• Tribology and Lubricants
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• v.38 no.4
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• pp.128-135
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• 2022

In the product development process, the reliability of the product can be secured through durability tests. However, since the durability test method is expensive and time consuming, a method to save time and money by utilizing virtual product development (VPD) is required. However, research on the accuracy of the results of virtual product development is required. In this paper, an accelerated durability test was designed and conducted using a planetary gear decelerator. And an analysis model under the same conditions was created and simulated. To correlate the results of the experiment with the results of the analytical model, created a model that can discriminate the wear region using one of the data mining methods, the k-means algorithm method and HSV (Hue, Saturation, Value). The wear area is compared by counting the number of pixels defined as wear through a discrimination model. A similar ratio was calculated by comparing the pixel ratio of the area determined as wear in the entire area. It showed a similar ratio of about 70%, and it is necessary to improve the discrimination method.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.206-206
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• 2022

제주도는 투수성이 좋은 대수층이 발달한 화산섬으로 지하수가 가장 중요한 수자원이다. 인위적 요인과 기후변화로 인해 제주도의 지하수위가 저하하는 추세를 보이고 있음에 따라 지하수의 적정 관리를 위해 지하수위의 정확하고 장기적인 예측이 매우 중요하다. 다양한 환경적인 요인이 지하수의 함양 및 수위에 영향을 미치는 것으로 알려져 있지만, 제주도의 특징적인 기상인자가 지하수 시스템에 어떻게 영향을 미치는지를 파악하기 위한 연구는 거의 진행되지 않았다. 지하수위측에 있어서 물리적 모델을 이용한 방안은 다양한 조건에 의해 변화하는 지하수위의 정확하고 빠른 예측에 한계가 있는 것으로 알려져 있다. 이에 본 연구에서는 제주도 애월읍과 남원읍에 위치한 지하수위 관측정의 일 수위자료와 강수량, 온도, 강설량, 풍속, VPD의 다양한 기상 자료를 대상으로 인공신경망 알고리즘인 다층 퍼셉트론(MLP)와 Long Short Term Memory(LSTM)에 기반한 표준지하수지수(SGI) 예측 모델을 개발하였다. MLP와 LSTM의 표준지하수지수(SGI) 예측결과가 상당히 유사한 것으로 나타났으며 MLP과 LSTM 예측모델의 결정계수(R²)는 애월읍의 경우 각각 0.98, 남원읍의 경우 각각 0.96으로 높은 값을 보였다. 본 연구에서 개발한 지하수위 예측모델을 통해 효율적인 운영과 정밀한 지하수위 예측이 가능해질 것이며 기후변화 대응을 위한 지속가능한 지하수자원 관리 방안 마련에 도움을 줄 것이라 판단된다.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.3
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• pp.67-74
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• 2024

In the context of rapid temperature rise in mid-to-high latitude regions, cold region wetlands have become a hotspot for current wetland carbon cycle research due to their high sensitivity to climate change. Strengthening the monitoring of CO₂ fluxes in wetland ecosystems is of great practical significance for clarifying the carbon balance of wetlands and maintaining the ecological balance of wetland ecosystems in China's high latitude regions. In this study, the carbon flux (NEE, Net ecosystem exchange; GPP, Gross Primary Production; RECO, Ecosystem response) of Jingxin Wetland was monitored by eddy correlation method from August 2021 to March 2024.2022-2023 shows CO₂ sinks, absorbing 349.4 g C·m^-2·yr^-1 annually. The correlation analysis showed that Ta, VPD and PPFD were the main environmental factors affecting CO₂ flux in Jingxin wetland.

• Journal of the Korean Society of Tobacco Science
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• v.16 no.1
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• pp.3-13
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• 1994

To minimize the time ordinarily spent in mono filter cigarette design, we studied the relationship between major seven independant variables ; filament(X1) and total denier(X2), porosity of the aller plug wrap(X3), filter length(X4), Porosity of the tip paper(X5) and cigarette paper(X6) and net weight of the reference cut tobacco(X7). Ninty trial numbers were obtained as a results of using rotatable central composite design and it is analyzed by the multiple regression analysis with stepwise in SAS/pc under restricted conditions. That is, UPD (Y1) = 82.96 - 3.80X1 + 2.50X2 - 3.29X3 - 3.15X5 - 0.83X22 + 1.88X5X6 - 1.38 X5X7(R2: 0.63), EPD(Y2) : 120.91 - 5.70X1 + 3.60X2 + 4.23X4 - 0.93X6 + 4.06X7 (R2=0.84), TVR(Y3) = 49.70 - 0.78X1 + 3.60X3 + 2.00X4 + 4.20X5 - 0.93X6 + 2.64X7 - 1.07X1X2 + 1.0IX1 X3 + 1.05X2X6 + 0.45X22 - 0.64X42 + 1.29X4X6 - 0.97X4X7 - 1.28X5X6 + 1.53X5X7 + 1.39X6X7(R2=0.65), and EVR(Y4) : 3.24-0.21X3-0.20X4 -0.24X5+0.67X6+0.26X4X7 (R2=0.55), where EPD : encapsulated pressure drop, VPD : unencapsulated pressure drop, TVR ; tip ventilation rate, and En : envelope ventilation rate. All variables in the model are significant at the 0.05 level.

