• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.275-292
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• 2022

In order to detect climate changes using satellite imagery, the GCOS (Global Climate Observing System) defines requirements such as spatio-temporal resolution, stability by the time change, and uncertainty. Due to limitation of GK-2A sensor performance, the level-2 products can not satisfy the requirement, especially for spatial resolution. In this paper, we found the optimal pan-sharpening algorithm for GK-2A products. The six pan-sharpening methods included in CS (Component Substitution), MRA (Multi-Resolution Analysis), VO (Variational Optimization), and DL (Deep Learning) were used. In the case of DL, the synthesis property based method was used to generate training dataset. The process of synthesis property is that pan-sharpening model is applied with Pan (Panchromatic) and MS (Multispectral) images with reduced spatial resolution, and fused image is compared with the original MS image. In the synthesis property based method, fused image with desire level for user can be produced only when the geometric characteristics between the PAN with reduced spatial resolution and MS image are similar. However, since the dissimilarity exists, RD (Random Down-sampling) was additionally used as a way to minimize it. Among the pan-sharpening methods, PSGAN was applied with RD (PSGAN_RD). The fused images are qualitatively and quantitatively validated with consistency property and the synthesis property. As validation result, the GSA algorithm performs well in the evaluation index representing spatial characteristics. In the case of spectral characteristics, the PSGAN_RD has the best accuracy with the original MS image. Therefore, in consideration of spatial and spectral characteristics of fused image, we found that PSGAN_RD is suitable for GK-2A products.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.13-13
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• 2023

디지털 기술은 오늘날 플랫폼과 디지털 트윈의 기술도입을 통해 현실 세계를 네트워크와 가상세계와의 연결이 통합되어진 가상 현실 세계의 입문 도약이다. 현실에서 가상현실의 사이의 디지털 전환(digital transformation)에는 디지털 기술과 솔루션을 비즈니스의 모든 영역에 통합하는 것이 포함된다. 이러한 디지털 전환의 핵심은 데이터에 관한 것이며, 데이터를 활용하여 가치를 창출하고 고객경험과 비즈니스 영역을 극대화하는 방식을 제공한다. 최적의 데이터를 제공하기 위한 플랫폼과 가상 현실세계 구현을 위한 디지털 트윈의 상호연계 관한 기본 개념은 데이터 수집, 데이터 분석, 데이터 시각화 및 데이터 보고와 같은 데이터 비즈니스이다. 현장 데이터는 디지털 양식을 통해 수집, 기록, 저장된다. 현장 IoT 기반 데이터(사진 및 비디오 매체 등)는 지속적으로 수집되고 종종 다른 데이터베이스에 저장되지만 지리 공간적 위치에 연결되지 않는다. 모든 디지털 발전을 조화시키고 지하수 데이터에서 더 빠른 이해를 도출하기 위해서는 디지털 트윈이 시작되어야 한다. 단일 지하수플랫폼에서 현장 조건을 시각화하고 실시간 데이터를 스트리밍하며, 과거 3D 데이터와 상호작용하여지질 또는 지화학 데이터를 선택적 사용을 위해 지하수 플랫폼과 디지털 트윈이 연계되어야 한다. 데이터를 디지털 정보모델과 연결하면 디지털 트윈에 생명을 불어넣을 수 있지만 디지털 트윈의 가치를 극대화하려면 여전히 데이터 플랫폼 서비스와 전달 방식을 선택해야 한다. 지하수 플랫폼동시성을 갖는 디지털 트윈은 정적 및 동적 데이터를 저장하는 데이터베이스 또는 크라우드 서비스에서 데이터를 가져오는 API(애플리케이션 프로그래밍 인터레이스), 디지털 트윈을 위한 호스팅 공간, 디지털 대상을 구축하는 소프트웨어, 구성 요소 간 읽기/쓰기를 위한 스크립트, chatGPT 및 API를 활용할 수 있다. 이를 통해 수집된 데이터의 실시간 양방향 통신기술인 지하수 플랫폼 기술을 활용하여 디지털 트윈을 적용하고 완성할 수 있고, 이를 지하수 분야에도 그대로 적용할 수 있다. 지하수 분야의 디지털 트윈 기술의 근간은 지하수 모니터링을 위한 관측장치와 이를 활용한 지하수 플랫폼의 구축 및 양방향 자료전송을 통한 분석 및 예측기술이다. 특히 낙동강과 같이 유역면적이 넓고 유역 내 지자체가 많아 이해관계가 다양하며, 가뭄과 홍수/태풍 등 기후위기에 따른 극한 기상이변가 자주 발생하고, 또한 보 및 하굿둑 개방 등 정부정책 이행에 따른 민원이 다수 발생하는 지역의 경우 하천과 유역에 대한 지하수 플랫폼과 디지털 트윈의 동시성 기술적용 시 지하수 데이터에 대한 고려가 반드시 수반되어야 한다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.445-455
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• 2023

