• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.959-962
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• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• Current Optics and Photonics
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• v.7 no.4
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• pp.337-344
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• 2023

Three-point bending is the main method for measuring the elastic modulus of a thin plate. Although various displacement transducers may be used to measure the bending, these are single-point measurements, and it is difficult to eliminate the error caused by eccentric load and shear force. Error-correction models for the elastic modulus of quartz glass using digital speckle interferometry are proposed for eccentric load and shear force. First, the positional misalignment between maximum deflection and load is analyzed, and the error caused by eccentric load is corrected. Then, the additional displacement caused by shear force at different positions of the quartz glass plate is explored. The effect of shear deformation is also corrected, by measuring two points. Since digital speckle interferometry has the advantage of full-field measurement, it can simultaneously obtain deflection data for multiple points to realize error correction. Experimental results are presented to demonstrate that the proposed model can effectively correct the measurement error of the elastic modulus.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.403-412
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• 1993

This paper presents the progress of the development of a nondestructive technique for the classification of normal, septicemic , and cadaver poultry carcasses by the Instrumentation and Sensing Laboratory at Beltsville, Maryland, U.S.A. The Sensing technique is based on the diffuse reflectance spectroscopy of poultry carcasses.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.91-93
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• 1993

This paper introduced an advanced PWM method to drive a variable speed AC motor. With this technique, a switching pattern is determined to minimize the error between a reference signal and feedback signal. In addition to its simplicity of implementation, the proposed technique has the advantage of control led constant voltage per frequency operation.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.10
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• pp.790-793
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• 2011

In this study, the surface modification for a silicon(Si) mold using $CHF_3$ inductively coupled plasma(ICP). The conditions under that plasma was treated a input ICP power 600 W, an operating gas pressure of 10 mTorr and plasma exposure time of 30 sec. The Si mold surface became hydrophobic after plasma treatment in order to $CF_x$(X= 1,2,3) polymer. However, as the de-molding process repeated, it was investigated that the contact angle of Si surface was decreased. So, we attempted to investigate the degradation mechanism of the accurate pattern transfer with increasing the count of the de-molding process using scanning electron microscope (SEM), contact angle, and x-ray photoelectron spectroscopy (XPS) analysis of Si mold surface.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.100-108
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• 2002

A fuzzy logic for collision avoiding navigation of marine vehicles is proposed in this paper. VFF(Virtual Force Field) method, which is used widely in the field of mobile robots, is modifiel to apply to marine vehicles. The method is named MVFF (Modified Virtual Force Field) mothod. The MVFF consists of the determination of the heading angles far track-keeping mode ($\psi_{ca}$)and collision avoidance mode ($\psi_{ca}$). The operator can choose the pattern of the track-keeping mode in the proposed algorithm. The collision avoidance algorithm can handle static and/or moving obstacles. These functons are implemented using fuzzy logic. Various simulation results verify the proposed alogorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.83-86
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• 1998

In this paper, a fuzzy model based on the Polynomial Neural Network(PNN) structure is proposed to estimate the emission pattern for air pollutant in power plants. the new algorithm uses PNN algorithm based on Group Mehtod of Data Handling (GMDH) algorithm and fuzzy reasoning in order to identify the premise structure and parameter of fuzzy implications rules, and the least square method in order to identify the optimal consequence parameters. Both time series data for the gas furnace and data for the NOx emission process of gas turbine power plants are used for the purpose of evaluating the performance of the fuzzy model. The simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• International Journal of Control, Automation, and Systems
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• v.2 no.2
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• pp.171-181
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• 2004

An autonomous navigation algorithm for marine vehicles is proposed in this paper using fuzzy logic under COLREG guidelines. The VFF (Virtual Force Field) method, which is widely used in the field of mobile robotics, is modified for application to the autonomous navigation of marine vehicles. This Modified Virtual Force Field (MVFF) method can be used in either track-keeping or collision avoidance modes. Moreover, the operator can select a track-keeping pattern mode in the proposed algorithm. The collision avoidance algorithm has the ability to handle static and/or moving obstacles. The fuzzy expert rules are designed deliberately under COLREG guidelines. An extensive simulation study is used to verify the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.227-232
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• 2003

Recently, support vector learning attracts an enormous amount of interest in the areas of function approximation, pattern classification, and novelty detection. One of the main reasons for the success of the support vector machines(SVMs) seems to be the availability of global and sparse solutions. Among the approaches sharing the same reasons for success and exhibiting a similarly good performance, we have KFD(kernel Fisher discriminant) approach. In this paper, we consider the problem of function approximation utilizing both predetermined basis functions and the KFD approach for regression. After reviewing support vector regression, semi-parametric approach for including predetermined basis functions, and the KFD regression, this paper presents an extension of the conventional KFD approach for regression toward the direction that can utilize predetermined basis functions. The applicability of the presented method is illustrated via a regression example.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3022-3024
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• 2000

Biometrics is the electronic recognition of individuals achieved through a process of extracting, and then verifying, features which are unique to that individual. This field is rapidly evolving technology that has to be widely adopted in a broad range of applications. Many methods have been studied such as extraction of the facial features, the voice, the vein and even a person's signature. Among biometrics, a hand veins provide large, robust, stable, hidden biometric features. Hand vein patterns have been proven to be absolutely unique by Cambridge Consultants Ltd. Because of this advantage, hand vein recognition are recently developing field in the field of a security.