• Journal of Positioning, Navigation, and Timing
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• 제4권2호
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• pp.79-85
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• 2015

Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

• 물과 미래
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• 제26권1호
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• pp.51-62
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• 1993

연유출량에 영향을 미치는 가장 직접적인 인자는 강수량인데 회귀분석을 이용한 이전의 연구에서는 유출률이 20% 미만 또는 100% 이상인 경우에는 강수와 유량자료는 이상점(outlier)으로서 분석에서 제외시킨 결과 강수량은 독립변수로서 의의가 없고 대신 유역면적을 중요한 독립변수로 포함시켰다. 본 연구에서는 유출률대신 (연강수량-연유출량)을 연증발산량의 좋은 추정치로 간주하고 우리나라에서 가능한 연증발산의 범위를 벗어나는 자료를 제외시키고 회귀분석을 한 결과 수문학적인 이론에 부합되며 결정계수가 높은 다음과 같은 회귀분석식을 얻었다. R=-518.25+0.8834P 단, R: 유출고(mm) P: 연강수량(mm) 이 회귀분석식은 cross-validation을 거친 결과 계수가 매우 안정되어 있어서 우리나라의 미계측 중소수게에서 사용할 수 있는 좋은 연유출량 추정모델로서 제안한다.

• 한국항해항만학회지
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• 제38권1호
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• pp.65-71
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• 2014

국내 경부고속도로와 남해고속도로는 부산항을 각각 남북방향과 동서방향으로 연계하며 20%이상의 중대형화물트럭 혼재율과 특정시간대 통행량이 집중되는 핵심 간선도로로 시간교통량계수(K-factor)에 대해 연구의 필요성을 깨닫게 되었다. 그리하여 본 연구에서는 경부고속도로와 남해고속도로의 기본구간에서 단기간동안 수집된 차량검지시스템(vehicle detection system, VDS)자료를 이용하여 고속도로의 K-factor와 K-factor추정치(estimate)사이의 상관분석을 통해서 고속도로의 K-factor추정모형 구축을 목적으로 연구하였다. 결과적으로 7일 VDS자료의 K-factor추정치(estimate)와 함께 파워(POW)모형이 K-factor를 추정에 높은 설명력과 신뢰성이 있음을 확인할 수 있었다.

• 보건교육건강증진학회지
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• 제23권4호
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• pp.13-28
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• 2006

Objectives: This study used the characteristics of the knowledge discovery and data mining algorithms to develop hypertension predictive model for hypertension management using the Korea National Health Insurance Corporation database(the insureds' screening and health care benefit data). Methods: This study validated the predictive power of data mining algorithms by comparing the performance of logistic regression, decision tree, and ensemble technique. On the basis of internal and external validation, it was found that the model performance of logistic regression method was the best among the above three techniques. Results: Major results of logistic regression analysis suggested that the probability of hypertension was: - lower for the female(compared with the male)(OR=0.834) - higher for the persons whose ages were 60 or above(compared with below 40)(OR=4.628) - higher for obese persons(compared with normal persons)(OR= 2.103) - higher for the persons with high level of glucose(compared with normal persons)(OR=1.086) - higher for the persons who had family history of hypertension(compared with the persons who had not)(OR=1.512) - higher for the persons who periodically drank alcohol(compared with the persons who did not)$(OR=1.037{\sim}1.291)$ Conclusions: This study produced several factors affecting the outbreak of hypertension using screening. It is considered to be a contributing factor towards the nation's building of a Hypertension Management System in the near future by bringing forth representative results on the rise and care of hypertension.

• Earthquakes and Structures
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• 제24권6호
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• pp.429-437
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• 2023

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

• 한국화재소방학회논문지
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• 제33권6호
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• pp.72-79
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• 2019

본 연구를 통해 화학사고 사상사고 예측모형을 개발하였다. 모형은 로지스틱회귀분석 모델을 활용하여 사상사고에 영향을 주는 변수를 도출하여 적용하였고, 통계적 검증방법과 오즈비를 활용하여 모형의 신뢰성 및 정확성을 검증하였다. 모형에 활용한 사고 자료는 과거 발생했던 화학사고 통계를 분석하여 활용하였으며, 사고의 유형, 원인, 발생 장소, 사상자 현황 및 사상자를 발생시킨 화학사고 등의 자료 분석을 통해 통계적으로 유의하게 나타난 독립변수(p < 0.05)를 적용하였다. 본 연구에서 개발한 모형은 사업장에서 화학사고로 인해 발생하는 사상사고의 예방 및 안전시스템 구축을 위한 연구로서 의의가 있다고 할 수 있다. 모형에 의한 분석결과 사상사고 발생에 가장 크게 영향을 미치는 변수는 폭발에 의한 화학사고인 것으로 조사되었다. 따라서 사업장에서 발생하는 폭발 유형의 화학사고를 예방하기 위한 대책마련이 시급하다고 판단된다.

