• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.286-290
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• 2011

This paper introduces the optimum macro-siting of a potential site for an offshore wind farm around Jeju Island using the RDAPS sea wind model. The statistical model was developed by analyzing the sea wind data from RDAPS model, and the meso-scale digital wind map was prepared. To develop the high resolution spatial calibration model, Artificial Neural Network(ANN) models were used to construct the wind and bathymetric maps. Accuracy and consistency of wind/bathymetric spatial calibration models were obtained using analysis of variance. The optimization problem was defined to maximize the energy density satisfying the criteria of maximum water depth and maximum distance from the coastline. The candidate site was selected through Genetic Algorithm(GA). From the results, it is possible to predict roughly a candidate site location for the installation of the offshore wind jam, and to evaluate the wind resources of the proposed site.

• Journal of Biosystems Engineering
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• v.6 no.1
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• pp.83-92
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• 1981

A simulation model of natural air drying to predict the changes of the grain moisture content and dry matter loss of rough rice was developed by the application of mass diffusion theory. A series of simulated drying tests was conducted using the 10 year weather data (1970-1979) obtained from Cheongju, Chuncheon, Daegu, Daejeon, Jeonju, Jinju and Suweon in Korea. System performance factors treated in this study were initial moisture content, airflow rate, bin diameter and grain depth. The results obtained in this study are summarized as follows: 1) The simulation model used in this study was validated with actual experimental results and was applicable to the natural air drying of rough rice. 2) Minimum airflow rates for safe drying were determined for different initial moisture contents and regional weather conditions as shown in Table 6. 3) Equations for estimating drying time and dry matter loss in terms of airflow rate and initial moisture content were derived in the form of an exponential function. 4) These results show that the natural air drying system of rough rice is feasible in Korea even for the poorest drying condition.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.190-190
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• 2016

The Water, Energy, and Food (WEF) nexus is an emerging concept for sustainable resources planning and management. The three valuable resources are inevitably interconnected, that is, it takes water to produce energy; it takes energy to extract, treat, and distribute water; and both water and energy are required to produce food. Although it is challenging to fully understand the complicated interdependency, a few studies have been devoted to interpret the concept and develop the assessment tools. The tools were mainly developed for nation-wide simulations without considering inter-basin or inter-state resources trade. This study tries to present an idea to develop and implement the WEF nexus simulation model in regional scale by advancing the existing nation-wide model with additional capability to simulate the inter-basin trade. This simulation could help local planners and engineers to determine optimal policies and infrastructure solutions to reach and ensure local demand satisfaction. The simulation model is implemented in hypothetical areas with different conditions of WEF demands and supplies. Although the inter-basin trade scenarios are simulated manually, it shows that the inter-basin resources trade could enhance the resources security for a longer time period. In future, an optimization model might be developed to provide the automatic calculation to reach optimum amount of WEF for the trade, which can be a helpful tool in decision making process.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.57-67
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• 2021

An earthquake occurred on 17 November 2017 in Pohang, South Korea with a strength of 5.4 Mw. This is the second strongest earthquake recorded by local authorities since the equipment was first installed. In order to improve understanding of earthquakes and surface deformation, many studies have been conducted according to these phenomena. In this research, we will estimate the surface deformation using the Okada model equation. The SAR images of three satellites with different wavelengths (ALOS-2, Cosmo SkyMed and Sentinel-1) were used to produce the interferogram pairs. The interferogram is used as a reference for surface deformation changes by using Okada to determine the source of surface deformation that occurs during an earthquake. The Non-linear optimization (Levemberg-Marquadrt algorithm) and Monte Carlo restart was applied to optimize the fault parameter on modeling process. Based on the modeling results of each satellite data, the fault geometry is ~6 km length, ~2 km width and ~5 km depth. The root mean square error values in the surface deformation model results for Sentinel, CSK and ALOS are 0.37 cm, 0.79 cm and 1.47 cm, respectively. Furthermore, the results of this modeling can be used as learning material in understanding about seismic activity to minimize the impacts that arise in the future.

• Atmosphere
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• v.30 no.4
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• pp.335-346
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• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• Asian Journal of Innovation and Policy
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• v.11 no.1
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• pp.110-147
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• 2022

Many megacities are exposed to natural hazards such as earthquakes, and when located in coastal regions, are also vulnerable to hurricanes and tsunamis. The physical infrastructures of transportation systems in megacities have become so complicated that very few organizations can understand their response to extreme events such as earthquakes and can effectively mitigate subsequent economic downfalls. The technological advances made in recent years to support these complex systems have not grown as fast as the rapid demand on these systems burdened by population shift toward megacities. The objective of this paper is to examine the risks imposed on and recoveries of transportation systems in megacities as the result of extreme events such as an earthquake. First, the physical damage to transportation infrastructure, loss of the transportation system performance, and the corresponding economic loss from disruptions to passenger and freight traffic is evaluated. Then, traffic flows are re-routed to reduce vehicles' delay due to earthquakes using a microscopic traffic flow simulator with an optimization model and macroscopic terminal simulator. Finally, the economic impact of the earthquake is estimated nationwide. Southern California is regarded as the region of study. The results demonstrate the effectiveness of the integrated model and provide what and how to prepare innovative resilience policies of urban infrastructure for a natural disaster occurrence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2701-2717
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• 2023