• Korean Journal of Medicinal Crop Science
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• v.26 no.6
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• pp.490-497
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• 2018

Background: The growth process of ginseng seedlings is very important in producing good quality ginseng. This study was carried out to investigate the effects of different microclimates on the growth characteristics of ginseng seedlings in a multi-layer bed facility. Methods and Results: Ginseng seedlings were cultivated in a three-layer bed facility. The air temperatures on the first and second floors were similar, while that on the third floor was about $1-4^{\circ}C$ higher than that on the other floors. The vapor pressure deficit (VPD) was higher inside than on the outside of the facility, and that on third floor was the highest in the multi-layer bed system. The photosynthetic rate, chlorophyll fluorescence, and growth characteristics of ginseng seedlings did not significantly differ among the three floors. The yield of ginseng seedlings was the highest at $721g/1.62m^2$ on the first floor. Conclusions: It was found that microclimate plays an important role in growing ginseng seedlings in multi-layer bed facilities, and therefore proper environmental control is important. In addition, producing ginseng seedlings using multi-layer bed facilities is a technology that is expected to provide a way to overcome climate change and stabilize ginseng production.

• Journal of Bio-Environment Control
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• v.22 no.2
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• pp.182-187
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• 2013

In closed plant production system like plant factory, changes in environmental factors should be identified for conducting efficient environmental control as well as predicting energy consumption. Since high relative humidity (RH) is essential for crop production in the plant factory, transpiration is closely related with RH and should be quantified. In this study, four varieties of lettuces (Lactuca sativa L.) were grown in a plant factory, and the leaf areas and transpiration rates of the plants according to DAT (day after transplanting) were measured. The coefficients of the simplified Penman-Monteith equation were calibrated in order to calculate the transpiration rate in the plant factory and the total amount of transpiration during cultivation period was predicted by simulation. The following model was used: $E_d=a*(1-e^{-k*LAI})*RAD_{in}+b*LAI*VPD_d$ (at daytime) and $E_n=b*LAI*VPD_n$ (at nighttime) for estimating transpiration of the lettuce in the plant factory. Leaf area and transpiration rate increased with DAT as exponential growth. Proportional relationship was obtained between leaf area and transpiration rate. Total amounts of transpiration of lettuces grown in plant factory could be obtained by the models with high $r^2$ values. The results indicated the simplified Penman-Monteith equation could be used to predict water requirements as well as heating and cooling loads required in plant factory system.

• Korean Journal of Environmental Agriculture
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• v.25 no.2
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• pp.164-169
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• 2006

This study was conducted for 10 days from 17 July to 26 July in 2005 to measure the amount of xylem sap flow under short-term variation of soil moisture regimes at -20 kPa, -50 kPa and -80 kPa in eight-year-old 'Fuji'/M.9 apple trees with different fruit loads. Fruit load was adjusted as three different treatments with standard (100%), 1/2 times (50%) and 2 times (200%) on the basis of optimum fruiting number per tree as the standard fruit load of Fuji cultivar. Trees with standard fruit load during the experimental period showed higher xylem sap flow at -50 kPa of soil moisture regimes than those of trees with 1/2 times and 2 times fruit load. Trees with 1/2 times and 2 times fruit load had similar patterns of the diurnal changes of xylem sap flow, vapor pressure deficit (VPD), and maximum evapotranspiration (ETm). However, trees with 2 times fruit load at -50 kPa and -80 kPa of soil moisture regimes produced lower amount of xylem sap flow than ETm. Trees with standard fruit load produced $1.06{\sim}3.93$ L/tree more amount of xylem sap flow than ETm at all soil moisture regimes. But xylem sap flow of tees with 2 times fruit load had 21% lower at -50 kPa and $31{\sim}36%$ lower at -20 kPa and -80 kPa of soil moisture regimes, respectively than that of trees with standard fruit load. Shoot growth and leaf area were significantly the highest in trees with standard fruit load while those of trees with 2 times fruit load recorded significantly lowest. Leaf water potential of trees with standard fruit load was lower than that of trees with 1/2 times and 2 times fruit load. It indicated that tees with standard fruit load had higher water use for transpiration than other treatments and tees with 2 times fruit load received more stress for the transpiration process under low soil moisture regimes. Consequently, 'Fuji'/M.9 apple trees, the fruit load and soil moisture should be maintained optimum to increase xylem sap flow and transpiration during higher growth period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Journal of Forest and Environmental Science
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• v.21 no.1
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• pp.92-97
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• 2005

