Study of the presidential veto power in Korea

본 연구의 목적은 한국 대통령의 법률안 거부권 행사가 어떠한 정치적 상황과 영향변수 하에서 어떻게 이루어져왔는가를 분석하고자 한다. 이를 위해 본 연구는 이승만 대통령부터 현 노무현 대통령에 이르기까지 거부권 행사 사례를 분석하여 이들 거부권 행사에 영향을 미친 요인들을 분석하고자 한다. 나아가 이러한 분석을 통해 거부권 행사와 관련된 각 대통령별 특징적인 요인들과 그 영향 정도를 살펴봄으로써 대통령과 국회의 발전적 관계를 재조명하고자 한다. This paper examined the political circumstances and causes of presidential veto from President Rhee Syng Man to President Roh Moo Hyun. In particular, this paper showed that the divided government, public support, electoral cycle, public concerns, relationship between North and South Korea, and presidential personality have significant effects on presidential veto in Korea. Interestingly, this paper argued that as the Korean society becomes more democratized politically, the internal and external political environments have more significant influences than presidential personality on presidential veto power

Radar Image Extraction Scheme for FMCW Radar-Based Human Motion Indication

본 논문에서는 FMCW 레이다 기반으로 휴먼 모션 인식을 위한 레이다 영상 추출 알고리즘을 제안하였다. 3D(거리-속도-각도) 스펙트럼을 생성하였고, 각 좌표방향으로 압축을 통해 세 개의 마이크로-프로파일 영상을 생성하였다. 이때 몸으로부터 반사된 신호를 억제하기 위한 클러터 억제 알고리즘을 적용하였다. 생성된 거리, 도플러. 각도-영상을 향후 영상처리 및 분류기에 적용함으로써, 다양한 모션 종류를 구별할 수 있을 것으로 판단된다.2

Camera and Radar Fusion Processing Scheme for Vehicle Outdoor Monitoring

We proposed a camera-radar sensor fusion scheme for a intelligence vehicle. For that, we employed track-level and feature-level based fusion technique. Especially, we proposed radar signal and post-data processing schemes for the both sensor fusion methods

Development of Data Logging Platform of Multiple Commercial Radars for Sensor Fusion With AVM Cameras

Currently, various sensors have been used for advanced driver assistance systems. In order to overcome the limitations of individual sensors, sensor fusion has recently attracted the attention in the field of intelligence vehicles. Thus, vision and radar based sensor fusion has become a popular concept. The typical method of sensor fusion involves vision sensor that recognizes targets based on ROIs (Regions Of Interest) generated by radar sensors. Especially, because AVM (Around View Monitor) cameras due to their wide-angle lenses have limitations of detection performance over near distance and around the edges of the angle of view, for high performance of sensor fusion using AVM cameras and radar sensors the exact ROI extraction of the radar sensor is very important. In order to resolve this problem, we proposed a sensor fusion scheme based on commercial radar modules of the vendor Delphi. First, we configured multiple radar data logging systems together with AVM cameras. We also designed radar post-processing algorithms to extract the exact ROIs. Finally, using the developed hardware and software platforms, we verified the post-data processing algorithm under indoor and outdoor environments.2