• ETRI Journal
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• v.32 no.6
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• pp.863-870
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• 2010

In recent years, the development of multimedia devices has meant that a wider multimedia streaming service can be supported, and there are now many ways in which TV channels can communicate with different terminals. Generally, scalable video streaming is known to provide more efficient channel capacity than simulcast video streaming. Simulcast video streaming requires a large network bandwidth for all resolutions, but scalable video streaming needs only one flow for all resolutions. In previous research, scalable video streaming has been compared with simulcast video streaming for network channel capacity, in two user simulation environments. The simulation results show that the channel capacity of SVC is 16% to 20% smaller than AVC, but scalable video streaming is not efficient because of the limit of the present network framework. In this paper, we propose a new network framework with an SVC extractor. The proposed network framework shows a channel capacity 50% (maximum) lower than that found in previous research studies.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1241-1248
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• 2004

A controller of wheeled mobile robot(WMR) based on Lyapunov theory is designed and a Fuzzy-Neural Network algorithm is applied to this system to adjust controller gain. In conventional controller of WMR that adopts fixed controller gain, controller can not pursuit trajectory perfectly when initial condition of system is changed. Moreover, acquisition of optimal value of controller gain due to variation of initial condition is not easy because it can be get through lots of try and error process. To solve such problem, a Fuzzy-Neural Network algorithm is proposed. The Fuzzy logic adjusts gains to act up to position error and position error rate. And, the Neural Network algorithm optimizes gains according to initial position and initial direction. Computer simulation shows that the proposed Fuzzy-Neural Network controller is effective.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1189-1195
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• 2004

This paper investigates construction of gene (interaction) networks from gene expression time-series data based on evolutionary computation. To illustrate the proposed approach in a comprehensive way, we first assume an artificial gene network and then compare it with the reconstructed network from the gene expression time-series data generated by the artificial network. Next, we employ real gene expression time-series data (Spellman's yeast data) to construct a gene network by applying the proposed approach. From these experiments, we find that the proposed approach can be used as a useful tool for discovering the structure of a gene network as well as the corresponding relations among genes. The constructed gene network can further provide biologists with information to generate/test new hypotheses and ultimately to unravel the gene functions.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.926-931
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• 2004

In this paper, we proposed security management architecture that combines programmable network technology and policy based network management technology to manage efficiently heterogeneous security systems. By using proposed security management architecture, a security administrator can manage heterogeneous security systems using security policy, which is automatically translated into a programmable security policy and executed on programmable middleware of security system. In addition, programmable middleware that has the features of programmable network can reduce excessive management traffic. We showed that the programmable middleware could reduce the load of management traffic by comparing processing time between the proposed architecture and PBNM architecture.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2178-2181
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• 2003

Active networks allow active node’s functionality to be extended dynamically through the use of active extensions. This flexible architecture facilitates the deployment of new network protocols and services. However, the active nature of a network also raises serious safety and security concerns. These concerns must be addressed before active networks can be deployed. In this paper we look at how we can control active extension’s access to different active nodes. Specifically, the authentication between active nodes is very important in this case. We use unique identity each node has for transferring access policies between active nodes. In this paper, we suggest a new method of transferring access policies performing authentications using identities between active nodes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5B
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• pp.491-497
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• 2004

In this Paper, we W a Hovel global traffic control architecture to isolate malicious network attacks and protect network infrastructure in Internet backbone networks. Unlike existing methods based on individual packets or flows, since the proposed detection and control methods are operated on the aggregate traffic level, the computational complexity can k significantly reduced, and they are applicable to develop a global defense architecture against network attack. Experimental results show that the proposed scheme can detect the network attack symptoms very exactly and quickly and protect the network resources as well as the normal traffic flows very efficiently.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.198-203
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• 2010

In this paper, a new routing protocol is proposed to manage selfish nodes which make a strategic choice to maximize only their own profits. To provide incentives to nodes on the path, VCG mechanism is introduced. Therefore, based on the collaborative actions among nodes, the entire network performance can be improved. With a simulation study, the proposed scheme can approximate an optimized solution while ensuring a well-balanced network performance under widely diverse network environments.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1518-1527
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• 1989

We proposed a technique to design a multimicrocomputer system for real-time parallel processing with an interconnection network which has good network latency time. In order to simplify the performance evaluation and the design procedure under the hard real-time constraints we defined network latency time which takes into account the queueing delays of the networks. We designed a dynamic interconnection network following the proposed technique, and the simulation results show that we can easily estimate the multimicrocomputer system's approximate performance using the defined network latency time before the actual design, so this definition can help the efficient design of the real-time parallel processing systems.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.120-126
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• 1995

The diffusion neural network can be cfficiently applied to the Gaussian processing. For example, a difference of two Gaussians(DOG) is performed by this network with ease. In this paper, we model a neural network to perform the function /t(.del.${\Delta}^{2}$G) by using the diffusion neural network. This model is used to detect the edges of moving target in image. By this model not only moving target is separated from stationary background but also their trajectories are obtained using accumulated past information in the diffusion neural network. Furthermore this model needs a small number of connections per cell and the connection weights are fixed-valued. Therefore its hardware can be easily implemented with simple structure.