• 한국인터넷방송통신학회논문지
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• 제10권6호
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• pp.77-84
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• 2010

본 논문은 이동 통신 네트워크에서 기지국과 집중국사이에 설치되어 전송 비용을 줄여줄 수 있는 RAN (Radio Access Network)전송 시스템을 구현하는 것이다. 이 시스템은 여러 세대의 이동 통신 기지국 개별적으로 사용하는 전송 링크를 공유함으로써 전송 링크 수를 감소시켜 줄 수 있고, 지연 시간에 민감하지 않은 트래픽을 분류하여 그 트래픽을 Ethernet/IP 네트워크를 통하여 전달해 줄 수 있다.

• 한국컴퓨터정보학회논문지
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• 제6권2호
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• pp.97-100
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• 2001

최근 인터넷 정보가전산업은 다양한 통신 기기와 통신이 가능하게 되었지만 각 가전기기들과의 통신이 많아지고 복잡해지고 있다 이런 기기들을 효과적으로 관리하고 기기 전체를 통합할 수 있는 홈네트워크 형태의 기술개발은 아직 진행 중에 있으며, 사용자에게 효과적인 QoS를 지원하기 위한 방법론의 고려가 부족한 실정이다. 그러므로 본 논문에서는QoS지원을 위해서 홈네트워크와 인터넷 기반의 policy-based network기술을 통합할 수 있는 미들웨어 서비스에 관하여 언급하였다.

• 한국경영과학회지
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• 제31권3호
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• pp.1-10
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• 2006

In this paper we deal with a cell planning issue arisen in a CDMA based multicast network. In a CDMA based wireless network, a terminal can significantly reduce the bit error rate via the cohesion of data streams from multiple base stations. In this case, multiple base stations have to be operated according to a common time line. The cells whose base stations are operated as such are called soft-combined cells. Therefore, a terminal can take advantage of error rate reduction, if the terminal is in a soft-combined cell and at least one neighboring cell is also soft-combined. However, as soft-combining operation gives heavy burden to the network controller, the limited number of cells can be soft-combined. Our problem us to find a limited number of soft-combined cells such that the benefit of the soft-combining operation is maximized.

• Tribology and Lubricants
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• 제14권3호
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• pp.74-80
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• 1998

The morphologies of the wear particles are directly indicative of wear process occuring in the machine. The analysis of wear particle morphology can therefore provide very early detection of a fault and can also ofen facilitate a dignosis. For this work, the neural network was applied to identify friction coefficient through four shape parameters (50% volumetric diameter, aspect, roundness and reflectivity) of wear debris generated from the machine. The averages of these parameters were used as inputs to the network. It is shown that collect identification of friction coefficient depends on the ranges of these shape parameters learned. The various kinds of the wear debris had a different pattern characteristics and recognized relation between the friction condition and materials very well by neural network. We discuss how the network determines difference in wear debris feature, and this approach can be applied for machine condition monitoring and fault diagnosis.

• 한국경영과학회지
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• 제34권4호
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• pp.113-121
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• 2009

In this paper, we consider the departure process from the open and nested tandem Queueing network with population constraint and constant service times. It is known that the Queueing network can be transformed into a simple Queueing network which can be easy to analyze. Using this simple Queueing network, upper and lower bounds on the interdeparture time are obtained. We prove that the variance of the interdeparture time is bounded within these two bounds. Validation against simulation data is shown that how it works the variance of the interdeparture time within two bounds. These bounds can be applied to obtain the better variance of the interdeparture time using a suitable method.

• 한국멀티미디어학회논문지
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• 제8권6호
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• pp.836-843
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• 2005

The Wireless Internet services widely spread out with the developments of CDMA(Code Division Multiple Access) networks and wireless units. In contrast to the telecommunication network, WPAN (Wireless Personal Area Network) enables to transmit data and voice in personal area. Although WPAN technologies are commercially utilized, the combined services with COMA network are not so poplar up to now. Various services can be provided using the combination between COMA and WPAN. This paper presents the practical and united model between COMA and WPAN. Specially, the main focus of this research lies on the design of the Middle-ware system of a handset which could be managing both COMA and WPAN. This system used Bluethooth by WPAN. For the devices with the proposed WPAN Middle-ware, service areas of the COMA network can be expanded to WPAN, various services can be realized by the transmission of data and voice, and consequently, the user computing environment could be improved.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.496-499
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• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• 경영과학
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• 제26권3호
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• pp.55-65
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• 2009

The objective of this paper is to propose an ant colony optimization (ACO) for clustering design in wireless sensor network problem. This proposed ACO approach is designed to deal with the dynamics of the sensor nodes which can be adaptable to topological changes to any network graph in a time. Long communication distances between sensors and a sink in a sensor network can greatly consume the energy of sensors and reduce the lifetime of a network. We can greatly minimize the total communication distance while minimizing the number of cluster heads using proposed ACO. Simulation results show that our proposed method is very efficient to find the best solutions comparing to the optimal solution using CPLEX in 100, 200, and 400 node sensor networks.

• 한국지능시스템학회논문지
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• 제11권8호
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• pp.701-708
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• 2001

최근 컴퓨터의 지능에 대한 연구가 활발히 진행되고 있으며, 불확실하고 복잡한 동적 환경에서도 적응할 수 있도록 그 영역을 확장해 가고 있다. 본 논문에서는 다치논리를 기반으로 한 다치오토마타 모델을 신경망으로 구현한 다치-신경망 시스템을 제안한다. 또한, 다치오토마타는 신경망으로 구현될 수 있고, 다치-신경망 모델은 다치오토마타로 시뮬레이션될 수 있음을 입증하였다. 그 결과, 다치-신경망 모델은 지능시스템, 뇌의 모델링과 같은 여러 응용 분야에 널리 사용될 수 있을 것으로 기대된다.

• 산업공학
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• 제10권3호
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• pp.179-187
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• 1997

The efficiency of material flow systems in terms of optimal network flow and minimum cost flow has always been an important design and operational goal in material handling and distribution system. In this research, an attempt was made to develop a new algorithm and the model to solve a stochastic material flow network with bidirectional and uncertain flows. A stochastic material flow network with bidirectional flows can be considered from a finite set with unknown demand probabilities of each node. This problem can be formulated as a special case of a two-stage linear programming problem which can be converted into an equivalent linear program. To find the optimal solution of proposed stochastic material flow network, some terminologies and algorithms together with theories are developed based on the partitioning and subgradient techniques. A computer program applying the proposed method was developed and was applied to various problems.