• Korean Journal of Environment and Ecology
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• v.26 no.5
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• pp.787-800
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• 2012

The purpose of this study was to investigate the vegetation structure of Bulguksa around Buddhist Temple Forest in the Gyeongju National Park. To do so, forty-two plots($100m^2$) were set up and surveyed. The surveyed plots were divided into four groups according to the analysis of classification by TWINSPAN; (I) Pinus densiflora-Pinus koraiensis community, (II) Pinus densiflora community, (III) Pinus densiflora-Acer palmatum community, (IV) Acer palmatum-Pinus densiflora community. The results of vegetation structure analysis were; Bulguksa around Buddhist Temple Forest in the Gyeongju National Park were dominated by Pinus densiflora. IV community, influx of Acer palmatum in Pinus densiflora community, Acer palmatum-Pinus densiflora community are believed to be a change to the community. But, recent spontaneously is growing Quercus variabilis, Quercus aliena, Quercus serrata, Quercus mongolica in understory and shrub layer. Later, it is expected that Pinus densiflora competition. The forest vegetation age of the study area is Pinus densiflora were dominant trees in forest was 30~100 years, old while that of Acer palmatum was 30~36 years old.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.38-38
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• 2011

일반적으로 레일마모는 열차의 주행안전 및 승차감에 미치는 영향이 크고, 소음 진동의 주요원인으로 작용한다. 또한 레일마모가 발생할 경우 궤도구조의 파괴를 촉진시킴으로써 차량 및 궤도유지보수비를 크게 증가시킨다. 따라서 구간 특성 및 환경 영향 인자 등 현장에서 발생하는 마모 원인을 체계적으로 분석함으로써 마모를 저감할 수 있도록 차량운행 조건과 선로선형 및 궤도구조를 설계하는 것은 중요한 과제이다. CART(Classification And Regression Tree; 분류와 회귀나무) 분석은 패키지화된 좋은 분류 및 예측도구 기법으로 나무의 상위 분리수준에서 일반적으로 나타나는 가장 중요한 입력변수들을 사용하는 등의 입력변수를 선정하는 경우 매우 유용하다. 본 연구에서는 다변수 구간특성 및 환경인자를 고려한 검측 자료 상관관계 분석을 위한 회귀 나무기반 모델(TBM: Tree Based Model) 분석 수행을 위해 지하철 2호선 마모 데이터와 마모 데이터에 영향을 미치는 각종 다변수 구간특성 및 환경인자를 사용하였다. 2호선 지하철의 구간특성 인자 및 환경인자는 레일의 종류, 레일의 위치, 도상, 곡률반경, 캔트 슬랙 및 운행 일수 등으로 구분하였다. 레일의 종류는 ks-50kg과 ks-60kg 두 종류의 레일이 있으며, 레일의 위치는 지상과 지하로 크게 구분할 수 있다. 도상은 콘크리트 도상, 자갈 도상과 일부 구간의 방진상 콘크리트 도상으로 구분할 수 있으며, 곡률반경은 직선구간과 완화곡선 구간 및 최소 250m부터 627m까지 분포된 원 곡선 구간으로 구분할 수 있다. 캔트 간격은 최소 96cm 부터 120cm 간격으로 구분하며, 슬랙은 5~9cm에 분포하고, 운행 기간은 해당 기간 동안 유지보수 이력이 없는 구간을 선정하여 2005년부터 2006년까지 4번에 걸쳐 검측된 지하철 2호선 내선 마모데이터를 사용하였다. 총 X1부터 X7까지 총 7개의 구간특성 또는 환경특성을 영향인자로 선정하였으며, 이러한 영향인자에 의해 결정되는 종속 인자로 Y1인 직마모와 Y2인 측마모를 선정하여 이 중 실질적으로 지하철 궤도의 성능 평가에 주요 판단인자로 사용되는 측마모와 구간특성 및 환경영향인자와의 상관관계 분석을 수행하였다. 해당 마모 데이터가 검측되는 기간 동안 유지보수 이력이 없는 12272 point의 데이터를 검출하였고 CART 프로그램을 이용하여 데이터를 분석하였으며, CART 프로그램의 해석을 위해 종속변수인 직마모량은 각 검측 지점의 마모량에 해당하는 등급으로 변환하여 분석을 수행하였다. 레일의 마모에 영향을 미치는 구간특성 및 환경인자와 종속 변수로 사용된 레일의 마모량 사이의 CART를 이용한 상관관계 분석은 실제 구조물에서 영향인자간의 상관 관계와 유사하며, 추후 연구에서는 이를 바탕으로 하여 정량화된 검측 데이터를 종속변수로 하여 구간특성 또는 환경인자 등 외부 영향인자를 고려한 궤도 검측데이터와의 상관관계 분석을 수행할 계획이다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.3
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• pp.132-140
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• 2006

