• 대한원격탐사학회지
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• 제17권1호
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• pp.57-69
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• 2001

본 연구는 무감독 영상분류를 위하여 공간지역 확장을 통하여 영상을 분할한 후 분할된 집단을 한정된 수의 클래스로 분류하는 다중단계 기법을 제안하고 있다. 제안된 알고리듬은 무감독 분석을 위하여 작은 집단들을 단계적으로 큰 집단들로 합병해 가는 계층집단연결 기법에 기반을 두고 있다. 다중단계 기법의 영상분할 단계는 공간적으로 근접하고 있는 이웃지역간의 결합을 통하여 최종적으로 전체영상 공간내의 모든 집단에 대해서 서로 이웃하고 있는 집단들의 물리적 특성이 서로 다르도록 영상을 분할하는 과정이고, 영상분류 단계는 결합 지역의 공간적 제약 없이 영상 분할 단계에서 분할된 지역을 상대적으로 적은 수의 클래스로 분류하는 과정이다. 제안 된 알고리듬에서 사용하고 있는 계층집단연결 기법의 계산/기억 상의 복잡성을 완화시키기 위해 상호최근사 이웃쌍과 다중창 작업을 사용하고 있다. 모의 자료를 사용하여 제단 된 알고리듬 대한 평가와 효율성을 검증하였고 경기도 용인.능평지역의 LANDSAT ETM+ 자료에 적용한 결과를 예시하고 있다.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.292-292
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• 2022

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제2권2호
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• pp.120-128
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• 2021

The objective of this study was to analyze the genotype of black-spotted pond frog (Pelophylax nigromaculatus) using seven microsatellite loci to quantify its genetic diversity and population structure throughout the spatial scale of basins of Han, Geum, Yeongsan, and Nakdong Rivers in South Korea. Genetic diversities in these four areas were compared using diversity index and inbreeding coefficient obtained from the number and frequency of alleles as well as heterozygosity. Additionally, the population structure was confirmed with population differentiation, Nei's genetic distance, multivariate analysis, and Bayesian clustering analysis. Interestingly, a negative genetic diversity pattern was observed in the Han River basin, indicating possible recent habitat disturbances or population declines. In contrast, a positive genetic diversity pattern was found for the population in the Nakdong River basin that had remained the most stable. Results of population structure suggested that populations of black-spotted pond frogs distributed in these four river basins were genetically independent. In particular, the population of the Nakdong River basin had the greatest genetic distance, indicating that it might have originated from an independent population. These results support the use of genetics in addition to designations strictly based on geographic stream areas to define the spatial scale of populations for management and conservation practices.

• Asian Pacific Journal of Cancer Prevention
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• 제16권9호
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• pp.4025-4029
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• 2015

Background: Gastrointestinal tract cancers are among the most common cancers in Iran and comprise approximately 38% of all the reported cases of cancer. This study aimed to describe the epidemiology and to investigate spatial clustering of common cancers of the gastrointestinal tract across the counties of Iran using full Bayesian smoothing and Moran I Index statistics. Materials and Methods: The data of the national registry cancer were used in this study. Besides, indirect standardized rates were calculated for 371 counties of Iranand smoothed using Winbug 1.4 software with a full Bayesian method. Global Moran I and local Moran I were also used to investigate clustering. Results: According to the results, 75,644 new cases of cancer were nationally registered in Iran among which 18,019 cases (23.8%) were esophagus, gastric, colorectal, and liver cancers. The results of Global Moran's I test were 0.60 (P=0.001), 0.47 (P=0.001), 0.29 (P=0.001), and 0.40 (P=0.001) for esophagus, gastric, colorectal, and liver cancers, respectively. This shows clustering of the four studied cancers in Iran at the national level. Conclusions: High level clustering of the cases was seen in northern, northwestern, western, and northeastern areas for esophagus, gastric, and colorectal cancers. Considering liver cancer, high clustering was observed in some counties in central, northeastern, and southern areas.

• 대한공간정보학회지
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• 제24권2호
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• pp.63-70
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• 2016

A housing market in an urban area is not just a single market but a combination of regionally different submarkets. This study begins with a critical mind that previous researches did not consider the spatial autocorrelation of each area where the housings are located. The clustering analysis of housing submarket which considers spatial autocorrelation is performed as it follows. First, 4 housing market attribute variables are reducted to 1 variable by principle component analysis. Then, after calculating $Gi^*max$ by AMOEBA, 7 housing submarkets which have similar characteristics based on $Gi^*max$ are classified. The characteristics of each submarket are investigated, then political implication is deduced as the following. Different level of housing policy should be made to each cluster because each cluster has different level of spatial autocorrelation.

