• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

• Journal of Radiation Industry
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• v.17 no.3
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• pp.265-273
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• 2023

To effectively and safely manage the radiation exposure to nuclear power plant (NPP) workers in accidents, major overseas NPP operators such as the United States, Germany, and France have developed and applied realistic 3D model radiation dose assessment software for workers. Continuous research and development have recently been conducted, such as performing NPP accident management using 3D-VR based on As Low As Reasonably Achievable (ALARA) planning tool. In line with this global trend, it is also required to secure technology to manage radiation exposure of workers in Korea efficiently. Therefore, in this paper, it is described the application method and assessment results of radiation exposure scenarios for workers in response to accidents assessment technology, which is one of the fundamental technologies for constructing a realistic platform to be utilized for radiation exposure prediction, diagnosis, management, and training simulations following accidents. First, the post-accident sampling after the Loss of Coolant Accident(LOCA) was selected as the accident and response scenario, and the assessment area related to this work was established. Subsequently, the structures within the assessment area were modeled using MCNP, and the radiation source of the equipment was inputted. Based on this, the radiation dose distribution in the assessment area was assessed. Afterward, considering the three principles of external radiation protection (time, distance, and shielding) detailed work scenarios were developed by varying the number of workers, the presence or absence of a shield, and the location of the shield. The radiation exposure doses received by workers were compared and analyzed for each scenario, and based on the results, the optimal accident response scenario was derived. The results of this study plan to be utilized as a fundamental technology to ensure the safety of workers through simulations targeting various reactor types and accident response scenarios in the future. Furthermore, it is expected to secure the possibility of developing a data-based ALARA decision support system for predicting radiation exposure dose at NPP sites.

• Resources Recycling
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• v.29 no.3
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• pp.43-50
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• 2020

This study reviewed the examples on analyses of the potential impacts to waste management, due to the recent trends of waste trade regulation, and summarized an analysis strategy of the impacts. As a result, a desirable analysis may begin with reasonable estimation of recent waste amounts and flows, and reasonable prediction of the future trends of waste amounts. Then, it is effective to list various key factors and derive future scenarios of the impacts, as well as employ the traditional viewpoints focusing on waste material flow or environmental regulations. The applicable analyses for each scenario can be largely divided into qualitative and quantitative methods. Due to a high uncertainty in the recent international situations with entailing possible innovative economic changes, qualitative methods may be considered in advance, and then quantitative techniques may be utilized to predict gradual changes at relieved uncertainty of the situations. Based on this review so far, proper methodology and procedures for the impact analysis were suggested on recent waste trade conditions in Korea. Given existence of the recent uncertainties such as the health and economic crises, the analysis preferably focused on deriving strategic scenarios with respect to various aspects, and suggested analysis methods applicable to each scenario.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.397-407
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• 2013

Seasons in Korea have very distinguishable features. Due to continental high pressure, spring in Korea is dry and has low precipitation. Due to climate change derived from the increase of greenhouse gases, climate variability had increased and it became harder to predict. This caused the spring drought harsher than usual. Since 1990s, numbers of chronic drought from winter to spring increased in southern regions of Korea. Such drought in the spring damages the growth and development of the crops sown in the spring and decreases its quantity. For stable agricultural production in the future, it is necessary to assess vulnerability of the relationship between spring drought and agricultural production as well as to establish appropriate measures accordingly. This research used CCGIS program to perform vulnerability assessment on spring drought based on climate change scenario SRES A1B, A1FI, A1T, A2, B1, B2 and RCP 8.5 in 232 regions in Korea. As a result, Every scenario showed that vulnerability of spring drought decreased from 2000s to 2050s. Ratio of decrease was 37% under SRES scenario but, 3% under RCP 8.5 scenario. Also, for 2050 prediction, every scenario predicted the highest vulnerability in Chungcheongnam-do. However, RCP-8.5 predicted higher vulnerability in Gyeonggi-do than SRES scenario. The reason for overall decrease in vulnerability of agriculture for future spring drought is because the increase of precipitation was predicted. The assessment of vulnerability by different regions showed that choosing suitable scenario is very important factor.

• Atmosphere
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• v.23 no.2
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• pp.131-141
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• 2013

Many studies have related the recent variations of wildfire regime such as the increasing number of occurrances, their patterns and timing changes, and the severity of their extreme cases with global warming. However, there are only a few numbers of wildfire studies to assess how the future wildfire regime will change in the interactions between land and atmosphere with climate change especially over East Asia. This study was performed to estimate the future changing aspect of wildfire danger with global warming, using Haines Index (HI). Calculated from atmospheric instability and dryness, HI is the potential of an existing fire to become a dangerous wildfire. Using the Weather Research and Forecasting (WRF) model, two separated 5-year simulations of current (1995~1999) and far future (2095~2099) were performed and analyzed. Community Climate System Model 3 (CCSM3) model outputs were utilized for the model inputs for the past and future over East Asia; future prediction was driven under the IPCC A1B scenario. The results indicate changes of the wildfire danger regime, showing overall decreasing the wildfire danger in the future but intensified regional deviations between north and south. The overall changes of the wildfire regime seems to stem from atmospheric dryness which is sensitive to soil moisture variation. In some locations, the future wildfire danger overall decreases in summer but increases in winter or fall when the actual fire occurrence are generally peaked especially in South China.

