• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.347-356
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• 2009

This paper is described clustering analysis of traffic characteristics-based highway classification in order to deviate from methodologies of existing highway functional classification. This research focuses on comparing the clustering techniques performance based on the total within-group errors and deriving the optimal number of cluster. This research analyzed statistical clustering method (Hierarchical Ward's minimum-variance method, Nonhierarchical K-means method) and Kohonen self-organizing maps clustering method for highway characteristic classification. The outcomes of cluster techniques compared for the number of samples and traffic characteristics from subsets derived by the optimal number of cluster. As a comprehensive result, the k-means method is superior result to other methods less than 12. For a cluster of more than 20, Kohonen self-organizing maps is the best result in the cluster method. The main contribution of this research is expected to use important the basic road attribution information that produced the highway characteristic classification.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.167-179
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• 2005

In hierarchical Mobile IPv4 Networks the highest FA(Foreign Agent) may experience serious congestion and delay since the highest FA plays a role of CoA(Care of Address) for all mobile nodes in the domain, In this paper, we propose mechanism called 'HRFA(Hierarchical Root Foreign Agent)', which distributes the load imposed on the highest FA. In the proposed HRFA scheme, multiple HRFAs are selected to provide the similar service that is provided by the highest FA. According to which entity determines HRFAs, HRFA scheme is categorized into 'Active' and 'Passive' approaches. HRFA scheme is further categorized into 'All MN(Mobile Node)s' and 'New MNs' approaches, depending on which mobile nodes are assigned to a newly elected HRFA. Through a course of simulations, we investigate the performance of 4 possible combinations of HRFA schemes. We also compare the performance of the proposed HRFA schemes with the LMSP(Local Multicast Service Provider) scheme, which is a scheme to distribute the load of FA for multicast service in hierarchical wireless network domain. The simulation results show that the Passive & New MN approach performs best with respect to both the overhead and the load balancing.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.113-120
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• 2024

With the advancement of information and communication technology, we can easily generate various forms of data in our daily lives. To efficiently manage such a large amount of data, systematic classification into categories is essential. For effective search and navigation, data is organized into a tree-like hierarchical structure known as a category tree, which is commonly seen in news websites and Wikipedia. As a result, various techniques have been proposed to classify large volumes of documents into the terminal nodes of category trees. However, document classification methods using category trees face a problem: as the height of the tree increases, the number of terminal nodes multiplies exponentially, which increases the probability of misclassification and ultimately leads to a reduction in classification accuracy. Therefore, in this paper, we propose a new node expansion-based classification algorithm that satisfies the classification accuracy required by the application, while enabling detailed categorization. The proposed method uses a greedy approach to prioritize the expansion of nodes with high classification accuracy, thereby maximizing the overall classification accuracy of the category tree. Experimental results on real data show that the proposed technique provides improved performance over naive methods.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.83-87
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• 1997

한국어는 실질형태소와 형식형태소가 결합되는 교착어라는 특성 때문에 품사 모호성을 비롯한 여러 가지 유형의 형태론적 모호성이 발생한다. 형태론적 모호성 해결의 관점에서 형태론적 모호성을 한국어의 특성에 따라 어근 유형 모호성, 형태소 분리 모호성, 형태소 길이 모호성, 불규칙 용언의 원형 복원 모호성, '아/에/이' 탈락 모호성 등으로 분류한다. 이 때 임의의 두 분석 결과에서 발생하는 모호성이 특정 유형에만 속하도록 모호성 유형들을 서로 독립적으로 정의한다. 또한 품사 모호성을 계층적 품사 분류 체계에 따라 $1{\sim}3$차적 품사 모호성으로 구분하고 국어사전에서 발견되는 품사 모호성을 분석한다. 이를 기반으로 형태론적 모호성의 유형을 단어 내에서 해결 가능한 것과 그렇지 않은 것으로 구분하여, 단어 내에서 해결 가능한 모호성을 해결하는 방법을 제안한다.

