• 한국전산유체공학회지
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• 제19권2호
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• pp.24-29
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• 2014

In this study, a parallel performance of CUPID-code has been investigated for both Ethernet and Infiniband network system to examine the effect of cache memory and network-speed. Bi-conjugate gradient solver of CUPID-code has been parallelised by using domain decomposition method and message passing interface (MPI). It is shown that the parallel performance of Ethernet-network system is worse than that of Infiniband-network system due to the slow network-speed and a small cache memory. It is also found that the parallel performance of each system deteriorates for a small problem due to the communication overhead, but the performance of Infiniband-network system is better than Ethernet-network system due to a much faster network-speed. For a large problem, the parallel performance depends less on network system.

• 대한전기학회논문지
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• 제41권4호
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• pp.331-338
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• 1992

The application of Connectionist expert system using neural network to fault diagnosis of power system is presented and compared with rule-based expert system. Also, the merits of Connectionist model using neural network is presented. In this paper, the neural network for fault diagnosis is hierarchically composed by 3 neural network classes. The whole power system is divided into subsystems, the neural networks (Class II) which take charge of each subsystem and the neural network (Class III) which connects subsystems are composed. Every section of power system is classified into one of the typical sections which can be applied with same diagnosis rules, as line-section, bus-section, transformer-section. For each typical section, only one neural network (Class I) is composed. As the proposed model has hierarchical structure, the great reduction of learning structure is achieved. With parallel distributed processing, we show the possibility of on-line fault diagnosis.

• 한국정밀공학회지
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• 제15권4호
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• pp.83-90
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• 1998

In this paper, we present neural network for control of Left Ventricular Assist Device(LVAD) system with a pneumatically driven mock circulation system. Beat rate(BR), Systole-Diastole Rate(SDR) and flow rate are collected as the main variables of the LVAD system. System modeling is completed using the neural network with input variables(BR, SBR, their derivatives, actual flow) and output variable(actual flow). It is necessary to apply high perfomance control techniques, since the LVAD system represent nonlinear and time-varing characteristics. Fortunately. the neural network can be applied to control of a nonlinear dynamic system by learning capability In this study, we identify the LVAD system with neural network and control the LVAD system by PID controller and neural network feedforward controller. The ability and effectiveness of controlling the LVAD system using the proposed algorithm will be demonstrated by experiment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1558-1562
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• 2005

This paper describes the design and implementation of a wireless home network system using Home Network Control Protocol (HNCP) called the wireless HNCP home network system. For wireless interfaces of HNCP, IEEE 802.11b and IEEE 802.15.4 standard protocols are considered. With the implementation of the wireless HNCP home network system, a simple analysis about coexistence between IEEE 802.11b and IEEE 802.15.4 is achieved. Through the implemented wireless HNCP home network system and the analytical results about the coexistence between both two different wireless protocols, the feasibility of the wireless HNCP home network system is shown.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (3)
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• pp.76-78
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• 2002

Multicasting over mobile IP network becomes more important with the increasing needs of supporting multimedia services in mobile network. The IETF has suggested two approaches which are remote subscription and bidirectional tunneling for supporting mobility management in multicasting over mobile IP. But these protocols have problems - the frequent reconstruction of multicast delivery tree, packet less during handoff, convergence problem, and so on. In this paper, we propose to use preconfiguration of multicast delivery tree when mobile host enters the foreign network. It will decrease the frequency of multicast delivery tree reconstruction, and reduce the packet loss during handoff, Also the multicast delivery tree maintained by Keep Alive messages makes the signaling overload of networks diminished.

