• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.607-614
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• 2014

This article aims to explore and discuss research trends in global cruise industry using keyword network analysis. We visualize keyword networks in each of four groups of 1982-1999, 2000-2004, 2005-2009, 2010-2014 based on the top 20 keyword nodes' degree centrality and betweenness centrality which are selected among four centrality measurements, comparing them with frequency order. The article shows that keyword frequency collected from 240 articles published in international journals is subject to Zipf's law and nodes degree distribution also exhibits power law. We try to find out research trends in global cruise industry to change some important keywords diachronically, visualizing several networks focusing on the top two keywords, cruise and tourism, belonging to all the four year groups, with high degree and betweenness centrality values. Interestingly enough, a new node, China, connecting the top most keywords, appears in the most recent period of 2010-2014 when China has emerged as one of the rapid development countries in global cruise industry. Therefore keyword network analysis used in this article will be useful to understand research trends in global cruise industry because of increase and decrease of numbers of network types in different year groups and the visual connection between important nodes in giant components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2675-2690
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• 2014

We study the problem of optimal opportunistic spectrum access with unknown and heterogeneous channel dynamics in cognitive radio networks. There is neither statistic information about the licensed channels nor information exchange among secondary users in the respective systems. We formulate the problem of maximizing network throughput. To achieve the desired optimization, we propose a win-shift lose-stay algorithm based only on rewards. The key point of the algorithm is to make secondary users tend to shift to another channel after receiving rewards from the current channel. The optimality and the convergence of the proposed algorithm are proved. The simulation results show that for both heterogeneous and homogenous systems the proposed win-shift lose-stay algorithm has better performance in terms of throughput and fairness than an existing algorithm.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.119-137
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• 1999

The World Wide Web(WWW) has provided multi-media cyberspace for electronic markets where suppliers and demanders can do global electronic business with each other directly and conveniently. There are two contradictory views on the roles of intermediaries in electronic markets. One says we may not need intermediaries in doing business because suppliers and demanders can contact with each other directly in electronic markets. The other thinks that the intermediary function may be vertically decomposed from the company's internal value chain because it can be done more efficiently through networks by external intermediaries. Intelligent software agent is a new emerging technology in the field of computer science. An intelligent agent can support and do actions on behalf of users on computer networks. We think that this technology can be utilized to implement more efficient cybermediaries for electronic commerce. This paper proposes an XML-based framework for financial software agent, which selects financial products best fitted for the customer's needs in electronic market environment.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1281-1284
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• 1998

This paper proposes an efficient time series prediction of the nonlinear dynamical discrete-time systems using multilayer neural networks of a hybrid learning algorithm. The proposed learning algorithm is a hybrid backpropagation algorithm based on the steepest descent for high-speed optimization and the dynamic tunneling for global optimization. The proposed algorithm has been applied to the y00 samples of 700 sequences to predict the next 100 samples. The simulation results shows that the proposed algorithm has better performances of the convergence and the prediction, in comparision with that using backpropagation algorithm based on the gradient descent for multilayer neural network.

• ETRI Journal
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• v.30 no.5
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• pp.674-684
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• 2008

This paper proposes a dual addressing scheme (DAS) for IPv6 over IEEE 802.15.4 wireless sensor networks (WSN). DAS combines a global unicast address to cope with association link changes and node mobility, and it links local addresses to lighten the overhead of the system to save energy and resources. This paper describes DAS address formats, address autoconfiguration, and address translation tables in the gateway. A detailed description of DAS is provided through examples. Simulations are performed to demonstrate the performance improvements of the DAS compared with the IPv6-based WSN, which uses the conventional single address.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.149-157
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• 2008

The reduction of leakage is a major issue of the South Korea water industry. The inclusion of pressure dependent leakage terms in network analysis allows the application of optimization techniques to identify the most effective means of reducing water leakage in distribution networks. This paper proposes a method to find optimal setting and location of control valve for reducing leakage efficiently. The proposed search method differs from previous methods for addressing optimal valve location problem and improves the GA simulation time with guaranteeing for getting the global optimal solution. The strength of this method has been demonstrated by means of case studies. This allows the procedure of optimization to be more robust and computational efficient.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.296-298
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• 1999

Five institutions, which are very active in data utilization of environmental satellites NOAA and GMS, are connected via high speed networks to construct the databases based on the observations of A AVHRR (Advanced very High Resolution Radiometer) of NOAA satellite and VISSR (Visible and Infrared Scanning Radiometer) of GMS (Geostationary Meteorological Satellite) and to create scientific data sets for land, ocean and ,atmosphere. And vegetation index, sea surface temperature, cloud distribution maps and so on are generated by high speed and huge volume data Processing for studies on long term variations of land, ocean and atmosphere in Asia. In this paper the concept of this project and the activities at the Science University of Tokyo are briefly introduced

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.445-448
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• 2003

During a time when cellular systems are being deployed in massive scale worldwide, international roaming is becoming increasingly important. This paper presents UIM (User Identification Module) for mobility support, authentication, and service portability between different mobile systems. We also introduce network model based on PASM(Portable Authentication and Mobility Service Machine) which will support signaling protocol and user information conversions with database for roaming between different mobile networks. Stored data types and elements in UIM, logical data structure and configuration, and registration procedures are described here in the case of DCN (Digital CDMA (Code Division Multiple Access) Network System) and GSM (Global System for Mobile Communications).

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.180-188
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• 1999

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which complex global intelligence form from simple local interactions. Here, we propose an architecture of neural network learning with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigate in a group. As the results of the simulations, the optimum weight is obtained in real time, which not only prevent the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.