• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.586-591
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• 2005

우리나라는 에너지의 안정적 공급과 에너지이용 과정에서 발생하는 환경적, 안보적 외부성을 최소화하는 에너지수급 구조를 마련하기 위해 2003년 12월 '제2차 신재생에너지 기술개발 및 이용보급 기본계획(2003-2012)'을 발표하였다. 이 계획에서는 2011년까지 전체 TPES의 $5\%$를 신재생에너지로 공급하는 것을 정책목표로 수립하고 수소, 태양광 그리고 풍력기술을 중점적으로 추진하기로 하였다. 특히 수소부문에서는 주택 및 건물용, 발전용, 수송용 연료전지의 개발을 중심으로 개발하여 세계 기술시장의 $20\%$를 확보한다는 계획을 발표하였다. 이러한 기술 잠재력을 기반으로 우리 정부도 미국이나 일본과 같이 수소경제로의 전환을 준비하고 있으며 2020년대 이후 우리나라의 에너지부문은 새로운 국면에 접어들 것으로 전망된다. 에너지나 환경기술의 효과적 인 개발을 위해서는 이들 기술의 직접적인 비용측면에 대한 분석 즉 경제성 평가와 새로운 기술변화로 인한 중장기적인 사회경제적 영향평가가 선행되어야 한다. 이러한 평가는 대상 기술의 사회경제적 파급효과가 광범위할수록 더욱 복잡한 분석이 요구된다. 본 연구의 주제인 수소에너지기술은 지금까지 이용되던 것과는 전혀 새로운 에너지캐리어(carrier)를 개발하는 것으로 에너지부문 및 여타 다른 산업부문이 공유하고 있는 에너지 관련 인프라의 전면적인 조정이 요구되며 에너지 이용과 관련된 사회경제적 측면의 급속한 변화를 수반한다. 본 연구는 수소경제로의 이행에 대한 사회경제적 영향평가의 방법론적 요소들과 기법을 제시한다."중등도 독성"으로 나타났다 이상의 결과는 전기도금을 이용하여 교정용 선재의 직경을 증가시키는 방법이 임상에 적용되기 위해서는 세포독성을 줄이기 위한 추가의 연구가 필요함을 시사하였다.의하게 가장 낮은 정지. 운동 마찰력을 보였고 브라켓-호선 각도가 증가함에 따라 유의하게 정지, 운동 마찰력도 증가하였다 (P<0.001)%$ 낮추지만(p value=0.260) 평균 $D_{max}$는 거의동일 하여($0.3\%$ 감소, p value=0.867), 전통적인 방법보다 우수성이 크게는 없는 것으로 평가되었다. 그러나 환자의 체곡선이 보상체와 잘 일치하는 경우에는 DII가 $18\%$까지 감소하였다. 결론 : Multistatic field 방법은 모든 환자에 대하여 선량분포의 균일성을 전반적으로 향상시키는 효과적인 방법으로 평가되는 반면 공용보상체의 사용은 보상체의 크기가 환자의 체 윤곽과 잘 일치하는 경우만 효과적으로, 적용의 범위에는 한계가 있는 방법으로 평가되었다.비교하여 계통에 따르는 차이가 있음을 알 수 있었다. 그러므로 가임기 여성의 방사선 진단 및 치료시 Rugh의 10일 법칙을 적용하여 착상전기 방사선 조사로 인한 부작용들을 적극적으로 예방하는 것이 매우 중요하다고 생각한다.equirements of the prematured infants during the early weeks of life. 모든 치근단 수준에서 비표준화 medium 크기 master cone 사용군이 ISO 표준화 규격의 master cone 사용군에 비해

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.393-407
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• 2012

This study focuses on the correction of topographic effects caused by a combination of solar elevation and azimuth, and topographic relief in single optical remote sensing imagery, and by a combination of changes in position of the sun and topographic relief in comparative analysis of multi-temporal imageries. For the Jeju Island, Republic of Korea, where Mt. Halla and various cinder cones are located, a Landsat 7 ETM+ imagery and ASTER GDEM data were used to normalize the topographic effects on the imagery, using two topographic normalization methods: cosine correction assuming a Lambertian condition and assuming a non-Lambertian c-correction, with kernel sizes of $3{\times}3$, $5{\times}5$, $7{\times}7$, and $9{\times}9$ pixels. The effects of each correction method and kernel size were then evaluated. The c-correction with a kernel size of $7{\times}7$ produced the best result in the case of a land area with various land-cover types. For a land-cover type of forest extracted from an unsupervised classification result using the ISODATA method, the c-correction with a kernel size of $9{\times}9$ produced the best result, and this topographic normalization for a single land cover type yielded better compensation for topographic effects than in the case of an area with various land-cover types. In applying the relative radiometric normalization to topographically normalized three multi-temporal imageries, more invariant spectral reflectance was obtained for infrared bands and the spectral reflectance patterns were preserved in visible bands, compared with un-normalized imageries. The results show that c-correction considering the remaining reflectance energy from adjacent topography or imperfect atmospheric correction yielded superior normalization results than cosine correction. The normalization results were also improved by increasing the kernel size to compensate for vertical and horizontal errors, and for displacement between satellite imagery and ASTER GDEM.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.284-293
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• 2015

