• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.130-134
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• 2006

본 연구의 목적은 하천 복원과 관리에 필수적인 하천의 특성 분석 및 물순환 분석시스템 구축에 있다. 연구 대상지역으로 최근 하천의 생태 기능 회복을 위해 도심생태하천조성 사업이 추진되고 있는 대전 3대 하천유역을 선정하였다. 대전 3대 하천 유역의 물수지와 도시화에 따른 영향을 파악하기 위하여 SWAT을 이용한 물순환 분석시스템을 구축하였다. 모형적용 결과, 유출량과 지하수 수위 변화 등 대전 3대 하천 유역의 특성을 관측치에 가깝게 모의할 수 있었다. 모델의 검보정 실시결과에서 나타난 모델의 계산 값들의 관측된 유출량뿐 아니라 기저유출량 및 지하수 수위와의 높은 상관관계는 본 연구에서 구축한 모델의 구조나 변수의 유효성에 많은 신뢰도를 제공한다고 판단된다. SWAT을 이용하여 대전 3대 하천 유역의 물수지 분석 및 도시화에 따른 영향을 평가하였다. 물수지 분석결과에 의하면, 전체적으로 총 유출량 중 지하수 유출량이 47%정도, 중간 유출량이 31% 그리고 지표유출량이 22%이다. 각 소유역의별 유출 성분 분석결과는 각 소유역의 토지 이용도, 토양 그리고 지형적 특징에 따른 유출 특성을 확인하였다. 도시화 영향 분석 결과 전체적으로 1975년에서 2000년까지 갑천 유역의 약 5%가량의 도시화는 총 유출량의 변화에 있어서는 현저한 차이를 보이지 않았으나, 각 유출 성분의 경우에는 많은 영향이 있는 것으로 나타났다. 특히 지표유출량은 45% 가량의 증가를 보였고, 전체 유역의 지하수함양 량이 5%정도 감소한 반면, 도시화가 31%정도 진행된 소유역의 경우에는 17%정도의 현저한 감소를 나타냈다. 본 연구에서 수행한 물수지 분석 및 도시화 영향분석 결과는 향후 대천 3대 하천의 생태하천복원을 위한 물순환 정상화 대책마련 및 하천의 유량확보방안 마련에 기초자료를 제공할 수 있을 것이다.득증대를 꾀함으로 농촌문제 해결에 도움이 될 것으로 기대된다. 본 연구를 통해 GIS 와 RS의 기술이 농촌분야에 더 효율적으로 적용될 것으로 기대되며, 농업기술센터를 통한 정보제공을 함으로써 대농민 서비스 및 농업기관의 위상이 제고 될 것으로 기대된다.여 전자파의 공간적인 가시화를 수행할 수 있었다. 본 전자파 시뮬레이션 기법이 실무에 이용될 경우, 일반인이 전자파의 분포에 대한 전문지식을 습득할 필요 없이, 검색하고자 하는 지역과 송전선, 전철 등 각종 전자파의 발생 공간 객체를 선택하여 실생활과 관련된 전자파 정보에 예측할 수 있어, 대민 환경정보 서비스 질의 개선측면에서 획기적인 계기를 마련할 것으로 사료된다.acid$(C_{18:3})$가 대부분을 차지하였다. 야생 돌복숭아 과육 중의 지방산 조성은 포화지방산이 16.74%, 단불포화지방산 17.51% 및 다불포화지방산이 65.73%의 함유 비율을 보였는데, 이 중 다불포화지방산인 n-6계 linoleic acid$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 지질 구성 총 지방산의 대부분을 차지하는 함유 비율을 나타내었다.했다. 하강하는 약 4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.630-637
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• 2018

Harmony search (HS) is a recently developed metaheuristic optimization algorithm. HS is inspired by the process of musical improvisation and repeatedly searches for the optimal solution using three operations: random selection, memory recall (or harmony memory consideration), and pitch adjustment. HS has been applied by many researchers in various fields. The increasing complexity of real-world optimization problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms and HS are required. We propose an improved clustering harmony search (ICHS) that uses a clustering technique to group solutions in harmony memory based on their objective function values. The proposed ICHS performs modified harmony memory consideration in which decision variables of solutions in a high-ranked cluster have higher probability of being selected than those in a low-ranked cluster. The ICHS is demonstrated in various optimization problems, including mathematical benchmark functions and water distribution system pipe design problems. The results show that the proposed ICHS outperforms other improved versions of HS.

