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스마트홈 서비스를 위한 사용자 피드백 기반 상황인지 모델 학습
권성철(Seongcheol Kwon),김세영(Seyoung Kim),류광렬(Kwang Ryel Ryu) 한국컴퓨터정보학회 2017 韓國컴퓨터情報學會論文誌 Vol.22 No.7
IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user ’s indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.
우주용 냉각기의 미소진동을 이용한 에너지 수확 시스템의 실험적 성능검증
정현모,권성철,오현웅,Jung, Hyunmo,Kwon, Seongcheol,Oh, Hyunung 항공우주시스템공학회 2016 항공우주시스템공학회지 Vol.10 No.3
The on-board appendages of satellites with mechanical moving parts such as the fly-wheel, the control-moment gyro, the cryocooler, and the gimbal-type directional antenna can generate an undesirable micro-vibration disturbance, which is one of the main causes of the image-quality degradation that affects high-resolution observation satellites. Consequently, the isolation of the micro-vibration issue has always been considered as salient, and the micro-vibration is therefore the focus of this study wherein a complex system that can provide the dual functions of a guaranteed vibration-isolation performance and electrical energy harvesting is proposed. The vibration-isolation and energy-harvesting performances of the complex system are predicted through a numerical analysis based on the characteristics that are obtained from component-level tests. In addition, the effectiveness of the complex system that is proposed in this study is verified through an assembly-level functional-performance test.