화제의 인물 : 도심(都心)속의 서당 -백곡서당(白谷書堂)과 한학자(漢學者) 백곡(白谷) 김대현(金大顯) 선생-

김대현 전국한자교육추진총연합회 2005 한글한자문화 Vol.76 No.-

천초근의 발암성 연구를 위한 분석 및 안정성 시험

김대현,박진호,김승현,성상현 한국생약학회 2012 생약학회지 Vol.43 No.2

The marker constituent was isolated from Rubia cordifolia as a major compound. Quantitative method for the marker of the natural medicine was developed using HPLC-DAD and using established method the extract of Rubia cordifolia was evaluated. In addition, long term and accelerated stability test in the extract was examined for six months. No significant change in content of the marker constituent of the extract observed during the period of long term test.

구조 건전성 감시 기술을 활용한 첨단 비파괴 검사 기술

김대현 한국비파괴검사학회 2012 한국비파괴검사학회지 Vol.32 No.1

Vibration-Monitoring of a Real Bridge by Using a Moir'e-Fringe-Based Fiber Optic Accelerometer

김대현,Jong-Jae Lee 한국비파괴검사학회 2007 한국비파괴검사학회지 Vol.27 No.6

This paper presents the use of a novel fiber optic accelerometer system to monitor ambient vibration (both wind-induced one and vehicle-induced) of a real bridge structure. This sensor system integrates the Moir fringe phenomenon with fiber optics to achieve accurate and reliable measurements. A low-cost signal processing unit implements unique algorithms to further enhance the resolution and increase the dynamic bandwidth of the sensors. The fiber optic accelerometer has two major benefits in using this fiber optic accelerometer system for monitoring civil engineering structures. One is its immunity to electromagnetic (EM) interference making it suitable for difficult applications in such environments involving strong EM fields, electrical spark-induced explosion risks, and cabling problems, prohibiting the use of conventional electromagnetic accelerometers. The other is its ability to measure both low- and high-amplitude vibrations with a constantly high resolution without pre-setting a gain level, as usually required in a conventional accelerometer. The second benefit makes the sensor system particularly useful for real-time measurement of both ambient vibration (that is often used for structural health monitoring) and strong motion such as earthquake. Especially, the semi-strong motion and the small ambient one are successfully simulated and measured by using the new fiber optic accelerometer in the experiment of the structural health monitoring of a real bridge.

Ambient Vibration-Measurement of Real Building Structure by Using Fiber Optic Accelerometer System

김대현 한국비파괴검사학회 2006 한국비파괴검사학회지 Vol.26 No.6

structural health monitoring is one of non-destructive evaluation (NDE) techniques for civil infrastructures. This paper presents a novel fiber optic accelerometer system to monitor civil engineering structures and a successful application of the novel sensor system for measuring ambient vibration of a real building structure. This sensor system integrates the Moir fringe phenomenon with fiber optics to achieve accurate and reliable measurements. The sensor system is immune to electromagnetic (EM) interference making it suitable for difficult applications in such environments involving strong EM fields, electrical spark-induced explosion risks, and cabling problems, prohibiting the use of conventional electromagnetic accelerometers. A prototype sensor system has been developed, together with a signal processing software. The experimental studies demonstrated the high-performance of the fiber optic sensor system. Especially, the sensor was successfully used for monitoring a real building on UCI (University of California Irvine, USA).

남여관계 풍자소설의 발전과 경험적 세계의 수용

김대현 근역한문학회 1990 漢文學論集 Vol.8 No.-

비화학양론적 Na⁺β-alumina를 위한 Mg 원자의 치환: 제일원리 계산

김대현,김대희,정용찬,서화일,김영철,Kim, Dae-Hyun,Kim, Dae-Hee,Jeong, Yong-Chan,Seo, Hwa-Il,Kim, Yeong-Cheol 한국재료학회 2010 한국재료학회지 Vol.20 No.2

