• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.1-9
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• 2009

Let us consider that the variance function in regression model has a discontinuity/change point at unknown location. Yu and Jones (2004) proposed the local polynomial fit to estimate the log-variance function which break the positivity of the variance. Using the local polynomial fit, Huh (2008) estimate the discontinuity point of the log-variance function. We propose a test for the existence of a discontinuity point in the log-variance function with the estimated jump size in Huh (2008). The proposed method is based on the asymptotic distribution of the estimated jump size. Numerical works demonstrate the performance of the method.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.373-381
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• 1998

본 연구는 교통사고 심각도와 관련된 중요변수를 찾고 이들 변수를 바탕으로 신경망, Decision Tree, 로지스틱 회귀분석을 이용하여 사고 심각도 분류 예측모형을 추정하였다. 다수의 범주형 변수로 이루어진 교통사고 통계원표상의 설명변수 들로부터 사고 심각도변화에 영향력 있는 변수선택을 위하여 $X^2$ 독립성 검정과 Decision Tree를 이용하였고, 선택된 변수들은 신경망과 로지스틱 회귀분석의 기초로 이용되었다. 분석결과 세가지기법간에 분류정확도에는 유의한 차이가 없는 것으로 나타났다. 그러나 decision Tree가 설명변수 선택능력과 분석수행시간, 사고 심각도 결정요인 식별의 용이함 측면에서 범주형 종속변수인 사고 심각도의 분석에 적합합 것으로 보이며 사고 심각도에는 보호장구가 가장 큰 영향을 미치는 것으로 재입증되었다.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.639-647
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• 2013

This paper is a methodological research aimed at developing a mental disorder recovery scale (MDRS) and testing its validity and reliability. After three sessions of factor analysis, a total of three factors using an Eigen value of 1.0 or more were drawn. The explanatory power was found to be 58.1%. All the items met the criteria for communality and factor loading with no item removed, and, ultimately, 25 items were selected. Criterion-related validity test showed that Pearson's correlation coefficient was significant at .71 (p<.01) with significant correlation with each factor (p<.01). The reliability test showed that Cronbach's ${\alpha}$ coefficient was .95 and that Cronbach's ${\alpha}$ coefficient for each factor ranged from .87 to .93. MDRS, which was developed in this study and possessing 3 factors and 25 items, had both its validity and reliability confirmed; therefore, the developed scale would be useful to evaluate the recovery of individuals with mental disorder.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.399-400
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• 2017

홍수나 가뭄 등 극치 현상의 통계분석 및 빈도해석에 있어 극치분포형이 널리 사용되고 있으며, 이러한 극치분포형의 특성을 이해하기 위해서는 분포형의 오른쪽 꼬리(right tail) 부분 특성을 자세히 분석할 필요가 있다. 이에 따라 본 연구에서는 Monte Carlo 모의를 통하여 다양한 극치분포형의 오른쪽 꼬리 부분의 통계적 특성 및 그 예측 능력을 연구하였다. 극치분포형으로는 우리나라 확률수문량 산정에 널리 활용되고 있는 generalized extreme value (GEV), Gumbel, generalized logistic 분포를 사용하였으며, 매개변수 산정 방법으로는 확률가중모멘트법을 사용하였다. 모의실험의 모분포로는 수문빈도해석에서 많이 사용되는 GEV 분포를 사용하였고, 30년 이상 자료를 보유한 기상청 지점 자료의 왜곡도를 조사하여 모의실험에 사용되는 모집단의 왜곡도로 가정하여 표본 자료를 발생시켰다. 예측 능력의 평가는 재현기간 10~1000년의 확률수문량을 왜곡도계수를 고려한 GEV 도시위치공식을 이용하여 GEV 확률지에 도시하고, 평균제곱근오차(root mean square error), 편의(bias), 평균상대오차(mean relative difference), 평균절대상대오차(mean absolute relative difference)를 이용하여 최적 분포형을 선정함으로써 이루어진다. 또한 예측 능력 평가결과의 타당성 확인을 위해 극치분포형의 적합정도를 잘 나타낸다고 알려진 modified Anderson-Darling 방법의 검정결과와 비교하여 적절성을 확인하였다.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.187-194
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• 1998