Forest vegetation classification and species composition of Mt. Ilwol, Yeongyang-Gun, Korea, were studied combining the Braun-Blanquet approach with numerical syntaxonomical analyses (TWINSPAN). Vegetation types and various ecological characteristics such as flora, constancy classes, species ratio of life-form, species diversity and importance value were analyzed. Sixty-eight samples were taken from a $100m^2$ square plot each. Forest communities were identified as two great types: arid landform of mountainside (AM) and humid fertility of piedmont and valley (HP). The former was divided into 3 communities (Rhododendron mucronulatum, Quercus variabilis, Hosta capitat community) and 2groups, and the latter into 3 communities (Tilia amurensis, Vitis coignetiae, Philadelphus schrenckii community) and 2 groups. Vegetation was classified into 8 units. Floristically, the most represented family was Compositae with 26 species. Species with percentage constance degree of more than 61% was Quercus mongolica (72.1%, IV); Carex siderosticat (III) and Fraxinus rhynchophylla (III) were 50.0 and 41.1%, respectively. Life-forms species ratios for trees, subtrees, shrub, vines, grominoids, forbs and ferns were 18.5, 5.7, 14.9, 6.6, 8.8, 42.4 and 3.1%, respectively, PH type showed from $1.70{\pm}0.50\;to\;1.97{\pm}0.57$ and AM type was from $1.40{\pm}0.18\;to\;1.62{\pm}0.20$ in species diversity; therefore, the former type showed higher species diversity than the latter, According to importance value analysis, Pinus densiflora, Quercus mongolica and Q. variabilis were higher in the tree layer, Q. mongolica in the subtree layer, Fraxinus sieboldiana, R. schlippenbachii, etc. in the shrub layer and Carex siderosticta, Carex humilis, etc. in the herb layer.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.379-388
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• 1999

As a first step for delineating the provenance regions of the forest trees in Korea, horizontal zones have been deduced primarily from the various climatic factors such as annual mean temperature, extremely low temperature, relative humidity, annual gum of possible growing days, duration of sunshine and dry index. The basic concept to the delineation of the provenance regions was based on the ecological regions, which was likely to be more practical than that on the basis of the typical provenance regions at the species level. Primary classification of the regions has been based on the forest zones(sub-tropical, warm-temperate, mid-temperate and cool-temperate) as a broad geographic region. Further classification has been carried out using cluster analyses among the basic regions within forest zone. On the basis of clustering, a total of 19 regions including 3 from sub-tropical, 6 from warm-temperate, 8 from mid-temperate and 2 from cool-temperate was horizontally delineated. Of the mean values of 6 climate factors at the broad geographic region level, three factors such as annual mean temperature, extremely low temperature, annual growing days showed directional tendencies from subtropical to cool-temperate, while the others didn't. The values of relative humidity, duration of sunshine and dry index varied among the provenance regions within forest zone. These three factors might he more sensitive by the micro-environment condition than by the macro-environment condition. Present study aimed to delineate the primary provenance regions for tentative application to forest practices. These will be stepwise revised through the supplement using accumulated information regard to genecological data.

• Korean Journal of Environment and Ecology
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• v.25 no.4
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• pp.581-589
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• 2011

The purpose of this study is to investigate the structure of vegetation dominated by deciduous broad-leaved trees at the Beomeosa(Temple) Valley of Mt. Kumjungsan in Busan. To this end, 28 plots were set up and surveyed. The result analyzed by TWINSPAN, one of the classification technique, showed that the communities were divided into six groups which are Carpinus tschonoskii-Deciduous broad-leaved forest community(I), Quercus serrata-C. tschonoskii community(II), C. tschonoskii-Q.s serrata-Pinus densiflora community(III), C. tschonoskii-Quercus serrata-Q. mongolica communtiy(IV), Q. serrata-Deciduous broadleaved forest community(V) and Chamaecyparis obtusa-C. tschonoskii community (VI). Species diversity ranged from 0.3832 to 0.0450. The lowest diversity was Chamaecyparis obtusa community(VI) but the highest was Carpinus tschonoskii-Deciduous broad-leaved forest community(I) and Q. serrata-Deciduous broadleaved forest community(V). The average number of species was 6.8${\pm}$3.2 in the unit area(100$m^2$). Carpinus tschonoskii community at the Beomeosa Valley of Mt. Geumjeongsan was a climatic climax forest having a value to preserve, so a continuous management will be needed.

