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Lee, Eunji,Chung, Yoonsung,Lee, Doohee,Yoon, Jaesik,Lincoln, Christopher,Prorok, Bart Charles,Woo, Sungpil,Yoon, Young Soo,Kim, Dong-Joo The Electrochemical Society 2017 ECS transactions Vol.77 No.11
<P>This work presents a facile solution method to fabricate graphene oxide (GO) on fabrics for a wearable electronic nose sensor. Three types of fabrics such as nylon, polyester, and cotton were used as wearable substrates. Thin PVC film was laminated on the fabrics to promote deposition of electrodes on the fabrics. To determine types of solution for constructing GO on the fabrics, water and ethanol were compared as typical solvents to disperse GO. Water distributed GO nanoflake was uniformly coated on the fabrics by simple drop coating. Room temperature gas sensing was examined with GO integrated on the fabrics, and it exhibited n-type gas sensing behavior on 100 ppm ammonia and its response showed comparable values in resistance change with flat substrates.</P>
Deep Learning in MR Image Processing
Lee, Doohee,Lee, Jingu,Ko, Jingyu,Yoon, Jaeyeon,Ryu, Kanghyun,Nam, Yoonho Korean Society of Magnetic Resonance in Medicine 2019 Investigative Magnetic Resonance Imaging Vol.23 No.2
Recently, deep learning methods have shown great potential in various tasks that involve handling large amounts of digital data. In the field of MR imaging research, deep learning methods are also rapidly being applied in a wide range of areas to complement or replace traditional model-based methods. Deep learning methods have shown remarkable improvements in several MR image processing areas such as image reconstruction, image quality improvement, parameter mapping, image contrast conversion, and image segmentation. With the current rapid development of deep learning technologies, the importance of the role of deep learning in MR imaging research appears to be growing. In this article, we introduce the basic concepts of deep learning and review recent studies on various MR image processing applications.
앙상블 기법을 활용한 대형복합건축물의 화재 피난가능시간 예측에 관한 해석적 연구
이두희(DooHee Lee),김학경(HakKyung Kim),김전수(Jeon Soo Kim),황현수(Hyun Soo Hwang),최두찬(DooChan Choi) 한국방재학회 2022 한국방재학회논문집 Vol.22 No.5
최근 건축물의 화재위험도가 높아짐에 따라 화재발생 시 많은 인명피해가 발생하고 있으며, 성능위주설계의 중요성이 강조되고있나. 그러나 성능위주 소방설계를 위한 시뮬레이션의 경우, 많은 인력 및 시간이 소요되며 경미한 변경에도 다시 수행해야하는 어려움이 있다. 따라서 본 연구에서는 앙상블기법을 적용하여 화재거리 별 허용피난시간을 화재인자 및 공간인자로쉽게 예측할 수 있는 예측모델을 개발하고자 하였다. FDS 데이터에 기반하여 기계학습을 통해 개발한 예측모델은 결정계수가0.91에 달하는 높은 예측률을 보였으며, 이러한 예측모델을 적용하여 실시간으로 거리별 ASET을 도출할 수 있을 것으로판단된다. With the recent increase in the risk of fire in buildings, the number of casualties that occur in the event of a fire have increased. This emphasizes the importance of performance-based design. However, simulating a performance-based design requires a lot of manpower and time, and re-simulation with minor changes is a difficult task. Therefore, in this study, we attempt to develop a prediction model that can easily predict the ASET for each fire distance as a fire factor and spatial factor by applying ensemble learning. The prediction model developed using machine learning based on FDS data showed a high coefficient of determination of 0.91, and we believe that ASET for each distance can be derived in real time by applying this prediction model.
이두희(Doohee Lee),김용재(Yongjae Kim),한석현(Seokhyeon Han),오승준(Seungjun Oh) 한국화재소방학회 2023 한국화재소방학회논문지 Vol.37 No.6
원자력발전소 주제어실에는 발전소 운전을 위한 운전원이 항시 거주하고 있다.그 러나 주제어실에서 화재가 발생한 경우, 다양한 기준에서 운전원의 거주성에 대한 상이한 조건을 제시하고 있으며, 그에 따라 다양한 피난안전성 평가결과가 도출될 수있 다.따 라서 본 연구에서는주 제어실에 대한 화재및 피난 시뮬레이션을수 행하여 ASET과 RSET을 도출함으로써 다양한 기준에 대한 주제어실의 피난안전성 및 거주성을 평가하였다. The operator is always present in the main control room (MCR) of a nuclear power plant. However, when a fire occurs in an MCR, different conditions for operator habitability are proposed using various criteria, and various evacuation safety evaluation results can be obtained. In this study, fire and evacuation simulations of an MCR were performed to determine the available safe egress time and required safe egress time. In addition, the evacuation safety and habitability of the MCR were evaluated for various criteria.
이두희 ( Doohee Lee ),김지호 ( Jiho Kim ),김형국 ( Hyung-guk Kim ),송오영 ( Ohyoung Song ) 한국정보처리학회 2012 한국정보처리학회 학술대회논문집 Vol.19 No.2
본 논문에서는 IEEE 802.15.4 Zigbee 통신기술을 이용하여 센서 네트워크를 구성하고 사용자의 위치를 사용자가 소지한 Zigbee 동글로부터 수신된 단말 정보와 사용자의 미디어 히스토리 정보를 기반으로 모바일 디바이스와 PC와 같은 디스플레이 자원에서 개인화된 멀티미디어 콘텐츠 이어보기 서비스를 제공하는 서비스 플랫폼을 제안하였다.