• International Journal of Contents
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• 제4권3호
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• pp.20-28
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• 2008

To obtain realistic performance measures for wireless networks, one should consider changes in performance due to failure related behavior. In performability analysis, simultaneous consideration is given to both pure performance and performance with failure measures. SRN is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. In this paper, a new methodology to model and analyze performability based on stochastic reward nets (SRN) is presented. Composite performance and availability SRN models for wireless handoff schemes are developed and then these models are decomposed hierarchically. The SRN models can yield measures of interest such as blocking and dropping probabilities. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results show the accuracy of the hierarchical model. The key contribution of this paper constitutes the Petri nets modeling techniques instead of complicate numerical analysis of Markov chains and easy way of performance analysis for channel allocation under SRN reward concepts.

• 한국전자거래학회지
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• 제7권1호
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• pp.153-166
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• 2002

Nowadays an information exchange on Bn such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to store XML data in object-relational database that support hierarchical structure. Accordingly the modeling methodology for storing XML data in object-relational database is needed. In order to build good quality application systems, modeling is an important first step. In 1997, the OMG adopted the UML as its standard modeling language. Since industry has warmly embraced UML its popularity should become more important in the future. So a design methodology based on UML is need to develop efficiently XML applications. In this paper, we propose a unified design methodology for In applications based on object-relational database using In. To this goal, first we introduce a XML modeling methodology to design W3C XML schema using UML and second we propose data modeling methodology for object-relational database schema to store efficiently XML data in object-relational databases.

• Journal of Information Technology Applications and Management
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• 제9권1호
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• pp.85-96
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• 2002

Nowadays an information exchange on XML such as B2B electronic commerce is spreading. Therefore the systematic and stable management mechanism for storing the exchanged Information is needed. For this goal there are many research activities for connection between XML application and relational database. But because XML data have hierarchical structures and relational database can store only flat-structured data, we need to store XML data in object-oriented database that support hierarchical structure. Accordingly the modeling methodology for storing XML data in object-oriented database is needed. In order to build good quality application systems, modeling is an important first step. In 1997, the OMG adopted the UML as its standard modeling language. Since industry has warmly embraced UML, its popularity should become more important in the future. So a design methodology based on UML is need to develop efficiently XML applications. In this paper, we propose a unified design methodology for XML applications based on object- oriented database using UML. To this goal, first we introduce a XML modeling methodology to design W3C XML schema using UML and second we propose data modeling methodology for object-oriented database schema to store efficiently XML data in object-oriented databases.

• Journal of the Korean Data and Information Science Society
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• 제27권6호
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• pp.1621-1629
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• 2016

This paper studies Bayesian pooling for analysis of categorical data from small areas. Many surveys consist of categorical data collected on a contingency table in each area. Statistical inference for small areas requires considerable care because the subpopulation sample sizes are usually very small. Typically we use the hierarchical Bayesian model for pooling subpopulation data. However, the customary hierarchical Bayesian models may specify more exchangeability than warranted. We, therefore, investigate the effects of pooling in hierarchical Bayesian modeling for the contingency table from small areas. In specific, this paper focuses on the methods of direct or indirect pooling of categorical data collected on a contingency table in each area through Dirichlet priors. We compare the pooling effects of hierarchical Bayesian models by fitting the simulated data. The analysis is carried out using Markov chain Monte Carlo methods.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2003년도 춘계학술대회 논문집
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• pp.101-106
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• 2003

This paper introduces the basic concept of computational modeling of perception processes for multimedia data. Such processes are modeled as hierarchical inter-and relationships amongst information in physical, physiological, psychological and cognitive layers in perception. Based on our framework, this paper gives the , algorithms for content-based retrieval for multimedia database systems.

• 정보처리학회지
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• 제11권1호
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• pp.8-19
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• 2004

Many Researchers and practitioners have expressed the view that artificial intelligence(AI) may have significant application to solution of manufacturing problems. Expert systems have been developed for solving problem areas.(omitted)

• 한국정밀공학회지
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• 제14권11호
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• pp.135-146
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• 1997

This paper describes fault diagnosis method in complex system with hierachical structure similar to human body structure. Complex system is divided into unit, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. Fault diagnosis system can forecast faults in a system and decide from current machine state signal information. Comparing with other diagnosis system for single fault, the developed system deals with multiple fault diagnosis comprising Hierarchical Neural Network(HNN). HNN consists of four level neural network, first level for item fault symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. UNIX IPC(Inter Process Communication) is used for implementing HNN wiht multitasking and message transfer between processes in SUN workstation with X-Windows(Motif). We tested HNN at four units, seven items per unit, seven components per item in a complex system. Each one neural newtork operate as a separate process in HNN. The message queue take charge of information exdhange and cooperation between each neural network.

• 정보처리학회논문지A
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• 제16A권5호
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• pp.307-318
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• 2009

컴퓨터 그래픽스에서 구름과 같은 대기 현상을 모델링하고 렌더링하는 것은 그 복잡성과 규모, 편재성 등으로 인해 상당히 까다로운 연구과제들 중의 하나이다. 본 논문은 컴퓨터 게임이나 항공 시뮬레이션 분야에서 요구되는, 실시간에 처리될 수 있는 구름 모델링과 렌더링 방법을 제안한다. 제안하는 방법은 사용자가 직관적이고 대화형 편집 과정을 거쳐 권운, 층운, 적운 등의 다양한 형태를 생성할 수 있다. 또한, 메타볼과 계층적 구형 파티클을 사용하여, 세부 묘사를 자동으로 추가할 수 있다. 생성된 파티클들은 다중 순방향 산란과 이방성 산란을 고려하여 빌보드 방식으로 출력함으로써 실시간 처리가 가능하다.

• 한국시뮬레이션학회논문지
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• 제17권1호
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• pp.33-42
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• 2008

시뮬레이션이 현실적으로 수행하기 어려운 시스템을 모의 실험한다는 특성상 대상 시스템은 크고 복잡한 경우가 많으며, 이러한 시스템의 변화를 관찰하고자 한다면 시뮬레이션 모델구조와 애니메이션 또한 그와 비슷한 복잡도로 행해져야 한다. 그러나, 모든 시스템 구성 요소들을 한꺼번에 애니메이션 하는 일은 복잡도 때문에 관찰하고자 하는 시스템 영역에 대한 초점을 흐리게 할 수 있다. 또, 시뮬레이션이 많은 컴퓨팅 자원을 요구하는 일인 것을 고려할 때, 복잡한 애니메이션 처리는 시스템에게 더욱더 많은 부하를 준다. 이와 관련한 문제를 해결하고자 전체 시스템 중 관찰하고자하는 특정 계층을 사용자가 선택하여 애니메이션 하는 계층적 애니메이션 기법이 제안되었다. 하지만, 이 연구에는 모델 작성자가 시뮬레이션의 동적 특성에 맞는 애니메이션 모델링을 체계적으로 기술 할 수 있는 모델링 형식은 정의되어 있지 않다. 이 연구에서는 계층적 애니메이션이 가능한 시뮬레이션 모델을 좀 더 체계적으로 정의 할 수 있도록 DESHA 형식론을 정의하고, 기존 연구의 구현물을 개선하여 DESHA 모델 실행 환경인 DESHA-C++로 정의하였다. 또, 이러한 계층적 애니메이션이 가능한 시뮬레이션 모델링 방식이 다양한 영역에서 활용될 수 있도록 DESHA와 HLA를 연동한 분산 시뮬레이션 모델링 환경을 제안하고 개발하였다.

• 한국시뮬레이션학회논문지
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• 제8권1호
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.