• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.3
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• pp.99-110
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• 2018

Compared to yellow dust coming from China or particulate matter created naturally in spring due to Total Suspended Particulate(TSP), particulate matter in winter season have much more serious effect on human body as they penetrate cell membranes. Although such particulate matter are becoming a social issue, there are no concrete plans on how to reduce them. Air-purifying plants are limited in maintaining the indoor air quality of large area because it is usually difficult to quantify their performance. In order to improve this, a bio-filter that can be connected to air conditioner is suggested as an option. This study seeks to improve air conditioning model-based monitoring method for bio-filters from prior studies and objectify correlations between applied vegetation and growing environment into quantitative indicators. By doing so, this study seeks to provide criteria on plants applied to artificial soil-based vegetation bio-filters and basic information to set air-conditioning features. The study results confirmed significant tendency on the growing stability of each purifying plant in mechanical air-conditioning environment. Among three models selected for bio-filter vegetation models, epipremnum aureum showed high performance in quantitative indicators, including soil moisture, EC, and leaf temperature, etc., indicating that it would assure the highest growing stability in this test air-conditioning environment.

• Journal of Korea Water Resources Association
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• v.38 no.10 s.159
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• pp.895-906
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• 2005

The diversity of observed hydrologic data and the development of geographic information system leads significant progress for developing distributed runoff models in the world. One of the typical examples is TOPMODEL, but the spatial coverage of its application Is limited on small headwater basins. The purpose of this study attempts to overcome its limitation and consequently develops a semi-distributed TOPMODEL. The developed model is composed of two components: a watershed runoff component for a lumped representation of hydrologic runoff process on the catchment scale and a kinematic wave type hydraulic channel routing component lot routing the catchment outflows. The application basin is the $2,703km^2$ upper Soyang dam site and several daily and hourly events are selected for model calibrations and verifications. The model parameters are estimated on 1990 daily event. The model performance on correlation coefficient between observed and computed flows are above 0.90 for the verification events. It is concluded that the developed model in this study can be used for flood analysis in large drainage basins.

• Journal of Environmental Science International
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• v.19 no.1
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• pp.39-45
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• 2010

When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

• Journal of the Korean GEO-environmental Society
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• v.18 no.7
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• pp.21-35
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• 2017

The 3S Basin is described as an important contributor in terms of many aspects in the Mekong River Basin in Southeast Asia. However, the 3S Basin has been suffering adverse consequences of changing discharge and sediment, which are derived from farming, deforestation, hydropower dam construction, climate change, and soil erosion. Consequently, a large population and ecology system that live along the 3S Basin are seriously affected. Accordingly, the calculating and simulating discharge and sediment become ever more urgent. There are many methods to simulate discharge and sediment. However, most of them are designed only during a single rainfall event and they require many kinds of data. Therefore, this study applied a Catchment-scale Soil Erosion model (C-SEM) to simulate discharge and sediment in the 3S Basin. The simulated results were judged with others references's data and the observed discharge of Strung Treng station, which is located in the mainstream and near the outlet of the 3S Basin. The results revealed that the 3S Basin distributes 31% of the Mekong River Basin's total discharge. In addition, the simulated sediment results at the 3S Basin's outlet also substantiated the importance of the 3S Basin to the Mekong River Basin. Furthermore, the results are also useful for the sustainable management practices in the 3S Basin, where the sediment data is unavailable.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.253-261
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• 2018

Cheongpungho number is located in the center of South Korea Jecheon Peninsula, Chungju cheongpungho be formed by hydroelectric dam construction in 1984, now has been changed to a large man-made freshwater sites during the past 30 years. Recent Jecheon government is developing natural healing resort and entertainment performances for the future, in comparison to the feasibility study of the region using remote sensing technology and site planning was conducted in geographic research and analysis, and as a result, we have a very effective to incorporate the color maps using aerial photography and digital terrain analysis and usage analysis to prove and was in the riverside area for the future of the business and the research proposal facilities and events of the brand, to be more multi-cultural festival form apply new high-tech fusion experiments suggest new direction for future tourism.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.471-483
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• 2020

