• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.34.1-34.1
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• 2013

Interstellar ices (e.g., $H_2O$, $CO_2$, and CO ices) are formed on the surface of dust grains in dense molecular clouds. In a near-infrared spectrum, we can observe deep absorption features particularly due to $H_2O$ ice at $3.05{\mu}m$ and $CO_2$ ice at $4.27{\mu}m$. These interstellar ices have many pieces of information on the interstellar environment. Among various ices, $CO_2$ ice is one of the most important ones as a probe of the interstellar environment. That is because $CO_2$ ice is a secondary product unlike $H_2O$ and CO ices which are primarily formed on dust grains. Past studies for $CO_2$ ice in nearby galaxies were performed only for the galactic center in a few galaxies. In order to utilize the information from $CO_2$ ice effectively, it is valuable to perform mapping observations of ices on a galactic scale. With AKARI, we obtain the spatially-resolved near-infrared ($2.5-5.0{\mu}m$) spectra for the central ~1 kpc region of the nearby starburst galaxy M 82. These spectra clearly show the absorption features due to interstellar $H_2O$ and $CO_2$ ices, and we created their column density maps. As a result, we find that the spatial distribution of $H_2O$ ice is significantly different from that of $CO_2$ ice; $H_2O$ ice is widely distributed, while $CO_2$ ice is concentrated near the galactic center. Our result for the first time reveals spatial variations in $CO_2/H_2O$ ice abundance ratio on a galactic scale, suggesting that the ice-forming interstellar environment changes within a galaxy. In this presentation, we discuss the cause of the variations in the ice abundance ratio.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.513-521
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• 2015

In the processing of ocean color remote sensing data, spatio-temporal binning is crucial for securing effective observation area. The validity determination for given source data refers to the information in Level-2 flag. For minimizing the stray light contamination, NASA OBPG's standard algorithm suggests the use of large filtering window but it results in the loss of effective observation area. This study is aimed for quality improvement of ocean color remote sensing data by recovering/extending the portion of effective observation area. We analyzed the difference between MODIS/Aqua standard and modified product in terms of chlorophyll-a concentration, spatial and temporal coverage. The recovery fractions in Level-2 swath product, Level-3 daily composite product, 8-day composite product, and monthly composite product were $13.2({\pm}5.2)%$, $30.8({\pm}16.3)%$, $15.8({\pm}9.2)%$, and $6.0({\pm}5.6)%$, respectively. The mean difference between chlorophyll-a concentrations of two products was only 0.012%, which is smaller than the nominal precision of the geophysical parameter estimation. Increase in areal coverage also results in the increase in temporal density of multi-temporal dataset, and this processing gain was most effective in 8-day composite data. The proposed method can contribute for the quality enhancement of ocean color remote sensing data by improving not only the data productivity but also statistical stability from increased number of samples.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.2
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• pp.63-70
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• 2008

This paper resents the spatial electric load forecasting algorithm using the multiple regression analysis method which is enhanced from the algorithm of the DISPLAN(Distribution Information System PLAN). In order to improve the accuracy of the spatial electrical load forecasting, input variables are selected for GRDP(Gross Regional Domestic Product), the local population and the electrical load sales of the past year. Tests are performed to analyze the accuracy of the proposed method for Gyeong-San City, Gu-Mi City, Gim-Cheon City and Yeong-Ju City of North Gyeongsang Province. Test results show that the overall accuracy of the proposed method is improved the percentage error 11.2[%] over 12[%] of the DISPLAN. Specially, the accuracy is enhanced a lot in the case of high variability of input variables. The proposed method will be used to forecast local electric loads for the optimal investment of distribution systems.

• Journal of the Korean Geographical Society
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• v.39 no.3
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• pp.360-373
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• 2004

The purpose of this study is establishing how to build the area of local agents and regional offices in the oil company using GIS technique by reviewing on the spatial distribution pattern and characteristics of the sales area of oil products. Location-allocation and spatial interaction model are cooperated in order to establish sales area of petroleum products distribution system. Location-allocation model is used in the capital region where local agents are concentrated on like Kyoung-gi local agent. Spatial interaction model is used in the rest of the area in Korea to analyze the sales range of the regional offices in oil company. Each office made a big difference in registered cars and population because of the level of petroleum consumption in each sales area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.855-868
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• 1996

In this paper, multiplhase only filter(MPOFs) are designed using simulated annealing algorithm. These filters have excellent recognition characteristics for similar patterns or rotated patterns and enhance optical efficiency as well as spatial-bandwidth product by deleting mirror image. As the result of computer simulation to certify recogntion characteristics of similar patterns, simulated annealing-MPOF(SA-MPOF) has superior discrimination and higher correlation peak values than cosine binary phase only filters(CBPOF) and simpulated annealing-BPOF (SA-BPOF). THe filter having training process for rotated patterns of arbitraty possible angle can overcome that phase only filter(POF) and CBPOF can't recognize rotated input patterns.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.82-88
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• 2008

