• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.235-250
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• 2021

The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO₂) and methane (CH₄) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (F_CO2), methane (F_CH4), and nitrous oxide (F_N2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

• The Journal of Society for e-Business Studies
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• v.20 no.1
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• pp.183-199
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• 2015

Due to the Four Major Rivers Restoration Project, Nakdong River Estuary Barrage's designed flood quantity has been largely increased, and this has caused to construct several drainage gates at the right side of Eulsukdo island to secure the safety of downstream river area. For successful functioning of Nakdong River Estuary Barrage, such as flood control, disaster prevention, and the securing of sufficient water capacity, drainage gates at the both sides of island have to operate systematically and reliably. To manage this under restricted personnel and resources, we have implemented the IOS (Integrated Operation System) by integrating previous facilities and resources via information and communication technologies. The IOS has been designed to have higher availability and fault tolerance to function continuously even with the partial system's failure under the emergency situation like flood. Operators can use the system easily and acknowledge alarms of facilities through its IWS (Integrated Warning System) earlier. Preparing for Integrated Water Resources Management and Smart Water Grid, the architecture of IOS conformed to open system standards which will be helpful to link with the other systems easily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Wetlands Research
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• v.23 no.3
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• pp.260-276
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• 2021

Wetlands are constantly affected by internal and external environments that make up the wetlands, and these effects make wetlands change. East Asia countries where about 15% of Ramsar's registered wetlands are located, is valuable conservation area due to various wetland types and biodiversity. However, due to climate change and other factors, the total area of wetlands has been reduced and biodiversity have been damaged. To mitigate these problems and to manage wetlands efficiently, it is important to identify the factors that change wetlands and to identify how each factor affects them. In this study, we conducted a wetland-related literature analysis in East Asia to derive factors that affect the changes in wetlands, and analyzed the relationships among the factors. Finally we presented research directions considering wetland change factors. In most of the East Asia countries, it was found that there is deficiency in research studies about extraction in direct factors and water-energy infrastructure, tourism & recreation in indirect factors. Also, we presented the necessity for future research using the result between connectivity & relationship analysis and indirect drivers of change and their influence on direct drivers of change. The results of this study could contribute to the establishment of an R&D cooperation system in East Asia region and strengthen wetland management.

• Journal of Wetlands Research
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• v.25 no.1
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• pp.64-73
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• 2023

Before 2022, there was a lot of confusion in the process of planning and implementing the projects for ecological restoration of the stream due to dualization the principal agent of stream management. Because the Ministry of Environment took charge of the project in 2022, securing the health of aquatic ecosystem of stream became an essential factor in the project. Therefore, in this study, the streams that require the project for ecological restoration was selected in Han River estuary, where it is essential to secure the health of the stream aquatic ecosystem as blackish water zone and Ramsar wetland are located. Physical, chemical, spatial/humanistic, health of aquatic ecosystems evaluation indexes were calculated based on the detailed facts and figures of the project for ecological restoration of the stream in the beginning. Ranking, re-scaling, z-score, and t-score normalization methods were applied to the calculated evaluation index, and the values were compared and analyzed. After that, the entropy weight method was applied to each evaluation index. Through this process, the streams(Mokgamcheon, Anyangcheon etc.) that require the project for ecological restoration were selected for the purpose of securing the health of the aquatic ecosystem in Han River estuary. The result of this study can be used as basic research data in the process of selecting the priority determination of the projects for ecological restoration of the stream.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.453-453
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• 2023

