• ETRI Journal
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• 제29권4호
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• pp.507-515
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• 2007

Skeleton transform of which the medial axis transform is the most popular has been proposed as a useful shape abstraction tool for the representation and modeling of human posture. This paper explains this proposition with a description of the areas in which skeletons could serve to enable the representation of shapes. We present algorithms for two-dimensional posture modeling using the developed simplified shock graph (SSG). The efficacy of SSG extracted feature vectors as shape descriptors are also evaluated using three different classifiers, namely, decision tree, multilayer perceptron, and support vector machine. The paper concludes with a discussion of the issues involved in using shock graphs to model and classify human postures.

• 한국전자파학회논문지
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• 제18권1호
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• pp.96-104
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• 2007

현재 국제적으로 수풀 손실 예측 모델이나 측정 데이터가 매우 부족하다. 본 논문에서는 2005년과 2006년, 2년에 걸쳐 $1{\sim}6\;GHz$ 대역 국내 수풀 및 가로 환경에 많이 분포하는 소나무(pine tree), 히말라야시다(hymalaya cedar),플라타너스나무(plane tree), 메타나무(dawn-redwood tree)등의 수풀에 대한 수풀 손실 특성 측정 수행 결과로부터, ITU-R P.833에서 제시하고 있는 RET(radiative energy transfer) 모델 파라미터를 도출하였으며, 모델 보정을 시도하였다. 본 연구 결과는 2005년, 2006년 ITU-R SG WP 3J 회의에서 권고서에 반영되었다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.463-467
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• 2006

Several segmentation algorithms have been proposed for DTM generation or building modeling from airborne LiDAR data. Three components are important for accurate segmentation: (i) the adjacent relationship of n-nearest points or mesh, etc. (ii) the effective decision parameters of height, slope, curvature, and plane condition, (iii) grouping methods. In this paper, we created the topology of point cloud data using the contour tree and implemented the region-growing Terrain and non-terrain points were classified correctly in the segmented data, which can be used also for feature classification.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.885-894
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• 2001

Decision tree methods is the one of data mining techniques. Classification trees are used to predict a class label. When a tree grows, the conventional splitting criteria use the weighted average of the left and the right child nodes for measuring the node impurity. In this paper, new splitting criteria for classification trees are proposed which improve the interpretablity of trees comparing to the conventional methods. The criteria search only for interesting subsets of the data, as opposed to modeling all of the data equally well. As a result, the tree is very unbalanced but extremely interpretable.

• ETRI Journal
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• 제29권4호
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• pp.527-529
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• 2007

In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

• 정보처리학회논문지D
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• 제15D권5호
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• pp.647-658
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• 2008

자연어로 작성된 고객의 요구사항은 개발과정에서 모델링 언어로 재작성 된다. 그러나 개발에 참여하는 다양한 계층의 사람들은 모델링 언어로 작성된 요구사항을 이해하지 못하는 경우가 많이 발생한다. 본 논문에서는 REED(REquirement EDitor)로 작성된 요구사항 모델을 자연어로 번역하여 개발에 참여하는 모든 계층의 사람들이 요구사항 모델을 이해할 수 있도록 도와주는 방안을 제시한다. 제시한 방법은 3단계로 구성되어 있다. 1단계 IORT(Input-Output Relation Tree) 생성, 2단계 RTT(Requirement Translation Tree) 생성, 3단계 자연어로 번역의 단계를 거친다.

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.141-146
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• 2024

Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

• 한국조경학회지
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• 제27권4호
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• pp.143-150
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• 1999

The purpose of this research is to find som ways to model tree forms more efficiently in reference with surveying structural data and handling parameters in plant Editor of AccuRender, the AutoCAD-based rendering software adopting the procedural plant modeling technique. In case of modelling a new tree, because it is efficient to modify an existing tree data as a template, we attempted to classify 81 species' data from existing plant library including conifers and deciduous tree. According to the qualitative characteristics and quantitative parameters of geometrical and branching structure, 8 types of tree form were classified with factor and cluster analysis. Some critical aspects found in the distributions of standardized scores of parameters in each type were discussed for explaining the tree forms intuitively. For adaptability of the resulted classification and typical parameters, 10 species of tree were measured and modelled, and proved to be very similar to the real structures of tree forms. CG or CAD-based plant modelling technique would be recommended not only as a presentation tool but for planting design, landscape simulation and assessment.

• Journal of the Korean Data and Information Science Society
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• 제20권1호
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• pp.179-190
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• 2009

금융 산업에서, 의사결정나무 분석은 분류분석을 위해서 널리 사용되는 분석기법이다. 그러나 금융 산업에서 실제로 의사결정나무 분석을 적용할 때, 발생하는 문제점 중 하나는 설명변수의 수가 너무 많다는 점이다. 따라서 모형의 결과에 별 영향을 미치지 않으면서 설명변수의 수를 줄이는 효과적인 방법을 연구할 필요가 있다. 본 연구에서는 의사결정 나무 분석에서 모형의 정확성에 근거한 최선의 변수 선택 방법을 구하기 위하여 다양한 변수 선택방법들을 비교 분석 하였다. 이를 위하여 본 연구에서는 한 보험회사의 연금 보험 상품 자료에 다양한 설명변수 축소방법을 적용하여, 가장 적은 수의 설명변수를 가지고 가장 높은 정확도를 제공하여 주는 설명변수 축소방법을 구하는 실증적인 연구를 시행하였다. 이러한 실험결과, 신경망의 민감도 분석을 이용하여 변수를 축소하고, 그 축소된 변수를 이용하여 의사결정나무 분석 모델을 생성하는 경우가 가장 효율적인 설명변수 축소방법임을 알 수 있었다.

• 대한음성학회지:말소리
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• 제59호
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• pp.53-68
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• 2006

We report the evaluation results of the Korean speech recognition platform called ECHOS. The platform has an object-oriented and reusable architecture so that researchers can easily evaluate their own algorithms. The platform has all intrinsic modules to build a large vocabulary speech recognizer: Noise reduction, end-point detection, feature extraction, hidden Markov model (HMM)-based acoustic modeling, cross-word modeling, n-gram language modeling, n-best search, word graph generation, and Korean-specific language processing. The platform supports both lexical search trees and finite-state networks. It performs word-dependent n-best search with bigram in the forward search stage, and rescores the lattice with trigram in the backward stage. In an 8000-word continuous speech recognition task, the platform with a lexical tree increases 40% of word errors but decreases 50% of recognition time compared to the HTK platform with flat lexicon. ECHOS reduces 40% of recognition errors through incorporation of cross-word modeling. With the number of Gaussian mixtures increasing to 16, it yields word accuracy comparable to the previous lexical tree-based platform, Julius.