• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.285-291
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• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.15.1-21
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• 1999

Radiosity method is a global illumination model for image synthesis. It computes all energy interactions among diffuse elements in a virtual environment. One of the major drawbacks if its time consuming computation. Existing radiosity algorithms for static scene is difficult to be applicable to dynamic environments. In this paper we proposed an hierarchical scene partition scheme to speedup the link update computations in the dynamic environments. Since the proposed spatial data structure is global, it not only can be used to speedup the culling of non-affected links after geometry change, but also can be used to accelerate the subsequent visibility computation. Several empirical tests are given to show the efficiency of our improved algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.404-408
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• 2005

Having flexibility in a manipulator will degrade trajectory tracking control and manipulator tip positioning. In practice, however, constraints imposed by various operating requirements, will render the presence of such flexibility unavoidable. The dynamic analysis of the flexible manipulator is essential in designing proper control systems. A flexible manipulator consists of infinite number of elastic modes and the modes are usually coupled to each other. For the practicality, however, it is usually assumed that the flexible system consists of finite number of elastic modes and the modes are decoupled. These assumptions result in a linear and decoupled mathematical model of the flexible manipulator and simplify the analysis of the dynamic behavior and the design of the control system. The decoupling and linearization of the flexible link, however, has been assumed without in depth analysis. This paper focuses on the analysis of the significance of the non-linear coupling factors.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.245-260
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• 2006

A practical use of the location information and user requirement are increased in a mobile environment which supports the portability. And Various service which GIS is related with a Spatial DB have been processed. Generally, logical relation of a traffic network which organizes the Road DB uses a basic node-link structure. In this way, Designed structure can not be flexible at various model apply and are not efficient with a database retrieval in a maintenance management side. In this research, We supplement with the problem of a existing network model and the limitation of the building through the design of a network model which uses dynamic segmentation. And we tried to implement efficient hierarchy model at the retrieval of the network and presentation. Designed model supports a stage presentation of various level and a hierarchy entity relation and We are expected to supplement a network spatial modelling function which the GIS has.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3A
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• pp.259-266
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• 2011

Femtocells are expected as the surest way to increase the system capacity with higher-quality links and more spatial reuse in future networks. In spite of their great potential, the system capacity is highly susceptible to network density because a large portion of users are exposed to inter-cell interference (ICI). In this work, we proposed a dynamic interference avoidance scheme in densely deployed cell environments. Our proposed DDIA (Distributed Dynamic ICI Avoidance) scheme not only works in a fully distributed manner, but also controls interference link connectivity of users with high agility so that it is suited for self-organizing networks (SONs). We introduced the concept of ICI-link and two-tier scheduling in designing the DDIA scheme. To avoid ICI without any central entity, our scheme tries to harmonize all base stations (BSs) with users adaptively. Through extensive simulations, it was shown that our proposed scheme improves the throughput of users by more than twice on average compared to the frequency reuse factor 1 scheme, who are exposed to ICI while maintaining or even improving overall network performance. Our scheme operates well regardless of network density and topology.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.989-999
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• 2006

In this paper, numerical analysis method to perform linear dynamic analysis of bridge considering the road surface roughness and bridge-vehicle interaction when vehicle is moving on bridge is presented. The vehicle and bridge are modeled as three-dimension where contact length of tire and pitching of tandem spring are considered and single truck with 2-axles and 3- axles, and tractor-trailer with 5-axles are modeled as 7-D.O.F., 8-D.O.F., and 14-D.O.F., respectively. Dynamic equations of vehicle are derived from the Lagrange's equation and solution of the equation is obtained by Newmark-${\beta}$ method. The surface roughness of bridge deck for this analysis is generated from power spectral density (PSD) function. Beam element for the main girder, shell element for concrete deck and rigid link between main girder and concrete deck are used. The equations of the motion of bridges are solved by mode-superposition procedures. The proposed procedure is validated by comparing the results with the experimental data by Whittemore and Fenves.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.10a
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• pp.158-158
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• 1998

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.