• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.462-469
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• 2007

ATM protocol has the techniques such as cell discarding priority, traffic shaping and traffic policing. ATM based MPLS(Multiprotocol Label Switching) is discussed for its provisioning QoS commitment capabilities, traffic engineering and smooth migration for BcN using conventional ATM infra in Korea. This paper proposes preventive congestion control mechanism for detecting HTR(Hard To Reach) LSP(Label Switched Path) in ATM based MPLS systems. In particular, we decide HTR LSP using real time signaling information(etc., PTI,AIS/RDI) for applying HTR concept in circuit switching to ATM based MPLS systems and use those session gap and percentage based control algorithm that were used in conventional PSTN call controls. We concluded that it maximized the efficiency of network resources by restricting ineffective machine attempts. Proposed control can handle 208% call processing and more than 147% success call, than those without control. It can handle 187% BHCA(Busy Hour Call Attempts) with 100 times less than use of exchange memory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.685-688
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• 2008

A Next Generation Network (NGN) is a packet-based network able to provide services including Telecommunication Services and able to make use of multiple broadband, QoS-enabled transport technologies and in which service-related functions are independent from underlying transport-related technologies. It offers unrestricted access by users to different service providers. It supports generalized mobility which will allow consistent and ubiquitous provision of services to users in this paper. we describe the trend of standardization activity related with open services environment capabilities which had been finally approved at September 2008 in ITU-T. ITU-T SG13 is responsible for studies relating to the architecture, evolution and convergence of next generation networks including frameworks and functional architectures, signalling requirements for NGN.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.1-9
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• 2001

In this paper, "a conceptual model of Reconnaissance-Strike-Logistics Complex(RSLC) in future warfare" is proposed. Basic idea of the RSLC model is to combine logistics and the pre-existing Reconnaissance-Strike Complex(RSC) through a C4 network system. That is, the RSLC model consists of reconnaissance, strike, logistics, and C4 network systems. The C4 network system creates new combat power by integrating all the other systems. The RSLC model generates three conceptual complex circles; the RSC, the SLC(Strke-Logistics Complex), and the RSLC circles. The RSC circles describes direct combat behaviors in the battlefield. On the other hand, the SLC circle indicates combat sustainment capabilities. The RSLC circle including the RSC and the SLC circles, can present a more complete combat process. There are two key advantages of the RSLC model. First of all, logistics is considered one of key combat components to form IDA(Information-Decision-Action) cycle for combat decision-making process more completely. Secondly, the capabilities of battlefield awareness which reconnaissance and war-net systems provide, can be applied not only to the strike system in the RSC circle, but also to the logistics system in the SLC circle. Thus, the RSLC model can maximize combat synergy effects by integrating the RSC and the SLC. With a similar logic, this paper develops "A Revised System of Systems with Logistics (RSSL)" which combines "A New system of Systems" and logistics. These tow models proposed here help explain several issues such as logistics environment in future warfare, MOE(Measure of Effectiveness( on logistics performance, and COA(Course of Actions) for decreasing mass and increasing velocity. In particular, velocity in logistics is emphasized.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.524-527
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• 1997

Conventional target tracking algorithms based on the linear estimation techniques perform quite efficiently when the target motion does not involve maneuvers. Target maneuvers involving short term accelerations, however, cause a bias in the measurement sequence. Accurate compensation for the bias requires processing more samples of which adds to the computational complexity. The primary motivation for employing a neural network for this task comes from the efficiency with which more features can be as inputs for bias compensation. A system architecture that efficiently integrates the fusion capabilities of a trained multilayer neural net with the tracking performance of a Kalman filter is described. The parallel processing capability of a properly trained neural network can permit fast processing of features to yield correct acceleration estimates and hence can take the burden off the primary Kalman filter which still provides the target position and velocity estimates.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.11
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• pp.70-77
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• 1992

Generally, the conventional tracking algorithms are very limited in the practical applications because of that the computation load is exponentially increased as the number of targets being tracked is increase. Recently, to overcome this kind of limitation, some new tracking methods based on neural network algorithms which have learning and parallel processing capabilities are introduced. By application of neural networks to multi-target tracking problems, the tracking system can be made computationally independent of the number of objects being tracked, through their characteristics of massive parallelism and dense interconnectivity. In this paper, a new neural network tracking algorithm, which has capability of adaptive target tracking with little increase of the amount of calculation under the clutter and noisy environments, is suggested and the possibility of real-time multi-target tracking system based on neural networks is also demonstrated through some good computer simulation results.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.125-130
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• 1997

In this paper, it is presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C3x is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, andsuitable for implementation of robust control.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.22-26
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• 2007

In the fibre to the home (FTTH) era, it is expected that broadband network provisioning will require thousands of optical fibres to be accommodated in a central office for optical access networks. An optical fibre line testing system could be used to reduce maintenance costs and improve service availability depending on the PON's element manager capabilities and the maintenance procedures adopted by the network supplier. When monitoring optical fibres transmitting communication lights, a wavelength of 1625 nm is used for maintenance testing. The splitter installed optical filters allow the communication light to pass but that cut off the test light in the front of optical line terminals (OLTs) and optical network terminals (ONTs). In the economic point of view, We design new planer lightwave circuit splitter embedded filtter and study it optical property.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.09a
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• pp.334-343
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• 1995

In recent years, neural networks have been developed as an alternative to traditional statistical techniques. In this study, a neural network model was compared to traditional forecasting models in terms of their capabilities to forecast passenger traffic for flights between U.S. and Korea. The results show that the forecasting ability of the neural networks was superior to the traditional models. In terms of accuracy, the performance of the neural networks was quite encouraging. Using mean absolute deviation, the neural network performed best. The new technique is easy to learn and apply with commercial neural network software. Therefore, airline decision makers should benefit from using neural networks in forecasting passenger loads.

• Journal of information and communication convergence engineering
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• v.10 no.4
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• pp.359-364
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• 2012

Harvesting energy from the environment is essential for many applications to slow down the deterioration of energy of the devices in sensor networks and in general, the network itself. Energy from the environment is an inexhaustible supply which, if properly managed and harvested from the sources, can allow the system to last for a longer period - more than the expected lifetime at the time of deployment, or even last indefinitely. The goal of this study is to develop a simple algorithm for ns-2 to simulate energy harvesting in wireless sensor network simulations. The algorithm is implemented in the energy module of the simulator. Energy harvesting algorithms have not yet been developed for ns-2. This study will greatly contribute to the existing knowledge of simulating wireless sensor networks with energy harvesting capabilities in ns-2. This paper will also serve as a basis for future research papers that make use of energy harvesting.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.481-486
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• 2007

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. The large number of sensor nodes in a WSN means that there will often be some nodes which give erroneous sensor data owing to several reasons such as power shortage and transmission error. Generally, these sensor data are gathered by a sink node to monitor and diagnose the current environment. Therefore, this can make it difficult to get an effective monitoring and diagnosis. In this paper, to overcome the aforementioned problems, intelligent sensor data validation method based on PCA(Principle Component Analysis) is utilized. Furthermore, a practical implementation using embedded system is given to show the feasibility of the proposed scheme.