• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1542-1550
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• 1994

For a class of singularly perturbed uncertain system, an output feedback control law is designed. The controller structure is designed based on the uncertain reduced-order system, and the controller parameters are determined by information on the reduced-order and full-order systems. It has been shown that the reduces-order system with the designed controller possesses a stability property(specifically, a global uniform attractivity). Furthermore, the stability property of this control scheme is robust with respect to singular perturbation ; i.e., the full-order system, subject to the same controller, possesses the global uniform attractivity, provided the singular perturbation parameter $\mu<\mu^{*}$, where a threshold value $\mu^{*}$ can be computed from the information available on the full-order system.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.70-75
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• 2000

After the patterning and probe process of wafer have been achieved, the dicing process is necessary to separate chips from a wafer. The dicing process cuts a wafer to lengthwise and crosswise direction to make many chips by using narrow circular rotating diamond blade. But inferior goods are made under the influence of complex dicing environment such as blade, wafer, cutting water and cutting conditions. This paper describes a monitoring algorithm using feature extraction in order to find out an instant of vibration signal change when bad dicing appears. The algorithm is composed of two steps: feature extraction and decision. In the feature extraction, two features processed from vibration signal which is acquired by accelerometer attached on blade head are proposed. In the decision. a threshold method is adopted to classify the dicing process into normal and abnormal dicing. Experiment have been performed for GaAs semiconductor wafer. Based upon observation of the experimental results, the proposed scheme shown a good accuracy of classification performance by which the inferior goods decreased from 35.2% to 12.8%.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.239-242
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• 2002

This paper has been realized PCB insert machine automation system. For the reduction of the install programming time as well as possible, a new technique is addressed. In detail, an image frame is initially divided into one area whose size decreases according to the distance from hole to hole on PCB. Searching center of hole using a threshold method after median filtering. At every moment of mouse click, area is shifted to locate the hole, and detect a center of hole in a new area. Experimental results are demonstrated to verify the superiority of this scheme in detecting position of part by comparing with a man of experience.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.167-170
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• 2002

We have proposed new pixel structures for Active Matrix OELD (AMOELD) to improve the uniformity of luminance and manufactured a full-color 3.6-inch QVGA AMOELD. The proposed pixel structures, composed of four TFTs and one capacitor, can display 64 gray scales by compensating threshold voltage (Vth) variation of driving TFTs. Nonuniformity and peak intensity of measured luminance are under 14% and over $200cd/m^2$, respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.95-101
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.130-130
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• 2000

This paper presents a robust fault diagnosis and fault tolerant control lot the actuator and sensor faults in the closed-loop systems affected by unknown inputs or disturbances. The fault diagnostic scheme is based on the residual set generation by using robust Parity space approach. Residual set is evaluated through the threshold test and then fault is isolated according to the decision logic table. Once the fault diagnosis module indicates which actuator or sensor is faulty, the fault magnitude is estimated by using the disturbance-decoupled optimal state estimation and a new additive control law is added to the nominal one to override the fault effect on the system. Simulation results show that the method has definite fault diagnosis and fault tolerant control ability against actuator and sensor faults.

• The Korean Journal of Applied Statistics
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• v.25 no.4
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• pp.589-603
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• 2012

Mahalanobis-Taguchi system(MTS) is a statistical tool for classifying the normal group and abnormal group in multivariate data structures. In addition to the classification itself, the MTS uses a method for selecting variables useful for the classification. This method can be used efficiently especially when the abnormal group data are scattered without a specific directionality. When the feedback adjustment procedure through the measurements of the process output for controlling process input variables is not practically possible, the reset procedure can be an alternative one. This article proposes a reset procedure using the MTS. Moreover, a method for identifying input variables to reset is also proposed by the use of the contribution. The identification of the root-cause parameters using the existing dimension-reduced contribution tends to be difficult due to the variety of correlation relationships of multivariate data structures. However, it became possible to provide an improved decision when used together with the location-centered contribution and the individual-parameter contribution.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.98-105
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• 2000

In this study, we developed rotating machine vibration condition monitoring system based upon Windows NT and DSP Board. Developed system includes signal analysis module, trend monitoring and simple diagnosis using threshold value. Trend analysis and report generation are offered with database management tool which was developed in MS-ACCESS environment. Post-processor, based upon Matlab, is developed for vibration signal analysis and fault detection using statistical pattern recognition scheme based upon Bayes discrimination rule and neural networks. Concerning to Bayes discrimination rule, the developed system contains the linear discrimination rule with common covariance matrices and the quadratic discrimination rule under different covariance matrices. Also the system contains k-nearest neighbor method to directly estimate a posterior probability of each class. The result of case studies with the data acquired from Pyung-tak LNG pump and experimental setup show that the system developed in this research is very effective and useful.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2086-2097
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• 2012

A terminal-based dynamic clustering algorithm is proposed in a multi-cell scenario, where the user could select the cooperative BSs from the predetermined static base stations (BSs) set based on dynamic channel condition. First, the user transmission rate is derived based on linear precoding and per-cell feedback scheme. Then, the dynamic clustering algorithm can be implemented based on two criteria: (a) the transmission rate should meet the user requirement for quality of service (QoS); (b) the rate increment exceeds the predetermined constant threshold. By adopting random vector quantization (RVQ), the optimized number of cooperative BSs and the corresponding channel conditions are presented respectively. Numerical results are given and show that the performance of the proposed method can improve the system resources utilization effectively.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.310-312
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• 2006

유비쿼터스 센서 네트워크(Ubiquitous Sensor Networks: USNs)환경은 주변 공간의 상황을 인식할 수 있고, 인식한 상황을 바탕으로 적절한 시기에 필요한 정보를 올바른 사용자나 사용자 장치에게 제공해주는 지능적인 환경을 제공한다. 이러한 환경에서 사용자의 위치정보는 매우 중요한 요소로 부각되고 있고 위치측정기술도 개발되고 있다. 하지만, 사용자의 위치정보를 측정하는 것은 다른 한편으로 사용자의 프라이버시를 침해 할 수도 있는 심각한 보안상의 문제점을 야기시킬 수 있다. 본 논문에서는 CBS(Covert Base Station)을 이용하여 베이스스테이션만이 노드의 위치를 파악할 수 있도록 하고, 위치를 파악하는 동안 노드 및 노드 주변의 다른 어떤 노드에게도 위치가 노출되지 않도록 하기 위한 (n, t+1) 쓰레시홀드 암호화 기법을 제시한다.