• Journal of Korea Game Society
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• v.4 no.3
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• pp.55-64
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• 2004

A dynamic graph is suitable for representing and managing dynamic changable obstacles or terrain information in 2D/3D games such as RPG and Strategy Simulation Games. We propose a dynamic hierarchical graph model with fixed level to perform a quick A* path finding. We divide a graph into subgraphs by using space classification and space model, and construct a hierarchical graph. And then we perform a quick path fading on the graph by using our dynamic graph operators. With our experiments we show that this graph model has efficient properties for finding path in a dynamic game environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.100-105
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• 2009

In this paper, we Propose a browsing system to reduce the contents retrieval time in the personalized broadcasting system. For this purpose, we add a subgenre table between Classification DS and Summarization DS of MPEG-7 MDS. The subgenre includes a subgenre list to shorten the searching time of contents which we want to find. In addition we divide metadata into event and object using Summarization DS of the MPEG-7 MDS. In this way, the hierarchical browsing of broadcasting contents is made possible. This structure may reduce the complexity of search by storing event and object separately. Our simulation results show that the search time of the proposed system is shorter than that of the previous works.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.534-536
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• 2000

EJB의 애플리케이션 개발환경은 객체지향 분산처리를 지원하는 컴포넌트를 개발하고 분산 배치를 위한 컴포넌트 구조이다. EJB를 이용하여 개발한 애플리케이션은 컴포넌트 모델의 개념을 결합하여 비즈니스 프로그램의 개발이 쉽도록 단순화시켰으며, 보안성, 리소스 풀링, 영구성, 동시성, 트랜잭션 무결성을 자동적으로 해결해 준다. 본 논문에서는 이러한 개발환경에서 EJB 컴포넌트가 충분한 유연성을 가질 수 있도록 기능별로 효율적인 빈의 유형을 추출하는 방법을 찾고자 하였으며, EJB 빈의 유형별 특성에 따라서 빈 유형을 쉽게 분류할 수 있는 방법을 표준화하여 시스템 분석 및 설계시 반영할 수 있도록 하였다. 본 논문의 제안모델은 단계별로 전 단계의 모델을 재사용하고, 객체를 쉽게 빈으로 매핑할 수 있도록 표현계층, 비즈니스 로직계층, 데이터계층으로 계층화하여 객체를 배치함으로써 빈의 유형을 쉽게 추출할 수 있는 방법을 제공한다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.13-15
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• 2002

오늘날 소프트웨어는 개발 방법론을 이용하여 양적으로나 질적으로 많은 발전이 이루어졌다. 이와 더불어 소프트웨어에 대한 소비자들의 요구와 지식 수준 또한 같이 높아짐으로써 소프트웨어 인증에 대한 관심과 인식도 같이 높아지고 있는 추세이다. 본 논문에서는 소프트웨어 품질 인증을 위한 메타 모델의 필요성을 알아보고 기존 연구[1]되었던 메타 모델의 개념 수준을 더욱 발전시켰다. 그리고 간단하지만 실질적인 예제를 통해서 메타 모델과 인증 모델, 인증 프로그램과의 관계를 명확하게 정립하고자 한다.

• Proceedings of the Korea Multimedia Society Conference
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• 2004.05a
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• pp.247-250
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• 2004

본 논문에서는 간단한 사각형 특징과 계층적 분류기를 이용하여 실시간으로 얼굴을 검출하는 방법을 제안하고자 한다. 우리는 다섯 가지 형태의 기본적인 특징 모델을 바탕으로 20*20 크기의 훈련 영상에 적용하여 많은 초기 특징 집합을 구성하였다. AdaBoost(Adaptive Boosting) 알고리즘을 이용한 학습을 통하여 초기 특징 집합 중에서 얼굴 검출하는데 강인한 집합들만을 선택하였다. 제안된 알고리즘을 이용한 실제 실험에서 90% 이상의 높은 검출율을 확인하였고 초당 10프레임의 실시간 검출에도 성공하였다.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.10-18
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• 2010

Due to a large number of classes in Hangul character recognition, it is usual to use the six-type preclassification stage. After the preclassification, the first consonent, vowel, and last consonent can be classified separately. Though each of three components has a few of classes, classification errors occurs often due to shape similarity such as 'ㅔ' and 'ㅖ'. So this paper proposes a hierarchical recognition method which adopts multi-stage tree structures for each of 6-types. In addition, to reduce the interference among three components, the method uses the recognition results of first consonents and vowel as features of vowel classifier. The recognition accuracy for the test set of PHD08 database was 98.96%.