• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.509-522
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• 2021

In many countries, including Korea, it has been challenging to understand flood-related social dynamics due to urbanization and climate change. In this regard, socio-hydrology has been proposed to consider the interaction between hydrologic systems, land-use change, and human activities. However, there is a general lack of understanding of the interactions of socio-hydrologicsystems. This study examines the interactions between human activities and hydrologic systems from a sociological perspective using a dynamic system model. In other words, this study aims to present a conceptualization model that considers the mutual interaction of flood and community from a socio-hydrologic perspective. Depending on the construction cost of the levee for the Yangjae River, this study considered three scenarios to simulate the interaction of socio-hydrologic systems. Socio-hydrologic interactions can effectively reproduce the changes in the Yangjae River. Moreover, It is expected that the proposed model can be further used to understand possible hydrologic changes and interaction with social systems in the future as a decision-making tool in water resources management.

• Korean Journal of Plant Resources
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• v.32 no.1
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• pp.45-52
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• 2019

In the process of adapting climate change, the government needs to provide policy and technical support necessary for growing promising crops imported from abroad. Therefore, this study was conducted to survey and analyze the conditions of growth of imported foreign crops and to derive response tasks. As a result, tropical and subtropical vegetables were cultivated 18 crops in 920 farms in 321 ha area (in 2015 year). The cultivation scale decreased in the order of Curcuma aromatica, Momordica charantia, Asparagus aethiopicus, Allium hookeri and Herbs. Tropical and subtropical fruits were cultivated 9 crops in 264 farms in 106.5 ha area (in 2015 year). Special and medicinal crops introduced abroad cultivated 10 crops in 753 farms in 276.3 ha area (in 2015 year). The cultivation scale decreased in the order of Curcuma longa, Glycyrrhiza uralensis, Lepidium meyenii and Moringa oleifera. For the stable settlement of domestic growth of tropical and subtropical crops introduced abroad, there should be safety and economic feasibility in terms of the cultivation environment according to the domestic culture adaptation test. Consideration needs to be given to the use of locally grown products in Korea, the securing of distribution and sales markets, and the competitiveness of imported products.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.590-596
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• 2019

Uses of fossil fuels like coal and oil increases with industrial development, and problems like abnormal climate come up as greenhouse gas increases. Accordingly, studies are actively conducted on eco-friendly renewable energy as a replacement for the main resources, and especially, wood pellets with high thermal efficiency are in the limelight as an alternative fuel in thermal power stations and gas boilers. However, despite a constant increase in their usage, few studies are conducted on their risks like fire and spontaneous combustion. Thus, this study found the auto-ignition temperature and critical ignition temperature of wood pellets with a change in flow rate in a thermostatic bath, using a sample vessel with 20 cm in length, 20 cm in height and 14 cm in thickness to predict their ignition characteristics. Consequently, at the flow rate of 0 NL/min, as the core temperature of the sample increased to higher than the ambient temperature, they ignited at $153^{\circ}C$, when the critical ignition temperature was $152.5^{\circ}C$. At the flow rates of 0.5 NL/min and 1.0 NL/min, it was $149.5^{\circ}C$, and at the flow rate of 1.5 NL/min, it was $147.5^{\circ}C$. Consequently, at the same storage, the more the flow rate, the lower the critical ignition temperature became.

• Journal of Korean Society of Disaster and Security
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• v.14 no.3
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• pp.1-16
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• 2021

Recently, large-scale projects are required in the water resources sector considering safety and publicitythe due to uncertainty of securing water resources and changes in the ecological environment by climate change. Among these large-scale projects, the projects that fall under the preliminary feasibility study are determined by comprehensive analysis based on economic analysis, policy analysis, and balanced regional development analysis. However, most of the results of the preliminary feasibility study showed a tendency to depend heavily on economic analysis. For this reason, projects in non-metropolitan areas sometimes fail in the preliminary feasibility study. To supplement this point, the Korea Development Institute revised the standard guidelines for preliminary feasibility studies for water resources sector projects that place a high weight on policy feasibility analysis. Therefore, the objective of this study is to analyze the cases of the preliminary feasibility study conducted previously and to suggest the direction of policy analysis in the preliminary feasibility study for water resources sector projects. For this, we analyze preliminary feasibility studies conducted for 18 years from 2002 to 2019, and suggest direction of policy analysis method using the benefit items not included in the economic analysis.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.25-36
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• 2020

