• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.93-106
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• 2015

In accordance with escalating demands for advanced technology products, the smart clothing that includes embedded ICT technology have expanded into fields of daily life. As a result of this trend, interest in smart clothing with digitally controllable heating has rapidly grown and the market for smart heated clothing has also expanded. Increasing of prospect in smart heated clothing market, the effectiveness and thermal sensation research of the location on the pad attached is insufficient. This study was conducted to find the optimal location of heated clothing via experimental research on changes in skin temperature and subjective thermal sensation when heating pads were placed on different areas of the body. For this experiment, the subjects consisted of 10 males in their 20's of standard physique. The skin temperature at 11 different areas of the body, rectal temperature, and subjective thermal sensation were taken at different stages (before testing, after a 20 minute rest period, 20 minute treatment period, and after a 40 minute recovery period) in an artificial-climate chamber at $-5^{\circ}C$. As a result, the optimal location for heating pads in smart clothing was estimated and suggested.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.2
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• pp.74-87
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• 2016

Potato phenology, growth, and yield are projected to be highly affected by global warming in the future. The objective of this study was to examine the responses of potato growth and yield to environmental elements like temperature, solar radiation, and daylength. Planting date experiments under open field condition were conducted using three cultivars differing in maturity group (Irish Cobbler and Superior as early; Atlantic as mid-late maturing) at eight different planting dates. In addition, elevated temperature experiment was conducted in four plastic houses controlled to target temperatures of ambient temperature (AT), $AT+1.5^{\circ}C$, $AT+3^{\circ}C$, and $AT+5^{\circ}C$ using cv. Superior. Tuber initiation onset was found to be hastened curve-linearly with increasing temperature, showing optimum temperature around $22-24^{\circ}C$, while delayed by longer photoperiod and lower solar radiation in Superior and Atlantic. In the planting date experiments where the average temperature is near optimal and solar radiation, rainfall, pest, and disease are not limiting factor for tuber yield, the most important determinant was growth duration, which is limited by the beginning of rainy season in summer and frost in the late fall. Yield tended to increase along with delayed tuber initiation. Within the optimum temperature range ($17^{\circ}-22^{\circ}C$), larger diurnal range of temperature increased the tuber yield. In an elevated temperature treatment of $AT+5.0^{\circ}C$, plants failed to form tubers as affected by high temperature, low irradiance, and long daylength. Tuber number at early growth stage was reduced by higher temperature, resulting in the decrease of assimilates allocated to tuber and the reduction of average tuber weight. Stem growth was enhanced by elevated temperature at the expense of tuber growth. Consequently, tuber yield decreased with elevated temperature above ambient and drop to almost nil at $AT+5.0^{\circ}C$.

• Journal of the Korean Institute of Telematics and Electronics
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• v.10 no.5
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• pp.16-20
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• 1973

The most important thing in locating disturbances in optimal rapid traffic singnal control is to collect information cocerning toraffit flow by means of a detection method. In order to set up an optimal traffic singnal period, the analysis of a delay time phenomena in the signal period must also be considered. In fact, each of the distributed traffic quantities on the road are not similar factors in view of speeds and distances of succeeding cars. The causing factors are analyzed by the method of control engineering analysis, and they are coincident with disturbance. Thus distubances cause errors. Distubances are fuctions of time, and are classified into three conditions: Natural road state and weather are the first. The second is structures and function of vehicles, and the third is inducedbydrivers. This thesis deals with the last two cases except the first one for maximum utilization of the existing road state and weather conditions. The first condition remains constant, and then there exist some relations between vehicles and drivers. In the long run, it can be shown that the scheme for minimizing whole errors in the optimal traffic signal time setting is definitely presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1767-1771
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• 2006

