• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.297-304
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• 2001

Procurement decisions for inspection equipment are often made heavily based on the initial purchase price instead of the effects of inspection cost, equipment calibration and utilization over the lifetime. Cost of ownership(COO) models that take into account all of these cost factors together have been developed focusing on a single quality characteristic. In modern manufacturing environment, inspection equipment often can deal with more than one quality characteristic simultaneously. In this paper, we propose the revised COO model for the economic evaluation of the inspection equipment that can accommodate multiple quality characteristics. We also employ an engineering economy model to compare equipments with different life span. Software is developed for handy comparison of the COO of alternative equipments along with sensitivity analysis far the optimal procurement decision.

• Food Science of Animal Resources
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• v.40 no.6
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• pp.896-907
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• 2020

Imaging technique or computer vision (CV) technology has received huge attention as a rapid and non-destructive technique throughout the world for measuring quality attributes of agricultural products including meat and meat products. This study was conducted to test the ability of CV technology to predict the quality attributes of beef. Images were captured from longissimus dorsi muscle in beef at 24 h post-mortem. Traits evaluated were color value (L*, a*, b*), pH, drip loss, cooking loss, dry matter, moisture, crude protein, fat, ash, thiobarbituric acid reactive substance (TBARS), peroxide value (POV), free fatty acid (FFA), total coliform count (TCC), total viable count (TVC) and total yeast-mould count (TYMC). Images were analyzed using the Matlab software (R2015a). Different reference values were determined by physicochemical, proximate, biochemical and microbiological test. All determination were done in triplicate and the mean value was reported. Data analysis was carried out using the programme Statgraphics Centurion XVI. Calibration and validation model were fitted using the software Unscrambler X version 9.7. A higher correlation found in a* (r=0.65) and moisture (r=0.56) with 'a*' value obtained from image analysis and the highest calibration and prediction accuracy was found in lightness (r²_c=0.73, r²_p=0.69) in beef. Results of this work show that CV technology may be a useful tool for predicting meat quality traits in the laboratory and meat processing industries.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.825-830
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• 2004

Kinematic calibration of Gough-Stewart platform using a new measurement device is presented in this paper. The device simultaneously measures components of position and orientation using commercially available gadgets. Additional kinematic parameters are defined to model the sources of inaccuracies for the proposed measurement device. Computer simulations reveal that all kinematic parameters of the Gough-Stewart platform and the additional kinematic parameters of the measurement device can be identified with the partial pose measurements of the device. Results also show that identification is robust for the initial errors and the noise in measurements. The device also facilitates the automation of easurement procedure.

• Journal of Sensor Science and Technology
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• v.11 no.4
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• pp.239-246
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• 2002

In this paper a new design of multi-layer perceptron(MLP) for camera calibration is proposed. Most existing techniques determine a transformation from 3D spatial points to their image points and camera parameters are tried to be estimated from the transformation. The technique proposed here, on the other hand, determines rays of sight uniquely from image points and parameters are estimated from the relationship using an MLP. By this approach projection and back-projection can be done more straightforwardly. Being based on a geometric model, a network design process becomes less ambiguous, which is a clear merit compared to other neural net based techniques. An MLP designed according to the technique proposed showed fast and stable learning in tests under various conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1458-1463
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• 2004

Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.125-134
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• 2003

Standard estimation methods for linear mixed models are sensitive to influential observations. However, tools and concepts for linear mixed model diagnostics are rudimentary until now and research is heavily demanded in linear mixed models. In this paper, we consider two diagnostics to evaluate the effects of individual observations in the estimation of fixed effects for linear mixed models. Those are Cook's distance and COVRATIO. Results of our limited simulation study suggest that the Cook's distance is not good statistical quantity in linear mixed models. Also calibration point for COVRATIO seems to be quite conservative.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.43-45
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• 2003

소프트웨어 공학이 소프트웨어 시스템에 관한 방법론, 기술 및 툴 등의 유지보수와 개발에 중점을 두어 왔는데 최근에는 프로세스 개선과 프로세스 능력수준의 향상에 초점을 두는 방향으로 발전하면서 CMM 및 SPICE 활동이 증가하고 있다. 이와 같은 심사기법은 대규모의 회사에서 주로 시행되고 있어서 중소규모의 조직을 위한 간략한 심사기법의 도입이 요구되는 있는 상황이다. 본 논문에서 제시하는 심사기법은 CMM 심사를 위한 KPA 설문서의 rating 방법을 응용한 것으로서 SPICE 심사를 받은 국내 기업 중 일부 회사를 대상으로 하였다. 이 방법론에 대한 신뢰성의 평가는 아직 미흡한 상황이다. 이를 위해서 통계학적 접근방법을 도입하였는데 사용된 통계 기법은 상환계수를 통한 가설검정이다. 그 결과 성숙도 설문서(MQ) 선정모델의 적합성을 통계적 기법을 통해서 검증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.423-426
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• 2017

최근 스마트 기기의 사용 증가로 인해 자세 관련 질환도 크게 증가하고 있다. 이는 올바르지 않은 자세로 스마트 기기를 사용하는 것에 기인한 것으로 많은 사람들이 자신의 자세를 인식하지 못한 채 올바르지 않은 자세로 스마트 기기를 사용한다. 본 연구에서는 컴퓨터 및 스마트폰의 사용자가 자신의 앉은 자세 정보를 데이터로 인식하기 위해서 키넥트 센서에서 제공하는 골격 모델의 특징점을 추출하여 사용하였다. 이를 바탕으로 앉은 자세의 각도를 계산하여 자세의 올바름의 정도를 알려주는 앉은 자세 측정값 모델 방법과 이 모델에 기반한 시스템을 제안하였다. 본 논문에서는 제안하는 자세 측정 모델 및 시스템의 설계 및 구현을 설명하였고, 실험을 통해서 제안된 모델의 상용화 가능성을 살펴보았다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1124-1128
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• 1995

This paper presents the appplication of computer vision for the purpose of determing the position of the unknown point in the plane. The presented contrik method is estimate the six view parameters reqresenting the relationship between the image plane coordinates and the real physical coordinates. The estimation of six parameters is indispensable for transforming the 2-dimensional camera coordinates to the 3-dimensional spatial coordinates. Then, the position of unknown point is estimated based on the estimated parameters depending on the cameras. The suitability of this control scheme is demonstrated experimentally by determining of position the unknown point in the plane.