• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.6
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• pp.692-696
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• 2011

A clutch is a very important component when engine starts and gear shifting is needed. The clutch the most commonly used is the dry clutch. This type of clutch has pads, and they are worn after disengagement of clutch little by little. The characteristics of the clutch changes as these pads wear, so wear needs to be measured, and the clutch should be controlled for proper operation. In this study, the clutch contact point estimation algorithm has been developed. From this algorithm, clutch force map changes depending on wear, and the clutch operates properly. We also see the shifting transient of a vehicle for drivability with throttle valve position control and synchronizer movement.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.305-307
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• 2000

이 논문은 OGC에서 제안하는 3계층 구조의 웹 매핑 테스트베드(Web Mapping Testbed) 환경에서 각 계층간의 통신량과 데이터 변화량으로 인한 속도 저하 문제를 해결하고자 한다. 이를 위해, 다수의 클라이언트가 일정 시간 내에 공통으로 접근하는 지도 영역에 대한 미들웨어 컴포넌트들의 중복된 작업 수를 줄이기 위해 맵 서버 컴포넌트들 간에 공유 캐쉬를 사용하는 구조를 설계 및 구현한다. 이 논문에서 제시하는 미들웨어의 캐쉬 구조는 전체 데이터 세트의 영역을 일정 간격의 그리드 셀로 나누어 관리함으로써 캐쉬 단위의 관리 비용을 줄이고 캐쉬를 효율적으로 사용한다. 또한, 기존의 교체 전략 기법을 접목하여, 다수의 클라이언트의 관심 대상인 영역을 중심으로 캐쉬를 유지하기 위해 접근 빈도수와 최근 사용 시간을 고려한 교체 전략을 사용한다.

• Journal of Power System Engineering
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• v.14 no.1
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• pp.40-46
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• 2010

This paper shows the development process for measuring three-dimensional flow velocity components in a web-browser. The system is developed in an embeddable C/C++ interpreter Ch and Ch-CGI toolkit. The interface for the web-based measurement system consists of a set of web HTML files and Ch files for CGI. All of data in web browser are passed to Ch-CGI script to generate the output of new HTML file. PC-Server and PC-Client can submit measurement parameters and receive the text/graphical results each other. PC-Client can control the test equipment by using a parameters that received from PC-Server. It also can pass the test results between the web-based measurement system. In summary, the designed measurement system is evaluated, the outputs shown well on the web browser.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.822-826
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of 10 persons show that the proposed method yields high recognition rates.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.69-72
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• 2002

본 논문에서 화자공간모델 evolution에 기반한 continuous density hidden Markov model (CDHMM)의 online 적응에 대한 새로운 기법을 제안한다. 학습화자의 a priori knowledge을 나타내는 화자공간모델은 factor analysis (FA) 또는 probabilistic principal component analysis (PPCA)와 같은 은닉변수모델(latent variable model)에 의해 효과적으로 나타내어진다. 은닉 변수모델은 화자공간모델뿐아니라 CDHMM 파라메터의 ajoint prior분포를 표시함으로, maximum a posteriori(MAP)적응기법에 직접 적용되어진다. 화자공간모델의 hyperparameters와 CDHMM파라메터를 동시에 순차적으로 적응하기 위해 quasi-Bayes (QB)추정 기술에 기반한 online 적응기법을 제안한다. 연속숫자음 인식과 관련된 화자적응 실험을 통해 제안된 기법은 적은 적응데이터에서 좋은 성능을 나타내며, 데이터가 증가함에 따라 성능이 지속적으로 증가함을 보여준다.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.369-378
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• 2010

The creation of the hydraulic turbine flow factor map will undoubtedly benefit its design by decreasing both the design cycle time and product cost. In this paper, the geometry and flow variables, which effectively affect the flow factor, are proposed, analyzed and determined. These flow variables are further used to create the operating condition maps by using different model approaches categorized into Response Surface Method (RSM) and Artificial Neural Network (ANN). The accuracies of models created by different approaches are compared and the performances of model approaches are analyzed. The influences of chosen variables and the combination of Principle Component Analysis (PCA) and model approaches are also studied. The comparison results between predicted and actual flow factors suggest that two-hidden-layer Feed-forward Neural Network (FFNN), and one.hidden-layer FFNN with PCA has the best performance on forming this mapping, and are accurate sufficiently for hydraulic turbine design.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.971-976
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• 2000

In this paper a new method for head gesture recognition is proposed. A the first stage, face image data are transformed into low dimensional vectors by principal component analysis (PCA), which utilizes the high correlation between face pose images. The a self organization map(SM) is trained by the transformed face vectors, in such a that the nodes at similar locations respond to similar poses. A sequence of poses which comprises each model gesture goes through PCA and SOM, and the result is stored in the database. At the recognition stage any sequence of frames goes through the PCA and SOM, and the result is compared with the model gesture stored in the database. To improve robustness of classification, probabilistic relaxation labeling(PRL) is used, which utilizes the contextural information imbedded in the adjacent poses.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.114-117
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• 2003

본 논문에서는 video stream내의 움직이는 객체 정보를 추정하고 동적 GTM(genetic tree-map) 알고리즘을 사용하여 얼굴 영역 검출 기법을 제안한다. 기존의 일반적인 객체 추정 기법은 클러스터(cluster)과정을 통하여 영상 정보를 분할하고 그 중 움직이는 객체 부분을 복원함으로서 추정하였다. 제안하는 기법은 BMA(block matching algorithm)［1］ 알고리즘을 사용하여 video stream 에서 움직이는 객체 정보를 얻고 클러스터 알고리즘으로 PCA(principal component analysis)를 사용한다. PCA 기법은 입력 데이터에 관해 통계적 특성을 이용하여 주성분을 찾는다. 주축과 영역분할 알고리즘을 사용하여 데이터를 분할하고, 분할된 객체 정보를 사용하여 특정 객체만을 추정하는 것이 가능하다. 이렇게 추정된 객체를 얼굴영역의 feature에 대하여 신경망 학습인 동적 GTM 알고리즘을 사용하여 생성된 동적 GTM 맵의 정보에 따라 객체의 얼굴영역만을 추출해 낼 수 있다［2-6］.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.726-732
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• 2013

It is required for UGV(Unmanned Ground Vehicle) to have a LPP(Local Path Plan) component which generate a local path via the center of road by analyzing binary map to travel autonomously unpaved road in rough environment. In this paper, we present the method of boundary estimation for unpaved road and a local path planning method based on RANGER algorithm using the estimated boundary. In specially, the paper presents an approach to estimate road boundary and the selection method of candidate path to minimize the problem of zigzag driving based on Bayesian probability reasoning. Field test is conducted with scenarios in rough environment in which bush, tree and unpaved road are included and the performance of proposed method is validated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.127-130
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• 2005

There are many methods in feature extraction have been developed. Recently, principal components analysis (PCA) and independent components analysis (ICA) is introduced for doing feature extraction. PCA and ICA linearly transform the original input into new uncorrelated and independent features space respectively In this paper, the feasibility of using nonlinear feature extraction will be studied. This method will employ the PCA and ICA procedure and adopt the kernel trick to nonlinearly map the data into a feature space. The goal of this study is to seek effectively useful feature for faults classification.