This research was carried out to elucidate the characteristics of stomatal transpiration, water efficiency, vapor pressure deficit of leaves by the light intensity Kalopanax pictus leaves. The results obtained are summarized as follows: 1. In the upper leaves of Kalopanax pictus seedlings, the stomatal transpiration rate increased continuously with increasing light intensity, but in the middle and lower leaves. it was saturated at $100{\mu}mol\;m^{-2}S^{-1}$. At the light saturated point. the stomatal transpiration rate was in the following order: the upper ($1.29mmol\;H_2O\;m^{-2}S^{-1}$) middle ($0.56mmol\;H_2O\;m^{-2}S^{-1}$) lower leaves ($0.31mmol\;H_2O\;m^{-2}S^{-1}$). 2. In the upper leaves, water use efficiency rapidly increased to $600{\mu}mol\;m^{-2}S^{-1}$, and then decreased. In the middle and lower leaves, it increased to $400{\mu}mmol\;m^{-2}S^{-1}$, and then showed a constant values. 3. The vapor pressure deficit (VPD) in according to leaf positions was linearly decreased with increasing photosynthetic photon flux density (PPFD).

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.26-27
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• 2013

산림생태계의 에너지, 물질, 정보의 교환 과정과 그 변화를 이해하려면 먼저 생태계의 구조와 기능이 어떻게 상호작용하는지를 이해해야 한다. 생태계의 기능은 한, 두 가지의 특징에 의해서만 이루어지는 것이 아니다. 그렇기 때문에 그 기능을 파악하고 적절히 이용하거나 대응하기 위해서는 한 생태계와 주변 환경 전체를 바라볼 수 있는 시스템 사고가 필요하다. 이에 우리는 생태계의 '구조'를 파악함으로써 생태계의 '상태'를 이해하고자 한다. 본 연구에서는 Ruddell and Kumar (2009)의 접근법을 따라, 어떻게 한 생태계의 상태를 파악할 수 있는가라는 질문을 광릉활엽수림에 적용하여 답하고자 한다. 즉, 우리는 산림생태계가 열린 복잡계라고 가정하고, 생태계 내에서 다양한 프로세스들 간의 시시각각 변하는 네트워크의 구조가 각 시점의 시스템의 상태를 나타내는 지표가 될 수 있다고 가정하였다. 이 연구에서는 그 구조적 특징을 정량화하여 나타내는데 초점을 맞추었다. 각각의 프로세스를 대표하는 상태 변수들 간의 정보 흐름의 양과 방향, 시간 규모를 계산해냄으로써 네트워크 구조를 파악하고자 하였다. 온대 산악지형 활엽수림인 GDK의 2008년 순생태계교환량(NEE), 총일차생산량(GPP), 생태계호흡량(RE), 현열플럭스(H), 잠열플럭스(LE), 하향단파복사(Rg), 강수량(Precipitation), 기압(Pressure), 기온(T), 포차(VPD)의 시계열 자료를 월별로 나누어 최장 18 시간 규모의 정보 흐름을 계산하였다. 정보 흐름의 구조를 파악하기 위하여 변수들 간의 전이엔트로피(Transfer entropy)와 상호정보(Mutual Information)를 계산하는 방법을 사용하였다. 또한 시계열 자료를 이용함으로써 변수들 간에 정보가 전달되는 시간 규모의 특성을 파악할 수 있었다. 최종적으로, 계산한 정보 흐름을 시각화하여 프로세스 네트워크 구조를 나타내었다. 결과는 월별로 생태계의 정보 흐름의 종류, 방향과 시간 규모, 그에 따른 프로세스 간 상호 작용의 특징 등을 보여준다. 이를 통해 계절적 환경 변화에 따라 시스템의 네트워크 구조와 상태가 어떻게 변화하는지 이해할 수 있을 것이다. 이 연구는 추후 우리 연구실에서 생산한 8 년 자료에 적용함으로써 다양한 날씨 및 기후변화와 환경 변화에 따라 생태계의 구조와 상태가 어떻게 변화하는지 연구하는 시작점이 될 것이다. 이 접근법은 단위나 차원에 무관하게 다양한 종류의 자료에 적용할 수 있는 반면에, 일관성 있게 정의된 시스템의 상태 및 그 상태를 구성하는 주요 하부 시스템들의 네트워크 상태를 이해하는데 이용될 수 있다. 본 연구는 비평형 열역학과 복잡계의 관점에서 바라 본 시스템 사고를 적용하려 하는 여러 연구 분야에 새로운 도전을 촉발할 좋은 선행연구가 될 것이라 기대된다.