상수관망의 수질사고와 이상상황 발생시 대응을 위해서는 급수구역에 설치되어 있는 자동수질측정기, 정밀여과장치, 재염소주입설비, 자동드레인 등의 계측·제어설비들 간의 유기적인 정보공유를 통한 제어를 필요로 한다. 스마트 상수관망 운영플랫폼은 이러한 인프라 시설의 운영방안을 고려하여 분산되어 있는 계측데이터를 통합감시 및 제어하는 시스템으로 개발되었다. 상수관망 운영플랫폼은 능동형 분석 제어기술을 도입하여, 스마트 상수관망 인프라 설비를 최적제어할 수 있도록 구현하였다. 통합운영 플랫폼은 PostgreSQL, PostGIS, GeoServer, OpenLayers 등의 기술을 활용하여 개발하였다. 플랫폼은 계측감시, 시설관리, 운영제어 등의 기능으로 구성되며, 상수도 업무지원을 위한 관망해석 및 네트워크 분석 기능을 지원한다. 본 시스템은 스마트 상수도 구축사업을 통해 구축한 유량·수질모니터링 장비와 수질관리를 위해 도입된 재염소, 자동드레인 설비의 운영상태를 실시간 조회하는 모니터링 프로그램과, 관망해석 프로그램 그리고 대상설비의 최적제어를 위한 운영관리 프로그램으로 구성되어 있다. 모니터링 프로그램은 현장에서 측정되고 있는 유량, 수압, 수질, 펌프운전 등의 상태를 실시간으로 감시하고 클라우드 데이터베이스에 저장·관리하는 기능을 수행한다. 관망해석 프로그램은 EPA_Net모형과 연계되어 관망수리·수질해석을 수행하는 부분으로 재염소설비의 염소 추가주입이나 자동드레인을 통한 배제시 나타나게되는 관의 수리·수질변화를 클라우드 컴퓨팅 환경에서 분석하고 결과를 가시화 하는 기능을 갖고 있다. 운영관리 프로그램은 재염소 주입이 필요할 경우 주입량의 산정하는 부분과 관망 파손이나 수질사고 발생시 최적 단수예상지역을 도출하는 기능을 보유하고 있다. 향후 스마트 상수관망의 능동형 수질관리를 추진하는 지자체에 도입하여 인프라운영관리 기술 확보 및 수질관리 능력 개선과 실시간 감시 및 위기 대응능력 향상에 기여할 것으로 기대된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Smart Structures and Systems
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• v.24 no.4
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• pp.541-552
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• 2019

Construction development and greenhouse gas emissions have globally required a strategic management to take some steps to stain and maintain the environment. Nowadays, recycled aggregates, in particular ceramic waste, have been widely used in concrete structures due to the economic and environmentally friendly solution, requiring the knowledge of recycled concrete. Also, one of the materials used as a substitute for concrete cement is wollastonite mineral to decrease carbon dioxide (CO2) from the cement production process by reducing the concrete consumption in concrete. The purpose of this study is to investigate the effect of wollastonite on the mechanical properties and durability of conventional composite concrete, containing recycled aggregates such as compressive strength, tensile strength (Brazilian test), and durability to acidic environment. On the other hand, in order to determine the strength and durability of the concrete, 5 mixing designs including different wollastonite values and recovered aggregates including constant values have been compared to the water - cement ratio (w/c) constant in all designs. The experimental results have shown that design 5 (containing 40% wollastonite) shows only 6.1% decrease in compressive strength and 4.9% decrease in tensile strength compared to the control plane. Consequently, the use of wollastonite powder to the manufacturing of conventional structural concrete containing recycled ceramic aggregates, in addition to improving some of the properties of concrete are environmentally friendly solutions, providing natural recycling of materials.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.208-216
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• 2023

The purpose of our study is to design datasets for Artificial Intelligence learning for cold sea fish farming. Salmon is considered one of the most popular fish species among men and women of all ages, but most supplies depend on imports. Recently, salmon farming, which is rapidly emerging as a specialized industry in Gangwon-do, has attracted attention. Therefore, in order to successfully develop salmon farming, the need to systematically build data related to salmon and salmon farming and use it to develop aquaculture techniques is raised. Meanwhile, the catch of pollack continues to decrease. Efforts should be made to improve the major factors affecting pollack survival based on data, as well as increasing the discharge volume for resource recovery. To this end, it is necessary to systematically collect and analyze data related to pollack catch and ecology to prepare a sustainable resource management strategy. Image data was obtained using CCTV and underwater cameras to establish an intelligent aquaculture strategy for salmon and pollock, which are considered representative fish species in Gangwon-do. Using these data, we built learning data suitable for AI analysis and prediction. Such data construction can be used to develop models for predicting the growth of salmon and pollack, and to develop algorithms for AI services that can predict water temperature, one of the key variables that determine the survival rate of pollack. This in turn will enable intelligent aquaculture and resource management taking into account the ecological characteristics of fish species. These studies look forward to achievements on an important level for sustainable fisheries and fisheries resource management.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.