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

• 한국산업융합학회 논문집
• /
• 제7권2호
• /
• pp.199-205
• /
• 2004

This paper describes the fault diagnosis method to order to construct CIM in complex system with hierarchical 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 a special neural network. Fault diagnosis system can forecast faults in a system and decide from the signal information of current machine state. Comparing with other diagnosis system for a single fault, the developed system deals with multiple fault diagnosis, comprising hierarchical neural network (HNN). HNN consists of four level neural network, i.e. first is fault symptom classification and second fault diagnosis for item, third is symptom classification and forth fault diagnosis for component. UNIX IPC is used for implementing HNN with 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 network represents a separate process in UNIX operating system, information exchanging and cooperating between each neural network was done by message queue.

• 한국통신학회논문지
• /
• 제19권7호
• /
• pp.1282-1295
• /
• 1994

본 논문에서는 계층 버스 구조를 기반으로 하는 계층 클러스터 다중프로세서 시스템(hierarchical cluster multiprocessor system)을 제안하고, 이 구조에 효율적인 캐쉬 일관성 프로토콜을 설계 및 구현한다. 계층 클러스터 구조는 클러스터 수의 증가에 따라 버스 계층을 추가함으로써 기존의 단일 버스 시스템에서의 병목 현상(bottleneck)을 없애주어 시스템 확장이 용이하게 된다. 제안된 캐쉬 프로토콜은 일반적인 N-레벨 (N>2) 계층 클러스터 구조에 적용할 수 있도록 설계되었다. 이를 시스템 버스에 구현하기 위하여 기존의 팬디드 프로토콜을 확장하였고 캐쉬 일관성 동작들을 확장된 팬디드 프로토콜상에서 설명한다.

• 한국시뮬레이션학회논문지
• /
• 제8권4호
• /
• pp.89-107
• /
• 1999

There are many issues in computer simulation such as verifying model code, validating models, understanding the dynamics of systems and training the personnel. The developers of simulation tool have been interested in the animation since it can help solve the problems related to the above listed issues. In practice, animation is one of the popular method for displaying the simulation output for solving these problems. Trying to display all the graphic objects representing the dynamics of the models being simulated, however, causes the distraction of focus, which results in solving the above listed problems difficult. The redundant graphic objects also Increase the computer computation overhead. This paper presents a hierarchical animation environment in which the users can have better focus on the dynamics of system components. In hierarchical animation environment the users can observe the dynamics of system by selectively choosing the hierarchical level and components with in a level of the hierarchically structured model. Especially when the model is large and complex the selection of observation level is needed. The design approach of the hierarchical animator is based on the DEVS(Discrete Event system Specification) formalism which is theoretically well grounded means of expressing modular and hierarchical models.

• ETRI Journal
• /
• 제41권5호
• /
• pp.648-657
• /
• 2019

A cluster topology was proposed with the assumption of zero noise to improve the performance of wireless body area networks (WBANs). However, in WBANs, the transmission power should be reduced as low as possible to avoid the effect of electromagnetic waves on the human body and to extend the lifetime of a battery. Therefore, in this work, we consider a bit error rate for a cluster-based WBAN and analyze the performance of the system while the transmission of sensors and cluster headers (CHs) is controlled. Moreover, a hierarchical topology is proposed for the cluster-based WBAN to further improve the throughput of the system; this proposed system is called as the hierarchical cluster WBAN. The hierarchical cluster WBAN is combined with a transmission control scheme, that is, complete control, spatial reuse superframe, to increase the throughput. The proposed system is analyzed and evaluated based on several factors of the system model, such as signal-to-noise ratio, number of clusters, and number of sensors. The calculation result indicates that the proposed hierarchical cluster WBAN outperforms the cluster-based WBAN in all analyzed scenarios.

