• Journal of the Korean Wood Science and Technology
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• v.44 no.5
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• pp.767-775
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• 2016

Wood properties are affected by environmental factors such as soil, topography, rainfall, and climate change. The physical and mechanical properties of Quercus glauca were analyzed in order to investigate the relationship between wood properties and forest stand characteristics related to regions and forest origins. Physical and mechanical properties of wood were influenced by region. And no significant difference was observed between natural and artificial forests with respect to wood quality properties. Therefore, these findings are expected to be useful as fundamental data for silviculture practices of these species for wood quality.

• The Korean Journal of Quaternary Research
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• v.16 no.1
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• pp.17-27
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• 2002

Analysis of No. 199∼145 cross-sections set up by the Ministry of Construction (1978) in the middle reaches of the Sumjin River around Sunchang, Daegang, and Goksung areas have been done for delineating the changes In fluvial geomorphic features. The entire river-bed in the study area has been considerably degraded since 1978. In some cross-sections, the thalweg shillings are observed. Two aspects are responsible for the erosion-dominant environment. First, flow velocity has been increased. Human activities including wetland destruction, ex-channel destruction and artificial levee construction reduced the channel width, and fixed the channel geometry. This has resulted in increase of the water velocity. Pebble and granule∼coarse sand are prevailing on the river-bed, indicate the high speed of the currents. Second, aggregate has been intensively mined during 1980s∼1990s around the areas. Especially, in the right side of the cross-sections No. 188∼187 and the left side of the cross-section No. 155, erosion toward under the artificial levee is remarkable. This can be led to bank failure in case of heavy rainfall.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.203-215
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• 2021

In the present study, hydrologic data and topographical data from 2010 to 2019 were collected from three gauging stations placed in the watershed of Naeseong stream to determine changes and rates of changes in rainfall, water level & mean velocity, and water level & discharge, together with changes in rates of erosion and deposition at cross-sections of the river. Besides, effects of regulated and non-regulated rivers according to the presence of artificial regulation of flow rate of the river via artificial structure located at Seo stream (Yeongju si (Wolhogyo) station), the tributary free from construction of dams, were compared and analyzed. Results of analyses conducted in the present study revealed vegetational establishment and landforming due to increasing area of vegetational sandbar evolved in the flood plain (intermediate- or high- water level) by the drought sustained from 2013 to 2015. Continuous erosion of river bed was appeared because of narrowed flow area with low water level and increased velocity and tractive force on river bed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.133-152
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• 2022

Rice is a fundamental staple food commodity all around the world. Globally, it is grown over 167 million hectares and occupies almost 1/5^th of total cultivated land under cereals. With a total production of 782 million metric tons in 2018. In Pakistan, it is the 2^nd largest crop being produced and 3^rd largest food commodity after sugarcane and rice. The stem borers a type of pest in rice and other crops, Scirpophaga incertulas or the yellow stem borer is very serious pest and a major cause of yield loss, more than 90% damage is recorded in Pakistan on rice crop. Yellow stem borer population of rice could be stimulated with various environmental factors which includes relative humidity, light, and environmental temperature. Focus of this study is to find the environmental factors changes i.e., temperature, relative humidity and rainfall that can lead to cause outbreaks of yellow stem borers. this study helps to find out the hot spots of insect pest in rice field with a control of farmer's palm. Proposed system uses temperature, relative humidity, and rain sensor along with artificial neural network to predict yellow stem borer attack and generate warning to take necessary precautions. result shows 85.6% accuracy and accuracy gradually increased after repeating several training rounds. This system can be good IoT based solution for pest attack prediction which is cost effective and accurate.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.5
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• pp.19-27
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• 2016

This study is to find appropriate plant for infiltration swale (which is natural LID infrastructure) and suggest basic research database for building infrastructure of LID facilities. Through the research inside, it first selects the plant strong to flooding and salt tolerance. Also, the research built infiltration swale along the road, planted those strong plants and monitored how well those plants adapted into the environment. Particularly, it showered 72mm/hr-speed artificial shower, also with natural shower, given that plants were vulnerable to flood because of influx of the rain. As a result of field applicability monitoring, Pennisetum alopecuroides and Equisetum hyemale (which degrade the pollutant well and adapt into rainy environment) are planting individually, or Juncus effusus var. decipiens, Liriope platyphylla, Miscanthus sinensis Andersson, Euonymus japonica (which are strong to rainy environment) and Pennisetum alopecuroides and Equisetum hyemale are mixed planting. The research should have monitored the plant for more than one year to study them, but the research only lasted five months. Therefore, it is hard to generalize. After all, through the long term research, it should pursue study more on appropriate plant materials and database that can be the reference for infrastructure establishment and maintenance.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.775-780
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• 2010