본 연구는 교통사고 심각도와 관련된 중요변수를 찾고 이들 변수를 바탕으로 신경망, Decision Tree, 로지스틱 회귀분석을 이용하여 사고 심각도 분류 예측모형을 추정하였다. 다수의 범주형 변수로 이루어진 교통사고 통계원표상의 설명변수 들로부터 사고 심각도 변화에 영향력 있는 변수 선택을 위하여 독립성 검정을 위한 $x^2$ test와 Decision Tree를 이용하였고, 선택된 변수들은 신경망과 로지스틱 회귀분석의 기초로 이용되었다. 분석결과 세가지기법간에 분류정확도에는 유의한 차이가 없는 것으로 나타났다. 그러나 Decision Tree가 설명변수 선택능력과 분석수행시간, 사고 심각도 결정요인 식별의 용이함 측면에서 범주형 종속변수인 사고 심각도의 분석에 적합한 것으로 보이며 사고 심각도에는 보호장구가 가장 큰 영향을 미치는 것으로 재입증되었다.

• Journal of Venture Innovation
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• v.3 no.2
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• pp.41-76
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• 2020

This study confirmed factors affecting smart factory technology acceptance through empirical analysis. It is a study on what factors have an important influence on the introduction of the smart factory, which is the core field of the 4th industry. I believe that there is academic and practical significance in the context of insufficient research on technology acceptance in the field of smart factories. This research was conducted based on the Unified Theory of Acceptance and Use of Technology (UTAUT), whose explanatory power has been proven in the study of the acceptance factors of information technology. In addition to the four independent variables of the UTAUT : Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions, Government Assistance Expectancy, which is expected to be an important factor due to the characteristics of the smart factory, was added to the independent variable. And, in order to confirm the technical factors of smart factory technology acceptance, the Task Technology Fit(TTF) was added to empirically analyze the effect on Behavioral Intention. Trust is added as a parameter because the degree of trust in new technologies is expected to have a very important effect on the acceptance of technologies. Finally, empirical verification was conducted by adding Innovation Resistance to a research variable that plays a role as a moderator, based on previous studies that innovation by new information technology can inevitably cause refusal to users. For empirical analysis, an online questionnaire of random sampling method was conducted for incumbents of domestic small and medium-sized enterprises, and 309 copies of effective responses were used for empirical analysis. Amos 23.0 and Process macro 3.4 were used for statistical analysis. For accurate statistical analysis, the validity of Research Model and Measurement Variable were secured through confirmatory factor analysis. Accurate empirical analysis was conducted through appropriate statistical procedures and correct interpretation for causality verification, mediating effect verification, and moderating effect verification. Performance Expectancy, Social Influence, Government Assistance Expectancy, and Task Technology Fit had a positive (+) effect on smart factory technology acceptance. The magnitude of influence was found in the order of Government Assistance Expectancy(β=.487) > Task Technology Fit(β=.218) > Performance Expectancy(β=.205) > Social Influence(β=.204). Both the Task Characteristics and the Technology Characteristics were confirmed to have a positive (+) effect on Task Technology Fit. It was found that Task Characteristics(β=.559) had a greater effect on Task Technology Fit than Technology Characteristics(β=.328). In the mediating effect verification on Trust, a statistically significant mediating role of Trust was not identified between each of the six independent variables and the intention to introduce a smart factory. Through the verification of the moderating effect of Innovation Resistance, it was found that Innovation Resistance plays a positive (+) moderating role between Government Assistance Expectancy, and technology acceptance intention. In other words, the greater the Innovation Resistance, the greater the influence of the Government Assistance Expectancy on the intention to adopt the smart factory than the case where there is less Innovation Resistance. Based on this, academic and practical implications were presented.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.91-94
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• 2007