The objective of this paper is to determine the conditions of road surface by utilizing the images collected from closed-circuit television (CCTV) cameras installed on roadside. First, a technique was examined to detect wet surfaces at nighttime. From the literature reviews, it was revealed that image processing using polarization is one of the preferred options. However, it is hard to use the polarization characteristics of road surface images at nighttime because of irregular or no light situations. In this study, we proposes a new discriminant for detecting wet and dry road surfaces using CCTV image data at night. To detect the road surface conditions with night vision, we applied the wavelet packet transform for analyzing road surface textures. Additionally, to apply the luminance feature of night CCTV images, we set the intensity histogram based on HSI(Hue Saturation Intensity) color model. With a set of 200 images taken from the field, we constructed a detection criteria hyperplane with SVM (Support Vector Machine). We conducted field tests to verify the detection ability of the wet road surfaces and obtained reliable results. The outcome of this study is also expected to be used for monitoring road surfaces to improve safety.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.871-874
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• 2010

Needs for Smart Grid development are increasing all over the world as a solution to its problem according to depletion of energy resources, climatic and environmental rapidly change and growing demand for electrical power. Especially decentralized power is attracting world's attention. In this mood a new era for a unit scale of decentralized power environment is on its way in building. However there is a problem to have to be solved in the uniformity of power quality because the amount of power generated from renewable energy resources such as wind power and solar light is very sensitive to climate fluctuation. And thus this paper tries to suggest an energy management method on basis of real time monitoring for meteorological data. In the current situation of lacking in USN-based killer application in Smart Grid field, this paper proposes the USN-based DER management system which collects the meteorological data and control power system througout utilizing wireless sensor network technique this business. This communication technique is regarded to be efficient in aspects of installation cost and tits maintenance cost. The proposed EMS model embodies the method for predicting the power generation by monitoring and analyzing the climatic data and controling the efficient power distribution between the renewable energy and the existing power. The ultimate goal of this paper is to provide the technological basis for achieving zero-energy house.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.485-492
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• 2021

The wind turbines with a rated capacity of 50kW or less are generally considered as small class. Small wind turbines are an attractive alternative for off-grid power system and electric home appliances, both as stand-alone application and in combination with other energy technologies such as energy storage system, photovoltaic, small hydro or diesel engines. The research objective is to develop the 50kW scale wind turbine blades in ways that resemble as closely as possible with the construction and methods of utility scale turbine blade manufacturing. The mold process based on wooden form is employed to create a hollow, multi-piece, lightweight design using carbon fiber and fiberglass with an epoxy based resin. A hand layup prototyping method is developed using high density foam molds that allows short cycle time between design iterations of aerodynamic platforms. A production process of five blades is manufactured and key components of the blade are tested by IEC 61400-23 to verify the appropriateness of the design. Also, wind system with developed blades is tested by IEC 61400-12 to verify the performance characteristics. The results of blade and turbine system test showed the available design conditions for commercial operation.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.279-285
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• 2019

To estimate daily canopy photosynthesis, accurate estimation of canopy light interception according to a daily solar position is needed. However, this process needs a lot of cost, time, manpower, and difficulty when measuring manually. Various modeling approaches have been applied so far, but it was difficult to accurately estimate light interception by conventional methods. The objective of this study is to estimate the spatial distributions of light interception and photosynthetic rate of paprika with time by using 3D-scanned plant models and optical simulation. Structural models of greenhouse paprika were constructed with a portable 3D scanner. To investigate the change in canopy light interception by surrounding plants, the 3D paprika models were arranged at $1{\times}1$ and $9{\times}9$ isotropic forms with a distance of 60 cm between plants. The light interception was obtained by optical simulation, and the photosynthetic rate was calculated by a rectangular hyperbola model. The spatial distributions of canopy light interception of the 3D paprika model showed different patterns with solar altitude at 9:00, 12:00, and 15:00. The total canopy light interception decreased with an increase of surrounding plants like an arrangement of $9{\times}9$, and the decreasing rate was lowest at 12:00. The canopy photosynthetic rate showed a similar tendency with the canopy light interception, but its decreasing rate was lower than that of the light interception due to the saturation of photosynthetic rate of upper leaves of the plants. In this study, by using the 3D-scanned plant model and optical simulation, it was possible to analyze the light interception and photosynthesis of plant canopy under various conditions, and it can be an effective way to estimate accurate light interception and photosynthesis of plants.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.307-313
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• 2022