• Tunnel and Underground Space
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• v.25 no.4
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• pp.341-358
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• 2015

This study analyzes the relationship between parameters of the discontinuity in Discrete Fracture Network model such as fracture intensity, fracture orientation, fracture size, fracture shape etc. In this paper, FracMan code was used to model and analyze 3D DFN. A sensitivity analysis was performed in order to analyze the relationship between linear fracture intensity measure ($P_{10}$) and parameters of the discontinuity in $100m{\times}100m{\times}100m$ model area. As a result the sensitivity analysis showed that key parameters affecting fracture intensity are fracture orientation (Trend / Plunge). Conversion factor($C_{13}$) for $P_{10}$, to calculate volumetric fracture intensity measure ($P_{32}$), is derived in case of vertical well and horizontal well when trend is $10^{\circ}$, $30^{\circ}$, $60^{\circ}$, $90^{\circ}$, $120^{\circ}$, $150^{\circ}$, $180^{\circ}$ (7cases) and plunge is $5^{\circ}$, $15^{\circ}$, $30^{\circ}$, $45^{\circ}$, $60^{\circ}$, $75^{\circ}$, $85^{\circ}$ (7cases). It is expected that this paper can be used effectively for modeling and understanding DFN model.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.461-474
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• 2020

Korea launched Geostationary Environmental Monitoring Satellite (GEMS), a UV/visible spectrometer that measure pollution gases on 18 February 2020. Because satellite retrieval is an ill-posed inverse solving process, the validation with ground-based measurements or other satellite measurements is essential to obtain reliable products. For this purpose, satellite-based OMI and OMPS total column ozone (TCO), and ground-based Pandora TCO in Busan and Seoul were selected for future GEMS validation. First of all, the goal of this study is to validate the ground ozone data using characteristics that satellite data provide coherent ozone measurements on a global basis, although satellite data have a larger error than the ground-based measurements. In the cross validation between Pandora and OMI TCO, we have found abnormal deviation in ozone time series from Pandora #29 observed in Seoul. This shows that it is possible to perform inverse validation of ground data using satellite data. Then OMPS TCO was compared with verified Pandora TCO. Both data shows a correlation coefficient of 0.97, an RMSE of less than 2 DU and the OMPS-Pandora relative mean difference of >4%. The result also shows the OMPS-Pandora relative mean difference with SZA, TCO, cross-track position and season have insignificant dependence on those variables.In addition, we showed that appropriate thresholds depending on the spatial resolution of each satellite sensor are required to eliminate the impact of the cloud on Pandora TCO.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.807-821
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• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1B
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• pp.37-45
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• 2011

We studied noise influence on nonlinear chaotic system by using Logistic data series which is known as a typical nonlinear chaotic system. We regenerated Logistic data series by the method of adding noise according to noise level. And, we performed some analyses such as phase space reconstruction, correlation dimension, BDS statistics, and DVS Algorithms which are known as the methods of nonlinear deterministic or chaotic analysis. If we see the results of analysis, the characteristics of data series are gradually changed from nonlinear chaotic data series to random stochastic data series according to increasing noise level. We applied Low Pass Filter (LPF) and Kalman Filter techniques for the investigation of removing effect of the added noise to data series. Typical nonparametric method cannot distinguish nonlinear random series but the BDS statistic can distinguish the nonlinear randomness of the time series. Therefore this study used the BDS statistic which is well known as nonlinear statistical method for the investigation of randomness of time series for the effect of removing noise of data series. We found that Kalman filter is better method to remove the noise of chaotic data series even for high noise level.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.6
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• pp.185-194
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• 2016