• 대한전자공학회논문지TC
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• 제42권1호`
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• pp.49-60
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• 2005

유무선 기간 망에서 사용되어 지는 Core Network System간 연동 부분의 Back Bone이 NO.7 Protocol이다. 그래서 유선망에서 기본적인 중계 ISUP이나, 지능망 INAP 처리, 그리고 이동망에서 각 Network Element System간 연동되는 MAP 연동 방식이 NO.7 방식을 사용하고 있다. 따라서 이 NO.7을 이용하는 Core Network에서 운영 중에 장애가 발생하거나, 기존에 인지되지 않고 지나온 문제점들을 최단시간에 감지하여 도출할 수 있는 시스템이 필요로 되었다. 본 논문에서는 Core Network 에서 사용되는 NO.7 Signaling 방식에 대해 더욱 신뢰성을 확보하고, 장애 발생 여부 등을 분석할 수 있도록 하기 위하여 NO.7 Signaling Message들을 추출하여 Core Network 시스템의 기능 및 성능을 분석하고 Report를 작성할 수 있는 NO.7 Protocol 분석 측정 시스템을 고안하였다. 이 시스템은 NO.7 Signaling을 담당하는 Core Network 시스템의 NO.7 HW Module 에 연결하여 Monitoring만 수행하고, 어떤 시나리오에 대한 Emulator 기능이나 Simulation 기능은 제공하지 않는다. 이 시스템은 현재 NO.7 MTP, ISUP, INAP, 그리고 MAP 에 대해 측정 및 분석기능을 수행하도록 하였고, 여러 유무선 기간 망 사업자에 제공하여 SW 및 HW 적인 면 그리고 운영적인면 등에서 여러 가지 문제들을 확인하여 교정할 수 있었다. 향후에는 이외에 BSC-MSC 연동되어 지는 A-Interface 등과 같은 기능도 제공함으로써 NO.7 Protocol 전반적인 분석과 동시에 Core Network 시스템에 효율적인 운영을 도모할 수 있다.

• 한국통신학회논문지
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• 제17권5호
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• pp.482-494
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• 1992

In this paper, the neuro-fuzzy inferene system for the effective object recognition is studied. The proposed neuro-fuzzy inference system combines learning capability of neural network with inference process of fuzzy theory, and the system executes the fuzzy inference by neural network automatically. The proposed system consists of the antecedence neural network, the consequent neural network, and the fuzzy operational part, For dissolving the ambiguity of recognition due to input variance in the neuro-fuzzy inference system, the antecedence’s fuzzy proposition of the inference rules are automatically produced by error back propagation learining rule. Therefore, when the fuzzy inference is made, the shape of membership functions os adaptively modified according to the variation. The antecedence neural netwerk constructs a separated MNN(Model Classification Neural Network)and LNN(Line segment Classification Neural Networks)for dissolving the degradation of recognition rate. The antecedence neural network can overcome the limitation of boundary decisoion characteristics of nrural network due to the similarity of extracted features. The increased recognition rate is gained by the consequent neural network which is designed to learn inference rules for the effective system output.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.307-313
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• 1999

This paper reviews and assesses the analogy between the human immune system and network intrusion detection systems. The promising results from a growing number of proposed computer immune models for intrusion detection motivate this work. The paper begins by briefly introducing existing intrusion detection systems (IDS's). A set of general requirements for network-based IDS's and the design goals to satisfy these requirements are identified by a careful examination of the literature. An overview of the human immune system is presented and its salient features that can contribute to the design of competent network-based IDS's are analysed. The analysis shows that the coordinated actions of several sophisticated mechanisms of the human immune system satisfy all the identified design goals. Consequently, the paper concludes that the design of a network-based IDS based on the human immune system is promising for future network-based IDS's

• 제어로봇시스템학회논문지
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• 제18권5호
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• pp.433-438
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• 2012

In this paper, a operation network system equipped with onboard wireless communication systems and ground-based mission control systems is proposed for swarm flight of small UAVs. This operating system can be divided into two networks, UAV communication network and ground control system. The UAV communication network is intend to exchange the informations of navigation, mission and flight status with minimum time delay. The ground control system consisted of mission control systems and UDP network. Proposed operation network system can make a swarm flight of various UAVs, execute complex missions decentralizing mission to several UAVs and cooperte several missions. Finally, PILS environments are developed based on the total operating system.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.2015-2020
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• 2008

Real-time communication network is important for KTX high speed train system because small problem can make a huge accident. Communication network for KTX high speed train system consists of IEEE 802.4 token bus network and FM0 encoding. The network device is developed by using MC68824 TBC, MC68185 TPM and MC68020 MPU. The network device make available to analysis of the network protocol among vehicles for Kyung-Boo high-speed train system.