EPCglobal은 기업 간의 물류 활동 촉진과 글로벌 유통물류 시스템 구축을 위하여 EPCglobal Architecture Framework을 제시 하였다. EPCglobal Architecture Framework의 한 구성요소인 EPCIS(Electronic Product Code Information Services)는 EPC 기반 물류 관련 정보에 대한 저장 및 검색 서비스를 제공한다. EPCIS는 단발성 질의(poll)와 연속 질의(subscribe) 검색 서비스를 제공한다. EPCIS의 연속 질의는 시스템 자동화 및 재고 관리, 공급망 관리를 위해 다양한 응용에서 활용이 가능하다. 일반적으로 연속 질의의 성능을 향상시키기 위해서는 질의 색인을 사용한다. 그러나 EPCIS는 13차원의 도메인과 모든 데이터 필드가 필수 조건이 아니라는 것으로 인해, 차원의 저주 및 무한 영역 질의 문제를 발생 시킨다. 본 논문에서는 EPCIS의 물류 데이터의 연속 질의 처리를 위한 다차원 색인 기법을 제안한다. 13차원의 도메인을 여러 개의 질의 색인으로 구성하고, 등록된 질의 및 입력되는 데이터에 의해 변경되는 동적 질의 실행 계획을 제안함으로써, 차원의 저주와 무한 영역 질의의 문제를 해결하고, EPCIS에서 다수의 연속 질의 등록 시 효율적으로 처리가 가능하도록 한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.2
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• pp.39-52
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• 2020

A high quality, long-term, high-resolution precipitation dataset is an essential in climate analyses and global water cycles. Rainfall data from station observations are inadequate over many parts of the world, especially North Korea, due to non-existent observation networks, or limited reporting of gauge observations. As a result, satellite-based rainfall estimates have been used as an alternative as a supplement to station observations. The Climate Hazards Group Infrared Precipitation (CHIRP) and CHIRP combined with station observations (CHIRPS) are recently produced satellite-based rainfall products with relatively high spatial and temporal resolutions and global coverage. CHIRPS is a global precipitation product and is made available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. In this study, we analyze the applicability of CHIRPS data on the Korean Peninsula by supplementing the lack of precipitation data of North Korea. We compared the daily precipitation estimates from CHIRPS with 81 rain gauges across Korea using several statistical metrics in the long-term period of 1981-2017. To summarize the results, the CHIRPS product for the Korean Peninsula was shown an acceptable performance when it is used for hydrological applications based on monthly rainfall amounts. Overall, this study concludes that CHIRPS can be a valuable complement to gauge precipitation data for estimating precipitation and climate, hydrological application, for example, drought monitoring in this region.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.1 s.19
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• pp.83-90
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• 2002

Control point survey by GPS can save labor and time and can obtain result of high accuracy, but if excessive error is contained to Control point that is used to GPS relative positioning, the error that has influence on new point is propagated to various configuration. therefore poor triangulation points that are caused by careless management are existed, a product of the triangulation points still are in many case. In order to select new point, this study carried out error-analysis of surrounding-control-points and performed selective process of control point. The propriety parts of control points that are used to verify precision is identified by means of comparing existing product with or GPS product about some control points after directly observe each baseline by using EDM. As the error is analyzed by static positioning the optimum control point is selected, the precision of survey data by EDM is improved than GPS data.

• Journal of the Korean association of regional geographers
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• v.18 no.3
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• pp.298-309
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• 2012

This paper studies the characteristics of the network of the Zhongguancun Cluster, the most representative innovative cluster of the high-tech industry in China at present. For this study, Zhongguancun Cluster was the first high-tech cluster created in China in 1988, the current Zhongguancun Cluster plays a leading role in the development of the high-tech industry in China. In addition, the Zhongguancun Cluster has attracted global attention and helped elevate China as a key region in terms of research development in relation to the high-tech industry. With regard to the spatial characteristics of the network belonging to the companies in Zhongguancun Cluster, purchase and producer services and information and R&D network have a strong tendency to be local, while on the other hand the product sales network has a strong tendency to be non-local. It is because the political support supplied by the government, institutional base that provides high-tech companies, producer services and information regarding producer services is relatively well prepared and managed in Zhongguancun Cluster. The spatial characteristics of the R&D network have a very strong local character is due to the location of the Zhongguancun Cluster where companies, universities and research centers with outstanding research development capacity as well as various support organizations for technology innovation within the cluster are included. On the other hand, because the high-tech products produced in this area are sold all across China as well as in foreign countries, the product sales network has a strong non-local character. Strengthening the local network in terms of the main agents of the cluster is the most important aspect in order to develop a certain industrial cluster into an innovative cluster. In this respect, if the Zhongguancun Cluster is seen from the perspective of a network, it has a basic network foundation. However, to strengthen international competitiveness, not only the local network but also the international network should be strengthened.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.