• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.75-86
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• 2019

Recently, natural disasters due to abnormal climates are frequently outbreaking, and there is rapid increase of damage to aged agricultural infrastructure. As agricultural infrastructure facilities are in contact with water throughout the year and the number of them is significant, it is important to build a maintenance management system. Especially, the current maintenance management system of pumping and drainage stations among the agricultural facilities has the limit of lack of objectivity and management personnel. The purpose of this study is to develop a performance evaluation model using the factors related to performance degradation of pumping and drainage facilities and to predict the performance of the facilities in response to climate change. In this study, we focused on the pumping and drainage stations belonging to each climatic zone separated by the Korea geographical climatic classification system. The performance evaluation model was developed using three different statistical models of POLS, RE, and LASSO. As the result of analysis of statistical models, LASSO was selected for the performance evaluation model as it solved the multicollinearity problem between variables, and showed the smallest MSE. To predict the performance degradation due to climate change, the climate change response variables were classified into three categories: climate exposure, sensitivity, and adaptive capacity. The performance degradation prediction was performed at each facility using the developed performance evaluation model and the climate change response variables.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• Journal of Gifted/Talented Education
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• v.24 no.2
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• pp.271-288
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• 2014

This study aimed to investigate the perception of earth system thinking of science gifted students in future problem solving (FPS) in relation to climate changes. In order to this study, the research problem associated with climate changes was developed through a literature review. The thirty seven science gifted students participated in lessons. The ideas in problem solving process of science gifted students were analyzed using the semantic network analysis method. The results are as follows. In the problem solving processes, science gifted students are 'changes of the sunlight by water layer', 'changes of the Earth's temperature', 'changes of the air pressure', ' change of the wind and weather' were represented in order. On other hand, regard to earth system thinking for climate changes, while science gifted students were used sub components related to atmospheres frequently, they were used sub components related to biosphere, geosphere, and hydrosphere a little. But, the analytical results of the structural relationship between the sub components related to earth system, they were recognised that biosphere, geosphere, and hydrosphere used very important in network structures. In conclusion, science gifted students were understood well that components of the earth system are influencing each other.

• Journal of Christian Education in Korea
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• v.71
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• pp.155-179
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• 2022

This study aims to apply Hannah Arendt's concept of 'collective responsibility' to the Christian education on environmental issues around the world, focusing on climate change. This study prepares the concept of 'collective responsibility' and the concept of 'collective guilt' and emphasizes the fact that the current climate change problem should be seen as a political task rather than a task of personal ethics. According to Arendt's theory, Christian education activities applying 'collective responsibility' for climate change can become action. This study has four suggestions for Christian learning to understand and recognize climate change. First, presenting and justifying the anxiety and anger toward climate change in the classroom. Second, transcending self-interest (egocentrism) through "Common Sense (enlarged mentality)" in Kantian terms. Third, building education communities through 'citizen participatory education,' running communication, and conversation. Fourth, encouraging experience and practice in every education community with "faith expressing itself through love (Gal 5:6)." Then, to be sure, this refers to not only love of neighbor in Christianity but also political friendship (philia politikē). The academic significance of this study is that it is the first interdisciplinary research paper in Korea which dealt with Arendt's political theory in relation to Christian education. Although it claims to be a theoretical work that applies Arendt's political theory from a systematic theological perspective to Christian education, the author is proud that it is accompanied by practical elements that can be actualized in the education field.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.55-64
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• 2021

The expansion of upland crop cultivation in rice paddy fields is recommended by the Korean government to solve the problem of falling rice price and reduction of rice farmer's income due to oversupply of rice. However, water use efficiency is significantly influenced by the land use change from paddy field to upland. Therefore, this study aimed to evaluate the water budget of soybean grown in using APEX (Agricultural Policy and Environmental eXtender) model. The amount of runoff was measured in a test bed located in Iksan, Jeollabu-do and used to calibrate and validate the simulated runoff by APEX model. From 2019 to 2020, the water budget of soybean grown in uplands were estimated and compared with the one grown in paddy fields. The calibration result of AP EX model for runoff showed that R² (Coefficient of determination) and NSE (Nash-Sutcliffe efficiency) were 0.90 and 0.89, respectively. In addition, the validated results of R² and NSE were 0.81 and 0.62, respectively. The comparative study of each component in water budget showed that the amounts of evapotranspiration and percolation estimated by APEX model were 549.1 mm and 375.8mm, respectively. The direct runoff amount from upland was 390.1 mm, which was less than that from paddy fields. The average amount of irrigation water was 28.7 mm, which was very small compared to the one from paddy fields.

