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기준 일증발산량 산정을 위한 인공신경망 모델과 경험모델의 적용 및 비교
최용훈 ( Yonghun Choi ),김민영 ( Minyoung Kim ),수잔오샤네시 ( Susan O’shaughnessy ),전종길 ( Jonggil Jeon ),김영진 ( Youngjin Kim ),송원정 ( Weon Jung Song ) 한국농공학회 2018 한국농공학회논문집 Vol.60 No.6
The accurate estimation of reference crop evapotranspiration (ET<sub>o</sub>) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of ET<sub>o</sub> has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict ET<sub>o</sub> using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily ET<sub>o</sub> was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of ET<sub>o</sub> and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against ET<sub>o</sub> calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.
Characterization of a Calcitonin Gene-Related Peptide Release Assay in Rat Isolated Distal Colon
Rejbinder Kaur,Celestine T. O'Shaughnessy,Emma M. Jarvie,Wendy J. Winchester,Peter G. Mclean 대한약학회 2009 Archives of Pharmacal Research Vol.32 No.12
The release of calcitonin gene-related peptide (CGRP) plays a key role gastrointestinal tract homeostasis. We aimed to investigate mechanisms that mediate CGRP release from the rat colon in vitro. Colon segments were stimulated and the amount of CGRP released was measured using an enzyme immunoassay. Capsaicin and low pH induced significant increases in CGRP release which was shown to be mediated by TRPV1 activation as demonstrated with the TRPV1 antagonists CTPC and capsazepine. The mast cell degranulator, compound 48/80 significantly increased CGRP release an effect that was blocked in the presence of the mast cell stabilizer, ketotifen and the selective Gi inhibitor benzalkonium chloride. The addition of a mixture of inflammatory mediators containing pro-inflammatory cytokines, 5HT, bradykinin and PGE2 showed no effect at neutral pH but at low pH a significant additive effect was observed. We conclude that CGRP release in the rat distal colon occurs in response to mast cell degranulation, inflammatory mediators, low pH and capsaicin and describe a role for TRPV1 receptors in mediating the response.
Particle Filtration Efficiency Testing of Sterilization Wrap Masks
Chau, Destiny F.,O'Shaughnessy, Patrick,Schmitz, Michael L. The Korean Society for Preventive Medicine 2021 Journal of Preventive Medicine and Public Health Vol.54 No.1
Objectives: Non-traditional materials are used for mask construction to address personal protective equipment shortages during the coronavirus disease 2019 (COVID-19) pandemic. Reusable masks made from surgical sterilization wrap represent such an innovative approach with social media frequently referring to them as "N95 alternatives." This material was tested for particle filtration efficiency and breathability to clarify what role they might have in infection prevention and control. Methods: A heavyweight, double layer sterilization wrap was tested when new and after 2, 4, 6, and 10 autoclave sterilizing cycles and compared with an approved N95 respirator and a surgical mask via testing procedures using a sodium chloride aerosol for N95 efficiency testing similar to 42 CFR 84.181. Pressure testing to indicate breathability was also conducted. Results: The particle filtration efficiency for the sterilization wrap ranged between 58% to 66%, with similar performance when new and after sterilizing cycles. The N95 respirator and surgical mask performed at 95% and 68% respectively. Pressure drops for the sterilization wrap, N95 and surgical mask were 10.4 mmH2O, 5.9 mmH2O, and 5.1 mmH2O, respectively, well below the National Institute for Occupational Safety and Health limits of 35 mmH2O during initial inhalation and 25 mmH2O during initial exhalation. Conclusions: The sterilization wrap's particle filtration efficiency is much lower than a N95 respirator, but falls within the range of a surgical mask, with acceptable breathability. Performance testing of non-traditional mask materials is crucial to determine potential protection efficacy and for correcting misinterpretation propagated through popular media.