• 대한안전경영과학회지
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• 제11권4호
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• pp.15-24
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• 2009

The object of this study is to understand the psychological factor of the worker on safety and recommend the experimental factor of safety education program. The following are the methods of this study. We analyzed the statistical data from survey to workers(N=139) about the psychological factor on safety. The survey consisted of 34 questions about 4 factors like private external characteristic, psychological characteristic, characteristics on behavior, and experience and reason of disaster. As the result of the analysis of the multi regression model on the base of correlation of each of the major factors, psychological health, effort on practicing, and satisfaction on their life were the variables with high influence on the safety mind of workers. So, it is good safety strategy for effective working to maintain healthy life with optimistic minds, and try to practice actively as usual. After considering the result, for the development of safety education program for working, we have to consider psychological factors of our workers that influence their safety and try to improve the experimental education opportunity, and it will be effective.

• 한국컴퓨터정보학회논문지
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• 제22권7호
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• pp.109-115
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• 2017

This study was performed to investigate the changes in turnover intention according to the level of occupational stress and to find the mediating factor that reducing the turnover intention among fire officer. To compare change of turnover intention according to the degree of occupational stress, statistical analyses were done by using the logistic regression model. In logistic regression analysis, the possibility of high turnover intention in a group with high occupational stress was hjgher by 4.11 times than a group with low occupational stress. The results of analyzing the degree of change in turnover intention after applying the mediating parameters(physical condition, emotional labor, burn out), turnover intention decreased by about 50.6%(from 4.11 times to 2.03 times) at the high level of occupational stress. As a result, it was found that the occupational stress experienced by the fire-officers had a positive effect on the turnover intention. In order to reduce the turnover intention due to the occupational stress of the fire-officers, it is necessary to manage factors such as work environmental factors(emotional labor, burn out) and individual factor(physical condition).

• 천문학회보
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• 제41권1호
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• pp.79.3-80
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• 2016

We have investigated the correlation analysis between global temperature anomaly and two main factors: geomagnetic activity (aa index) of Earth external factor and CO2 of Earth internal factor. For this, we used NOAA Global Surface Temperature anomaly (Ta) data from 1868 to 2015. The aa index indicates the geomagnetic activity measured at two anti-podal subauroral stations (Canberra Australia and Hartland England) and the CO2 data come from historical ice core records and NOAA/ESRL data. From the comparison between (Ta) and aa index, we found several interesting things, First, the linear correlation coefficient between two parameters increases until 1985 and then decreases rapidly. Second, the scattered plot between two parameters shows a boundary of the correlation tendency (positive and negative correlation) near 1985. A partial correlation of (Ta) and two main factors (aa index, CO2) also shows that the geomagnetic effect (aa index) is dominant until about 1985 and the CO2 effect becomes much more important after then. These results indicate that the CO2 effect become very an important factor since at least 1985. For a further analysis, we simply assume that Ta = Ta(aa)+Ta(CO2) and made a linear regression between (Ta) and aa index from 1868 to 2015. A linear model is then made from the linear regression between energy consumption (a proxy of CO2 effect) and Ta-Ta(aa) since 1985. Our results will be discussed in view of the prediction of global warming.

• Geomechanics and Engineering
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• 제28권4호
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• pp.397-404
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• 2022

Accurate prediction of the undrained shaft resistance is essential for robust design of bored piles in undrained condition. The undrained shaft resistance is calculated using the undrained adhesion factor multiplied by the undrained cohesion of the soil. However, the available correlations to predict the undrained adhesion factor have been developed using simple regression techniques and the accuracy of these correlations has not been thoroughly assessed in previous studies. The lack of the assessment of these correlations made it difficult for geotechnical engineers to select the most accurate correlation in routine designs. Furthermore, limited attempts have been made in previous studies to use advanced data mining techniques to develop simple and accurate correlation to predict the undrained adhesion factor. This research, therefore, has been conducted to fill these gaps in knowledge by developing novel and robust correlation to predict the undrained adhesion factor. The development of the new correlation has been conducted using the multi-objective evolutionary polynomial regression analysis. The new correlation outperformed the available empirical correlations, where the new correlation scored lower mean absolute error, mean square error, root mean square error and standard deviation of measured to predicted adhesion factor, and higher mean, a20-index and coefficient of correlation. The correlation also successfully showed the influence of the undrained cohesion and the effective stress on the adhesion factor. Hence, the new correlation enhances the design accuracy and can be used by practitioner geotechnical engineers to ensure optimized designs of bored piles in undrained conditions.