• Journal of The Korean Society of Agricultural Engineers
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• v.49 no.4
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• pp.13-22
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• 2007

The uncertainty in water quality model predictions is inevitably high due to natural stochasticity, model uncertainty, and parameter uncertainty. An integrated modeling system under uncertainty was described and demonstrated for use in watershed management and receiving-water quality prediction. A watershed model (HSPF), a receiving water quality model (WASP), and a wetland model (NPS-WET) were incorporated into an integrated modeling system (modified-BASINS) and applied to the Hwaseong Reservoir watershed. Reservoir water quality was predicted using the calibrated integrated modeling system, and the deterministic integrated modeling output was useful for estimating mean water quality given future watershed conditions and assessing the spatial distribution of pollutant loads. A Monte Carlo simulation was used to investigate the effect of various uncertainties on output prediction. Without pollution control measures in the watershed, the concentrations of total nitrogen (T-N) and total phosphorous (T-P) in the Hwaseong Reservoir, considering uncertainty, would be less than about 4.8 and 0.26 mg 4.8 and 0.26 mg $L^{-1}$, respectively, with 95% confidence. The effects of two watershed management practices, a wastewater treatment plant (WWTP) and a constructed wetland (WETLAND), were evaluated. The combined scenario (WWTP + WETLAND) was the most effective at improving reservoir water quality, bringing concentrations of T-N and T-P in the Hwaseong Reservoir to less than 3.54 and 0.15 mg ${L^{-1}$, 26.7 and 42.9% improvements, respectively, with 95% confidence. Overall, the Monte Carlo simulation in the integrated modeling system was practical for estimating uncertainty and reliable in water quality prediction. The approach described here may allow decisions to be made based on probability and level of risk, and its application is recommended.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.354-361
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• 2011

Increasing interest and technological advances in smart home has led to active research on context-awareness service and prediction algorithms such as Bayesian Networks, Tree-Dimensional Structures and Genetic prediction algorithms. Context-awareness service presents that providing automatic customized service regarding individual user's pattern surely helps users improve the quality of life. However, it is difficult to implement context-awareness service because the problems are that handling coincidence with context information and exceptional cases have to consider. To overcome this problem, we proposes an Intelligent Sequential Matching Algorithm(ISMA), models context-awareness service using Timed Petri-net(TPN) which is petri-net to have time factor. The example scenario illustrates the effectiveness of the Timed Petri-net model and our proposed algorithm improves average 4~6% than traditional in the accuracy and reliability of prediction.

• Journal of the Korea Society for Simulation
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• v.19 no.3
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• pp.127-135
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• 2010

Modern marine navigation requires officers on the bridge to monitor a torrent of data on both the insides and outsides of the ship from numerous useful devices. But despite these tools, navigators can still find it difficult to make a safe decision for two reasons: one is that too much data if provided too quickly tends to cause fatigue and overwhelm the officer, and the other is that any inconsistency across data from several different types of devices can lead to confusion. Indeed, the fact remains that the many marine accidents can be attributed to human error, and hence there is a strong need for decision-support tools for marine navigation. One technique of providing decision support is through the use of simulation to evaluate or predict system dynamics over time using an accurate model. This paper, as a simulation method for risk prediction for a navigation safety information system of ship, suggests a navigation prediction simulation system using various knowledge bases and discrete event simulation methodology, and supports the validity of the system through the examples of components in a restricted navigation situation scenario.

• Journal of Korean Society of Disaster and Security
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• v.11 no.2
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• pp.37-43
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• 2018

The storm surge is caused by an typhoons and it is not easy to predict the location, strength, route of the storm. Therefore, research using a scenario for storms occurrence has been conducted. In Korea, hazard maps for various scenarios were produced using the storm surge numerical simulation. Such a method has a disadvantage in that it is difficult to predict when other scenario occurs, and it is difficult to cope with in real time because the simulation time is long. In order to compensate for this, we developed a method to predict the storm surge damage by using research database. The risk grade prediction for the storm surge was performed predominantly in the study area of the East coast. In order to estimate the equation, COMSOL developed by COMSOL AB Corporation was utilized. Using some assumptions and limitations, the form of the basic equation was derived. the constants and coefficients in the equation were estimated by the trial and error method. Compared with the results, the spatial distribution of risk grade was similar except for the upper part of the map. In the case of the upper part of the map, it was shown that the resistance coefficient, k was calculated due to absence of elevation data. The SIND model is a method for real-time disaster prediction model and it is expected that it will be able to respond quickly to disasters caused by abnormal weather.

• Spatial Information Research
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• v.18 no.3
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• pp.33-40
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• 2010

Many cities have provided growth management measure for preventing urban sprawl and disordered development by rapid urbanization. Many Korean cities also, have been pressed by development issues as well as the Seoul Metropolitan Area. This study aims to predict urban growth and develop Urban Growth Management Model with Geographic Information System and quantitative method. Especially, this study provides reasonable management method by presenting prediction scenario considered institutional-oriented and demand-oriented. This study also, provides a scientific basis using GIS and quantitative analysis, and present decision making of planning and implementation process through simulation.