simplifies the problem of high dimensional joint probability estimation into a series of univariate probability estimations. Thus $Na{\ddot{i}}ve$ Bayes classier is often adopted in the analysis of massive data sets such as in spam e-mail filtering and recommendation systems. In this paper, we propose a variable selection method based on ${\chi}^2$ statistic on input and output variables. The proposed method retains the simplicity of $Na{\ddot{i}}ve$ Bayes classier in terms of data processing and computation; however, it can select relevant variables. It is expected that our method can be useful in classification problems for ultra-high dimensional or big data such as the classification of diseases based on single nucleotide polymorphisms(SNPs).

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.961-975
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• 2016

The hierarchically penalized support vector machine (H-SVM) has been developed to perform simultaneous classification and input variable selection when input variables are naturally grouped or generated by factors. However, the H-SVM may suffer from estimation inefficiency because it applies the same amount of shrinkage to each variable without assessing its relative importance. In addition, when analyzing imbalanced data with uneven class sizes, the classification accuracy of the H-SVM may drop significantly in predicting minority class because its classifiers are undesirably biased toward the majority class. To remedy such problems, we propose the weighted adaptive H-SVM (WAH-SVM) method, which uses a adaptive tuning parameters to improve the performance of variable selection and the weights to differentiate the misclassification of data points between classes. Numerical results are presented to demonstrate the competitive performance of the proposed WAH-SVM over existing SVM methods.

• Journal of Korean Society of Steel Construction
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• v.24 no.4
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• pp.469-478
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• 2012

In this study, structural behavior of high tension bolted connections was analyzed in order to investigate effective utilizations. Also, the simplified numerical analysis method showing bolt behavior was proposed using the connector element in the ABAQUS, a nonlinear finite element program and verified by numerical analyses on the basis of the experiment of previous study. In an effort to analyze strength properties of plate girder which high tension bolts are applied to, the effects of each design parameter were compared and analyzed after moment-displacement relations were investigated according to design parameters (upper flange, lower flange, upper and lower flange, web) by action force standards.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.871-883
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• 2015

Vector autoregressive (VAR) models in high dimension suffer from noisy estimates, unstable predictions and hard interpretation. Consequently, the sparse vector autoregressive (sVAR) model, which forces many small coefficients in VAR to exactly zero, has been suggested and proven effective for the modeling of high dimensional time series data. This paper studies coupling measures to select non-zero coefficients in sVAR. The basic idea based on the simulation study reveals that removing the effect of other variables greatly improves the performance of coupling measures. sVAR model coefficients are asymmetric; therefore, asymmetric coupling measures such as Granger causality improve computational costs. We propose two asymmetric coupling measures, filtered-cross-correlation and filtered-Granger-causality, based on the filtered residuals series. Our proposed coupling measures are proven adequate for heavy-tailed and high order sVAR models in the simulation study.

• Journal of Korean Society of Transportation
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• v.17 no.1
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• pp.113-129
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• 1999

It is widely recognized that the value of travel time (VOT) plays an important role both in choosing the transportation alternatives on an individual level, and in analyzing and evaluating transportation plans and other public policy makings on a collective level. There is, however, a great deal of difficulties to correctly estimate the VOT. In addition, although there are lots of methods to estimate the VOT so for, not many recommendations have been presented to reflect the localities associated with the VOT derivation in Korea. This study aims at deriving the VOT for different trip purposes and travel modes with their significances tested. To accomplish this purposes, a logit-based travel mode choice model based on revealed preference (RP) data has been formulated, calibrated using the discrete choice model of LIMDEP package for various trip purpose models. For each trip purpose and travel mode, the VOT has been calculated along with the significance testing of the derived VOTs. From the results given in this research, the VOTs for different purposes and modes are identified different, and they are statistically significant. The updated results here in this paper may be a yardstick in evaluating the transportation plans and policies by providing more detailed VOT information for different categories, especially in urban context.

