• 한국군사과학기술학회지
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• 제2권2호
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• pp.209-217
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• 1999

In this paper, an integrated S/W system from CAD to optimal design has been suggested and an application to a precision machine tool structure shown. The integrated system is so designed to reduce manual interfacing effort. An object-oriented programming language is used for combining 3-D CAD program, FEM and optimal design tools. In this system parametric modelling technique is applied and users can get the optimum design iteratively without much user intervention. The CAD model is automatically updated when the design parameters are transferred back to the CAD program. Not only design time can be dramatically reduced but unnecessary operation errors avoided by the integration.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.135-137
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• 2005

In servo system demanding precision dynamic characteristics, application of the Permanent Magnet Linear Synchronous Machines (PMLSM) has advantage of analysis convenience by simple geometry and thrust ripple reduction from the sinusoidal back electromotive force and excited stator. Therefore, this paper presents design of surface-mounted PMLSM with slotless iron cored stator according to coil turns to satisfy the rate thrust. Also, from dynamic analysis for servo application of manufactured motor with heavy mass, we offer accurate range of the DC link voltage and acceleration in rate speed. This is applied to speed reference profile considering system characteristics in total length of moving position.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.132-134
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• 2005

The severe problem in improving the positioning precision of a permanent linear synchronous motor(PMLSM) is the large detent force caused by the PM. It is generally an undesired effect that contributes to the torque ripple, vibration and noise of machine. In this paper, the method to reduce detent force according to the mover skew is studied and analyzed using the analytical method. The analytical results are validated by finite clement analyses.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 금형가공,미세가공,플라스틱가공 공동 심포지엄
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• pp.147-152
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• 2005

In recent industry, according to pursuit the miniaturization and high-precision of machine part with development of new technology as IT, BT the development of mold manufacturing technology for mass production is accompanied. In this study, the spiral type injection mold with a $200{\mu}m$ thickness shape is made for investigation of influence for injection molding process variables and the flow length is measured through an experiment. Beside, the result of each experiment Is compared with the analysis result of CAE. Taguchi method is used in this experiment and the obtained data are analyzed using ANOVA method.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
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• pp.259-261
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• 2004

생물학 분야의 문헌으로부터 유전자 및 단백질 이름을 추출하는 기술은 바이오 텍스트 마이닝 분야의 기반 기술로 그 중요성이 점차 증대되고 있다. 이 연구에서는 생물학 분야 문헌의 초록으로부터 하나의 토큰으로 구성된 single gene name은 물론 여러 개의 토큰으로 이루어진 multi gene name까지 유전자나 단백질의 이름을 자동으로 추출하는 시스템 TagGeN(Tagger for Gene Name)을 제안한다. TagGeN은 기존의 태거와 달리, 문자나 숫자 이외의 기호를 포함한 유전자나 단백질 이름의 품사 처리에 있어 개선 방안을 제시하고, 여러 토큰으로 이루어진 이름의 인식에 있어 나란한 두 토큰이 갖는 태그 정보를 이용한 조건부 확률에 근거하여 Markov 모델을 도입한다. 위와 같은 개선방안을 구현한 TagGeN은 성능면에서 기존의 유사시스템에 비해 recall 20.8%, precision 4.7%의 성능향상을 보임으로써 본 연구에서 제안한 방법론의 효과를 입증한다.

• 드라이브 ㆍ 컨트롤
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• 제11권3호
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• pp.1-6
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• 2014

In forklifts, the machine performance is largely depended on the transmission performance. The aim of this paper is to develop a complete model of transmission control valve (TMV) system of a typical forklift using AMESim simulation tool. By using the developed TMV model, it becomes easy to investigate the system concept, working principle, and performance. In addition, an optimization on the TMV structure can be achieved by using this model with tunable parameters. Simulations have been carried out in a comparison with the actual experiments to verify the model.

• 한국기계기술학회지
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• 제13권4호
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• pp.49-55
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• 2011

Recently, various efforts to make more speedy and precision machine tool to improve productivity and also various efforts to solve environmental problem are going on, so that dry cutting in manufacturing industry, which needs environmental conscious design and development of manufacturing technique, is becoming a very important assignment to solve. Because dry cutting does not use cutting fluid, we need other methods that can be used instead of cutting fluid, which does cooling, lubricating, chip washing, and anti-corrosion. Especially, because turning is a continuous work, the consideration of tool life and surface roughness due to continuous heat and poor lubrication is important. The purposes of this paper are the consideration of how well the compressed air can work instead of cutting fluid, and also the development of the method to select the optimum machining condition by the minimum numbers of experiments through the Taguchi method.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 춘계학술발표대회
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• pp.429-431
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• 2012

Vehicle-logo recognition technology is very important in vehicle automatic recognition technique. The intended application is automatic recognition of vehicle type for secure access and traffic monitoring applications, a problem not hitherto considered at such a level of accuracy. Vehicle-logo recognition can improve Vehicle type recognition accuracy. So in this paper, introduces how to vehicle-logo recognition. First introduces the region of the license plate by algorithm and roughly located the region of car emblem based on the relationship of license plate and car emblem. Then located the car emblem with precision by the distance of Hausdorff. On the base, processing the region by morphologic, edge detection, analysis of connectivity and pick up the PCA character by lowing the dimension of the image and unifying the PCA character. At last the logo can be recognized using the algorithm of support vector machine. Experimental results show the effectiveness of the proposed method.

• Journal of Power Electronics
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• 제19권2호
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• pp.443-453
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• 2019

As the core component of transmission systems, converters are very prone to failure. To improve the accuracy of fault diagnosis for wind power converters, a fault feature extraction method combined with a wavelet transform and compressed sensing theory is proposed. In addition, an improved AdaBoost-SVM is used to diagnose wind power converters. The three-phase output current signal is selected as the research object and is processed by the wavelet transform to reduce the signal noise. The wavelet approximation coefficients are dimensionality reduced to obtain measurement signals based on the theory of compressive sensing. A sparse vector is obtained by the orthogonal matching pursuit algorithm, and then the fault feature vector is extracted. The fault feature vectors are input to the improved AdaBoost-SVM classifier to realize fault diagnosis. Simulation results show that this method can effectively realize the fault diagnosis of the power transistors in converters and improve the precision of fault diagnosis.

• Journal of Multimedia Information System
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• 제6권2호
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• pp.87-90
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• 2019

Machine learning techniques have been applied in almost all the domains of human life to aid and enhance the problem solving capabilities of the system. The field of medical science has improved to a greater extent with the advent and application of these techniques. Efficient expert systems using various soft computing techniques like artificial neural network, Fuzzy Logic, Genetic algorithm, Hybrid system, etc. are being developed to equip medical practitioner with better and effective diagnosing capabilities. In this paper, a comparative study to evaluate the predictive performance of subtractive clustering based ANFIS hybrid system (SCANFIS) with Fuzzy C-Means (FCM) based ANFIS system (FCMANFIS) for Alzheimer disease (AD) has been taken. To evaluate the performance of these two systems, three parameters i.e. root mean square error (RMSE), prediction accuracy and precision are implemented. Experimental results demonstrated that the FCMANFIS model produce better results when compared to SCANFIS model in predictive analysis of Alzheimer disease (AD).