Flood prediction is an important issue to prevent damages by flood inundation caused by increasing high-intensity rainfall with climate change. In recent years, machine learning algorithms have been receiving attention in many scientific fields including hydrology, water resources, natural hazards, etc. The performance of a machine learning algorithm was investigated to predict the water elevation of a river in this study. The aim of this study was to develop a new method for securing a large enough lead time for flood defenses by predicting river water elevation using the a long- short-term memory (LSTM) technique. The water elevation data at the Oisong gauging station were selected to evaluate its applicability. The test data were the water elevation data measured by K-water from 15 February 2013 to 26 August 2018, approximately 5 years 6 months, at 1 hour intervals. To investigate the predictability of the data in terms of the data characteristics and the lead time of the prediction data, the data were divided into the same interval data (group-A) and time average data (group-B) set. Next, the predictability was evaluated by constructing a total of 36 cases. Based on the results, group-A had a more stable water elevation prediction skill compared to group-B with a lead time from 1 to 6 h. Thus, the LSTM technique using only measured water elevation data can be used for securing the appropriate lead time for flood defense in a river.

• Informatization Policy
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• v.20 no.1
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• pp.61-84
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• 2013

This article examines how the Chinese government blocks the inflow of undesirable information, focusing on the technical aspect of the control mechanism. Unlike Cuba and North Korea, which regulate the whole Internet, China uses both state-of-the-art technological supervision and labor-intensive physical control due to economic reasons in order to prepare for actors who can threaten the Communist party. The Chinese government will not overlook the inflow of information which can be the link between demonstrations and democratization. This is because stronger protests utilizing information technology will trigger the Chinese government's flexible control based on large scale violation and technology. In this article, we first review the concept of universal internet control involved in internet regulation in nations, and then focus on China's internet censorship and its regulatory control from the '90s to the present. Finally, we analyze how the Chinese government actively controls the internet access by utilizing the relationship dynamics between the central and local governments, depending on protest issue. This thesis will assume that it is difficult for China to become democratized due to its information interception, and search how the government manages the internet.

• Journal of Korea Water Resources Association
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• v.52 no.spc2
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• pp.835-844
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• 2019

This study dealt with a systematic approach for sediment replenishment works which defines the artificial supply of coarse sediment to downstream river channels of dams. That is an increasing practice in Japanese, American and European rivers for the purpose of compensating sediment deficits downstream and rehabilitating geomorphological habitats below dams. We introduced five main objectives of the sediment replenishment, simply from construction of artificial spawning redds for anadromous fish to restoration of fluvial geomorphological process of river system. Then we suggested determination of sediment size distribution and quantity of coarse sediment as well as selecting an effective implementation method in corresponding to specific objectives and local restrictions in the basin, reservoir and river.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.152-152
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• 2019

This study demonstrates a novel approach of remotely sensed estimates of stream flow at fifteen hydrological station in the Han River Basin, Korea. Multi-temporal data of the European Space Agency's Sentinel-1 SAR satellite from 19 January, 2015 to 25 August, 2018 is used to develop and validate the flow estimation model for each station. The flow estimation model is based on a power law relationship established between the remotely sensed surface area of water at a selected reach of the stream and the observed discharge. The satellite images were pre-processed for thermal noise, radiometric, speckle and terrain correction. The difference in SAR image brightness caused by the differences in SAR satellite look angle and atmospheric condition are corrected using the histogram matching technique. Selective area filtering is applied to identify the extent of the selected stream reach where the change in water surface area is highly sensitive to the change in stream discharge. Following this, an iterative procedure called the Optimum Threshold Classification Algorithm (OTC) is applied to the multi-temporal selective areas to extract a series of water surface areas. It is observed that the extracted water surface area and the stream discharge are related by the power law equation. A strong correlation coefficient ranging from 0.68 to 0.98 (mean=0.89) was observed for thirteen hydrological stations, while at two stations the relationship was highly affected by the hydraulic structures such as dam. It is further identified that the availability of remotely sensed data for a range of discharge conditions and the geometric properties of the selected stream reach such as the stream width and side slope influence the accuracy of the flow estimation model.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.