본 연구는 소유역의 강수계측망별 빈도해석에 의한 확률강우량 예측으로 최적 설계홍수량을 추적하고자 한다 빈도해석은 대전유역내 지방기상청의 낮은 계측망 멸도와 13개 소구역으로 분할된 지자체의 높은 계측망 멸도에서 측정된 강우량 자료를 대상으로 하였다 해석에는 낮은 밀도의 한 지점에서 $1969{\sim}2005$년까지 36년간 자료와 높은 밀도의 13 개 지점에서 $2002{\sim}2006$년까지 6년간 자료를 연초과치 계열로 확장하여 각각 2개군으로 구성하였다 강우자료 분석결과 낮은 밀도의 지속기간 1시간에서 79.1mm, 장시간에서 327.0mm, 높은 밀도의 지속기간 1시간에서 85.0mm, 24시간에서 245.0mm로 나타났다. 본 연구에서는 Gumbel 분포와 2변수 Gamma 분포 및 일반극치분포, $2{\cdot}3$ 변수 대수정규분포, 2변수 Weibull 분포에 ${\chi}^2$검정, K-S 검정으로 적합도를 검정하여 Gumbel 분포가 가장 적합한 것으로 나타났다 유도된 강우강도-지속기간-재현기간 관계식은 소유역내 확률강우강도 예측과 설계홍수량 산정에 유용하게 사용될 수 있을 것이다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1415-1425
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• 2017

Typhoons are accompanied by strong wind and heavy rains. It causes casualties and property damage on the Korean peninsula every year. The effect of typhoon to daily precipitation should be quantified to prevent the damage of typhoon. Daily precipitation, maximum wind speed and, mean wind speed data was collected from 60 weather stations between 1976 and 2016. The parameters of the generalized extreme value distribution were estimated through the maximum likelihood estimation and the L-moment estimation. The impact of a typhoon can be obtained through a comparison of return levels between the whole data and typhoon excluded data. We conclude that the eastern and southern coastline are exposed to the risk of heavy rainfall which is caused by typhoon.

• Fire Science and Engineering
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• v.30 no.1
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• pp.138-148
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• 2016

A firefighting simulation was developed in order to assess the physical work capacity of firefighters. The simulation consisted of eight common firefighting tasks, including walking with radiant heat for 3 min while wearing full personal protective equipment (PPE). Nine professional firefighters performed the test a total of three times with a 5 min rest interval between each session. The entire series of tests took approximately 30 min to complete ($381{\pm}30s$). Rectal temperatures were found to increase from $37.4{\pm}0.3^{\circ}C$ to $38.5{\pm}0.4^{\circ}C$, while heart rates were found to increase from $92{\pm}18bpm$ to $185{\pm}13bpm$ during testing. Time to completion of the test drills and non-modified physical fitness values showed a significantly negative correlation (r = -0.728, p < 0.05). Firefighters who had longer periods of firefighting service had longer duration time and also recorded higher scores using an integrated scoring system of time to completion (TTC) and physiological strain index (PhSI). The results indicated that the determination of TTC alone can be a misrepresentation of capability, as it neglects to account for accumulated heat strain. The simulated firefighting test provided a useful insight into physical fitness level, but also the comprehensive work capacity of the firefighters when assessed based on TTC and PhSI.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.797-810
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• 2017

The Korean peninsula is exposed to typhoons every year. Typhoons cause huge socioeconomic damage because tropical cyclones tend to occur with strong winds and heavy precipitation. In order to understand the complex dependence structure between strong winds and heavy precipitation, the copula links a set of univariate distributions to a multivariate distribution and has been actively studied in the field of hydrology. In this study, we carried out analysis using data of wind speed and precipitation collected from the weather stations in Busan and Jeju. Log-Normal, Gamma, and Weibull distributions were considered to explain marginal distributions of the copula. Kolmogorov-Smirnov, Cramer-von-Mises, and Anderson-Darling test statistics were employed for testing the goodness-of-fit of marginal distribution. Observed pseudo data were calculated through inverse transformation method for establishing the copula. Elliptical, archimedean, and extreme copula were considered to explain the dependence structure between strong winds and heavy precipitation. In selecting the best copula, we employed the Cramer-von-Mises test and cross-validation. In Busan, precipitation according to average wind speed followed t copula and precipitation just as maximum wind speed adopted Clayton copula. In Jeju, precipitation according to maximum wind speed complied Normal copula and average wind speed as stated in precipitation followed Frank copula and maximum wind speed according to precipitation observed Husler-Reiss copula.