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민석기 ( S. K. Min ),한호성 ( H. S. Han ),김영우 ( Y. W. Kim ),이선영 ( S. Y. Yi ),유권 ( K. Yu ),이남준 ( N. J. Yi ),김유진 ( E. G. Kim ),최용만 ( Y. M. Choi ) 대한소화기학회 2002 대한소화기학회 춘계학술대회 Vol.2002 No.-
〈목적〉 총수 담관 결석의 치료 방법은 내시경적 괄약근 절개를 이용한 결석의 제거나 주된 치료방법이었으나 복강경 수술 방법이 등장하면서 담낭 절제를 포함하여 총수담관 결석을 동시에 치료하는 방법이 대안을 제시되고 있다. 환자의 상황에 따라 이들의 치료 방법이 갖는 장점과 단점을 고려하여 가장 적절한 치료 방법을 적용하는 것이 중요한 것이다, 연구의 목적은 총수 담관 결석의 치료 방법으로 복강경 수술의 적응증과 제한점을 제시하고자 하는 것이다. 〈방법〉
신상욱(S-W Shin),임종민(J-M Lim),황명근(M-K Hwang),이진우(C-W Yi) 한국조명·전기설비학회 2008 한국조명·전기설비학회 학술대회논문집 Vol.2008 No.10월
In recent years, LED's have been adopted for and ever widening range of applications and numerous examples of the replacement of incandescent and fluorescent light sources due to the dramatic improvements in the efficiency of white LED's can be found. Automotive lighting devices, as with other lighting equipment, should exhibit low power consumption, long lifetime and provide new design opportunities. In this paper, an overview of trends of technology and standardization of LED headlamp were investigated and performed various experiments using LED headlamp
U.-K. YI,J.W. LEE,K R. BAEK 한국자동차공학회 2005 International journal of automotive technology Vol.6 No.1
We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distnbution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about 99% of the time.