수자원 개발과 계획 및 최적의 관리를 위해서는 댐지점의 수자원부존량 평가가 선행되어야 하며, 이를 위해서는 장기간의 유출량(저수지 유입량) 자료계열의 획득이 필요하다. 장기유출은 저수지의 저수용량결정, 저수지관개용수의 이용, 갈수기의 이수계획수립, 하천유지용수량결정 등에 이용되며, 장기 수자원 계획을 수립하기 위해서는 장기유출량의 정확한 추정이 매우 중요한 사항이다. 특히 동절기에 보다 정확한 유출해석을 하기 위해서는 융설에 관한 사항을 고려가 필수적이다. 그러나 국내에서는 아직 융설에 관한 실험이나 수치모형에 대한 연구가 거의 없는 실정이며 모형의 매개변수 추정 및 검증을 위한 융설 자료를 측정하기에는 매우 어려운 점이 있다. 따라서 본 연구에서는 비교적 지역적 영향을 적게 받는 개념적 융설모형과 유출모형을 결합하여 안동댐 유역에 적용하였다. 융설을 고려한 경우 융설 고려전보다 3월과 4월 사이의 유출 모의 결과가 크게 개선된 것으로 나타났다. 향후 수자원 계획 수립시 겨울철의 적설과 융설을 고려한 유출분석을 적용한다면 기후변화에 따른 수자원 확보의 불확실성이 크게 줄어들 것으로 기대한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.511-511
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• 2023

기후변화로 동절기 기온 저하에 따른 수도계량기의 동파는 지속적으로 심화되고 있으며, 이는 계량기 교체 비용, 누수, 누수량 동결에 의한 2차 피해, 단수 등 사회적 문제를 야기한다. 이와같은 문제를 해결하고자 구조적 대책으로 개별 가정에서 동파 방지형 계량기를 설치할 수 있으나 이를 위한 비용발생이 상당하고, 비구조적 대책으로는 기상청의 동파 지도 알림 서비스를 활용하여 사전적으로 대응하고자 하나, 기상청자료는 대기 온도를 중심으로 제공하고 있기 때문에 해당서비스만으로는 계량기의 동파를 예측하는데 필요한 추가적인 다양한 변수를 활용하는데 한계가 있다. 최근 정부와 공공부문에서 22개 지역, 110개소 이상의 수도계량기함내 IoT 온도센서를 시범 설치하여 계량기 함내의 상태 등을 확인할 수 있는 사업을 수행했다. 전국적인 계량기 상태의 예측과 진단을 위해서는 추가적인 센서 설치가 필요할 것이나, IoT센서 설치 비용 등의 문제로 추가 설치가 더딘 실정이다. 본 연구에서는 겨울 동파 예방을 위해 실제 온도센서를 기반으로 가상센서를 구축하고, 이를 혼합한 하이브리드 방식으로 동파위험 기준에 따라 전국 동파위험 지도를 구축하였다. 가상센서 개발을 위해 독립변수로 위경도, 고도, 음·양지, 보온재 여부 및 기상정보(기온, 강수량, 풍속, 습도)를 활용하고, 종속변수로 실제 센서의 온도를 사용하여 기계학습 모델을 개발하였다. 지역 특성에 따라 정확한 모델을 구축하기 위해 위치정보 및 보온재여부 등의 변수를 활용하여 K-means 방법으로 군집화 하였으며, 각 군집별로 3가지의 기계학습 회귀모델을 적용하였다. 최적의 군집 수를 검토한 결과 4개가 적정한 것으로 판단되었다. 군집의 특성은 지역별 구분과 유사한 패턴을 보이며, 모든 군집에서 Gradient Boosting 회귀모델을 적용하는 것이 적합한 것으로 나타났다. 본 연구에서 개발한 모델을 바탕으로 조건에 따라 동파 예측 알람서비스에 실무적으로 활용할 수 있도록 양호·주의·위험·매우위험 총 4개의 기준을 설정하였다. 실제 본 연구에서 개발된 알고리즘을 국가상수도정보 시스템에 반영하여 테스트 수행중에 있으며, 향후 지속 검증을 할 예정에 있다. 이를 통해 동파 예방 및 피해 최소화, 물절약 등 직간접적 편익이 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.307-307
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• 2022

