• Korean Journal of Environmental Biology
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• v.17 no.3
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• pp.233-247
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• 1999

A survey of syntaxa of vegetation of evergreen broad-leaved forests in Korea, class Camellietea japonicae is presented. 399 releve's were arranged two phytosociological tables, each representing an alliance. A synoptic table comprising all alliances is presented. The vegetation of evergreen broad-leaved forests is divided into three alliances including twelve new associations: (1) Querco - Castanopsion all. nov., split into four associations, Castanopsietum sieboldii, Quercetum acutae, Quercetum myrsinaefoliae and Litseetum japonicae; (2) Machilo-Camellion all. nov., separate into ten associations, Machiletum thunbergii, Pittosporetum tobirae, Aucubetum japonicae, Neolitsetum sericeae, Euryetum emarginatae, Elaeagnetum macrophyllae, Camellietum japonicae, Theo-Camellietom japonicae, Raphiolepietum umbellatae and Daphniphylletum macropodae; (3) Dendropanaco-Castanopsion sieboldii including one association, Hosto minoris-Castanopsietum sieboldii. The alliances are floristically and ecologically characterized and their distribution in Korea shown on the map.

• Journal of the Korean earth science society
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• v.18 no.6
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• pp.515-521
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• 1997

To investigate the nature of the waste materials in the Nanjido Landfill, we have conducted multivariate statistical analysis of geophysical data set comprised of magnetic, gravity, LandSat TM thermal band and surface depression measurement data. Because these data sets show different responses to the depth, we have transformed the observed total field magnetic data and gravity data to the residual reduced-to-pole(RTP) magnetic anomalies and the three dimensional density anomalies, respectively, and utilized the informations about the upper shallow part of the landfills only in the following process. For the statistical analysis at the points of depression measurement, the magnetic, density and LandSat data values at these points are determined by interpolation process. Since the multivarite statistical analysis technique utilizes a clustering algorithm for classification of data set and we have measured the dissimilarity between objects by using Euclidean distance, standardization was applied prior to distance calculation in order to eliminate any scaling effects due to different measurement unit of each data set. The hierarchial grouping technique was used to construct the dendrogram. The optimum number of statistical groups(clusters), which are classified on the basis of geophysical and geotechnical characteristics, appeared to be six on the resulting dendrogram. The result of this study suggests that the dimension and nature of the multicomponent waste landfills can be identified by application of the multivarite statistical analysis technique to integrated geophysical data sets.

• Korean Journal of Ecology and Environment
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• v.53 no.2
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• pp.208-219
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• 2020

Forest thinning brought the large variation to forest ecosystem including environment and animal. Our study was result of long-term monitoring for ground-dwelling arthropod communities after thinning in forest ecosystem. In this study, we conducted field study on plantation forest in Chuncheon, Korea in 2018, and compared with previous study data (2006 and 2008). We found that the effect of thinning was still existent 10 years later from thinning with difference of habitat environment(depth of ground organic matter, coverage rate of ground vegetation and canopy). And ground-dwelling arthropod communities showed changes of abundance and taxa at the study area and thinning conditions. Ground-dwelling arthropod communities in 2018 were dominant in the order of Diptera, Hymenoptera, Coleoptera (Insecta), Araneae (Arachnida) and Collembola (Collembola). Among the conditions of thinning, Araneae (Arachnida), Coleoptera and Hymenoptera (Insecta) showed amount of abundance in heavy thinning. And Collembola (Collembola) and Diptera (Insecta) were most common in area of light thinning. In 2018 ground-dwelling arthropod communities, abundance of Diptera and Coleoptera (Insecta) and Isopoda (Crustacea) were decreased although Hemiptera and Orthoptera (Insecta) were increased than 2008 arthropod communities. Arthropod communities in 2018 were more similar with those in 2008 (after thinning) than with those in 2006 (before thinning).

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.355-369
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• 2005

Genome sequencing and microarray technology produce ever-increasing amounts of complex data that needs statistical analysis. Visualization is an effective analytic technique that exploits the ability of the human brain to process large amounts of data. In this study, biplot approach applied to microarray data to see the relationship between genes and samples. The supplementary data method to classify new sample to known category is suggested. The methods are validated by applying it to well known microarray data such as Golub et al.(1999), Alizadeh et al.(2000), Ross et al.(2000). The results are compared to the results of several clustering methods. Modified graph which combine partitioning method and biplot is also suggested.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.87-97
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• 2024

This study analyzed the water shortage hotspot areas in South Korea using spatial clustering analysis for water shortage estimates in 2030 of the Master Plans for National Water Management. To identify the water shortage cluster areas, we used water shortage data from the past maximum drought (about 50-year return period) and performed spatial clustering analysis using Local Moran's I and Getis-Ord Gi*. The areas subject to spatial clusters of water shortage were selected using the cluster map, and the spatial characteristics of water shortage areas were verified based on the p-value and the Moran scatter plot. The results indicated that one cluster (lower Imjin River (#1023) and neighbor) in the Han River basin and two clusters (Daejeongcheon (#2403) and neighbor, Gahwacheon (#2501) and neighbor) in the Nakdong River basin were found to be the hotspot for water shortage, whereas one cluster (lower Namhan River (#1007) and neighbor) in the Han River Basin and one cluster (Byeongseongcheon (#2006) and neighbor) in the Nakdong River basin were found to be the HL area, which means the specific area have high water shortage and neighbor have low water shortage. When analyzing spatial clustering by standard watershed unit, the entire spatial clustering area satisfied 100% of the statistical criteria leading to statistically significant results. The overall results indicated that spatial clustering analysis performed using standard watersheds can resolve the variable spatial unit problem to some extent, which results in the relatively increased accuracy of spatial analysis.

