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CURRENT STATUS OF NUCLEAR FUSION ENERGY RESEARCH IN KOREA
MYEUN KWON,YOUNG SOON BAE,SEUNGYON CHO,최원호,홍봉근,황용석,JIN YONG KIM,KEEMAN KIM,YAUNG-SOO KIM,JONG-GU KWAK,HYEON GON LEE,SANGIL LEE1,나용수,BYUNG-HOON OH,YEONG-KOOK OH,박지연,HYUNG LYEOL YANG,IN KEUN YU 한국원자력학회 2009 Nuclear Engineering and Technology Vol.41 No.4
The history of nuclear fusion research in Korea is rather short compared to that of advanced countries. However, since the mid- 1990s, at which time the construction of KSTAR was about to commence, fusion research in Korea has been actively carried out in a wide range of areas, from basic plasma physics to fusion reactor design. The flourishing of fusion research partly owes to the fact that industrial technologies in Korea including those related to the nuclear field have been fully matured, with their quality being highly ranked in the world. Successive pivotal programs such as KSTAR and ITER have provided diverse opportunities to address new scientific and technological problems in fusion as well as to draw young researchers into related fields. The frame of the Korean nuclear fusion program is now changing from a small laboratory scale to a large national agenda. Coordinated strategies from different views and a holistic approach are necessary in order to achieve optimal efficiency and effectiveness. Upon this background, the present paper reflects upon the road taken to arrive at this point and looks ahead at the coming future in nuclear fusion research activities in Korea.
이상일(Sangil Lee),이한솔(Hansol Lee),유호영(Hoyoung Yu),김영민(Youngmin Kim),이형민(Hyung-Min Lee) 대한전자공학회 2018 대한전자공학회 학술대회 Vol.2018 No.11
In this paper, we analyze the reverse engineering tools for FPGA devices and experimentally verify their performance and limitations. The paper introduces the design flow for Xilinx FPGAs with emphasis on Xilinx Design Language (XDL), XDL Report (XDLRC), and bitstream. Then, existing reverse engineering tools, which utilize the bitstream to recover the netlist, are analyzed with quantitative comparison of measured recovery rates.
친환경 원격 레이저 용접 가공 조건 예측을 위한 신경망 모델 개발
이상일(Sangil Lee),류광열(Kwangyeol Ryu),이화섭(Hwaseop Lee),이경준(Gyeongjun Lee),김덕영(Duckyoung Kim) (사)한국CDE학회 2014 한국 CAD/CAM 학회 학술발표회 논문집 Vol.2014 No.2
원격 레이저 용접(Remote Laser Welding; RLW)은 공정 시간의 감소, 용접 품질의 향상, 유연성 있는 공정 등의 장점을 가지고 있기 때문에 제품 생산 공정에서 각광받는 새로운 기술 중에 하나이다. 뿐만 아니라, 에너지 소비량에 있어서 효율성, 친환경적인 공정 등으로 많은 장점을 가지고 있다. 하지만 원격 레이저 용접은 운영 시스템의 한계로 인하여 레이저 용접 공정 도중에는 제품의 결점 및 용접 공정 에러 여부를 판단할 수 없다는 단점을 지니고 있다. 따라서 본 논문에서는 친환경 원격 레이저 용접시 가공 조건을 예측하기 위하여 신경망을 활용한 원격 레이저 용접 가공 조건 예측 모델을 개발 및 제안한다. 제안된 예측 모델은 레이저 용접 시 레이저 온도, 세기 등을 실시간을 관측하여 불량 및 결점을 줄일 수 있도록 실시간으로 레이저 용접 가공 조건을 변화 시킬 수 있도록 하기 위한 것이며 이를 위해 인공 신경망(Artificial Neural Network; ANN)을 사용한다. 제안된 모델은 원격 레이저 용접에 필요한 컨트롤 모듈로 활용될 수 있으며 제품 결점 및 불량률 감소, 에너지/자원 소비량 감소, 생산성 향상에 많은 도움일 될 것으로 예상된다.