• KEPCO Journal on Electric Power and Energy
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• 제2권1호
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2022년도 춘계학술대회
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• pp.277-279
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• 2022

Rapid Development and adoption of AIS as a survailance tool has resulted in widespread application of data analysis technology, in addition to AIS ship trajectory clustering. AIS data-based clustering has become an increasingly popular method for marine traffic pattern recognition, ship route prediction and anomaly detection in recent year. In this paper we propose a route waypoint extraction by clustering ships CoG variance trajectory using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm in both port approach channel and coastal waters. The algorithm discovers route waypoint effectively. The result of the study could be used in traffic route extraction, and more-so develop a maritime anomaly detection tool.

• 환경영향평가
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• 제22권5호
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• pp.513-523
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• 2013

This purpose of this work is to explore the characteristics of urban thermal environment distribution with the case of Daejeon. To do that, this work applied GIS Spatial Statistics to the LandSAT images gathered from 2000 to 2011. The urban thermal environment distribution at the time point of 2 showed high spatial autocorrelation. Therefore, it is judged that spatial autocorrelation is needed to increase the reliability and explanatory power of the characteristics of thermal environment distribution. In the case of the thermal in Daejeon, its positive clustering appeared high at the time point of 2, and its clustering in 2011 more gradually decreased than that in 2000 to 2011. In particular, given the decrease in the core H-H region, it was found that the thermal environment of Daejeon was greatly improved. However, since the rise in the region L-L means another changed like construction of a new city, it is judged that it is necessary to come up with a proper plan. It is considered that this analysis of the characteristics of urban thermal environment distribution in consideration of spatial autocorrelation L-L be useful for providing a fundamental material necessary for the policy and project of thermal environment improvement.

• Journal of the Korean Data Analysis Society
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• 제20권6호
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• pp.2917-2932
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• 2018

우리나라 식생활에 밀접한 관련을 가지고 있는 채소인 양파의 수급불균형 해결을 위한 생산량 예측 모형 개발의 노력이 많은 연구를 통해 이뤄지고 있다. 하지만 양파의 수확기와 저장 가능성을 고려해 봤을 때 생산량 예측만으로는 수급불균형 해결이 어렵다. 따라서 본 논문에서는 양파의 생산량 정보와 가격의 다양한 요인이 포함되어 있으며 일상에서 쉽게 접할 수 있는 인터넷 기사를 이용하여 가격 예측을 위한 감성사전을 구축하고자 한다. 양파 기사는 2012년부터 2016년까지의 데이터를 사용하였고 도매시장 가격을 통한 문서구분을 통해 4가지 TF-IDF를 비교하여 적합한 TF-IDF를 사용하였다. 분석을 위하여 분할적 군집분석 중 k-means 군집, 밀도기반군집(DBSCAN; density based spatial cluster applications with noise), 가우시안혼합분포군집(GMM; Gaussian mixture model) 군집을 통하여 가격에 대한 긍정/부정 단어를 구분한 결과 GMM 군집이 의미 있는 긍정, 부정, 무정의 3개의 사전으로 구성되었다. 구축된 사전의 합리성을 비교하기 위하여 가격 상승 기사와 가격 하락 기사의 분류에 로지스틱 회귀분석을 적용한 결과 85.7%의 정확도로 구축된 사전의 합리성을 확인할 수 있었다.

• Spatial Information Research
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• 제11권3호
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• pp.203-212
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• 2003

본 연구에서는 지반공간의 이해를 증진시키기 위하여 지반조사 자료를 통합하기에 용이한 3차원 GIS를 기반으로 하는 접근을 제안하고, 무안의 주거지 밀집지역에서 발생한 지반침하 지역에 대한 연구를 수행하였다. 본 연구대상 지역은 석회암을 기반암으로 하는 지역이므로 기반암종의 지질적인 구성이 침하발생에 중요한 인자가 된다. 석회암은 지하수로 인해 용식되어 공동을 생성하기 때문에 지하수의 통로가 되는 절리나 파쇄대의 파악이 중요하다. 따라서 유사한 기반암 구성별로 군집화하여 지반을 분류하였으며, 효과적인 지반정보 분석을 위하여 3차원 GIS를 통해 시추공 정보를 가시화하고 통합 분석하였다. 이에 따라 지반정보의 왜곡이 감소되어 지반공간에 대한 효율적인 분석이 가능하게 하였다.