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system for power generation. This suggested approach was created using a fuzzy-based combination of the Giza Pyramids Construction (GPC) and Recalling-Enhanced Recurrent Neural Network (RERNN). GPC is a meta-heuristic algorithm that deals with solutions for many groups of problems, whereas RERNN has selective memory properties. The evaluation of the current load requirements and production profile information system is the main objective of the suggested method. The Central Electricity Authority database, the Indian National Load Dispatch Centre, regional load dispatching centers, and annual reports of India were some of the sources used to compile the data regarding profiles of electricity loads, capacity factors, power plant generation, and transmission limits. The RERNN approach makes advantage of the ability to analyze the ideal power generation from energy data, however the optimization of RERNN factor necessitates the employment of a GPC technique. The proposed method was tested using MATLAB, and the findings indicate that it is effective in terms of accuracy, feasibility, and computing efficiency. The suggested hybrid system outperformed conventional models, achieving the top result of 93% accuracy with a shorter computation time of 6814 seconds.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.108-113
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• 2012

Routing paths are mightily important for the network security in WSNs. To maintain such routing paths, sustained path re-selection and path management are needed. Region segmentation based path selection method (RSPSM) provides a path selection method that a sensor network is divided into several subregions, so that the regional path selection and path management are available. Therefore, RSPSM can reduce energy consumption when the path re-selection process is executed. However, it is hard to guarantee optimized secure routing path at all times since the information using the path re-selection process is limited in scope. In this paper, we propose partial path selection method in each subregion using preselected partial paths made by RSPSM for routing path optimization in SEF based sensor networks. In the proposed method, the base station collects the information of the all partial paths from every subregion and then, evaluates all the candidates that can be the optimized routing path for each node using a evaluation function. After the evaluation process is done, the result is sent to each super DN using the global routing path information (GPI) message. Thus, each super DN provides the optimized secure routing paths using the GPI. We show the effectiveness of the proposed method via the simulation results. We expect that our method can be useful for the improvement of RSPSM.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.36-51
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• 2012

The demand for a climatological dataset with a regular spaced grid is increasing in diverse fields such as ecological and hydrological modeling as well as regional climate impact studies. PRISM(Precipitation-Elevation Regressions on Independent Slopes Model) is a useful method to estimate high-altitude precipitation. However, it is not well discussed over the optimization of PRISM parameters and DEM(Digital Elevation Model) resolution in South Korea. This study developed the PRISM and then optimized parameters of the model and DEM resolution for producing a gridded annual average precipitation data of South Korea with 1km spatial resolution during the period 2000-2005. SCE-UA (Shuffled Complex Evolution-University of Arizona) method employed for the optimization. In addition, sensitivity analysis investigates the change in the model output with respect to the parameter and the DEM spatial resolution variations. The study result shows that maximum radius within which station search will be conducted is 67km. Minimum radius within which all stations are included is 31km. Minimum number of stations required for cell precipitation and elevation regression calculation is four. Optimizing DEM resolution is $1{\times}1km$. This study also shows that the PRISM output very sensitive to DEM spatial resolution variations. This study contributes to improving the accuracy of PRISM technique as it applies to South Korea.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.121-129
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• 2019

An Earthquake Early Warning (EEW) system is a technology that alerts people to an incoming earthquake by using P waves that are detected before the arrival of more severe seismic waves. P-wave analysis is therefore an important factor in the production of rapid seismic information as it can be used to quickly estimate the earthquake magnitude and epicenter through the amplitude and predominant period of the observed P-wave. However, when a large-magnitude teleseismic earthquake is observed in a local seismic network, the significantly attenuated P wave phases may be mischaracterized as belonging to a small-magnitude local earthquake in the initial analysis stage. Such a misanalysis may be sent to the public as a false alert, reducing the credibility of the EEW system and potentially causing economic losses for infrastructure and industrial facilities. Therefore, it is necessary to develop methods that reduce misanalysis. In this study, the possibility of seismic misclassifying teleseimic earthquakes as local events was reviewed using the Filter Bank method, which uses the attenuation characteristics of P waves to classify local and outside Korean peninsula (regional and teleseismic) events with filtered waveform depending on frequency and epicenter distance. The data used in our analysis were analyzed for maximum P_v values using 463 events with local magnitudes (2 < M_L ≦ 3), 44 (3 < M_L ≦ 4), 4 (4 < M_L ≦ 5), 3 (M_L > 5), and 89 outside Korean peninsula earthquakes recorded by the KMA seismic network. The results show that local and telesesimic earthquakes can be classified more accurately when combination of filtering bands of No. 3 (6-12 Hz) and No. 6 (0.75-1.5 Hz) is applied.