$Na^+$ ion conductivity can be improved by the substitution of an Mg atom for an Al atom to form a nonstoichiometric $Na^+$ $\beta$-alumina. We performed a first principles study to investigate the most stable substitution site of an Mg atom and the resulting structural change of the nonstoichiometric $Na^+$ $\beta$-alumina. Al atoms were classified as four different layers in the spinel block that are separated by conduction planes in the nonstoichiometric $Na^+$ $\beta$-alumina. The substitution of an Mg atom for an Al atom at a tetragonal site was more favorable than that at an octahedral site. The substitution in the spinel block was more favorable than that close to the conduction plane. This result was well explained by the volume changes of the polyhedrons, by the standard deviation of the Mg-O distance, and by the comparison with bulk MgO structure. Our result indicates that the most preferable site for the Mg atom was the tetrahedral site at the spinel block in the nonstoichiometric $Na^+$ $\beta$-alumina.

Application of Neural Network Model to Vehicle Emissions

김대현,이정 서울시립대학교 도시과학연구원 2010 도시과학국제저널 Vol.14 No.3

The issue of air quality is now a major concern around the world and the vehicle emissions model is very important. Most of the current vehicle emission models are multiple regression techniques. In this study, a neural network-based model has been proposed to achieve better estimation accuracy. The estimation performance of two models, the proposed neural network-based model and a general regression model, has been compared using mean absolute error (MAE). A comparative study between two models to estimate vehicle emissions, the proposed neural network-based model and a general regression model, has been conducted to assess the estimation performance of the proposed model in terms of mean absolute percentage error. Experimental results in this study revealed that the neural network model performed better as it was able to decrease the error for emission estimation comparing with the multiple regression models. More importantly, in this study a lookup table (LUT) method has been proposed to overcome the black-box problem, which is a disadvantage of the neural network models. It could be useful for any other researches to estimate emissions without developing and training the neural network model which can be a time-consuming task. The issue of air quality is now a major concern around the world and the vehicle emissions model is very important. Most of the current vehicle emission models are multiple regression techniques. In this study, a neural network-based model has been proposed to achieve better estimation accuracy. The estimation performance of two models, the proposed neural network-based model and a general regression model, has been compared using mean absolute error (MAE). A comparative study between two models to estimate vehicle emissions, the proposed neural network-based model and a general regression model, has been conducted to assess the estimation performance of the proposed model in terms of mean absolute percentage error. Experimental results in this study revealed that the neural network model performed better as it was able to decrease the error for emission estimation comparing with the multiple regression models. More importantly, in this study a lookup table (LUT) method has been proposed to overcome the black-box problem, which is a disadvantage of the neural network models. It could be useful for any other researches to estimate emissions without developing and training the neural network model which can be a time-consuming task.

Neural Network-based O-D Matrix Estimation from Link Traffic Counts

김대현,장요한 서울시립대학교 도시과학연구원 2008 도시과학국제저널 Vol.12 No.2

The Origin-Destination (O-D) trip table is an essential ingredient in a wide variety of travel analysis and planning studies and increasing attention has been paid to methods for the estimation of O-D matrices from traffic counts over past decade. The O-D estimation from link traffic counts has attracted lot of interest and many methods have been proposed to obtain O-D trip tables based on link counts. In this study, we propose a neural network model for O-D estimation from link traffic counts in more complicated urban street networks. Moreover, a training method for the application of a neural network model in O-D estimation has been proposed in order to achieve more accurate predictive results. The experimental results showed that the proposed neural network model can be much more efficient and accurate than currently usual methods based on traffic assignment models. The Origin-Destination (O-D) trip table is an essential ingredient in a wide variety of travel analysis and planning studies and increasing attention has been paid to methods for the estimation of O-D matrices from traffic counts over past decade. The O-D estimation from link traffic counts has attracted lot of interest and many methods have been proposed to obtain O-D trip tables based on link counts. In this study, we propose a neural network model for O-D estimation from link traffic counts in more complicated urban street networks. Moreover, a training method for the application of a neural network model in O-D estimation has been proposed in order to achieve more accurate predictive results. The experimental results showed that the proposed neural network model can be much more efficient and accurate than currently usual methods based on traffic assignment models.

웨이퍼레벨 진공패키지 적외선 센서의 신호특성 연구

김대현,박안진,엄주범,신인희,이병일 한국진공학회 2015 한국진공학회 학술발표회초록집 Vol.2015 No.2