Over 90% of the livestock excretions were treated and utilized by land application in Korea. Excessive application of the livestock manure as fertilizer has been issued as a main pollutant source in groundwater and watersheds. This study was seasonally conducted to identify the discharging characteristics with a certain artificial rainfall intensity (13 mm/hr) in terms of surface runoff, groundwater, and soil residue mass depending on the livestock manure types. A experimental field was constructed with three different sites that pig liquid fertilizer (LF), cattle manure (CM), and standard (S). The pig liquid fertilizer of 1,200 L and cattle manure of 900 kg were sprayed on each site ($50m^2$). The standard area was firmly prevented from any other contaminants. In the LF site, farmland discharging rate (FDR) was computed as 0.006 in CODcr, 0.015 in TN, and 0.029 in TP, resulted from the mass balance among total injection mass, surface runoff and groundwater. In the CM site, 29% of the nitrogen and phosphorus in each were discharged to the surface, and 64% and 58% of them were remained in the farmland. Surface runoff rate of the CM was higher than that of the LF, resulted from the solid form of the CM.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.301-306
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• 2006

본 연구에서는 강우의 시 공간적 분포의 불규칙한 변동성을 고려한 강우-유출예측을 위해 인공신경망(Artificial Neural Networks: ANNs)의 기법의 일종인 자기조직화(Self Organizing Map: SOM) 이론과 역전파 학습 알고리즘(Back Propagation Algorithm: BPA) 이론을 복합적으로 이용하였다. 기존의 인공신경망 연구에서 야기된 저..갈수기의 유출량에 대한 과대평가, 홍수기의 유출량에 대한 과소평가, 예측값이 선행 유출량의 지속성을 갖는 Persistence 현상을 해결하기 위하여 패턴분류 성능을 지닌 SOM 이론을 도입하여 예측모형의 전처리 과정으로 이용하였다. 이는 기존의 인공신경망 모형이 하나의 모형을 구성하여 유출량의 전 범위에 해당하는 자료를 예측하는 방법을 개선한 것으로 SOM에 의해 패턴이 분류된 강우-유출관계의 각 패턴별 예측모형을 통해 분류된 자료들의 예측을 수행하는 방법이다. 이와 같이 SOM을 강우-유출예측모형의 전처리과정으로 이용함으로서 기존의 인공신경망 연구에서 야기된 현상들을 해결할 수 있었고, 예측력 또한 기존의 인공신경망 모형의 결과에 비해 우수하였다.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.749-758
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• 2010

Embankment Slope (or Fill Slope) is defined as artificial slope formed by the filling of soil or rocks on the original ground. Recently a lot of embankment failures and collapse has occurred due to the increase of torrential rainfall and typhoons. Embankment collapse has lead to a great loss of lives and property therefore there is a need to establish a systematic embankment slope management system that will handle the maintenance and repair of risky embankment slopes. The objective of this study is to establish an "Embankment Slope Management Method" for embankment slopes located along national highways all over Korea. The method for field investigation of embankment slopes was recommended and the system for investment priority determination was also developed. The factors that lead to the collapse of embankment slopes caused by natural calamities were also determined through the initial survey of embankment slopes located along river fronts and mountainous areas.

• Asian Journal of Atmospheric Environment
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• v.11 no.3
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• pp.176-183
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• 2017

Although it is well known that rain plays an important role in capturing air pollutants, its quantitative evaluation has not been done enough. In this study, the effect of raindrop size on pollutant scavenging was investigated by clarifying the chemical nature of individual size-resolved raindrops and their residual particles. Raindrops as a function of their size were collected using the raindrop collector devised by our oneself in previous study (Ma et al., 2000) during high atmospheric loading for $PM_{2.5}$. Elemental analyses of solid residues and individual residual particles in raindrops were subsequently analyzed by Particle Induced X-ray Emission (PIXE) and Scanning Electron Microscopy (SEM) with Energy Dispersive X-Ray Analysis (EDX), respectively. The raindrop number concentration ($m^{-2}h^{-1}$) tended to drastically decrease as the drop size goes up. Particle scavenging rate, $R_{sca.}$ (%), based on the actual measurement values were 38.7, 69.5, and 80.8% for the particles with 0.3-0.5, 0.5-1.0, and $1.0-2.0{\mu}m$ diameter, respectively. S, Ca, Si, and Al ranked relatively high concentration in raindrops, especially small ones. Most of the element showed a continuous decrease in concentration with increasing raindrop diameter. The source profile by factor analysis for the components of residual particles indicated that the rainfall plays a valuable role in scavenging natural as well as artificial particles from the dirty atmosphere.