http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
최현태 ( Hyun Tae Choi ) 한국환경법학회 2012 環境法 硏究 Vol.34 No.1
The Remedies of the Private Law on the Damage for the Light Pollution Choi, Hyun Tae Recently, as society develop, Legal disputes about environmental issues has been increasing. Nevertheless, Great attention has been shown to the question of Prospect Right and Right to have sunlight. But researchers pay scant attention to the Legal protection of Light Pollution in Korea until now, although much has been said about the Legal protection of Light Pollution in other country. This article emerged from the question of the civil liability about Damage caused by Light pollution in civil case term, because The Protection Law of Light Pollution caused by the scattering of artificial light enacted by parliament in this year. Light pollution is the night sky glow caused by the scattering of artificial light in the atmosphere. To prevent light pollution, an outdoor lighting fixture that exceeds a certain output may be installed, replaced, maintained, or operated using state funds only if it is a cutoff luminaire, meaning one emitting only a limited amount of light above the plane of the light. Although legal disputes created by Light Pollution hasn`t arisen so far, the disputes will take in the court since this law take effect in 2013. So far, very little has been done about this. Therefore, the article will look for what is reasonable to apply the civil law principles by reviewing action for infringement of the environment that dealt with noise pollution, vibration, and others. This article is expected to contribute civil litigation concerning light pollution to important material.
인공지능 : 날씨,조명 판단 및 적응적 색상모델을 이용한 도로주행 영상에서의 이정표 검출
김태형 ( Tae Hung Kim ),임광용 ( Kwang Yong Lim ),변혜란 ( Hye Ran Byun ),최영우 ( Yeong Woo Choi ) 한국정보처리학회 2015 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.4 No.11
Road-view object classification methods are mostly influenced by weather and illumination conditions, thus the most of the research activities are based on dataset in clean weathers. In this paper, we present a road-view object classification method based on color segmentation that works for all kinds of weathers. The proposed method first classifies the weather and illumination conditions and then applies the weather-specified color models to find the road traffic signs. Using 5 different features of the road-view images, we classify the weather and light conditions as sunny, cloudy, rainy, night, and backlight. Based on the classified weather and illuminations, our model selects the weather-specific color ranges to generate Gaussian Mixture Model for each colors, Green, Yellow, and Blue. The proposed method successfully detects the traffic signs regardless of the weather and illumination conditions.