• Korean Journal of Organic Agriculture
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• v.29 no.4
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• pp.485-505
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• 2021

This study investigated consumers' perceptions and willingness to pay (WTP) for fruit and vegetables grown using renewable energy such as solar power, geothermal, waste heat from incinerators, hot water from thermal power plants. To this end, this study conducted an online survey of 1,050 consumers in Seoul, Gyeonggi, and the six metropolitan cities, and the main findings are as follows. First, most of the consumers perceived climate change as a serious problem, and 82.8% recognized the government's declaration of carbon zero was appropriate, which means that the government's active response to climate change is important. Second, on the pros and cons of the use of renewable energy when cultivating fruits and vegetables, opinions in favor of solar power were the highest, followed by geothermal heat, waste heat from waste incineration plants, and thermal power generation hot drainage. Third, at least 28.0% to 41.7% of consumers were willing to purchase fruits and vegetables using renewable energy more expensive than fruits grown using fossil energy such as kerosene. This means that the fruit and vegetable market using renewable energy is valuable as a niche market.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.511-517
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• 2022

Recently, due to rapid climate change, the population of honey bees has decreased, posing a great threat to the existence of the Earth's ecosystem. In particular, the colony collapse phenomenon in which bees disappeared nationwide in early 2022 had devastating consequences for beekeepers. In order to solve the problems of beekeeping due to climate change, it is urgent to develop a system that can monitor the situation inside the hive through various IoT sensors. This paper develops a system that can measure the activity of bees inside the hive and uses it to measure the number of times of entry and exit of the hive. The data measured by the developed system can be monitored in real time on a smartphone through the cloud server. The system developed in this paper can monitor the ecology of bees according to climate change and measure internal and external bee activities. Using this method, it is possible to check in advance for the colony collapse phenomenon in which bees disappeared in early 2022. This is very meaningful in that it presents an alternative that can identify the cause of the problem through early detection.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.27-32
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• 2003

Atmospheric and oceanic numerical models are usually initial-value and/or boundary-value problems. Change in either initial or boundary conditions leads to a variation of model solutions. Much of the predictability research has been done on the response of model behavior to an initial value perturbation. Less effort has been made on the response of model behavior to a boundary value perturbation. In this study, we use the latest version of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM3) to study the model uncertainty to tiny SST errors. The results show the urgency to investigate the second kind predictability problem for the climate models.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.157-157
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• 2018

A reliable and accurate downscaling model which can provide climate change information, obtained from global climate models (GCMs), at finer resolution has been always of great interest to researchers. In order to achieve this model, linear methods widely have been studied in the past decades. However, nonlinear methods also can be potentially beneficial to solve downscaling problem. Therefore, this study explored the applicability of some nonlinear machine learning techniques such as neural network (NN), extreme learning machine (ELM), and ELM autoencoder (ELM-AE) as well as a linear method, least absolute shrinkage and selection operator (LASSO), to build a reliable temperature downscaling model. ELM is an efficient learning algorithm for generalized single layer feed-forward neural networks (SLFNs). Its excellent training speed and good generalization capability make ELM an efficient solution for SLFNs compared to traditional time-consuming learning methods like back propagation (BP). However, due to its shallow architecture, ELM may not capture all of nonlinear relationships between input features. To address this issue, ELM-AE was tested in the current study for temperature downscaling.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.265-273
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• 2017

Recently the Paris Climate Change Accord has been officially put into effect, making global efforts to implement Greenhouse Gas (GHG) reductions, and also International environmental regulations in the automotive sector will be further strengthened. The electric vehicle, which minimizes the particulate matter generated by existing internal combustion engine automobiles, is evaluated as a representative eco-friendly automobile. However, charging the battery of an electric vehicle is not fully environment-friendly if it is fueled by electricity that is being generated by fossil fuels as an energy source. The energy generated by the photovoltaic power generation system, which is an infinite clean energy, can be used to charge an electric vehicle's battery. Currently, shortage of charging facilities, time of charging, and high battery prices are the problem of activating the supply of electric vehicles. This study is to build a conjunction between the EVBSS (Electric Vehicle Battery Supply System) and ESS (Energy Storage System), which can quickly supply the photovoltaic charged battery to the required demand. If the charged battery in the Battery Swapping Station (BSS) is swapped swiftly, it will dramatically shorten the waiting time for charging the battery. As a result, if the battery is rented when it is needed, electric vehicles can be sold without the cost of a battery, which accounts for a large portion of the total cost, then the supply of electric vehicles are expected to expand. Furthermore, it will be an important alternative to maneuver climate change by minimizing GHG emissions from internal combustion engine vehicles.