최근 기후변화와 댐 상류 토지이용 변화 등과 같은 다양한 원인에 의해 댐 유입량의 변동성이 증가하면서 댐 관리 및 운영조작 의사 결정에 어려움이 발생하고 있다. 따라서 이러한 댐 유입량의 변동 특성을 반영하여 댐 유입량을 정확하고 효율적으로 예측할 수 있는 방안이 필요한 실정이다. 머신러닝 기술이 발전하면서 Auto-ML(Automated Machine Learning)이 다양한 분야에서 활용되고 있다. Auto-ML은 데이터 전처리, 최적 알고리즘 선택, 하이퍼파라미터 튜닝, 모델 학습 및 평가 등의 모든 과정을 자동화하는 기술이다. 그러나 아직까지 수문 분야에서 댐 유입량을 예측하기 위한 모델을 개발하는데 있어서 Auto-ML을 활용한 사례는 부족하고, 특히 댐 유입량의 예측 정확성을 확보하기 위해 High-inflow and low-inflow 의 변동 특성을 고려한 하이브리드 결합 방식을 통해 Auto-ML 기반 앙상블 모델을 개발하고 평가한 연구는 없다. 본 연구에서는 Auto-ML의 패키지 중 Auto-sklearn을 통해 홍수기, 비홍수기 유입량 변동 특성을 반영한 하이브리드 앙상블 댐 유입량 예측 모델을 개발하였다. 소양강댐을 대상으로 적용한 결과, 하이브리드 Auto-sklearn 앙상블 모델의 댐 유입량 예측 성능은 R² 0.868, RMSE 66.23 m³/s, MAE 16.45 m³/s로 단일 Auto-sklearn을 통해 구축 된 앙상블 모델보다 전반적으로 우수한 것으로 나타났다. 특히 FDC (Flow Duration Curve)의 저수기, 갈수기 구간에서 두 모델의 유입량 예측 경향은 큰 차이를 보였으며, 하이브리드 Auto-sklearn 모델의 예측 값이 관측 값과 더욱 유사한 것으로 나타났다. 이는 홍수기, 비홍수기 구간에 대한 앙상블 모델이 독립적으로 구축되는 과정에서 각 모델에 대한 하이퍼파라미터가 최적화되었기 때문이라 판단된다. 향후 본 연구의 방법론은 보다 정확한 댐 유입량 예측 자료를 생성하기 위한 방안 수립뿐만 아니라 다양한 분야의 불균형한 데이터셋을 이용한 앙상블 모델을 구축하는데도 유용하게 활용될 수 있을 것으로 사료된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.69 no.3
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• pp.133-144
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• 2024

To review active climate change responses, especially adjustments to the transplanting time, seven varieties of early-maturing ecotypes grown at Sangju sub-station, located in a mid-mountainous region, were studied from 2007 to 2022. During the ripening stage (July 29 to October 17), the average temperature was 23.2℃, which was a relatively disadvantageous environment compared to the optimal ripening temperature of 20 to 22℃. The heading date of early-growing cultivars was greatly shortened by 10 days for both normal (May 20) and late (June 5) transplanting. In an analysis of the growth characteristics and yield components, the culm and panicle length, number of spikelets/panicles, and the ripening rate showed high variation without a constant tendency over the study period. However, the number of panicles/plants and the ratio of brown rice increased, regardless of the transplanting time, while the 1,000-grain weight tended to decrease. There were no significant differences in yield observed between the two transplanting times, except for some years. Therefore, based on various variables, such as growth, yield, and quality (although not assessed in this study), the shift in transplanting time for early-maturing varieties in the mid-mountainous region from the current time (May 20) to a later time (June 2) needs to be considered to cope with the future impacts of climate change.

• Journal of The Geomorphological Association of Korea
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• v.17 no.2
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• pp.87-98
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• 2010

There have been growing concerns for the sea level rise due to global warming in recent years. Sea level rise is a serious problem to densely populated coastal areas, because it may affect the coastal landforms to be damaged. Especially coastal sand deposits like coastal dunes are more sensitive than the other coastal landforms. In this paper, Ground Penetrating Radar (GPR) and Optically Stimulated Luminescence (OSL) dating method were used to identify the Holocene geomorphic changes of coastal dune field in Shinduri located at the western coast. The main results in this study that are the dunefield in the study area may have begun to form at around 6.8 ka and it has grown seaward thereafter. Then, dunefield appears to have extensively developed since 3.7 ka. This result, together with previous works on the sea level and climatic changes in the western coast of Korea suggest that the dunefield has been affected by the sea level regression since the Holocene high stand in the Holocene at around 6 ka and climatic change from warm and humid to cold and dry conditions occurred at 4.5 ka.