As the development of renewable energy expands internationally to cope with global warming and climate change, the share of wind power generation has been gradually increasing. Although wind farms can produce electric power for 24 h a day compared to solar power plants, Their interfere with the operation of nearby radars or communication equipment must be analyzed because large-scale wind power turbines are installed. This study analyzed whether a land radio station can receive sufficient signals when a ship sailing outside the offshore wind farm transmits distress signals on the VHF band. Based on the geographic information system digital map around the target area, wind turbine CAD model, and wind farm layout, the area of interest and wind farm were modeled to enable numerical analysis. Among the high frequency analysis techniques suitable for radio wave analysis in a wide area, a dedicated program applying physical optics (PO) and shooting and bouncing ray (SBR) techniques were used. Consequently, the land radio station could receive the electromagnetic field above the threshold of the VHF receiver when a ship outside the offshore wind farm transmitted a distress communication signal. When the line of sight between the ships and the land station are completely blocked, the strength of the received field decreases, but it is still above the threshold. Hence, although a wind farm is a huge complex, a land station can receive the electromagnetic field from the ship's VHF transmitter because the wave length of the VHF band is sufficiently long to have effects such as diffraction or reflection.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.193-205
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• 2023

A large amount of floating debris from land-based sources during heavy rainfall has negative social, economic, and environmental impacts, but there is a lack of monitoring systems for floating debris accumulation areas and amounts. With the recent development of artificial intelligence technology, there is a need to quickly and efficiently study large areas of water systems using drone imagery and deep learning-based object detection models. In this study, we acquired various images as well as drone images and trained with You Only Look Once (YOLO)v5s and the recently developed YOLO7 and YOLOv8s to compare the performance of each model to propose an efficient detection technique for land-based floating debris. The qualitative performance evaluation of each model showed that all three models are good at detecting floating debris under normal circumstances, but the YOLOv8s model missed or duplicated objects when the image was overexposed or the water surface was highly reflective of sunlight. The quantitative performance evaluation showed that YOLOv7 had the best performance with a mean Average Precision (intersection over union, IoU 0.5) of 0.940, which was better than YOLOv5s (0.922) and YOLOv8s (0.922). As a result of generating distortion in the color and high-frequency components to compare the performance of models according to data quality, the performance degradation of the YOLOv8s model was the most obvious, and the YOLOv7 model showed the lowest performance degradation. This study confirms that the YOLOv7 model is more robust than the YOLOv5s and YOLOv8s models in detecting land-based floating debris. The deep learning-based floating debris detection technique proposed in this study can identify the spatial distribution of floating debris by category, which can contribute to the planning of future cleanup work.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.111-124
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• 2010

To monitor the environment of land surface change is considered as an important research field since those parameters are related with land use, climate change, meteorological study, agriculture modulation, surface energy balance, and surface environment system. For the change detection, many different methods have been presented for distributing more detailed information with various tools from ground based measurement to satellite multi-spectral sensor. Recently, using high resolution satellite data is considered the most efficient way to monitor extensive land environmental system especially for higher spatial and temporal resolution. In this study, we use two different spatial resolution satellites; the one is SPOT/VEGETATION with 1 km spatial resolution to detect coarse resolution of the area change and determine objective threshold. The other is Landsat satellite having high resolution to figure out detailed land environmental change. According to their spatial resolution, they show different observation characteristics such as repeat cycle, and the global coverage. By correlating two kinds of satellites, we can detect land surface change from mid resolution to high resolution. The K-mean clustering algorithm is applied to detect changed area with two different temporal images. When using solar spectral band, there are complicate surface reflectance scattering characteristics which make surface change detection difficult. That effect would be leading serious problems when interpreting surface characteristics. For example, in spite of constant their own surface reflectance value, it could be changed according to solar, and sensor relative observation location. To reduce those affects, in this study, long-term Normalized Difference Vegetation Index (NDVI) with solar spectral channels performed for atmospheric and bi-directional correction from SPOT/VEGETATION data are utilized to offer objective threshold value for detecting land surface change, since that NDVI has less sensitivity for solar geometry than solar channel. The surface change detection based on long-term NDVI shows improved results than when only using Landsat.