• 상하수도학회지
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• 제21권3호
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• pp.305-314
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• 2007

Forecasting of water quality variation is not an easy process due to the complicated nature of various water quality factors and their interrelationships. The objective of this study is to test the applicability of neural network models to the forecasting of the water quality at Dalchun station in Han River. Input data is consist of monthly data of concentration of DO, BOD, COD, SS and river flow. And this study selected optimal neural network model through changing the number of hidden layer based on input layer(n) from n to 6n. After neural network theory is applied, the models go through training, calibration and verification. The result shows that the proposed model forecast water quality of high efficiency and developed web-based water quality forecasting system after extend model

• 전기학회논문지
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• 제60권8호
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• pp.1586-1591
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• 2011

This paper considers synchronization problem of a complex dynamical network. For the problem, the virtual target node is chosen as one of nodes in the complex network and only one connection is needed between an isolate target node and virtual target node not any more connections. Moreover, our synchronization scheme does not need additional conditions and information of coupling matrix comparing with existing works. Based on Lyapunov stability theory, a design criterion for a novel adaptive feedback controller for the synchronization between the isolate target node and another nodes of the complex network is proposed. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.194-197
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• 2002

This paper considers the problem of routing connections in a optical multi tree networks using WDM (Wavelength Division Multiplexing), where each connection between a pair of nodes in the network is assigned a path through the network and a wavelength on that path, so that connections whose paths share a common link in the network are assigned different wavelengths. The problem of optimal coloring of the paths on the optical multi-networks is NP-hard[1], but if that is the coloring of all paths, then there exists efficient polynomial time algorithm. In this paper, using a "divide & conquer" method, we give efficient algorithm to assign wavelengths to all the paths of a tree network based on the theory of [7]. Here, our time complexity is 0(n4log n).

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.228-231
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• 1997

In this paper, we designed an ART(Adaptive Resonance Theory) network based on LPC(Linear Prediction Coefficient) for classification of PVB (Premature Ventricular Beat: PVC, LBBB, RBBB). The procedure of proposed system consists of the error calculation, feature generation and processing of the ART network. The error is calculated after processing by linear prediction algorithm and the features of ART network or classification are obtained from the binary ata determined by threshold method. In conclusion, ART network has good performance in classification of PVB.

• 아동학회지
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• 제27권4호
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• pp.165-184
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• 2006

This ethnography explored the construction of a social network and its function in a classroom of toddlers in a day-care center located in Vermont. The classroom activities of 9 two-year-old toddlers were observed for about two months, compiled and categorized. Then, the themes of psychological functions were reconstructed in data analysis. Results showed that toddlers constructed multiple relations with all peers beyond the dyadic. They also transmitted information to teachers as well as peers in indirect ways. These direct-multiple interactions as well as indirect interactions reflect the social network of Lewis' (2005) theory. In the construction of social networks, the toddlers developed communication skills, turn-taking skills, leadership, and imitation.

• 한국해양공학회지
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• 제18권2호
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• pp.33-38
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• 2004

All adaptive neural network controller has been developed for a model of an underwater vehicle. This controller combines a radial basis neural network and sliding mode control techniques. No prior off-line training phase is required, and this scheme exploits the advantages of both neural network control and sliding mode control. An on-line stable adaptive law is derived using Lyapunov theory. The number of neurons and the width of Gaussian function should be chosen carefully. Performance of the controller is demonstrated through computer simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.264-269
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• 2008

In this paper, two neural networks as a material model, which are based on the state-space method, have been proposed. One outputs the rates of inelastic strain and material internal variables whereas the outputs of the other are the next state of the inelastic strain and material internal variables. Both the neural networks were trained using input-output data generated from Chaboche's model and successfully converged. The former neural network could reproduce the original stress-strain curve. The neural network also demonstrated its ability of interpolation by generating untrained curve. It was also found that the neural network can extrapolate in close proximity to the training data.

• 한국정보시스템학회지:정보시스템연구
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• 제21권4호
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• pp.133-153
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• 2012

This study explores the factors influencing user satisfaction of mobile IPTV and their relationship. We formulate the research model based on characteristics of mobile device and IPTV. Responsiveness, contents satisfaction, price satisfaction, aesthetic simplicity, network quality are proposed as essential antecedents of mobile IPTV satisfaction. We also suggest network quality and gender as moderators. Our data analysis with 297 mobile IPTV users shows contents and price have significant positive effect on mobile IPTV satisfaction. Network quality shows positive moderation effect on the relationship between responsiveness and satisfaction.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2013년도 춘계 학술논문 발표대회
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• pp.199-201
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• 2013

In a construction project in which cooperation among project members gets its importance, trust among construction site members should be foundation to enhance team spirit and achievement. This study analyzes the trust network among staff by using social network analysis (SNA) theory for organizations in apartment complex construction sites in Korea. The analysis illustrates higher level of trust for those positioning in the higher positions in hierarchy and having greater experiences. It might be attributable to own features of construction works where skills are acquired by site experience.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권2호
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• pp.93-99
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• 2001

A new type geometric and mathematical network reduction model is introduced. Large-scale network is analyzed with analytic approach. The graph has many nodes, branches and loops. Circuit equation are obtained from these elements and connection rule. In this paper, the analytic relation between voltage source has a mutual different graphic property. Node-reduction procedure is achieved with this circuit property. Consequently voltage source value is included into the adjacent node-analyzing equation. A resultant model equations are reduced as much as voltage source number. Matrix rank is (n-1-k), where n, k is node and voltage source number. The reduction procedure is described and verified with geometric principle and circuit theory. Matrix type circuit equation can be composed with this technique. The last results shall be calculated by using computer.