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유동층 열분해로에 의하여 생산된 상수리나무 바이오오일의 특성
이선훈,엄민섭,유경선,이영수,김남찬,이시훈,이재구,김재선,Lee Sun-Hoon,Eom Min-Seop,Yoo Kyung-Seun,Lee Young-Soo,Kim Nam-Chan,Lee See-Hoon,Lee Jae-Goo,Kim Jae-Ho 한국자원리싸이클링학회 2006 資源 리싸이클링 Vol.15 No.1
Fast pyrolysis of Quercus acutissima was carried out in a fluidized bed pyrolyser and then the physicochemical properities of obtained bio-oil were analyzed using GC/MS. The yields of bio-oil of Quercus acutissima and Larix leptolepis from a fluidized bed pyrolyzer were maximized at $350^{\circ}C\;and\;400^{\circ}C$, respectively. This is due to the difference or cellulose content between the two tree species. Above the optimum temperature, the yields of char and oil decreased as the reaction temperature increased, but the yield of gas-phase and water fraction increased. It is concluded that this phenomenon is occured by secondary pyrolysis in the free board. The feeding rate of the sample in a fluidized bed pyrolyser did not affect the yields and composition of products, because of a sufficient mixing between bed materials and sand. 유동층 열분해로에서 상수리나무의 급속열분해를 수행하고 생성된 바이오오일의 물리화학적 특성을 GC/MS를 이용하여 분석하였다. 유동층 열분해로에서 얻어진 상수리나무와 낙엽송의 바이오오일 수율은 각각 $350^{\circ}C,\;400^{\circ}C$에서 최대치를 보였으며 이는 두 수종간의 셀룰로오스 함량차이에 기인하는 것으로 추정된다. 최적온도 이상에서는 반응온도가 증가할수록 프리보드에서의 2차 열분해에 의하여 촤와 오일의 수율이 감소하였고 가스상 성분과 수분의 함량이 증가하였다. 유등층 열분해로에서 시료의 투입량은 생성물의 수율과 조성에는 큰 영향을 주지 않았으며 이는 충분한 혼합이 이루어지기 때문으로 판단되었다.
상관우물들이 분포하는 화산섬 집수역에 대한 지하수 양수능의 평가 2. 수질을 고려한 경우
이선훈 ( Sun Hoon Lee ),정전공 ( MACHIDA Isao ),정본유향리 ( IMOTO Yukari ) 한국환경영향평가학회 2003 환경영향평가 Vol.12 No.3
The withdrawal method for protecting the uncontaminated part from the spread of contaminants was suggested by a simultaneous equation. The formulation of them is based upon the build up of the ridge part between the contaminated and uncontaminated parts that resulted from the efficient use of barrier wells. The quality in the withdrawn groundwater depends upon the heads at wells no. 5 and 6. The determination of pumping rates and qualities with changing the heads at wells no. 5 and 6 should be given by considering the demand for water use and the capacity and cost for removing the contained contaminants. The results of this study should be used in taking a plan for supplying water use as well as preventing the spread of contaminants from some known contaminated sources.
이선훈 ( Seon Hoon Lee ),오흥선 ( Heung-seon Oh ) 한국정보처리학회 2019 한국정보처리학회 학술대회논문집 Vol.26 No.1
일반적으로 멀티 온라인 배틀 게임은 게임의 참가자들이 팀을 이루어 전략을 짜고 협력하여 주어진 목적을 성취하면 승리한다. 게임에서는 승리를 판가름 할 수 있는 다양한 요소(e.g. 골드, 아이템, 캐릭터의 레벨 등)들이 있다. 본 논문에서는 게임 플레이 중에 다양한 요소를 분석하여 실시간으로 승률을 예측할 수 있는 딥러닝 기반의 모델을 제안하고 이를 리그오브레전드 게임에 적용하여 그 결과를 분석하였다.
불확실성을 이용한 딥러닝 기반의 항공 이미지 객체 탐지
박주찬(Joo-Chan Park),이선훈(Seon-Hoon Lee),정준욱(Jun-Uk Jung),손성빈(Sung-Bin Son),오흥선(Heung-Seon Oh),정유철(Yuchul Jung) 제어로봇시스템학회 2020 제어·로봇·시스템학회 논문지 Vol.26 No.11
Object detection in aerial images is an important task because it is used in various applications such as land management, disaster monitoring, national security, and map production, However, owing to the characteristics of aerial images, such as high resolution, data imbalance between classes, lack of data, and densely appearing objects, it is difficult to improve the performance even with the recent deep learning-based object detection models. To overcome these challenges, this paper proposes an uncertainty-based max-margin learning method and a data augmentation method based on attribute transformation specialized for aerial images. The superiority of the proposed methods based on a deep learning-based object detection model is revealed by it winning the aerial image object detection contest 2020.
반도체 불량원인 분석을 위한 딥뉴럴네트워크 기반의 패치 이미지 병합 시스템
손성빈(Sung-Bin Son),이선훈(Seon-Hoon Lee),박주찬(Joo-Chan Park),정준욱(Jun-Uk Jung),박용준(Yong-Joon Park),오흥선(Heung-Seon Oh) 제어로봇시스템학회 2021 제어·로봇·시스템학회 논문지 Vol.27 No.8
In the integrated circuit/chip manufacturing process, failure analysis performed to find defects utilizes high-resolution chip images obtained through auto-shot scope equipment, which combines microscopy and automatic photography. However, due to the incorrect focus and the unexpected overlap size depending on the distance between the microscope and the chip, these systems are noisy. Thus, failure analysis cannot be performed effectively because the individual conduction the examination is exposed to noisy images, thereby taking a long time. We proposed a system called DeepMerge that utilizes deep learning-based learning-based features such as pint extraction and feature matching to overcome the aforementioned challenges. We will be indicating the effectiveness and efficiency of our system by obtaining practical image data from the industry.