• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.716-725
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• 2004

It is extremely important to minimize network access time in constructing a high-performance PC cluster system. For PC cluster systems, it is possible to reduce network access time by maintaining network cache in each cluster node. This paper presents a Network Cache Coherent NUMA (NCC-NUMA) system to utilize network cache by locating shared memory on the PCI bus, and the NCC-NUMA card which is core module of the NCC-NUMA system is developed. The NCC-NUMA card is directly plugged into the PCI slot of each node, and contains shared memory, network cache, shared memory control module and network control module. The network cache is maintained for the shared memory on the PCI bus of cluster nodes. The coherency mechanism between the network cache and the shared memory is based on the IEEE SCI standard. According to the SPLASH-2 benchmark experiments, the NCC-NUMA system showed improvements of 56% compared with an SCI-based cluster without network cache.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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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.

• Proceedings of the KIEE Conference
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• 2004.11c
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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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.

• Proceedings of the KIEE Conference
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• 2011.07a
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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.

• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.13-24
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• 1999

In this paper, we propose a classifier based on modular networks using an unsupervised learning method. The structure of each module is designed through stochastic analysis of input data and each module classifier data independently. The result of independent classification of each module and a measure of the nearest distance are integrated during the final data classification phase to allow more precise c classification. Computation time is decreased by deleting modules that have been classified to be incorrect during the final classification phase. Using this method. a neural network sharing the best performance was implemented without considering. lots of of variables which can affect the performance of the neural network.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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.

• Computers and Concrete
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• v.26 no.5
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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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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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.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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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.