• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.468-475
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• 2008

This paper presents a method for estimating the transient stability status of the power system using radial basis function(RBF) neural network with a fast hybrid training approach. A normalized transient energy margin(${\Delta}V_n$) has been obtained by the potential energy boundary surface(PEBS) method along with a time-domain simulation technique, and is used as an output of the RBF neural network. The RBF neural network is then trained to map the operating conditions of the power system to the ${\Delta}V_n$, which provides a measure of the transient stability of the power system. The proposed approach has been successfully applied to the 10-machine 39-bus New England test system, and the results are given.

• East Asian mathematical journal
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• v.36 no.5
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• pp.547-554
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• 2020

Synchronization of unidirectional identical FitzHugh-Nagumo systems coupled in a ring structure under ionic and external electrical stimulations is investigated. In this network, each neuron is only connected and transmit signals to its next neuron via synaptic strength called gapjunctions. Adaptive control theory and Lyapunov stability theory are used to propose a unique control scheme with necessary and sufficient conditions which guarantee the synchronization of the neuronal network. Finally, the effectiveness of the proposed scheme is shown through numerical simulations.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.59-64
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• 2008

In this paper, stability and transparency analysis for client/server haptic-based networked virtual environment (NVE) is introduced. From this analysis the appropriate communication structure for the more stable and transparent haptic interactions can be derived. Also, it is possible to expect and compensate the quality deterioration of haptic interactions according to certain network conditions In order to verify the usefulness of the analysis, simple haptic-based NVE application is implemented. For the stability verification, the vibration or strange movement of haptic interface and virtual object are measured under various network states. In addition, the usefulness of the proposed transparency analysis and network delay compensation scheme is verified by comparing distorted and compensated force feedbacks with real force feedback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1866-1888
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• 2017

Efficient energy consumption in WSN is one of the key design issues for improving network stability period. In this paper, we propose a new Heterogeneity-aware Energy-efficient Clustering (HEC) technique which considers two types of heterogeneity - network lifetime and of sensor nodes. Selection of cluster head nodes is done based on the three network lifetime phases: only advanced nodes are allowed to become cluster heads in the initial phase; in the second active phase all nodes are allowed to participate in cluster head selection process with equal probability, and in the last dying out phase, clustering is relaxed by allowing direct transmission. Simulation-based performance analysis of the proposed technique as compared to other relevant techniques shows that HEC achieves longer stable region, improved throughput, and better energy dissipation owing to judicious consumption of additional energy of advanced nodes. On an average, the improvement observed for stability period over LEACH, SEP, FAIR and HEC- with SEP protocols is around 65%, 30%, 15% and 17% respectively. Further, the scalability of proposed technique is tested by varying the field size and number of sensing nodes. The results obtained are found to be quite optimistic. The impact of energy heterogeneity has also been assessed and it is found to improve the stability period though only upto a certain extent.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.678-689
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• 2004

The major concern of networked control system is network uncertainties such as time delay and data loss. Because these uncertainties may degrade the performance of networked control system and destabilize the entire system. Therefore, the performance and the stability variation of networked control system due to network uncertainties must be considered first in designing networked control system. In particular, the stability analysis of networked control system is most important issue since time delay and data loss can make the overall systems unstable. In this paper, we present a new stability analysis method of networked control system with time delay and data loss, which is impossible in previous works. The proposed method can determine maximum time delay and allowable transmission rate that preserve stability performance of networked control system. The results of the simulation validate effectiveness of our stability analysis method.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.564-567
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• 2002

This paper evaluates the stability of the terminal group for he inter-vehicle communication (IVC) network with an autonomous relay access scheme. Some stability criterions such as updating rate, terminal group convergence probability and total path average holding time have been conducted by computer simulation. As the results, dynamic moving of the terminal is the serious problem that can degrade the stability of the terminal group and directly affect to overall performance of the IVC network.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.759-763
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• 2010

Currently available evaluation checklists are developed for specific purposed using different parameters and items determined by different weighting factors. Those items with different weighting are sometimes said that they are based on the engineering judgement and leap of faith and, therefore, there is a limitation to adapt those checklists for slope-stability evaluation in the field. This study reviews factors affecting Rock-slope stability, analyze the relationship between those factors and slope failures using artificial neural network, and proposed a slope-stability evaluation model for adequate weighting for the factors.

• Journal of Ocean Engineering and Technology
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• v.20 no.5 s.72
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• pp.70-76
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• 2006

A Probabilistic neural network (PNN) technique for predicting the stability number for the armor blocks of breakwaters is presented. A PNN is prepared using the experimental data of van der Meer and is then compared with the empirical formula and previous artificial neural network (ANN) model. This comparison shows that a PNN can effectively predict the stability numbers in spite of data complexity, incompleteness, and incoherence, and can be an effective tool for the designers of rubble mound breakwaters to support their decision process and to improve design efficiency.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.1342-1348
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• 2010

Currently available evaluation checklists are developed for specific purposed using different parameters and items determined by different weighting factors. Those items with different weighting are sometimes said that they are based on the engineering judgement and leap of faith and, therefore, there is a limitation to adapt those checklists for slope-stability evaluation in the field. This study reviews factors affecting slope stability, analyze the relationship between those factors and slope failures using artificial neural network, and proposed a slope-stability evaluation model for adequate weighting for the factors.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2231-2233
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• 2002

Recently NCS(Networked Control System) is widely used in distributed control system design. The insertion of the network in the feedback control loop makes the analysis and design of NCS complex. Especially, the network-induced delay can vary the system stability and even destabilizes the entire control system. This paper deals with the stability analysis method of NCS. Also, we analyze the influence of sampling period and network-induced delay on power plant stability.