• 한국전자파학회논문지
• /
• 제12권7호
• /
• pp.1037-1047
• /
• 2001

본 논문에서는 역방향 링크상의 전파 음영 채널에서 불완전 전력제어 및 불완전 섹터화를 고려하여 DS/CDMA 계층 셀룰라 시스템의 용량을 분석한다. 실제 시스템에서는 이론과는 달리 완전한 전력제어가 되지 않기 때문에 불완전 전력제어, 불완전 섹터화 및 처리이득, 매크로셀의 사용자 수와 같은 파라미터를 고려하여 시스템의 용량 변화를 유도하였다. 해석한 결과, 전력제어 및 섹터화가 불완전 할수록, 매크로셀과 마이크로셀의 전력비가 커질수록, 처리이득이 작을수록, 마이크로셀의 사용자 수가 감소할수록 DS/CDMA 계층 셀룰라 시스템의 용량은 감소하였다. 또한, 계층셀 구조가 단일 매크로셀 구조에 비해 1.54 배에서 3.89 배로 사용자 용량을 증가시킬 수 있음을 보였다.

• 한국항행학회논문지
• /
• 제16권6호
• /
• pp.975-981
• /
• 2012

서로 다른 품질을 요구하는 데이터들의 동시 전송 또는 효율적인 영상전송시스템에 응용될 수 있는 계층 16QAM (Quadrature Amplitude Modulation) 시스템에 대한 SNR 추정성능에 대해 분석한다. 계층 16QAM은 계층 변조파라미터를 제어하여 성좌점들의 형태를 변형시켜 사용자에게 고품질과 저품질 데이터서비스를 동시에 제공할 수 있는 변조 시스템이다. AWGN (Additive White Gaussian Noise) 채널환경에서 계층 16QAM 시스템에서 계층변조파라미터와 성좌점별 특성을 고려한 SNR (Signal to Noise power Ratio) 추정성능 특성을 분석하였다. 시뮬레이션 결과, 계층 16QAM의 여러성좌점들 중에 SNR 추정이 상대적으로 정확하게 이루어지는 성좌점이 존재함을 확인하였고, 계층변조파라미터 값에 따라 SNR 추정이 유리한 영역이 달라진다는 것을 알아내었다.

• 한국산학기술학회논문지
• /
• 제7권2호
• /
• pp.126-130
• /
• 2006

PLC는 산업용 제어시스템에서 널리 사용되고 있으며, 중요한 역할을 하고 있다. PLC에서 사용되는 언어중 SFC는 이산 제어 프로그램에서 순차제어 논리의 기술에 적합한 그래픽 언어이며, SFC로 공정제어 시스템을 구현할 때는 분산제어 구조와 계층제어 구조로 구현하게 된다. 계층제어 구조에서는 서브시스템 간에 동기를 맞추기 위해서 서브시스템은 별도로 구성하고 동기신호만을 주고받게 된다. 그러면 메모리 효율 및 시스템 성능이 좋지 않게 된다. 본 논문에서는 계층제어 구조에서 메모리 효율을 향상시키는 방법을 제안하였고, 실례를 통해 그의 타당성을 확인하였다.

• 산업경영시스템학회지
• /
• 제29권3호
• /
• pp.111-118
• /
• 2006

This paper presents design and development of a simulator evaluates the performance of a hierarchical cellular system. The proposed hierarchical cellular simulator, consisting of macro, micro, and pico cells, applies the wrap-around technique to reduce simulation time. The simulator is implemented as object oriented class models by using the C++ language in a PC environment. The resulting application can evaluate the interference, SIR(Signal to Interference Ratio), and capacity of a hierarchical cellular system in various configurations. Moreover, it can be used in other applications such as power control, call admission control, hand over scheme.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
• /
• pp.187-190
• /
• 2001

Due to the recent proliferation of the internet, it is broadly granted that the necessity of the automatic document categorization has been on the rise. Since it is a heavy time-consuming work and takes too much manpower to process and classify manually, we need a system that categorizes them automatically as their contents. In this paper, we propose the automatic E-mail response system that is based on 2 hierarchical document clustering methods. One is to get the final result from the classifier trained seperatly within each class, after clustering the whole documents into 3 groups so that the first classifier categorize the input documents as the corresponding group. The other method is that the system classifies the most distinct classes first as their similarity, successively. Neural networks have been adopted as classifiers, we have used dendrograms to show the hierarchical aspect of similarities between classes. The comparison among the performances of hierarchical and non-hierarchical classifiers tells us clustering methods have provided the classification efficiency.