An increasing frequency and intensity of natural disasters have been observed due to climate change. To better prepare for these, the MOIS (ministry of the interior and safety) announced a comprehensive plan for minimizing damages associated with natural disasters, including drought and heavy snowfall. The spatial-temporal pattern of snowfall is greatly influenced by temperature and geographical features. Heavy snowfalls are often observed in Gangwon-do, surrounded by mountains, whereas less snowfall is dominant in the southern part of the country due to relatively high temperatures. Thus, snow depth data often contains zeros that can lead to difficulties in the selection of probability distribution and estimation of the parameters. A generalized mixture distribution approach to a maximum snow depth series over the southern part of Korea (i.e., Changwon, Tongyeoung, Jinju weather stations) are located is proposed to better estimate a threshold (𝛿) classifying discrete and continuous distribution parts. The model parameters, including the threshold in the mixture model, are effectively estimated within a Bayesian modeling framework, and the uncertainty associated with the parameters is also provided. Comparing to the Daegwallyeong weather station, It was found that the proposed model is more effective for the regions in which less snow depth is observed.

• The Journal of Bigdata
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• v.5 no.2
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• pp.53-67
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• 2020

This study employees a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. The dependent variable was set as the number of supervised inspection detections over the past five years from 2014 to 2018, and the objective function was to maximize the probability of detecting the nonconforming companies. The data was preprocessed by reflecting not only basic attributes such as revenues, operating duration, number of employees, but also the inspections track records and extraneous climate data. After applying the feature variable extraction method, the machine learning algorithm was applied to the data by deriving the company's risk, item risk, environmental risk, and past violation history as feature variables that affect the determination of nonconformity. The f1-score of the decision tree, one of ensemble models, was much higher than those of other models. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.55-63
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• 2021

Interest in smart parks has been increasing due to the recent rapid rise of smart cities, but concerns are growing over the development of technology-oriented smart parks. The purpose of this study is to evaluate the relative importance of park services through Focus Group Interviews and the Analytic Hierarchy Process (AHP) to develop user-oriented smart parks in the future. To this end, literature on park functions and services was reviewed, and interviews with experts in the field of landscape architecture and IT were conducted to derive service items. The AHP model consisted of four values, and 15 park services were established and used to survey 38 landscape experts. As a result, services for improving the park's essential functions, such as contact with nature, relaxation, and exercise-walking, were deemed important. Services related to the environment and safety in response to climate change, such as the amelioration of pollution and heatwaves were also high. The importance of social integration services was relatively low, but it was considered an important service to when enhancing community participation. Future smart parks should enhance the health benefits of contact with nature rather than implementing excessive artificial facilities and technology. Additionally, smart technology will need to be applied based on users' needs while reflecting local characteristics. Efforts should be made to enhance user intimacy and improve the understanding of smart parks by strengthening public relations education.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.35-40
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• 2022

In the agricultural environment, pesticide control requires a high risk of work and a high labor force for farmers. The effectiveness of pesticide control using unmanned aerial vehicles varies according to climate, land type, and characteristics of unmanned aerial vehicles. Therefore, an effective method for pesticide control by unmanned aerial vehicles considering the spraying conditions and environmental conditions is required. In this paper, we propose an efficient pesticide control system based on agricultural unmanned aerial vehicles considering the application conditions and environmental information for each crop. The effectiveness of the proposed model was demonstrated by measuring the drop uniformity of pesticides according to the change in altitude and speed after attaching the sensory paper and measuring the penetration rate of the drug inside the canopy according to the change in crop growth conditions. Experiment result, the closer the height of the UAV is to the ground, the more evenly the crops are sprayed, but for safety reasons, 2m more is suitable, and on average a speed of 2m/s is most suitable for control. The proposed control system is expected to help develop intelligent services based on the use of various unmanned aerial vehicles in agricultural environments.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.