• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1792-1802
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• 1996

The analysis of prepositional phrases in English-to Korean machine translation has problem on the PP-attachment resolution, semantic analysis, and acquisition of information. This paper presents an analysis system for prepositional phrases, which solves the problem. The analysis system consists of the PP-attachment resolution hybrid system, semantic analysis system, and semantic feature generator that automatically generates input information. It provides objectiveness in analyzing prepositional phrases with the automatic generation of semantic features. The semantic analysis system enables to generate natural Korean expressions through selection semantic roles of prepositional phrases. The PP-attachment resolution hybrid system has the merit of the rule-based and neural network-based method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.3
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• pp.619-625
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• 2000

A many control techniques have been proposed in order to improve the control performance of the discrete-time domain control system. In the position control system, the output of a controller is generally used as the input of a plant but the undesired noise is included in the output of a controller. Therefore there is a need to used a precompensator for rejecting the undesired noise. In this paper, The expanded I-PD control system with a precompensator is constructed. The precompensator and I-PD controller are designed by a neural network and these coefficients are changed automatically to be a desired response of system when the response characteristic of system is changed under a condition.

• Journal of Power Electronics
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• v.8 no.3
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• pp.228-238
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• 2008

Many induction motor broken bar diagnosis methods are based on evaluating special components in machine signals spectrums. Current, power, flux, etc are among these signals. Frequencies related to a broken rotor fault are slip dependent, therefore, correct diagnosis of fault - especially when obtrusive frequency components are present - depends on accurate determination of motor velocity and slip. The traditional methods typically require several sensors that should be pre-installed in some cases. This paper presents a diagnosis method based on only a vibration sensor. Motor velocity oscillation due to a broken rotor causes frequency components at twice slip frequency difference around speed frequency in vibration spectrum. Speed frequency and its harmonics as well as twice supply frequency, can easily and accurately be found in a vibration spectrum, therefore th motor slip can be computed. Now components related to rotor fault can be found. It is shown that a trained neural network - as a substitute for an expert person - can easily categorize the existence and the severity of a fault according to the features extracted from the presented method. This method requires no information about th motor internal and has been able to diagnose correctly in all the laboratory tests.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.26-34
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• 1996

One of the challenging tasks in visual inspection using CCD camera is to identify surface defects in an image with complex textured backgeound. In microscopic view, the surface of real objects shows regular or random textured patterns. In this paper, we present a visual inspection algorithm to extract abnormal surface defects in an image with textured background. The algorithm uses the space and frequency information at the same time by introducing the Dominant Frequency Map(DFM) which can describe the frequency characteristics of every small local region of an input image. We demonstrate the feasibility and effectiveness of the method through a series of real experiments for a 14" TV CRT mold. The method successfully identifies a variety of infinitesimal defects, whose size is larger than $50\mu\textrm{m}$, of the mold. The experimental results show that the DFM based method is less sensitive to the environmental changes, such as illumination and defocusing, than conventional vision techniques.ques.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.187-192
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• 2008

A saturation and deadzone compensator is designed for robot systems using fuzzy logic (FL) and neural network (NN). The classification property of FL system and the function approximation ability of the NN make them the natural candidate for the rejection of errors induced by the saturation and deadzone. The tuning algorithms are given for the fuzzy logic parameters and the NN weights, so that the saturation and deadzone compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded parameter estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The NN saturation and FL deadzone compensator is simulated on a robot system to show its efficacy.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.4
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• pp.112-117
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• 2004

This paper describes the analysis of the UHF signal characteristics due to the partial discharge sources which can exist in a GIS. For the experiment, a model GIS was made and 5 types of discharge source were created as follows; corona discharge, surface discharge, void discharge, discharge due to free particle, discharge from floating electrode. The frequency spectra and the phase characteristics of UHF signals were induced by UHF signal analysis. The results were quantified to systematically adapt to analyze the PD sources in the GIS and utilized as algorithm data based on the neural network for Back-Propagation Algorithm with a multi-layer structure. The perception rate of the constructed algorithm showed approximately 94[%] and 82[%] in learning and testing data, respectively.

• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.11-17
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• 2002

The purpose of this study was to present the method to choose the optimization machining condition for the wire electric machine. This was completed by examining the ever-changing quality of the material and by improving the function of the wire electric discharge machine. Precision metal mold products and the unmanned wire electric discharge machining system were used and then applied in industrial fields. This experiment uses the wire electric discharge machine with brass wire electrode of 0.25mm. To measure the precision of the machining surface, average values are obtained from 3 samples of measures of center-line average roughness by using a third dimension gauge and a stylus surface roughness gauge. In this experiment, we changed no-node voltage to 7 and 9, pulse-on-time to $6{\mu}s,\;8{\mu}s$ and $10{\mu}s$, pulse-off-time to $8{\mu}s,\;10{\mu}s$ and $13{\mu}s$, and experimented on wire tension at room temperature by 1000gf, 1200gf, and 1400gf, respectively.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1035-1045
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• 2004

In this paper, we describe a method that can recognize gestures and evaluate the degree of the gestures from sequential gesture images by using Gesture Feature Space. The previous popular methods based on HMM and neural network have difficulties in recognizing the degree of gesture even though it can classify gesture into some kinds. However, our proposed method can recognize not only posture but also the degree information of the gestures, such as speed and magnitude by calculating distance among the position vectors substituting input and model images in parametric eigenspace. This method which can be applied in various applications such as intelligent interface systems and surveillance systems is a simple and robust recognition algorithm.

• Korean Journal of Artificial Intelligence
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• v.5 no.2
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• pp.43-53
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• 2017

In this paper, the pattern of extracting the same expression is proposed by using the Android intelligent device to identify the facial expression. The understanding and expression of expression are very important to human computer interaction, and the technology to identify human expressions is very popular. Instead of searching for the emoticons that users often use, you can identify facial expressions with acamera, which is a useful technique that can be used now. This thesis puts forward the technology of the third data is available on the website of the set, use the content to improve the infrastructure of the facial expression recognition accuracy, in order to improve the synthesis of neural network algorithm, making the facial expression recognition model, the user's facial expressions and similar e xpressions, reached 66%.It doesn't need to search for emoticons. If you use the camera to recognize the expression, itwill appear emoticons immediately. So this service is the emoticons used when people send messages to others, and it can feel a lot of convenience. In countless emoticons, there is no need to find emoticons, which is an increasing trend in deep learning. So we need to use more suitable algorithm for expression recognition, and then improve accuracy.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.1-7
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• 2014

Brushless Direct Current(BLDC) Motor is essential to measure a rotor position because of that this motor type needs to synchronize the rotor's position and changeover phase current instead of a brush and commutator used on the existing dc motor. Recently, many researches have studied on sensorless control drive for BLDC motor. The conventional control methods are a compensation value dq, Kalman filter, Fuzzy logic, Neurons neural network, and the like. These methods has difficulties of detecting BEMF accurately at low speed because of low BEMF voltage and switching noise. And also, the operation is long and complex. So, it is required a high-performance microprocessor. Therefore, it is not suitable for a small BLDC motor sensorless drive. This paper presents control methods suitable for economic small BLDC motor sensorless drive which are an improved design of the BEMF detection circuit, simplifying a complex algorithm and computation time reduction. The improved motor sensorless drive is verified stability and validity through being designed, manufactured and analyzed.