• The Plant Pathology Journal
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• v.34 no.1
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• pp.23-34
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• 2018

The Ralstonia solanacearum species complex (RSSC) can be divided into four phylotypes, and includes phenotypically diverse bacterial strains that cause bacterial wilt on various host plants. This study used 93 RSSC isolates responsible for potato bacterial wilt in Korea, and investigated their phylogenetic relatedness based on the analysis of phylotype, biovar, and host range. Of the 93 isolates, twenty-two were identified as biovar 2, eight as biovar 3, and sixty-three as biovar 4. Applied to the phylotype scheme, biovar 3 and 4 isolates belonged to phylotype I, and biovar 2 isolates belonged to phylotype IV. This classification was consistent with phylogenetic trees based on 16S rRNA and egl gene sequences, in which biovar 3 and 4 isolates clustered to phylotype I, and biovar 2 isolates clustered to phylotype IV. Korean biovar 2 isolates were distinct from biovar 3 and 4 isolates pathologically as well as genetically - all biovar 2 isolates were nonpathogenic to peppers. Additionally, in host-determining assays, we found uncommon strains among biovar 2 of phylotype IV, which were the tomato-nonpathogenic strains. Since tomatoes are known to be highly susceptible to RSSC, to the best of our knowledge this is the first report of tomato-nonpathogenic potato strains. These results imply the potential prevalence of greater RSSC diversity in terms of host range than would be predicted based on phylogenetic analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.386-390
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• 2003

Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields. Classifying a group into subgroups is one of the most important subjects in data mining. Tree-based methods, known as decision trees, provide an efficient way to finding the classification model. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variable should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present some methods for measuring the node impurity, which are applicable to data sets with multivariate target variables. For illustration, a numerical cxample is given with discussion.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.53-63
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• 2008

It is commonly believed that disease of human or economic traits of livestock are caused not by single gene acting alone, but by multiple genes interacting with one an-other. This issue is difficult due to the limitations of parametric statistical method like as logistic regression for detection of gene effects that are dependent solely on interactions with other genes and with environmental exposures. Multifactor dimensionality reduction (MDR) nonparametric statistical method, to improve the identification of single nucleotide polymorphism (SNP) associated with the Hanwoo(Korean cattle) carcass cold weight, is applied and compared with ANOVA results.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1607-1611
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• 2009

본 연구에서는 현재 가뭄을 관측하는데 주로 이용되는 가뭄지수의 단점 등을 보완하고자 가뭄에 관련되는 식생지수를 연계한 공간해상도 높은 가뭄지수를 제시하였다. 우리나라 지상관측을 통해 산출할 수 있는 PDSI(Palmer Drought Severity Index)와 SPI(Standardized Precipitation Index) 같은 가뭄지수는 기온과 강수량 등의 기후자료만을 이용하여 산정할 수 있다. 두 가뭄지수는 관측하기 어려운 가뭄의 시기와 심도를 설명하고자 여러 연구를 통해 개발한 지수이지만, 두 가뭄지수만을 가지고 우리나라 전역의 가뭄의 공간적인 분포를 설명하기에는 다소 무리가 있다. PDSI의 경우 강수량과 기온과 토양의 수분함유량을 가지고 산출하는데, 전 관측지점을 똑같은 토양수분함유량을 가지고 있다는 가정 하에 계산되고, SPI의 경우 강수량만을 이용하여 산정한다. PDSI의 경우 과거의 가뭄의 정도를 판단하는데 매우유용하다고 알려져 있다. 하지만, 현재의 가뭄정도를 나타내는 데는 문제를 가지고 있고, SPI의 경우는 누적강수량을 가지고 시간단위로 계산한다는 점에서 다양한 가뭄의 정도를 예측할 수 있지만, 입력 자료로 강수량만 들어간다는 점에서 약점을 가진다. 이런 기후지수만을 이용한 가뭄정보 생산이 공간정보를 구현하는데 한계를 가지는 문제점을 개선하고자 가뭄에 직간접적으로 관련이 있는 보다 세밀한 공간정보를 가진 식생, 토지이용, 고도 등의 자료와 기후정보로부터 산정된 가뭄지수간의 관계를 분석하였다. 나아가 기존의 기후지수보다 고해상도를 가진 위성의 정규식생지수(NDVI; Normalized Difference Vegetation Index)와 같은 식생지수를 이용하여 기존보다 더 향상된 해상도의 가뭄지수를 산정하고자 하였다. 우리나라 지상관측소 76개 지점 중에 MODIS(Moderate Resolution Imaging Spectroradiometer) 정규식생지수 자료와의 관계를 분석하고자 자료의 보유기간이 짧은 지점과 섬지점 등을 제외한 57개 지점을 선정하고, 연구기간동안의 강수량과 기온자료를 이용하여 PDSI와 SPI를 산출하였다. PDSI와 SPI자료를 고해상도 가뭄지수 산정의 기본 변수로 사용하기 위하여 역거리가중평균법을 이용한 연구기간동안의 한반도 지역 PDSI와 SPI 가뭄지수 지도를 생산하였다. 각각의 가뭄지수와 식생 상태를 나타내는 NDVI와의 상관특성과 계절 변화에 따른 변화특성을 분석하고, CART(Classification and Regression Trees) 알고리즘을 이용하여, 지상 자료만을 사용한 가뭄지수가 가지는 시공간적 변화 특성 제시에 대한 문제점을 개선한 보다 해상도가 높은 조합가뭄지수를 제시하였다.