• Journal of Communications and Networks
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• v.2 no.1
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• pp.35-45
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• 2000

this paper presents the concept of "mobile ATM', a proposal for third-generation (3G) mobile communication network infrastructure capable of supporting flexible evolution of radio technologies from today's cellular and data services towards future wireless multimedia services. Mobile ATM provides generic mobility management and QoS-based transport capabilities suitable for integration of multiple radio access technologies including cellular voice. wireless data, and future broadband wireless services. The architecture of a mobile ATM network is outlined in terms of the newly-defined "W-UNI" interface at the radio link and "M-UNI"and "M-UNI" interface which supports unified access for WATM and non-ATM mobile terminals through corresponding interworking functions (IWF) is explained. leading to an understanding of how different radio access technologies are supported by the same ATM-based core network infrastructure. Generic mechanisms for handoff and location management within the core mobile network are discussed. and related protocol extensions over the "W-UNI" and "M-UNI/NNI"interfaces are proposed. the issue of "crossover switch (COS)" selection in mobile ATM is considered, and a unified handoff signaling syntax which supports flexibility in COS selection is described. Typical signaling sequences for call connection and handoff using the proposed protocols are outlined. Experimental results form a proof-of-concept mobile ATM network prototype are presented in conclusion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.31-36
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• 2008

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the enviromuent. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.49.2-49.2
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• 2013

We report preliminary results from a radio study of central galaxies in cool and non-cool core clusters. A cooling flow is expected to rapidly form in the center of galaxy clusters unless additional heating mechanisms such as merging with sub clusters are at work. It has been suggested that cool flows can feed the AGN in the central galaxies, increasing their power. On the other hand, the AGN feedback can also affect the surrounding medium, heating back up the gas in the cluster core region. In this study, we investigate the co-evolution of cool flows and the AGN of galaxies located in the cluster center. For this study, we have selected 13 radio bright central galaxies from clusters with a range of cooling time scale. In this work, we present results of our recent observations using the Korean VLBI Network. We discuss the properties of the sample in radio and other wavelengths.

• IE interfaces
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• v.14 no.3
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• pp.227-235
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• 2001

There is a rapidly growing demand for wireless telecommunication. However, the number of usable channel is very limited. Therefore, the problem of channel assignment becomes more and more important to use channels as efficiently as possible. The objective of this paper is to develop an evolution program (EP) to find an efficient dynamic channel assignment method for minimum interference among the channels within reasonable time. The series of specific channel number is used as a representation of chromosome. The only changed chromosomes by crossover and mutation are evaluated in each generation to save computation time and memory for the progress of improved EP. We can easily differentiate the fitness value of each chromosome using proposed evaluation function. We also control the weighting factor of the mutation rate and the used number of elitist chromosomes for the speed of convergence to the optimal solution.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.920-924
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• 2005

This paper presents adaptive learning data of evolvable neural networks (ENNs) for time series prediction of nonlinear dynamic systems. ENNs are a special class of neural networks that adopt the concept of biological evolution as a mechanism of adaptation or learning. ENNs can adapt to an environment as well as changes in the environment. ENNs used in this paper are L-system and DNA coding based ENNs. The ENNs adopt the evolution of simultaneous network architecture and weights using indirect encoding. In general just previous data are used for training the predictor that predicts future data. However the characteristics of data and appropriate size of learning data are usually unknown. Therefore we propose adaptive change of learning data size to predict the future data effectively. In order to verify the effectiveness of our scheme, we apply it to chaotic time series predictions of Mackey-Glass data.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.149-149
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• 2000

We experimented on AGV driving test with color CCD camera which is setup on it. This paper can be divided into two parts. One is image processing part to measure the condition of the guideline and AGV. The other is part that obtains the reference steering angle through using the image processing parts. First, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, AGV knows the driving conditions of AGV. After then using of those information, AGV calculates the reference steering angle changed by the speed of AGV. In the case of low speed, it focuses on the left/right error values of the guide line. As increasing of the speed of AGV, it focuses on the slop of guide line. Lastly, we are to model the above descriptions as the type of PID controller and regulate the coefficient value of it the speed of AGV.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.120-129
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• 2001

A two-degree-of-freedom quarter-car model is used as the basis for LQ and the proposed controller design for a semi-active suspension. The LQ controller results in the best rms performance trade-offs(as defined by performance index) between ride, handling and packaging requirements. In LQ controller, however, the conflict between road holding and ride comfort remains. The adaptive semi-active suspension control based on the road frequency are introduced in this paper. With this method, the trade-off between road holding and ride comfort can be relaxed. The road frequency is estimated by wavelet transform if rattle space signal. The simulation results show that the proposed controller is superior to the conventional LQ controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.259-262
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• 1997

This paper presents a visual servoing of RV-M2 robot manipulators to track and grasp moving object, using pruned dynamic recurrent neural networks(DRNN). The object is stationary in the robot work space and the robot is tracking and grasping the object by using CCD camera mounted on the end-effector. In order to optimize the structure of DRNN, we decide the node whether delete or add, by mutation probability, first in case of delete node, the node which have minimum sum of input weight is actually deleted, and then in case of add node, the weight is connected according to the number of case which added node can reach the other nodes. Using evolutionary programming(EP) that search the struture and weight of the DRNN, and evolution strategies(ES) which train the weight of neuron, we pruned the net structure of DRNN. We applied the DRNN to the Visual Servoing of a robot manipulators to control position and orientation of end-effector, and the validity and effectiveness of the pro osed control scheme will be verified by computer simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.641-644
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• 2017

Usage of LTE(Long Term Evolution) technology is expanded to industrial an emergency service field beyond commercial communications of mobile internet focused on smartphone. In this paper, transmission performance of LTE technology be supplied to various service area is analyzed on the level of application traffics. Performance is evaluated with compter simulation based NS(Network Simulator)-2, CBR(Constant Bit Rate), VBR(Variable Bit Rate File) traffic is used as simulation target. Results and methods of this paper can be used for research and developmemt of LTE based networks.

• Journal of Korean Vacuum Science & Technology
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• v.7 no.1
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• pp.1-7
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• 2003

The pressure distributions in the test stand built for developing KSTAR NBI ion sources were obtained using a network system composed of conductance elements modeling the ion source, the neutralizer, and other beam line components. The allowable regime was defined on the coordinates of the gas supply rate to the ion source and the neutralizer, considering the proper conditions of the three critical parameters, the ion source pressure for good arc discharge, the pressure integral in the neutralizer for sufficient neutralization, and the chamber pressure for minimum neutral beam loss. The neutral beam evolution along the path from the ion source extraction grid to the calorimeter through the neutralizer, the bending magnet and the vacuum chamber was estimated for typical pressure distributions.