• Culinary science and hospitality research
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• v.21 no.6
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• pp.38-48
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• 2015

This study examined the factors that affect the relationship between dessert cafe customer attribute election, relationship quality and behavioral intention. A total of 260 questionnaires were distributed to consumers, of which 250 were deemed suitable for analysis after the removal of 10 unusable responses. In order to perform statistical analyses required by the study, the SPSS 18.0 Statistical Program was employed for frequency analysis, factor analysis, reliability analysis, correlation, and regression analysis. The results of the exploratory factor analysis showed that three factors regarding attributes selection were extracted from all measurements with a KMO of 0.757 and a total cumulative variance of 67.885%, With regard to relationship quality, three factors were extracted with a total cumulative variance of 76.070% and a KMO score of 0.715. One factor for behavioral intention was extracted that accounted for a total cumulative variance of 66.254% and a KMO score of 0.771. All factors were significant to 0.000 and the correlation between variables was significant. Thus, based on the results, the main research hypothesis that identifies the relationships attributes selection between relationship quality and behavioral intention was partially adopted.

• Culinary science and hospitality research
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• v.22 no.4
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• pp.181-191
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• 2016

This study examined the factors that affect the relationship between eco-friendly agricultural products selection criteria, consumer trust, and recommendation intention. A total of 220 questionnaires were distributed to consumers, of which 210 were deemed suitable for analysis after the removal of 10 unusable responses. In order to perform statistical analyses required in the study, SPSS 18.0 Statistical Program was employed for frequency analysis, factor analysis, reliability analysis, correlations, and regression analysis. The results of exploratory factor analysis showed that four factors regarding eco-friendly agricultural products were extracted from all measurements with a KMO of 0.735 and a total cumulative variance of 79.373%, With regard to consumer trust, one factor was extracted with a total cumulative variance of 75.431% and a KMO score of 0.695. One factor for recommendation intention was extracted that accounted for a total cumulative variance of 68.428% and a KMO score of 0.694. All factors were significant to .000 and the correlation between variables was significant. Thus, based on the results, the main research hypotheses that identify the relationships between selection criteria, consumer trust and recommendation retention were adopted.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.676-681
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• 2018

This paper is designed to address the extent of impacts that religious musicals may have upon on audience in contrast to the mainstream musicals by exploring choice attributes of Christian musicals, which are based on the stories of the Bible. Through empirical analysis, the paper shows that there is positive correlation between choice attributes and viewing satisfaction, while explaining choice attributes' impact on behavioral intention of audience, typically in word-or-mouth intention. It further shows that choice attribute of Christian musicals have direct positive impacts on both of behavioral and word-of-mouth intentions, which revisit intention is positively related to its reputation and the performance place. This study's significance lies in the use of Christian musicals to explore the complex interactions between choice attributes and audiences' behavioral intentions afterwards. However, it will also further benefit if future research include further mediating, control variable, including non-Christians.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.1
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• pp.31-36
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• 2001

본 논문에서는 지점근처에 납-전단 댐퍼(LSD)가 설치된 케이블의 동적 거동에 대해 다루었다. 이러한 동적 거동에 대한 파악은 케이블의 진동 감소 목적으로 댐퍼를 설계하는 경우 중요한 절차중 하나이다. 납-전단 댐퍼와 같은 이력형 댐퍼의 실제 이력곡선에 기초하여 본 연구에서는 납-전단 댐퍼의 이력곡선을 완전 탄소성으로 가정하였다. 납-전단 댐퍼의 역학적 모델은 등가 켈빈 모델을 사용하였으며 케이블의 새그 효과를 고려하였다. 납- 전단 댐퍼의 용량이라고 할 수 있는 항복력을 설계변수로 선택하고 케이블에 최적의 감쇠효과를 부여하는 동적학적 관계에 대해 연구하였다. 또한 댐퍼가 케이블에 설치되는 지점과 케이블의 장력에 대한 댐퍼의 감쇠효과에 대해서도 연구하였다. 매개변수 해석결과 케이블의 기하학적 형상 및 댐퍼의 설치조건에 따라 납-전단 댐퍼가 케이블에 부가하는 감쇠의 크기가 변함을 알 수 있었으며, 이때 최대의 감쇠성능을 발휘하는 최적 항복력이 존재하는 것을 알았다.