Recently, as the popularization of the mobile and the internet, the need of big data technology using a vast amount of data which contains the information has emerged. Big data technology has been used in various fields but use of the public sector is still insufficient. So, this study applies them. This study explores factors influencing silver industry as keywords, graving has effect on the present as well as future society. Results, five variables are 'silver Industry', 'senior citizen who lives alone', 'aging', 'birth' and 'retirement' were searched, and it was confirmed that they are correlated with one another. Results of analyzing the influence of the other four parameters on "Silver Industry", they have an effect significantly. In addition, it proposed the need of the 'providing living space of senior citizen who lives alone', 'childbirth support policy', 'support to vitalize silver startup senior manpower of technology' as an alternative to develop the silver industry. This study provided the theoretical implications that is exploring factors through a quantitative approach using big data and the practical implication is to suggest an alternative.

• Tunnel and Underground Space
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• v.30 no.3
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• pp.226-241
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• 2020

The stability of underground mine cavity is closely related with pillar strength. The vulnerability of pillars can be judged and reinforced if the pillar strength is known. The pillar strength is affected by characteristics of discontinuities and shape of a pillar. The change of pillar strength due to a discontinuity passing through the center of a pillar, width-to-height ratio of a pillar and small joints existing within a pillar was analyzed using PFC 3D. The result showed that the pillar strength is influenced by dip angle of a discontinuity and it increases as width-to-height ratio of a pillar increases. The pillar strength decreases as the number of contained joints increases. The relationship between total trace length observable from the pillar surface and the pillar strength was regressed with exponential function. The correlation coefficient of the regression was high enough so that pillar strength can be predicted using total trace length if a joint set exists in a pillar. Lastly, the method to estimate the strength of a pillar that includes two joint sets was proposed if the joint dip angles are 60°, 30°. The method also need total trace lengths of two joint sets.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.697-706
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• 2013

In recent, Korea has faced on water quality management problems in reservoir and river because of increasing water temperature and rainfall frequency caused by climate change. This study is effectively to manage water quality for establishment of algal bloom forecasting models with artificial neural network. Daecheong reservoir located in Geum river has suitable environment for algal bloom because it has lots of contaminants that are flowed by rainfall. By using back propagation algorithm of artificial neural networks (ANNs), a model has been built to forecast the algal bloom over short-term (1, 3, and 7 days). In the model, input factors considered the hydrologic and water quality factors in Daecheong reservoir were analyzed by cross correlation method. Through carrying out the analysis, input factors were selected for algal bloom forecasting model. As a result of this research, the short term algal bloom forecasting models showed minor errors in the prediction of the 1 day and the 3 days. Therefore, the models will be very useful and promising to control the water quality in various rivers.

• Korean Journal of Ecology and Environment
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• v.45 no.2
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• pp.139-149
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• 2012

Four in situ incubation experiments were conducted in May, August and November 2009, as well as February 2010 to determine the seasonal primary productivity and the community structure of phytoplankton at the Seomjin estuary. The primary production of phytoplankton ranged from 9 to 3560 mgC $m^{-2}\;d^{-1}$. Primary productivity was the highest in the summer season (August), which was influenced by improved optical and temperature conditions of the water, as well as the supply of nutrients derived from its surrounding watershed. Particularly, the upper station (SJ-1, SJ-2) of Seom-jin estuary showed a higher productivity, as a result of inflow of input nutrients originated from the terrestrial source. The fucoxanthin, as an index pigment of diatoms showed the highest concentration (0.74~9.51 ${\mu}g\;L^{-1}$) at all stations, occupying 30~80% to total Chl a concentrations. The phytoplankton species composition determination, using a microscope showed similar results to the pigment analysis, which indicated diatom Skeletonema costatum, as the dominant species. The primary productivity in Seom-jin estuary indicates temporally and spatially large variation, according to different environmental conditions. Also, Skeletonema costatum has euryhaline features with relatively higher contribution.