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재배온도 및 유전자원에 따른 동부나물 생장반응 및 영양성분 변화
김 동관,김 영민,천 상욱,임 요섭,최 진경,권 오도,박 흥규,신 해룡,최 경주 한국작물학회 2014 Korean journal of crop science Vol.59 No.3
The purpose of this study was to establish the optimal growth temperature and to select genetic resources for production of cowpea sprouts. Seowon was treated between 15°C and 30°C at intervals of 3°C to investigate growth temperature. Twelve resources, including Seowon, IT154149, IT154153, Tvu7426, and Tvu7778, were used for cultivating sprouts at a temperature of 27°C. The yield ratio of cowpea sprouts was highest at 27°C (657%), and was reduced when growth temperature was decreased. The hard seed rate was lower when the growth temperature was increased. Vitamin C content was highest at 24°C (2.85 mg/g), ranged between 2.15 and 2.29 mg/g at other growth temperatures, and increased with the length of the growth period. The inorganic component content of cowpea sprouts did not vary based on growth temperature, while the amino acid content increased with increasing growth temperature between 15°C and 24°C, and then subsequently decreased as growth temperature rose from 24°C to 30°C. IT154153 had the highest yield ratio of cowpea sprouts per genetic resource (647%), followed by Seowon (615%), and Tvu7426 (608%). Genetic resources with a higher yield ratio had smaller seeds, a thinner seed coat, and superior germinability. The inorganic components found at highest concentrations in the cowpea sprouts were potassium, magnesium, calcium, sodium, iron, molybdenum, and zinc (in that order). In comparison to raw seeds, the protein, calcium, zinc, molybdenum, and iron content in the cowpea sprouts was higher, while the content of aluminum and boron was lower.
양파(Allium cepa L.) 유전자원의 Flavonol 배당체 조성 및 함량
이 정로,이 민기,김 헌웅,이 성현,이 영민,장 환희,황 경아,곽 재균,고 호철,김 정봉,조 진웅 한국작물학회 2014 Korean journal of crop science Vol.59 No.3
Flavonols as a major kind of plant secondary metabolites are known for health-promoting compounds in onions (Allium cepa L.). The objectives of this study are to determine profiles of flavonol glycosides in different 75 onion accessions. A total of five flavonols (quercetin 3,4'- diglucoside, Q34'diG; quercetin 3-glucoside, Q3G; quercetin 4'-glucoside, Q4'G; isorhamnetin 4'-glucoside, I4'G; quercetin, Q) were identified from onion accessions. In positive ion mode using LC-ESI-MS, individual flavonols were confirmed from one and two glycosylation binding with aglycone such as quercetin and isorhamnetin. Total flavonol contents were distributed in white onion (range of 0.18-6.47 mg/g DW) and purple onion accessions (range of 2.39-6.47 mg/g), respectively. The mean of flavonol contents in purple onion (4.41 mg/g) showed 1.4-fold higher than white onion (3.23 mg/g). The Q34'diG and Q4'G were considered as the major compounds of flavonol glycosides in onion accessions.
은영민 ( Young-min Eun ),김민성 ( Min-seong Kim ),오세엽 ( Se-yeop Oh ),신선웅 ( Seon-woong Shin ),김상훈 ( Sang-hoon Kim ) 한국정보처리학회 2012 한국정보처리학회 학술대회논문집 Vol.19 No.2
본 논문은 진공을 이용한 흡착방식과 바퀴형 이동방식을 이용하고 환경 탐지용 센서를 부착한 벽면 이동형 로봇의 구현에 관한 연구로서, 대형 구조물의 안전 검사 및 위험한 시설물의 보수 작업등을 보조하기 위한 목적이 있다. 로봇의 무게에 따른 중력을 견딜 수 있도록 강력한 진공흡착방식을 고안하여 다양한 벽면재질에도 견딜 수 있도록 설계하였으며, 바퀴형 이동방식을 택하여 높은 이동성과 제어 능력을 고려하였다. 또한 환경 감지를 위한 센서와 카메라를 부착하여 시각정보 등 유용한 정보를 관리자와 통신을 통해 교환할 수 있도록 하여 지능능력과 활용성을 갖추었다.
심층 강화학습을 이용한 모바일 로봇의 맵 기반 장애물 회피 알고리즘
선우영민(Yung-Min Sunwoo),이원창(Won-Chang Lee) 한국전기전자학회 2021 전기전자학회논문지 Vol.25 No.2
심층 강화학습은 학습자가 가공되지 않은 고차원의 입력 데이터를 기반으로 최적의 행동을 선택할 수 있게 하는 인공지능 알고리즘이며, 이를 이용하여 장애물들이 존재하는 환경에서 모바일 로봇의 최적 이동 경로를 생성하는 연구가 많이 진행되었다. 본 논문에서는 복잡한 주변 환경의 이미지로부터 모바일 로봇의 이동 경로를 생성하기 위하여 우선 순위 경험 재사용(Prioritized Experience Replay)을 사용하는 Dueling Double DQN(D3QN) 알고리즘을 선택하였다. 가상의 환경은 로봇 시뮬레이터인 Webots를 사용하여 구현하였고, 시뮬레이션을 통해 모바일 로봇이 실시간으로 장애물의 위치를 파악하고 회피하여 목표 지점에 도달하는 것을 확인하였다. Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.
경영민,류광렬,정영득,조규갑,Kyoung, Young-Min,Ryu, Kwang-Ryel,Jeong, Yeong-Deug,Cho, Kyu-Kab 한국정밀공학회 1995 한국정밀공학회지 Vol.12 No.11
This paper describes a hierarchical structure for feature definition and classification, and feature representation method based on frame structure for process planning of prismatic machined components of injection mold. The concept of Volume Removal Directions and Vertical Faces is proposed to develop a method to define and to classify features for components of injection mold systematically. A method for classifying features by the combination of volume removal directions and vertical faces is developed, and also a feature representation method by using frame structure to represent design and manufacturing information is presented.