입자상 물질 수량 규제 대응을 위한 디젤 승용자동차의 국내연구기관간 입자상 물질 배출 상관성 시험 및 평가
이형민(Hyungmin Lee),권상일(Sangil Kwon),이상민(Sangmin Lee),전종익(Jongik Jun),우영민(Youngmin Woo),이민호(Minho Lee),명차리(Cha-Lee Myung),박심수(Simsoo Park) 한국자동차공학회 2009 한국자동차공학회 부문종합 학술대회 Vol.2009 No.4
In early 2008, the ILCE (Inter-Laboratory Correlation Exercise) was performed by the Korea Particle Measurement Program (KPMP) with a domestic diesel passenger vehicle equipped with a catalyzed DPF between three certification laboratories and the research center of an automotive manufacturer to meet EURO 5 and EURO 6 of particle number concentration for light-duty vehicles. This paper focused on measuring the particle number and mass levels from a representative light-duty diesel passenger vehicle during new European driving cycle (NEDC) mode to analyze the repeatability and reproducibility between laboratories in Korea. In addition, particle size distribution characteristics from ILCE test vehicle were compared with LPG, gasoline, and non-DPF diesel vehicles. From the ILCE test results in Korea, the mean total particle number concentration levels ranged from 5.43E+10 #/㎞ to 1.58E+11 #/㎞ and 0.0003 g/㎞ to 0.0036 g/㎞ for particle mass. Repeatability between participating laboratories ranged from 32% to 66% for particle number, 11% to 70% for particle mass; the reproducibility level was 46% for particle number, and 66% for particle mass emission.
Realtime Object-aware Monocular Depth Estimation in Onboard Systems
Sangil Lee,Chungkeun Lee,Haram Kim,H. Jin Kim 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.9
This paper proposes the object depth estimation in real-time, using only a monocular camera in an onboard computer with a low-cost GPU. Our algorithm estimates scene depth from a sparse feature-based visual odometry algorithm and detects/tracks objects’ bounding box by utilizing the existing object detection algorithm in parallel. Both algorithms share their results, i.e., feature, motion, and bounding boxes, to handle static and dynamic objects in the scene. We validate the scene depth accuracy of sparse features with KITTI and its ground-truth depth map made from LiDAR observations quantitatively, and the depth of detected object with the Hyundai driving datasets and satellite maps qualitatively. We compare the depth map of our algorithm with the result of (un-) supervised monocular depth estimation algorithms. The validation shows that our performance is comparable to that of monocular depth estimation algorithms which train depth indirectly (or directly) from stereo image pairs(or depth image), and better than that of algorithms trained with monocular images only, in terms of the error and the accuracy. Also, we confirm that our computational load is much lighter than the learning-based methods, while showing comparable performance.
Exposure Correction and Image Blending for Planar Panorama Stitching
Sangil Lee,Seung Jae Lee,Jaehyun Park,H. Jin Kim 제어로봇시스템학회 2016 제어로봇시스템학회 국제학술대회 논문집 Vol.2016 No.10
In this paper, we propose a planar panorama stitching method to blend consecutive images captured by a multirotor equipped with a fish-eye camera. In addition, we suggest an exposure correction method to reduce the brightness difference between contiguous images, and a drift error correction method to compensate the estimated position of multirotor. In experiments, the multi-rotor flies at 35 meters above the ground, and the fish-eye camera attached in gimbals system takes pictures. Then we validate the performance of the algorithm with processing video frames. In order to supervise and observe a specific region, it is more efficient to blend multiple captured images, because it is possible to construct a planar map with higher resolution at low cost. In detail, first, geographic relation between consecutive images is estimated by using Euclidean homography. At the same time, the proposed algorithm estimates the position of multi-rotor on the planar map, so that it is possible to blend images with minimizing the variance of drift error. Then, the proposed algorithm uses histogram matching to compensate the different brightness of images. For this, we divide an image into three layers: background, foreground, and overexposure. Finally, we use multi-band blending to create a seamless panorama.