• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.346-349
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• 2003

This paper is intended to assess a system reliability that is changed as time passes. The proposed methodology consists of two steps: (1) predicting probabilities that each component fails at specific time by using a Markov Chain model and (2) calculating reliability of the whole system via Bayesian network. The proposed methodology includes extended Bayesian network model reflecting the case that components are mutually dependent.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.105-117
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• 1993

Methods for calculating k shortest paths in a network system, are based on a analogy which exists between the solution of a network problem and traditional techniques for solving linear equations. This paper modifies an algebraic structure of the K shortest path method and develops k maximum flow methods. On the basis of both theoretical and algebraic structure, three iteration methods are developed and the effective procedure of each method are provided. Finally, computational complexity is discussed for those methods.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.150-153
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• 2007

The intent of this paper is to describe a neural network structure called multi dynamic neural network(MDNN), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the MDNN, are described. Computer simulations are demonstrate the effectiveness of the proposed learning using the MDNN.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.403-413
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• 1996

Two-phase self-organizing neuro-modeling (SONM). the global SONM and local SONM, is designed for tracking non-stationary manufacturing processes. Radial basis function (RBF) neural network is employed, and self-tuning estimator is also developed for the determination of RBF network parameters on-line. A pattern recognition approach is presented for identifying a correct RBF neural network, which is used for identifying current manufacturing processes. Experimental results showed that the proposed approach is suitable for tracking non-stationary processes.

• Journal of Industrial Technology
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• v.12
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• pp.37-49
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• 1992

We proposed an integrated simulator scheme for communication networks. The network modeling and Analysis methologies are firstly discussed along the design procedure of a network simulator, and then, the structure, kernel, and user interfaces are defined for the simulator. Finally, for the verification of our approach, simulations are performed for a simple queueing network and a pure ALOHA system using Ptolemy, a multi-paradigm simulation enviroment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.211-220
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• 1996

We consider the problem of scheduling a maximal amount of additional, low priority transport through a large multiperiod network, given that we may not interfere with an existing schedule for high priority transport. The problem is transformed into the Time-Expanded network(TENET) without traverse time using TENET Generator (TENETGEN). We describe two specialized heuristic algorithms that guarantee the optimal solutions and show the effectiveness of them by comparing quite favorably with Dinic.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.4
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• pp.329-350
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• 2019

This paper examines individual and social strategies to form profitable cooperation networks. These two types of strategies measure network stability and efficiency that may not meet in a single network. We apply restrictions on knowledge flows (R&D spillovers) and links formation to integrate these benefits into structures that ensure high outcomes for both strategies. The results suggest that linking the spillovers to the firms' positions and restricting cooperation contribute to reducing the conflict between the individual and social strategies in the development of cooperative networks.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1066-1070
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• 2002

We propose a neural network based up-trend detector. An auto-associative neural network was trained with 'up-trend' data obtained from the KOSPI 200 future price. It was then used to predict an up-trend Simple investment strategies based on the detector achieved a two year return of $19.8\%$ with no leverage.

• Journal of Industrial Technology
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• v.32 no.A
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• pp.9-13
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• 2012

In this paper, we investigate maximum transmission capacity of wireless ad-hoc networks. In the investigation, we consider a network topology with regularly located nodes. For the topology, we investigate the maximum transmission capacity with RTS/CTS medium access protocol, and next, we study the maximum transmission capacity without the protocol. We see that the results of our study overall follows the result of Gupta and Kumar's research.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.87-101
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• 2013

In industrial applications, sensor networks have to satisfy specified time requirements of exchanged messages. IEEE 802.15.4 defines the communication protocol of the physical and medium access control layers for wireless sensor networks, which support real-time transmission through guaranteed time slots (GTSs). In order to improve the performance of IEEE 802.15.4 in industrial applications, this paper proposes a new traffic scheduling algorithm for GTS. This algorithm concentrates on time-critical industrial periodic messages and determines the values of network and node parameters for GTS. It guarantees real-time requirements of periodic messages for industrial automation systems up to the order of tens to hundreds of milliseconds depending on the traffic condition of the network system. A series of simulation results are obtained to examine the validity of the scheduling algorithm proposed in this study. The simulation results show that this scheduling algorithm not only guarantees real-time requirements for periodic message but also improves the scalability, bandwidth utilization, and energy efficiency of the network with a slight modification of the existing IEEE 802.15.4 protocol.