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전승일 ( Jeon Seung Il ),조경제 ( Jo Gyeong Je ) 한국하천호수학회 2004 생태와 환경 Vol.37 No.1
Primary productivity of phytoplankton was measured by ^(14)C method from January to October of 1996 in Seonakdong River. This river was a highly productive freshwater showing the euphotic depth of 1.4m in August and 2.1m in the remaining season. Cholrophyll-a concentrations of phytoplankton ranged from 67㎍L^(-1) to 894 ㎍L^(-1) and showed the great increase in August. Maximum specific productivity was 2.1∼4.3㎎C㎎chal-a^(-1)hr^(-1) and occured above 0.4m depth. In photosynthesis-irradiance relation, phytoplankton occured clearly in the cold seasons, while phytoplankton(mainly Microcystis aeruginosa and its relatives) in August did not show any symptom of the photosynthetic inhibition aganinst the high irradiance. The specific productivity of phytoplankton was eventually dependant upon incident irradiance to show the linear correlation with received irradiance in field, and the areal productivity of phytoplankton upon chlorophyll-a standing drops. In the downstream of the Nakdong River, phytoplankton productions have linearly increased since the estuarine barrage construction to reflect the gradual eutrophication in the estuarine area. Average chlorophyll-a increase of 10㎍ chl-a L^(-1) absolutely corresponded to the primary proceduction acceleration of 30㎎Cm^(-2)day^(-1) on the annual basis.
AMOLED 디스플레이용 3-채널 DC-DC 변환기 설계
전승기(Seung-Ki Jeon),김찬유(Chan-You Kim),김학윤(Hak-Yoon Kim),최호용(Ho-Yong Choi) 대한전자공학회 2018 대한전자공학회 학술대회 Vol.2018 No.11
In this paper, we design a highly integrated 3-channel DC-DC converter. Two channel, a positive voltage VPOS and a negative voltage VNEG, are designed for two supply voltages of AMOLED display. For positive voltage, VPOS, a boost converter followed by a LDO (Low Dropout) is designed using PSM/PWM dual mode to minimize power dissipation and decrease output voltage ripple. For a negative voltage, VNEG, a 0.5 x regulated inverting charge pump is designed to decrease size and power dissipation. For an additional positive voltage, V A VDD , a LDO is designed using an error amplifier to drive another fixed positive voltage. The proposed circuit has been designed using a 0.18㎛ BCDMOS process. Simulation results show that our integrated power supply has power efficiency of 57% ~ 89% for load current range of 1 mA ~ 70 mA and output voltage ripple less than 20 mV.
전승병 ( Seung Byung Jeon ),김진수 ( Jin Su Kim ),김광원 ( Kwang Won Kim ),손광석 ( Kwang Suk Son ),김동규 ( Dong Gyu Kim ) 대한금속재료학회(구 대한금속학회) 2014 대한금속·재료학회지 Vol.52 No.1
This work assesses the hot ductility behavior of high manganese steel under hot working conditions. Reduction of area (RA) behavior of 16 Mn-0.5 C steel was investigated to consider it for production in a slab and subsequent hot rolling process. All specimens were machined from the as-cast slab. A hot ductility test was accomplished by a cast simulator through a temperature range of 650 ℃-1200 ℃ with 50 ℃ intervals. The obtained RA values ranged between 30% and 60%, with a maximum at 850℃, and this is far from the general RA behavior of low carbon steel. This result could be attributed to the fact that the specimen is fully austenitic through all test temperatures, and that there is no ferrite at the low temperature end and reduced dynamic recrystallization at the high temperature end. Microstructural evaluation of the fractured specimen revealed that the deformation was concentrated at the grain boundary, and there was little matrix deformation. These results suggest that the grain boundary sliding is the basic cause of the fracture and low values of hot ductility in high manganese steel.
전승배(Jeon, Seung Bae),오행열(Oh, Haeng Yeol),정명훈(Jeong, Myeong Hun) 대한공간정보학회 2020 대한공간정보학회지 Vol.28 No.4
수질평가지수(water quality index, WQI)는 식수와 해수의 질을 결정한다. 현재 대한민국은 WQI값을 기준으로 연안 및 해수 품질을 5등급으로 분류하여 모니터링 및 관리하고 있다. 해양환경공단(korea marine environment management, KOEM)은 해양수질자동측정망을 활용해 연안환경의 데이터를 수집하고 있다. 하지만, 이러한 데이터에는 WQI를 계산하기 위한 변수 중 일부분을 포함하지 않고 있다. 때문에 KOEM은 매년 4회 수동으로 WQI를 평가한다. 본 연구는 해양수질자동측정망으로 측정한 데이터에 근거하여 기계 학습(machine learning, ML)을 통해 WQI를 기반으로 한 수질 등급을 추정한다. 실험 결과 랜덤 포레스트(random forest, RF)와 서포트 벡터 머신(support vector machine, SVM) 알고리즘이 다른 알고리즘들보다 성능이 우수하였다. 본 연구의 결과는 수동으로 WQI를 평가하여 수질 등급을 결정하는 방식에서 자동으로 결정할 수 있는 방법을 제공하며, 이는 실시간으로 수질 상태를 모니터링하는 데 적용될 수 있다. The water quality index(WQI) determines the quality of drinking water and seawater. Currently, the Republic of Korea classifies coastal and seawater quality into five grades based on WQI values and monitors and manages them. The Korea marine environment management(KOEM) collects data on the coastal environment using an automatic environmental sensor network. However, this data does not include some of the variables for calculating WQI. Therefore, KOEM manually evaluates WQI four times a year. This study estimates the water quality level using machine learning(ML), based on the automatic environmental sensor network’s data. The experiments demonstrated that the random forest(RF) and support vector machine(SVM) models outperform other models. The proposed method enables to automatically determine the water quality level, which can be applied to monitor the water quality level real-time.