( Minyoung Kim ),( Susan O’shaughnessy ),( Paul Colaizzi ),( Yonghun Choi ),( Jonggil Jeon ),( Youngjin Kim ) 한국농업기계학회 2018 한국농업기계학회 학술발표논문집 Vol.23 No.1
Reliable, rapid and non-destructive measurement of plant water status is essential for irrigation scheduling. Using infrared thermometry to measure canopy temperature is an easier way to monitor plant water stress compared with in-situ soil water measurements and the soil water balance approach in terms of time, effort, and cost. This study aimed to apply Artificial Neural Networks (ANNs) to predict crop canopy temperature using climatic variables. Field experiment was conducted at the Conservation Production and Research Laboratory (Bushland, TX, U.S.A.) and grain corn (Zea mays L) was grown for high yield using practices common for the northern Texas Panhandle, Texas. Canopy temperatures were recorded by the infrared thermometers (SAP-IRT, Dynamax, USA) at 1.0 m above the canopy and meteorological data (air temperature, relative humidity, solar radiation, etc.) were obtained from the nearby Agro-climatological weather station. During the study period (from June to October), the canopy temperature under full irrigation condition varied from 7.6 to 36.5°C and its thermal regime was largely controlled by climatic conditions. All data used for ANN computation were scaled using the Min-Max normalization method, and 70%, 15% and 15% of data were randomly selected for model training, validation and testing, respectively. The best network was selected as 1-9-1 based on the network that was trained with the feed-forward Backpropagation using the conjugate gradients. The overall findings of this study showed that ANN with Backpropagation algorithm could well predict the time-dependent canopy temperature (R<sup>2</sup>=0.98) and air temperature was highly correlated with canopy temperature, which was then followed by relative humidity, wind speed and solar radiation.
김민영 ( Minyoung Kim ),최용훈 ( Yonghun Choi ),( Susan O’ Shaughnessy ),( Paul Colaizzi ),김영진 ( Youngjin Kim ),전종길 ( Jonggil Jeon ),이상봉 ( Sangbong Lee ) 한국농공학회 2019 한국농공학회 학술대회초록집 Vol.2019 No.-
작물 수분스트레스 지수(Crop Water Stress Index, CWSI)는 토양 내 수분 부족으로 인해 작물체내 가용할 수 있는 물의 양이 줄어듦에 따라 작물이 받는 수분스트레스의 정도를 나타내는 척도이다. 작물이 수분 스트레스를 받게 되면 기공감소에 따라 증산작용이 저하할 뿐만 기공을 닫게 되고, 이로 인해 캐노피 온도(Canopy temperature, T<sub>c</sub>)가 상승하게 된다. Jackson 등(1981)에 의해 개발된 CWSI 이론식은 외기 환경변화, 특히 일사량 및 풍속의 변화를 작물 수분스트레스 정량화에 고려하고 있기 때문에 최근 들어 작물 재배를 위한 적정 관개계획 연구에 많이 쓰이고 있다. 외기 환경변화 및 토양조건을 반영하여 가장 정확하게 작물이 받는 스트레스 척도를 가늠하는 이론식임에도 불구하고, 산정과정이 복잡하다는 단점이 제기되어 왔다. 따라서 본 연구에서는 작물 수분스트레스 지수를 물리적 측정 및 복잡한 수식과정에 따른 산정방법이 아닌 기상항목과 작물 수분스트레스 지수간의 비선형적인 상관관계를 분석하고, 이를 인공신경망 역전파 알고리즘(Backpropagation algorithm)을 활용해 예측하고자 하였다. 역전파 알고리즘 적용을 위한 입력변수로 대기 온습도, 풍속, 일사량이 사용되었으며, 출력변호로 작물 수분스트레스 지수가 사용되었다. 분석에 사용되는 모든 데이터는 Min-Max normalization 과정을 거쳐, K-fold cross validation을 통해 모든 데이터를 훈련 및 검증 과정에 사용할 수 있게 하였다. 시행착오법을 통해 훈련, 검증 및 테스트 과정을 거쳐 최종 인공신경망 네트워크 구조(4-5-1)가 선정되었으며, 예측결과 높은 정확도를 얻을 수 있었다(R<sup>2</sup>=0.81).
SEGMENTATION IN AN EMERGING MARKET: INVESTOR RESPONSE TO MEXICAN STOCKS DUALLY-TRADED IN THE U.S.
Craig A Peterson,K C O'Shaughnessy People&Global Business Association 2002 Global Business and Finance Review Vol.7 No.2
In recent years capital markets have become less segmented as political and legal barriers that impede flows of financial capital have eased. As a result, many foreign corporations have chosen to offer their equity for sale in the United States. We examine the returns, risk, volatility and liquidity effects realized by domestic investors for a sample of American depository receipt programs established by Mexican companies.