Sea level rise due to global warming is accelerating. According to the IPCC survey, the expected sea level rise in 2100 was analyzed to be 47cm in the low-carbon scenario (SSP 1-2.6) and 82cm in the high-carbon scenario (SSP 5-8.5). Sea level rise can cause serious damage to port infrastructure and reduce the safety of ships docked inside ports. In this study, Mokpo Port, which frequently suffers from flooding during high tide, was selected and the sensitivity of mooring evaluation factors was analyzed for actual berthing ships according to sea level rise scenarios. From the analysis, we found that the tension of mooring line, the load of bollard, vertical angle of mooring line, and ship's motion of 6-DOF, which are evaluation factors, generally increased when the sea level increased. The most sensitive evaluation factor was sway motion of 6-DOF. Also, we analyzed that the value of mooring evaluation factors decreased when the crown height was raised. This was beneficial in improving ship and pier safety. The results of this study can be used as basic data to secure measures to improve port and ship safety according to sea level rise in Mokpo Port.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.173-184
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• 2023

Due to climate change, algal blooms frequently occur not only in Korea but also around the world, and the risk of toxicity of harmful algae has recently been issued. It is known that the representative harmful algae, cyanobacteria, are caused by the intersection of three factors: water temperature, residence time, and nutrients. In this study, water quality simulation was carried out using EFDC, a three-dimensional numerical model, to analyze the variations in water quality due to the decrease of residence time according to the opening of Yeongju Dam in Naeseong-Cheon. In fact, the concentration of chlorophyll-a in Yeongju Dam in the summer of 2021 was significant, exceeding the 'algae warning' for a long time based on the previous algae warning system. On the other hand, as a result of performing the simulation under the condition that the dam gate was completely opened, the concentration of chlorophyll-a was mostly reduced below the 'algae warning' level during the simulation period. It was confirmed that reducing the residence time by restoring the flow of Naeseong-Cheon is a way to immediately reduce algae in Yeongju Dam.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.279-289
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• 2022

Since the frequency of heavy rainfall is increasing due to climate change, water levels in the river exceed past historical records. The rating-curve is to convert water level into flow dicscharge from the regression analysis of the water level and corresponding flow discharges. However, the rating-curve involves many uncertainties because of the limited data especially when observed water level exceed past historical water levels. In order to compensate for insufficient data and increase the accuracy of flow discharge data, this study estimates the flow discharge in the river computed mathematically using Monte Carlo simulation based on a 1D hydrodynamic numerical model. Based on the existing rating curve, a random combination of coefficients constituting the rating-curve creates a number of virtual rating curve. From the computed results of the hydrodynamic model, it is possible to estimate flow discharge which reproduces best fit to the observed water level. Based on the statistical evaluation of these samples, a method for mathematically estimating the water level and flow discharge of all cross sections is porposed. The proposed methodology is applied to the junction of Yochoen Stream in the Seomjin River. As a result, it is confirmed that the water level reproducibility was greatly improved. Also, the water level and flow discharge can be calculated mathematically when the proposed method is applied.

• Journal of Bio-Environment Control
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• v.32 no.3
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• pp.197-204
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• 2023

Heat stress causes a decrease in immunity and disease occurrence in livestock, increasing mortality and impairing productivity. In particular, chickens are very vulnerable to high temperatures compared to other livestock species because their entire body is covered with feathers and sweat glands are not developed. Currently, air conditioning systems are essential in broiler houses to prevent high-air temperature damage to broilers, but conventional cooling facilities are greatly affected by the external environment, so there are limits to their use. In this study, to propose a cooling method, thermal insulation paint and a heat pump were apply in the broiler houses to evaluate the temperature reduction effect. The heat pump experiment was to analyze the cooling effect according to the change in ventilation rate and propose an appropriate. As a result of the experiment, the heat-insulating paint reduced the temperature of the broiler houses by maximum 1-2℃, and in the broiler houses where the heat pump was operated, the temperature decrease was the largest when the ventilation rate was the lowest. When the air temperature in the house is similar to or lower than the outside air temperature, it is considered to be most effective to use a heat pump while maintaining only the minimum ventilation rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.139-147
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• 2023

As heavy precipitation rates have increased due to climate change, the risk of landslides has also become greater. Studies in the field of disaster risk assessment predominantly focus on evaluating intrinsic importance represented by the use or role of facilities. This work, however, focused on evaluating risks according to the external conditions of facilities, which were presented via debris flow simulation. A random walk model (RWM) was partially improved and used for the debris flow simulation. The existing RWM algorithm contained the problem of the simulation results being overly concentrated on the maximum slope line. To improve the model, the center cell height was adjusted and the inertia application method was modified. Facility information was collected from a digital topographic map layer. The risk level of each object was evaluated by combining the simulation result and the digital topographic map layer. A risk assessment technique suitable for the polygon and polyline layers was applied, respectively. Finally, by combining the evaluated risk with the attribute table of the layer, a system was prepared that could create a list of objects expected to be damaged, derive various statistics, and express the risk of each facility on a map. In short, we used an easy-to-understand simulation algorithm and proposed a technique to express detailed risk information on a map. This work will aid in the user-friendly development of a debris flow risk assessment system.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.817-823
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• 2023