• Korean Journal of Environment and Ecology
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• v.9 no.2
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• pp.156-165
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• 1996

To investigate the forest structure and to suggest the management of vegetation landscape in Noinbong area, Pdaesan National Pa, twelve plots were set up and surveyed. According to the acalysis of classification by TWINSPAN, the community was divided by two groups of Carpinus laxiflora - Quercus mongolica community and the other is Betula costata - schmidtii - C. laxiflora community. It was found out that the successional stage of Noinbong forests was climax and introduced-climax by the analysis of species structure, similarity index and species diversity. The number of individuals was about 120~130 and species was 17 per 100m$^{2}$. Through the analysis of basal area and DBH class distribution, it was estimated that C. laxiflora, B. costata, and B. schmidtii will be clmax species instead of Q. mongolica in tree layer, and in the subtree layer, Acer pseudo-sieboldianum will be dominant species.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.525-532
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• 2021

In the ocean, it is difficult to separate the effects of one cause due to the multiple causes, but the self-organizing map can be analyzed by adding other factors to the cluster result. Therefore, in this study, the results of the clustering of sea level data were applied to sea surface temperature. Sea level data was clustered into a total of 6 nodes. The difference between sea surface temperature and sea level height has a one-month delay, which applied sea surface temperature data a month ago to the clustered results. As a result of comparing the mean of sea surface temperature of 140 to 150°E, where the sea surface temperature was variously distributed, in the case of nodes 1, 3, and 5, it was possible to find a meandering sea surface temperature distribution that is clearly distinguished from the sea level data. While nodes 2, 4 and 6, the sea surface temperature distribution was smooth. In this study, sea surface temperature data were applied to the clustered results of sea level data, but later it is necessary to apply wind or geostrophic velocity data to compare.

• Korean Journal of Environment and Ecology
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• v.14 no.1
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• pp.28-37
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• 2000

지리산국립공원의 아고산지대를 중심으로 분포하고 있는 한국특산종 구상나무의 생육현화과 구상나무림의 군집구조를 파악하여 앞으로의 구사나무림 관리의 기초자료를 마련하고자 구상나무가 생육하고 있는 지역에 42개의 방형구(20m$\times$20m)를 설치하여 식생을 조사하였다 분석한 결과 조사대상지는 세 개의 군집인 신갈나무-당단풍군집 구상나무-신갈나무군집 구상나무군집으로 분류되었다 수종간의 상관관계에서는 물들메나무와 함박꽃나무 함박꽃나무와 층층나무 구상나무와 잣나무 거제수나무와 노각나무 물들메나무와 말발도리 거제수나무와 물들메나무 거제수나무와 물갬나무 거제수나무와 함박꽃나무 철쭉과 회나무 주목과 미역줄나무 물갬나무와 노각나무, 잣나무와 마가목, 진달래와 명자순 명자순과 시닥나무, 가문비나무와 마가목 등의 수종들간에는 높은 정의 상관관계가 인정되었고 당단풍과 미역줄나무 등의 수종들간에는 높은 부의 상관관계가 인정되었다 본 조사지의 종다야도는 1.2389-1.2552으로 높게 나타났다 구상나무의 활력은 저조한 것으로 나타났으며 12.92%가 고사목이었다 생육현황표의 점수 평균은 13.88이었다.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2000.05a
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• pp.361-362
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• 2000

해양의 대형무척추동물은 어류의 먹이가 되고, 서식처나 먹이를 놓고 어류와 경쟁을 하며, 심지어 어류를 포식하는 등 어류 군집 구조에 많은 영향을 주는 생물적 요인이 된다. 새우류는 절지동물문 갑각목 십각아목에 속하는 무척추동물이며, 국내에서 이루어진 새우류 군집에 관한 연구는 광양만 잘피밭에 서식하는 새우류 군집의 종조성과 계절 변동 (Huh and An, 1997), 고리 주변 해역 새우류의 종조성과 계절 변동(Huh and An, 1999)이 있을 뿐 아직까지 우리나라 연안에서 출현하고 있는 새우류의 군집 연구가 부족한 상태이다. 본 연구에서는 가덕도 주변 해역에서 출현하는 새우류 군집의 종조성과 계절변동을 파악함으로써 상위 영양단계를 점유하고 있는 어류 군집을 연구하는데 기초 자료를 제공하고자 하였다. (중략)

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1147-1161
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• 2015

Nowadays we are considering and analyzing not only classical data expressed by points in the p-dimensional Euclidean space but also new types of data such as signals, functions, images, and shapes, etc. Symbolic data also can be considered as one of those new types of data. Symbolic data can have various formats such as intervals, histograms, lists, tables, distributions, models, and the like. Up to date, symbolic data studies have mainly focused on individual formats of symbolic data. In this study, it is extended into datasets with both histogram and multimodal-valued data and a divisive clustering method for the mixed feature-type symbolic data is introduced and it is applied to the analysis of industrial accident data.