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미니수박의 재배유형과 재식거리에 따른 생육 및 과실특성
정택구(Taek-Gu Jeong),노솔지(Sol-Ji Noh),한종우(Jong-Woo Han),김영상(Young-Sang Kim),김익제(Ik-Jei Kim),김태일(Tae-Il Kim),홍성택(Sung-Taek Hong) (사)한국생물환경조절학회 2018 생물환경조절학회지 Vol.27 No.2
최근 1인 가족 증가 및 핵가족화로 인해 미니수박에 대한 소비가 증가되고 있다. 따라서 미니수박에 대한 표준재배법을 확립하기 위하여, 재배유형에 따른 재식거리가 미니수박의 생육, 수량성, 과실특성과 라이코펜 및 당함량 등에 미치는 영향을 조사하였다. 정식 30일 및 90일후 생육은 재배유형별로 재식거리가 클수록 생육이 양호하였으며, 수확기의 후기생육은 포복형 재배보다는 아치형이나 ∩자형에서 가장 양호하였다. 주당 착과수는 재배유형별로 유의한 차이는 없었으나, 단위면적당 수량은 밀식재배가 가능한 ∩자형이 아치형과 포복형에 비해 50% 이상 높았으며, 당도가 다소 증가하였다. ‘Minimi’의 과실당 종자수는 대과종인 ‘삼복꿀’과 비슷하였으나, 종자 100립중은 ‘삼복꿀’의 1/3크기로 작았다. 라이코펜 함량은 ‘삼복꿀’보다 ‘Minimi’에서 30% 이상 높았고, 당성분은 유의한 차이가 없었다. 따라서 미니수박의 재배방식은 ∩자형 지주재배가 포복재배나 아치형에 비해 단위면적당 수량과 품질이 높았으며, 재식거리는 120×40cm에서 수광량, 생육, 수량 및 품질 등에서 가장 양호하였다. Recently, the interest and consumption of mini watermelon (Citrullus lunatus Thunb.) are increasing due to nuclear family and one person household. However, there’s no research for mini watermelon. Therefore, the purpose of the study is to develop standard cultivation method of mini watermelon. The test cultivar is ‘Minimi’, which is a small-sized fruit, the rootstock is ‘Bullojangsaeng’, which is a cucurbit line. Grafted plants were transplanted on April 5, 2017, and harvested in early July. Cultivated types were 3 methods, which are ∩-form, arched, and runner type, and plant spacing were 40, 60, and 80 cm, respectively. The rowth and yield in ∩-form was higher than that of the arched and runner types, and the sugar content was higher a bit. The yield per unit area was about 50% higher than ∩-form, which can be plant density cultivation than that of the runner type. The number of seeds per fruit of ‘Minimi’ was similar to that of ‘Sambokggul’, but seed weight was one third lower than that of ‘Sambokggul’. The content of lycopene was 30% higher than that of ‘Sambokggul’ watermelon, and the main sugar content is similar to or slightly less. In conclusion, the ∩-form staking cultivation was superior to the runner type or arched cultivation in terms of fruit setting ratio, yield and quality.
배출허용기준 및 주행모드에 따른 중형화물차의 대기오염물질 배출특성
정택호 ( Taek Ho Chung ),김선문 ( Sun Moon Kim ),이종철 ( Jong Chul Lee ),임윤성 ( Yun Sung Lim ),김인구 ( In Gu Kim ),이종태 ( Jong Tae Lee ),김형준 ( Hyung Jun Kim ) 한국액체미립화학회 2020 한국액체미립화학회지 Vol.25 No.1
NOx, PN and CO emissions from diesel trucks make up a significant portion of domestic air pollutant emissions. Therefore, test vehicles with various emission standards and driving modes were selected to evaluate the emission characteristics of regulated pollutants (NOx, PN, CO) in medium-duty trucks. As a result of test, all test vehicles were satisfied with Euro 5 or 6 regulation. NOx emissions of Euro 6 vehicles with after-treatment of LNT + DPF were lower than those of Euro 5 vehicles with DPF. In WLTC mode, all vehicles have high NOx emissions at section of extra high speeds, which are determined by increased fuel consumption and high combustion temperatures. CO and PN emissions from all vehicles were found to be low at section of low speeds. Also, The NO<sub>2</sub>/NOx ratio was analyzed at 7-23% in each mode, and the NO<sub>2</sub>/NOx ratio increased as the average vehicle speed increased. In NIER 9 mode, the CO, HC, and PN emissions were higher under cold conditions of engine than hot conditions of engine. In addition, vehicles with after-treatment system of LNT have similar NOx emissions level in this study.
딥러닝 방식의 웨어러블 센서를 사용한 미국식 수화 인식 시스템
정택위(Teak-Wei Chong),김범준(Beom-Joon Kim) 한국전자통신학회 2020 한국전자통신학회 논문지 Vol.15 No.2
수화는 청각 장애인이 다른 사람들과 의사소통할 수 있도록 설계된 것이다. 그러나 수화는 충분히 대중화되어 있지 않기 때문에 청각 장애인이 수화를 통해서 일반 사람들과 원활하게 의사소통하는 것은 쉽지 않은 문제이다. 이러한 문제점에 착안하여 본 논문에서는 웨어러블 컴퓨팅 및 딥러닝 기반 미국식 수화인식 시스템을 설계하고 구현하였다. 이를 위해서 본 연구에서는 손등과 손가락에 장착되는 총 6개의 IMUs(Inertial Measurement Unit) 센서로 구성된 시스템을 구현하고 이를 이용한 실험을 수행하여 156개 특징이 수집된 데이터 추출을 통해서 총 28개 단어에 대한 미국식 수화 인식 방법을 제안하였다. 특히 LSTM (Long Short-Term Memory) 알고리즘을 사용하여 최대 99.89%의 정확도를 달성할 수 있었고 향후 청각 장애인들의 의사소통에 큰 도움이 될 것으로 예상된다. Sign language was designed for the deaf and dumb people to allow them to communicate with others and connect to the society. However, sign language is uncommon to the rest of the society. The unresolved communication barrier had eventually isolated deaf and dumb people from the society. Hence, this study focused on design and implementation of a wearable sign language interpreter. 6 inertial measurement unit (IMU) were placed on back of hand palm and each fingertips to capture hand and finger movements and orientations. Total of 28 proposed word-based American Sign Language were collected during the experiment, while 156 features were extracted from the collected data for classification. With the used of the long short-term memory (LSTM) algorithm, this system achieved up to 99.89% of accuracy. The high accuracy system performance indicated that this proposed system has a great potential to serve the deaf and dumb communities and resolve the communication gap.