• Journal of Information Processing Systems
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• v.18 no.4
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• pp.510-523
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• 2022

Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of two-wheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.559-569
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• 2004

It has become more difficult to correspond an cyber attack quickly as a pattern of attack becomes various and complex. And, current security mechanisms just have passive defense functionalities. In this paper, we propose new network security architecture to respond various cyber attacks rapidly and to chase and isolate the attackers through cooperation between security zones. The proposed architecture make possible to deal effectively with cyber attacks such as IP spoofing or DDoS(Distributed Denial of Service) using active packet technology including a mobile sensor on active network. Active Security Management System based on proposed security architecture consists of active security node and active security server in a security zone, and is designed to have more active correspondent than that of existing mechanisms. We implemented these mechanisms in Linux routers and experimented on a testbed to verify realization possibility of Active Security Management System. The experimentation results are analyzed.

• Journal of Internet Computing and Services
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• v.10 no.1
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• pp.19-31
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• 2009

Network management involves configuring and operating various network elements in a suitable manner. Generally, a network management system can perform basic functionalities such as configuration management, performance management, and fault management. Due to the open structure of the Internet, the volume of network traffic and the network equipment used have increased in size and complexity. Therefore, it is expensive and time consuming to develop a network management program for heterogeneous network equipment in an SNMP.based network. In order to facilitate the management of network environments and the control of heterogeneous devices in an efficient manner, we propose an Active Network Management System (ANMS) comprising an automatic generator that uses triggers to generate a network management program. The concept of triggers can be represented through event condition action rules performed in response to a change in the status of a network environment. The proposed ANMS comprises basic components for real time network management and also includes an automatic generator (AG). When the ANMS is monitoring network elements that are newly added or changed, a trigger rule is activated and these components are then able to collaborate and automatically generate a new network management program by using the information provided along with the SNMP libraries. Our method is useful for expanding the network structure and replacing network equipment. Through experiments, we have proved that our ANMS is useful when new network objects are added or changed in the network environment to expand the network structure. Further, we have verified that our ANMS system reduces the time and cost required to develop a network management program as compared to the manual method used in existing network management systems.

• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.69-78
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• 2006

In this paper, we presents the efficiency and a transmission quality of the system which is composed of the optical elements from physical layer of the active optical ring network. For a simulation it will use the Transmissionmaker WDM and it will be able to observation a optical transmission quality of the optical transmission system. The active optical network is composed of two rings(main ring and sub-ring). It measures the BER(Bit Error Rate) quality which it follows node number from the sub ring and physical distance of the node. Performance analysis from the physical layer becomes the standard of the plan for the efficiency optimization of the active optical ring network. Consequently it will be able to compose the efficient optical transmission system which reflects the physical distance, a traffic demand quantity of each node and a number of users from actual network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.488-494
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• 2013

For the activeness and autonomy of a sensor network, the efficient migration method of a mobile agent and the consistent naming services are the required components of a sensor network. Accordingly, this paper presented the implementation of backward migration of an active rule mobile agent applying the naming method based on RMI that used the meta_table including the informations about the components of a sensor network. This study implemented based on the extension of the forward migration[12], and the results of the various experiments present the efficacy of mobile agent middleware system and the possibility of constructing efficient sensor network application environment. And, the results of this study are able to enhance the adaptability on dynamic changes of environment in sensor network application development.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.7 s.124
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• pp.662-667
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• 2007

A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network(PNN). Therefore. it is the so-called lattice probabilistic neural network(LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However. control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for three story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.266-268
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• 2006

In this paper, we design a Linear Quadratic Gaussian(LQG) controller for active suspensions. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Using an optimization-algorithm, Evolution Strategy(ES), we find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1530-1533
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• 2005

In this paper, we design a Linear Quadratic Gaussian controller for the active suspension. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Because any definite rules for selecting weights do not exist, we use an optimization-algorithm, Evolution Strategy (ES) to find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies. For the full-state feedback control, Kalman filter observes the full states and Fourier transform is used to detect the frequency of the road.

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.291-295
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• 2004

Recently, distributing information on the Internet is common in our daily li(e. Also, data exchange on Internet has rapidly changed the way we connect with other people. But current firewall and IDS(Intrusion Detection System) of the network level suffers from many vulnerabilities in internal computing informations and resources. In this paper, we analyzes Traceback System that based on active network and design of Traceback System that based on active network for efficiently traceback.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1589-1592
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• 2004

현재 무선 인터넷 환경은 이동 단말에 컨텐츠 서비스를 제공할 경우, 서비스 사용자가 소유한 단말 환경의 다양성을 고려한 컨텐츠 최적화 작업을 필요로 한다. 기존 환경에서는 이런 기능을 위한 서버를 따로 설치하여 관리함으로 사용자가 늘어나게 되면 서버에 부하가 집중되어 제공되는 서비스의 질이 저하되는 문제가 발생한다. 본 논문에서는 이런 컨텐츠 최적화 기능을 망에서 제공하여 서버의 부하 집중 문제를 해결하는 이동 컨텐츠 적응형 네트워크(Mobile Contents Adaptation: MobiCAN)를 제안한다. MobiCAN 시스템은 ABone(Active Network Backbone) 데몬과 ANTS(Active Network Transfer System) 실행환경, 컨텐츠 최적화를 위한 액티브 응용으로 구성된다. 본 연구에서는 위와 같이 구성된 MobiCAN 시스템을 실제 무선 인터넷 망과 연동시킴으로 해서 액티브 네트워크의 무선 인터넷 적용 가능성을 확인하였다.