• 제목/요약/키워드: network module

검색결과 1,421건 처리시간 0.037초

고성능 PC 클러스터 링을 위한 SCI 기반 Network Cache Coherent NUMA 시스템의 설계 및 구현 (Design and Implementation of an SCI-Based Network Cache Coherent NUMA System for High-Performance PC Clustering)

  • 오수철;정상화
    • 한국정보과학회논문지:시스템및이론
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    • 제31권12호
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    • pp.716-725
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    • 2004
  • 고성능 PC 클러스터 시스템을 구축하기 위해서는 네트워크 접근 시간을 최소화하는 것이 중요하다. SCI 기반 PC 클러스터 시스템에서는 각 노드에 네트워크 캐쉬를 유지함으로써 네트워크 접근 시간을 줄이는 것이 가능하다. 본 논문에서는 공유 메모리를 PCI 버스상에 위치시킴으로써 네트워크 캐쉬지원을 가능하게 하였으며, 이에 기반한 Network Cache Coherenet NUMA(NCC-NUMA) 시스템을 제안하고, 핵심 모듈인 NCC-NUMA 카드를 개발하였다. NCC-NUMA 카드는 각 노드의 PCI 슬롯(slot)에 plug-in되는 형태이며, 공유메모리, 네트워크 캐쉬, 공유메모리 제어 모듈 및 네트워크 제어 모듈을 포함한다. 공유메모리와 네트워크 캐쉬 사이의 일관성은 IEEE SCI 표준에 의해 유지된다. NCC-NUMA 시스템의 성능 측정을 위해 SPLASH-2 벤치마크를 수행하였으며, NCC-NUMA 시스템이 네트워크 캐쉬를 활용하지 않는 NUMA 기반 클러스터 시스템에 비해서 최대 56%의 성능향상을 보임을 알 수 있었다.

Hybrid Neuro-Fuzzy Network를 이용한 실시간 주행속도 추정 (The Estimation of Link Travel Speed Using Hybrid Neuro-Fuzzy Networks)

  • 황인식;이홍철
    • 대한산업공학회지
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    • 제26권4호
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    • pp.306-314
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    • 2000
  • In this paper we present a new approach to estimate link travel speed based on the hybrid neuro-fuzzy network. It combines the fuzzy ART algorithm for structure learning and the backpropagation algorithm for parameter adaptation. At first, the fuzzy ART algorithm partitions the input/output space using the training data set in order to construct initial neuro-fuzzy inference network. After the initial network topology is completed, a backpropagation learning scheme is applied to optimize parameters of fuzzy membership functions. An initial neuro-fuzzy network can be applicable to any other link where the probe car data are available. This can be realized by the network adaptation and add/modify module. In the network adaptation module, a CBR(Case-Based Reasoning) approach is used. Various experiments show that proposed methodology has better performance for estimating link travel speed comparing to the existing method.

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신경회로망 연산기의 구조 결정 모듈 성능에 관한 시뮬레이션 (Simulation on Performance of Constructive Module for Neural Network Processor)

  • 유인갑;정제교;위재우;동성수;이종호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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    • pp.101-103
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    • 2004
  • Expansible & Reconfigurable Neuro Informatics Engine(ERNIE) is effective in reconfigurability and extensibility. But ERNIE have the problem which have limited performance in initial network. To solve this problem, the constructive module using the reconfigurable ERNIE is implemented in simulation model. In this paper, simulation results on sonar data are showed that ERNIE using the constructive module obtains the better performance compared to ERNIE without it.

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An Adaptive Probe Detection Model using Fuzzy Cognitive Maps

  • Lee, Se-Yul;Kim, Yong-Soo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.660-663
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    • 2003
  • The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using Fuzzy Cognitive Maps(FCM) that can detect intrusion by the Denial of Service(DoS) attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The Sp flooding Preventer using Fuzzy cognitive maps(SPuF) model captures and analyzes the packet information to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. The result of simulating the "KDD ′99 Competition Data Set" in the SPuF model shows that the Probe detection rates were over 97 percentages.

