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웹 카메라를 이용한 시설 내 국화생산 광 환경 원격 모니터링
정선옥(Sun-Ok Chung),김용주(Yong-Joo Kim),이규호(Kyu-Ho Lee),성남석(Nam-Seok Sung),이철휘(Cheol-Hwi Lee),노현권(Hyun-Kwon Noh) 충남대학교 농업과학연구소 2015 농업과학연구 Vol.42 No.4
Increase of national family income improved demand of high-quality and year-round horticultural products including chrysanthemum. To meet these demand, farmers have introduced protected facilities, such as greenhouses, of which environmental conditions could be monitored and controlled. Environment management up to three weeks after transplanting is critical for chrysanthemum quality. Artificial lighting and light-blocking screen are especially important for long-day (day period > 13 hours) and short-day (night period > 13 hours) treatments. In this study, a web-camera was installed, and the image was obtained and transmitted to mobile phones to monitor the status of 3-wavelength(RGB) lighting environments. RGB pixel values were used to determine malfunctioning of the lighting lamps, and leaking out and incoming illumination status during short-day and long-day treatment periods. Normal lighting lamps provided RGB pixel values of 240~255. During long-day treatment period, G pixel values were useful to detect abnormal lighting conditions (e.g., leaking). During short-day treatment period, R pixel values were useful to determine incoming light (e.g., sun-light). Results of this study would provide useful information for remote monitoring of light conditions for protected chrysanthemum production under artificial lights.
Modeling of CO<sub>2</sub> Emission from Soil in Greenhouse
Lee, Dong-Hoon,Lee, Kyou-Seung,Choi, Chang-Hyun,Cho, Yong-Jin,Choi, Jong-Myoung,Chung, Sun-Ok Korean Society of Horticultural Science 2012 원예과학기술지 Vol.30 No.3
Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.
Modeling of CO₂ Emission from Soil in Greenhouse
Dong Hoon Lee,Kyou Seung Lee,Chang Hyun Choi,Yong Jin Cho,Jong-Myoung Choi,Sun-Ok Chung 한국원예학회 2012 원예과학기술지 Vol.30 No.3
Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, CO₂ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of CO₂ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse CO₂ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of CO₂ level. In this study, a mathematical model was developed to estimate the CO₂ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between CO₂ concentrations at the soil surface and 5-㎝ depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of CO₂ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict CO₂ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for CO₂ enrichment in a soil-based greenhouse.
Causes of a Low Measles Seroprevalence among Young Healthcare Workers in Korea
Chung Hyemin,Cho Sung-Kwan,Joo Jiyeon,Kim Sun-Kyung,Kim Eun Ok,Kim Min Jae,Chong Yong Pil,Choi Sang-Ho,Lee Sang-Oh,Kim Yang Soo,Jung Jiwon,Kim Sung-Han 대한감염학회 2023 Infection and Chemotherapy Vol.55 No.3
Background: Sporadic measles outbreaks have continued to occur in Korea, mainly in adults in their 20s and 30s, most notably in 2014 and 2019. We here evaluated the possible causes of a low seroprevalance of measles by testing young healthcare workers (HCWs). Materials and Methods: This study was conducted in a 2,743-bed tertiary-care hospital in Seoul between 2020 and 2021. We performed a measles antibody test (chemiluminescence immunoassay), measured the IgM/IgG index ratio, and conducted an avidity test at 1-month after Measles-Mumps-Rubella (MMR) vaccination in HCWs who had been seronegative for measles. Measles vaccination histories were obtained from the national vaccine registry. Results: Of the 3,173 HCWs newly employed in our hospital during the study period, 54 with a negative measles IgG at commencement were enrolled. Thirty six (67%) of these subjects were female, and the median age was 25 years (interquartile range [IQR]: 24 - 27). Fourty nine (91%) showed seroconversion at 1 month after the first vaccination. Of these individuals, 38 received both measles IgM and IgG test, and all had an IgM/IgG index <1. Of the 49 seroconverters, all HCWs showed a high avidity index. According to the national immunization registry, 45 (83%) received at least 2 doses of an MMR vaccination. Conclusion: Secondary vaccine failure may underlie vaccine failure in young Korean adults. HCWs born after 1985 with a negative measles antibody may need only a single dose booster vaccination rather than a 2-dose vaccination regimen.
Sensing Technologies for Grain Crop Yield Monitoring Systems: A Review
( Sun-ok Chung ),( Moon-chan Choi ),( Kyu-ho Lee ),( Yong-joo Kim ),( Soon-jung Hong ),( Minzan Li ) 한국농업기계학회 2016 바이오시스템공학 Vol.41 No.4
Purpose: Yield monitoring systems are an essential component of precision agriculture. They indicate the spatial variability of crop yield in fields, and have become an important factor in modern harvesters. The objective of this paper was to review research trends related to yield monitoring sensors for grain crops. Methods: The literature was reviewed for research on the major sensing components of grain yield monitoring systems. These major components included grain flow sensors, moisture content sensors, and cutting width sensors. Sensors were classified by sensing principle and type, and their performance was also reviewed. Results: The main targeted harvesting grain crops were rice, wheat, corn, barley, and grain sorghum. Grain flow sensors were classified into mass flow and volume flow methods. Mass flow sensors were mounted primarily at the clean grain elevator head or under the grain tank, and volume flow sensors were mounted at the head or in the middle of the elevator. Mass flow methods used weighing, force impact, and radiometric approaches, some of which resulted in measurement error levels lower than 5% (R<sup>2</sup> = 0.99). Volume flow methods included paddle wheel type and optical type, and in the best cases produced error levels lower than 3%. Grain moisture content sensing was in many cases achieved using capacitive modules. In some cases, errors were lower than 1%. Cutting width was measured by ultrasonic distance sensors mounted at both sides of the header dividers, and the errors were in some cases lower than 5%. Conclusions: The design and fabrication of an integrated yield monitoring system for a target crop would be affected by the selection of a sensing approach, as well as the layout and mounting of the sensors. For accurate estimation of yield, signal processing and correction measures should be also implemented.