Manufacturing plants face the challenge of reducing energy use in response to climate change. Reducing energy consumption can be seen as one of the most important issues, such as reducing production costs and improving efficiency. Among manufacturing industries, the increase in energy consumption in the food industry is gradually increasing along with the improvement of the standard of living and the increase in population. In order to save energy in food processing plants, it is important to identify and analyze energy consumption characteristics in energy-consuming processes. Prior to this, it is necessary to monitor and analyze existing energy consumption to derive reduction measures. In this study, a small and medium-sized food processing plant producing processed meat products was used as a case study to identify and analyze the energy consumption structure at typical cycle/stage level of the batch heating process. From this, we tried to establish realistic and quantitative goals that can be obtained under individual process operating conditions. The results of this study will be used as basic data for the development of diffusion and pervasive energy saving FEMS technology for common core processes of food factories of small and medium-sized enterprises in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.227-234
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• 2008

This study examines which models are more suitable for representing mechanical property of unbound materials to analyze behavior of asphalt pavement structure. Results from FWD (Falling Weight Deflectometer) test were used to apply to nonlinear elastic model. The new method which can deduct material constants of nonlinear elastic model is suggested from FWD test data rather than laboratory resilient modulus ($M_R$) test. It is confirmed that the material constants are within the common range in subbase. Test output from FWD and MDD (Multi-Depth Deflectometer) was used to verify reliability of the model. From the results of verification, this study shows that a non-linear elastic model agrees to MDD test data more than a linear elastic model does.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.42-42
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• 2022

지금까지도 유역에서의 녹조 모니터링은 현장채수를 통한 점 단위 모니터링에 크게 의존하고 있어 기후, 유속, 수온조건 등에 따라 수체에 광범위하게 발생하는 녹조를 효율적으로 모니터링하고 대응하기에는 어려운 점들이 있어왔다. 또한, 그동안 제한된 관측 데이터로 인해 현장 측정된 실측 데이터 보다는 녹조와 관련이 높은 NDVI, FGAI, SEI 등의 파생적인 지수를 산정하여 원격탐사자료와 매핑하는 방식의 분석연구 등이 선행되었다. 본 연구는 녹조의 모니터링시 정확도와 효율성을 향상을 목표로 하여, 우선은 녹조 측정장비를 활용, 7000개 이상의 녹조 관측 데이터를 확보하였으며, 이를 바탕으로 동기간의 고해상도 위성 자료와 실측자료를 매핑하기 위해 다양한Machine Learning기법을 적용함으로써 그 효과성을 검토하고자 하였다. 연구대상지는 낙동강 내성천 상류에 위치한 영주댐 유역으로서 데이터 수집단계에서는 면단위 현장(in-situ) 관측을 위해 2020년 2~9월까지 4회에 걸쳐 7291개의 녹조를 측정하고, 동일 시간 및 공간의 Sentinel-2자료 중 Band 1~12까지 총 13개(Band 8은 8과 8A로 2개)의 분광특성자료를 추출하였다. 다음으로 Machine Learning 분석기법의 적용을 위해 algae_monitoring Python library를 구축하였다. 개발된 library는 1) Training Set과 Test Set의 구분을 위한 Data 준비단계, 2) Random Forest, Gradient Boosting Regression, XGBoosting 알고리즘 중 선택하여 적용할 수 있는 모델적용단계, 3) 모델적용결과를 확인하는 Performance test단계(R², MSE, MAE, RMSE, NSE, KGE 등), 4) 모델결과의 Visualization단계, 5) 선정된 모델을 활용 위성자료를 녹조값으로 변환하는 적용단계로 구분하여 영주댐뿐만 아니라 다양한 유역에 범용적으로 적용할 수 있도록 구성하였다. 본 연구의 사례에서는 Sentinel-2위성의 12개 밴드, 기상자료(대기온도, 구름비율) 총 14개자료를 활용하여 Machine Learning기법 중 Random Forest를 적용하였을 경우에, 전반적으로 가장 높은 적합도를 나타내었으며, 적용결과 Test Set을 기준으로 NSE(Nash Sutcliffe Efficiency)가 0.96(Training Set의 경우에는 0.99) 수준의 성능을 나타내어, 광역적인 위성자료와 충분히 확보된 현장실측 자료간의 데이터 학습을 통해서 조류 모니터링 분석의 효율성이 획기적으로 증대될 수 있음을 확인하였다.