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네트워크 기반 보호계전기 시뮬레이터용 과전류 계전 알고리즘 모듈 구현 (Development of an Over-Current Relaying Algorithm Module for a Network-Based Protective Relay Simulator)

  • 박건호;김동희;고자영;강상희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.741-742
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    • 2011
  • In this paper, an over-current relay algorithm module for a network-based protective relay simulator is proposed. The proposed protective simulator is based on the client-sever paradigm. The module composed of a server and user interface provides a network-based simulation environment.

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비지도 학습 방법을 적용한 모듈화 신경망 기반의 패턴 분류기 설계 (A Design of Cassifier Using Mudular Neural Networks with Unsupervised Learning)

  • 최종원;오경환
    • 인지과학
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    • 제10권1호
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    • pp.13-24
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    • 1999
  • 논문에서는 모듈화 신경 을 이용한 비지도 학습방법의 분류기를 제안한다. 각 모듈은 데이터의 통계학적인 분석의 결과로 설계되어져서, 데이터의 독립적인 군집들을 나타내게 된다. 이런 신경의 독립적인 분류 결과와 근접거리 척도를 이용한 유사도 측정을 통해 더욱 정확한 분류를 가능케 하며, 오 분류를 하는 모듈을 삭제함으로써 계산 을 줄인다. 이런 과정을 통해 신경 에 사용되는 각종 변수에 대한 별다른 조사 과정 없이 최상의 성능을 발휘하는 신경 에 준 는 성능을 가진 신경 망을 구축했다.

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Intelligent Air Quality Sensor System with Back Propagation Neural Network in Automobile

  • Lee, Seung-Chul;Chung, Wan-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.468-471
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    • 2005
  • The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.

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Crack detection based on ResNet with spatial attention

  • Yang, Qiaoning;Jiang, Si;Chen, Juan;Lin, Weiguo
    • Computers and Concrete
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    • 제26권5호
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    • pp.411-420
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    • 2020
  • Deep Convolution neural network (DCNN) has been widely used in the healthy maintenance of civil infrastructure. Using DCNN to improve crack detection performance has attracted many researchers' attention. In this paper, a light-weight spatial attention network module is proposed to strengthen the representation capability of ResNet and improve the crack detection performance. It utilizes attention mechanism to strengthen the interested objects in global receptive field of ResNet convolution layers. Global average spatial information over all channels are used to construct an attention scalar. The scalar is combined with adaptive weighted sigmoid function to activate the output of each channel's feature maps. Salient objects in feature maps are refined by the attention scalar. The proposed spatial attention module is stacked in ResNet50 to detect crack. Experiments results show that the proposed module can got significant performance improvement in crack detection.

시뮬레이터를 이용한 B-NT 시스템 성능분석 (Performance analysis of the B-NT system using simulstor)

  • 이규호;기장근;노승환;최진규;김재근
    • 한국통신학회논문지
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    • 제23권6호
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    • pp.1503-1513
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    • 1998
  • This paper is related to a performance analysis of B-NT system, which is essential compositional equipment of B-ISDN access network. A simulator enabling performance analysis according to the change of network configuration topology and the change of user traffic is developed in this study. The developed B-NT, system simulator consists of graphic user interface module, simulation program automatic generator module, and B-NT system model library module. As examples of the results of performance analysis using the simulator, end-to-end user cell transmission delay time, queueing delay time in each system, and cell loss rate in the head node switch are presented. The simulator developed in this paper can be utilized in determining the network topology of B-NT system.

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이동통신망 관리용 운용시스템 설계에 관한 연구 (A Study on the design of operations system for managing the mobile communication network)

  • 하기종
    • 한국시뮬레이션학회논문지
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    • 제6권2호
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    • pp.71-79
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    • 1997
  • In this paper, operations system was designed for the centralization of data processing of various state information from the facilities of mobile communication network. And the system performance experimental system module was measured and analyzed from the designed experimental system module. The configuration of system design was presented with the centralized type to monite and control the facilities of mobile communication network in the central office. The communication process design of the internal system was implemented with the resource of message queue having a excellent transmission ability for processing of a great quantity of information in the inter-process communication among communication resources of UNIX system. The process with a server function from the internal communication processes was constructed with a single server or a double server according to the quantity of operations and implemented with the policy of the presented server. And then, we have measured performance elements in accordance with the change of input parameters from the designed experimental module : response time, waiting time, buffer length, the maximum quantity existing in message queue. And from these results, we have compared and analyzed the system state each server algorithm according to performance variations.

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