• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.778-781
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• 2005

In this paper, we describe a development of a Bluetooth Access Point for the WAN connection of home network devices. Especially, users can access the PSTN at home instead of expensive digital cellular network through the AP, using the 'one-phone', which is the Bluetooth enabled cellular phone. The simultaneous benchmark test about telephone service and LAN access service shows the perfect compatibility and reasonable performance of the access point. The one-phone service can become a convergence of wired and wireless communication through the AP.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2198-2202
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• 2005

In this paper we have presented a condition monitoring method of check valve using neural network. The acoustic emission sensor was used to acquire the condition signals of check valve in direct vessel injection (DVI) test loop. The acquired sensor signal pass through a signal conditioning which are consisted of steps; rejection of background noise, amplification, analogue to digital conversion, extract of feature points. The extracted feature points which represent the condition of check valve was utilized input values of fault diagnosis algorithms using pre-learned neural network. The fault diagnosis algorithm proceeds fault detection, fault isolation and fault identification within limited ranges. The developed algorithm enables timely diagnosis of failure of check valve’s degradation and service aging so that maintenance and replacement could be preformed prior to loss of the safety function. The overall process has been experimented and the results are given to show its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.779-784
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• 2008

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

• Journal of electromagnetic engineering and science
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• v.15 no.4
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• pp.258-265
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• 2015

A de-embedding method for multiport networks, especially for coupled odd interconnection lines, is presented in this paper. This method does not require a conversion from S-parameters to T-parameters, which is widely used in the de-embedding technique of multiport networks based on cascaded simple two-port relations, whereas here, we apply an operation to the S-matrix to generate all the uncoupled and coupled coefficients. The derivation of the method is based on the relations of incident and reflected waves between the input of the entire network and the input of the intrinsic device under test (DUT). The characteristics of the intrinsic DUT are eventually achieved and expressed as a function of the S-parameters of the whole network, which are easily obtained. The derived coefficients constitute ABCD-parameters for a convenient implementation of the method into cascaded multiport networks. A validation was performed based on a spice-like circuit simulator, and this verified the proposed method for both uncoupled and coupled cases.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.1
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• pp.1-6
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• 2011

This paper describes the high speed PLC-based remote control system that can monitor and control textile machineries bi-directionally through Internet. There are many textile machineries without network functions in the factory. We apply the PLC technology in order to give a network function to them in which the existing electric power line is used with network communication lines without separate wiring constructions. In order to realize this system, we have implemented a protocol for network communication of system, high-speed PLC modules, and Ethernet-to-UART modules. Finally we confirmed the effectiveness of system by applying actual test environments.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.75-78
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• 1995

In this paper it is concerned to develop control method using jar-test results in order to predict the optimum dosage of coaglant, PAC(PoliAluminum Chloride). Considering the relations with the reactions with the reaction of coagulation and flocculation, the five independent variables ( e, g, turbidity of raw water, water turbidity in flocculators, temperature, pH, and alkalynity) are selected out of parameters and they are put into calculation to develop a neural network model for PAC dosing process in water purification system. This model is utilized to predict optimum dosage of PAC. That is, the optimum dosage of PAC is searched in neural network model for PAC dosing process to minimize the water turbidity in flocculators. This searching is implemented by means of expert heuristics. The efficacy of the proposed contorl schemem and feasibility of acquired neural network model for PAC dosing contorl in water purification system is evaluated by means of computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.738-746
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• 1998

This paper presents a neural network-based adaptive controller for a single flexible-link. The control for feedback-error loaming of neural network is designed by using the re-definition approach. The neural network controllers are implemented on an single flexible-link experimental test-bed. The tip response is significantly improved and the vibrations of the flexible modes are damped very fast. Experimental and simulation results are presented of the proposed tip position tracking controllers over the conventional PD-type, passive controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.551-560
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• 1998

This paper presents a neural network model representing complex hydro-thermo-dynamic characteristics of a steam generator in nuclear power plants. The key modeling processes include training data gathering process, analysis of system dynamics and determining of the neural network structure, training process, and the final process for validation of the trained model. In this paper, we suggest a training data gathering method from an unstable steam generator so that the data sufficiently represent the dynamic characteristics of the plant over a wide operating range. In addition, we define the inputs and outputs of neural network model by analyzing the system dimension, relative degree, and inputs/outputs of the plant. Several types of neural networks are applied to the modeling and training process. The trained networks are verified by using a class of test data, and their performances are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.243-246
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• 2003

The design of router that converts IP packets from IPv4 network to IPv6 network using embedded Linux toolkit based on processor is presented. As an address transition platform, IPv6 module is transplanted to Linux using processor and the experiment was done with IPv4 and IPv6. In order to build the test network, it is constructed with Tunneling mechanism of IPv4 and IPv6 network. The packet value is obtained about 2$\mu$sec on average a 2 hops on the ICMP ping6.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.310-318
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• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.