• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.2
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• pp.327-333
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• 2019

For sustainable lunar exploration, the most required resources should be procured on site because it takes tremendous cost to transfer the resources from the Earth to the Moon. The technologies required for use of lunar resources refers to In-Situ Resource Utilization (ISRU). As the ISRU technology cannot be verified in the Earth, a lunar surface environment simulator is necessary to be prepared in advance. The Moon has no atmosphere, and the average temperature of the lunar surface reaches to $107^{\circ}C$ during the daytime and $-153^{\circ}C$ at night. The lunar surface is also covered with very fine soils with sharp particles that are electrostatically charged by solar radiation and solar wind. In this research, generation of vacuum environment with lunar soil mass in a chamber and simulation of electrostatically charged soils are taken into consideration. It was successful to make a vacuum environment of a chamber including lunar soils without soil disturbance by controlling evacuation rate of a vacuum chamber. And an experiment procedure for simulating the charged lunar soil was suggested by theoretical consideration in charging phenomena on lunar dust.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.590-596
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• 2020

In the island areas where system connection with the commercial power grid is difficult, it is quite important to find a method to efficiently manage energy produced with independent microgrids. In this paper, a prosumer management system for P2P power transaction was realized through the testing the power meter and the response rate of the collected data for the power produced in the small-scale microgrids in which hybrid models of solar power and wind power were implemented. The power network of the microgrid prosumer was composed of mesh structure and the P2P power transaction was tested through the power meter and DC power transmitter in the off-grid sites which were independently constructed in three places. The measurement values of the power meter showed significant results of voltage (average): 380V + 0.9V, current (average): + 0.01A, power: 1000W (-1W) with an error range within ±1%. Stabilization of the server was also confirmed with the response rate of 0.32 sec. for the main screen, 2.61 sec. for the cumulative power generation, and 0.11 sec for the power transaction through the transmission of 50 data in real time. Therefore, the proposed system was validated as a P2P power transaction system that can be used as an independent network without transmitted by Korea Electric Power Corporation (KEPCO).

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.561-568
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• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.543-552
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• 2022

When frost occurs, crops are directly damaged. When crops come into contact with low temperatures, tissues freeze, which hardens and destroys the cell membranes or chloroplasts, or dry cells to death. In July 2020, a sudden sub-zero weather and frost hit the Minas Gerais state of Brazil, the world's largest coffee producer, damaging about 30% of local coffee trees. As a result, coffee prices have risen significantly due to the damage, and farmers with severe damage can produce coffee only after three years for crops to recover, which is expected to cause long-term damage. In this paper, we tried to predict frost using frost generation data and weather observation data provided by the Korea Meteorological Administration to prevent severe frost. A model was constructed by reflecting weather factors such as wind speed, temperature, humidity, precipitation, and cloudiness. Using XGB(eXtreme Gradient Boosting), SVM(Support Vector Machine), Random Forest, and MLP(Multi Layer perceptron) models, various hyper parameters were applied as training data to select the best model for each model. Finally, the results were evaluated as accuracy(acc) and CSI(Critical Success Index) in test data. XGB was the best model compared to other models with 90.4% ac and 64.4% CSI, followed by SVM with 89.7% ac and 61.2% CSI. Random Forest and MLP showed similar performance with about 89% ac and about 60% CSI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.381-395
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• 2023

This paper presents a GIS-based site suitability analysis for a smart hydrogen energy plant in the Gangwon-Do region, South Korea. A GIS-based multi-criteria decision analysis (MCDA) was implemented in this study to identify the most suitable sites for the development of smart hydrogen energy plants. The study utilizes various spatial data layers, including hydrogen generation potential and climatic conditions, environmental and topographic conditions, and natural catastrophic conditions, to evaluate the suitability of potential sites for the hydrogen energy plant. The spatial data layers were then used to rank and prioritize the sites based on suitability. The findings revealed that 4.26% of the study area, or 712.14 km², was suitable for constructing smart hydrogen energy plants. Some regions of Cheorwon-gun, Chuncheon-si, Wonju-si, Yanggu-gun, Gangneung-si, Hoengseong-gun, and near the coastal region along the east coast were found to be suitable for solar and wind energy utilization. The proposed MCDA provides a valuable tool for decision-makers and stakeholders to make informed decisions on the location of smart hydrogen energy plants and supports the transition to a sustainable and low-carbon energy system. Decision-makers can use the results of this study to select suitable sites for constructing smart hydrogen energy plants.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.45-52
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• 2020

This study analyzed the components contained in the pine needles of first and second-year-olds to analyze the factors that the in vivo content of inorganic elements affects the sex determination of pine trees. In response, the plan for pine tree plant and maintenance was intended to be presented in consideration of the reproductive environment and physiological characteristics. The results are as follows. First, last year, when there were many encyclopedias, the analyzed N(%) content was found to be high. The nitrogen content of the previous year's soil was found to affect the production of the spheres the following year. This is believed to be possible to reduce the rate of Pine pollen produced in the new plant in the following year through a dispute over quality consumption in the spring of the previous year. Second, the weapons elements involved in the Pine cones and the generation of the Pine pollen in the new plant appeared to be P(%), K(%), Ca(%), and Fe(%). However, the nutrients from the previous year's leaves of Ca(%) and Fe(%) were found to have a low influence on the sex determination of first-year pine trees. Because Ca(%) and Fe(%) are not able to move nutrients accumulated in aging organs due to the nature of the components, feeding nutrients in the fall when the growth of the previous year's branches is reduced is expected to affect oral generation. Third, pine trees are extremely positive and Pine pollen is related to the time of the northeast wind. Therefore, it is believed that it would be good to be located in the northern direction, where the sunlight is good, in an outdoor space. In addition, it is important to use vaginal consumer products in spring and carry out a quarrel involving Mg and Fe during fall to reduce the effect of the Pine pollen, which is an outdoor plant. This is an important part of maintaining and managing pine trees in outdoor spaces as well as the sex determination of pine trees. This study suggested that plant planning, which derives the correlation between pine inorganic element content on sexual determination and takes into account the physiological characteristics of pine trees, is an important issue in the creation of outdoor space. Follow-up research on other factors affecting pine tree sex determination is expected.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.356-365
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• 2022

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. The agrivoltaic systems are expected to reduce the incident solar radiation, the consequent surface cooling effect, and evapotranspiration, and bring additional income to farms through solar power generation by combining crops with solar photovoltaics. In this study, to evaluate if agrivoltaic systems are suitable for viticulture, we investigated the microclimatic change, the growth of vines and the characteristics of grape grown under solar panels set by planting lines compared with ones in open vineyards. There was high reduction of wind speed during over-wintering season, and low soil temperature under solar panel compared to those in the open field. There was not significant difference in total carbohydrates and bud burst in bearing mother branches between plots. Despite high content of chlorophyll in vines grown under panels, there is no significant difference in shoot growth of vines, berry weight, cluster weight, total soluble solid content and acidity of berries, and anthocyanin content of berry skins in harvested grapes in vineyards under panels and open vineyards. It was observed that harvesting season was delayed by 7-10 days due to late skin coloration in grapes grown in vineyards under panels compared to ones grown in open vineyards. The results from this study would be used as data required in development of viticulture system under panel in the future and further study for evaluating the influence of agrivoltaic system on production of crops including grapes.