• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.685-688
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• 2004

This paper addresses the study on developing the angular vibration calibration system which requires the highly accurate measurement technique of the amplitude and period of an oscillating angular motion. Two developed models for the low and high frequency ranges are introduced and their main features are also compared. In addition to the angular vibration exciters, a new measurement method, referred to the 'equi-angle sampling method', is proposed and its theoretical backgrounds are introduced. The proposed method is shown to provide much less measurement uncertainty, compared the fringe counting method. Experimental results demonstrate what amount of angular vibration amplitude measurement uncertainty is improved by suing the proposed equi-angle sampling method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.285-292
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• 1996

In the case of existence of second-hand market, some methods for economic depreciation measurement have been developed. Among them, we consider two method. Those are Box -Cox model by Halten and Wykoff and Ratio method of T-factor by Iowa State University. Here, we suggest a new measurement method of economic depreciation based on the above two methods. According to the new method, we can get the failure rate of a equipment under the appropriate assumption. Then we can measure the economic depreciation more simply.

• International Journal of Advanced Culture Technology
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• v.1 no.2
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• pp.1-6
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• 2013

In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.433-438
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• 2001

Noise is one of the major environmental problems in human life. To reduce the noise emitted from the control valve it is necessary to develop the measurement method, measurement system, analysis method applicable to the field. In this study IEC and ISO standards were investigated and measurement method for the valve noise was proposed. Noise from the valve was measured in the reverberation room and sound power level was calculated. The sound power level increased as the flow rate and pressure difference increased. The noise characteristics are useful to predict valve noise for given conditions, to compare the performance of different valves and to develope low-noise valves.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1485-1492
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• 2015

This paper proposes a double frequency method using FTP(Fourier Transform Profilometry) in fringe projection techniques for 3D measurement systems. In fringe projection techniques, fringe pattern images are projected and captured, and then object is measured by analysing phase. PMP(Phase Measuring Profilometry) for analysing phase provides high-resolution and is robust to object's reflection and background intensities. However, the measurement range is narrow due to 2π ambiguity. In order to overcome this problem, a double frequency method is often used. This method can widen the range of measurement while maintaining the high-resolution, but the measurement time is taken about twice due to grab 2 times number of images. The proposed double frequency method using FTP requires an additional image for resolving 2π ambiguity. The proposed method effectively reduces the measurement time while maintaining the same accuracy.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.165-175
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• 2003

The concept of measurement uncertainty has been recognised for many years since "Guide to the Expression of Uncertainty in Measurement" was published 1993 by ISO. This study firstly propose the mathematical model to evaluate uncertainty considering the dispersion of samples because the mathematical model of a measurement is an important to evaluate uncertainty, and it must contains every quantify which contribute significantly to uncertainty in the measurement result. Secondly the standard uncertainty of the result of a measurement, namely combined standard uncertainty is evaluated using the law of propagation of uncertainty, what is termed in GUM method. In GUM method, a measurand is usually approximated by a linear function of its variables by the transforming its input quantities. Furthermore central limit theorem is applied to the input quantity. However the mathematical model of a measurement is generally not always a linearity function, and a distribution function of input or output quantity is not necessarily normal distribution. Then, in some cases GUM method is not favorable to evaluate a measurement uncertainty. Therefore this study propose a new method and its algorithm which use the Monte-carlo simulation to evaluate a measurement uncertainty in both case of linearity or non-linearity function. function.

• 한국가시화정보학회:학술대회논문집
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• 2001.12a
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• pp.62-74
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• 2001

Present paper describes the principles of PIV measurement approaching from the analytical view, which enables to explain the general form of principles covering all the PIV measurement, and that gives theoretical basis for its higher measurement performances. The explanation of the measurement principles started from the definition of governing equation in differential form as same as the gradient method, and the integral along the particle path line was executed to show the principle of the correlation method with same basis. The integral processes clearly shows the analytical reason why the correlation peak gives the terminal point of path line, and how the effects of deformation and rotation of fluid appears in the correlation map. These results have no differences from our experiences and understandings of the conventional PIV measurement definition in final form. However, the analytical approach enable to understand those facts a priori, and it makes easy to achieve the innovative higher performances of measurement. Analytical explanation clearly shows the behavior of the residual errors caused by the fluid motion, and it enables to analyze the measurement uncertainty theoretically.

• Structural Engineering and Mechanics
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• v.47 no.3
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• pp.361-381
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• 2013

A Bayesian probabilistic method is proposed for online estimation of the process noise and measurement noise parameters for Kalman filter. Kalman filter is a well-known recursive algorithm for state estimation of dynamical systems. In this algorithm, it is required to prescribe the covariance matrices of the process noise and measurement noise. However, inappropriate choice of these covariance matrices substantially deteriorates the performance of the Kalman filter. In this paper, a probabilistic method is proposed for online estimation of the noise parameters which govern the noise covariance matrices. The proposed Bayesian method not only estimates the optimal noise parameters but also quantifies the associated estimation uncertainty in an online manner. By utilizing the estimated noise parameters, reliable state estimation can be accomplished. Moreover, the proposed method does not assume any stationarity condition of the process noise and/or measurement noise. By removing the stationarity constraint, the proposed method enhances the applicability of the state estimation algorithm for nonstationary circumstances generally encountered in practice. To illustrate the efficacy and efficiency of the proposed method, examples using a fifty-story building with different stationarity scenarios of the process noise and measurement noise are presented.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.168-178
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• 2021

Objective: To provide an automatic method for segmentation and diameter measurement of type B aortic dissection (TBAD). Materials and Methods: Aortic computed tomography angiographic images from 139 patients with TBAD were consecutively collected. We implemented a deep learning method based on a three-dimensional (3D) deep convolutional neural (CNN) network, which realizes automatic segmentation and measurement of the entire aorta (EA), true lumen (TL), and false lumen (FL). The accuracy, stability, and measurement time were compared between deep learning and manual methods. The intra- and inter-observer reproducibility of the manual method was also evaluated. Results: The mean dice coefficient scores were 0.958, 0.961, and 0.932 for EA, TL, and FL, respectively. There was a linear relationship between the reference standard and measurement by the manual and deep learning method (r = 0.964 and 0.991, respectively). The average measurement error of the deep learning method was less than that of the manual method (EA, 1.64% vs. 4.13%; TL, 2.46% vs. 11.67%; FL, 2.50% vs. 8.02%). Bland-Altman plots revealed that the deviations of the diameters between the deep learning method and the reference standard were -0.042 mm (-3.412 to 3.330 mm), -0.376 mm (-3.328 to 2.577 mm), and 0.026 mm (-3.040 to 3.092 mm) for EA, TL, and FL, respectively. For the manual method, the corresponding deviations were -0.166 mm (-1.419 to 1.086 mm), -0.050 mm (-0.970 to 1.070 mm), and -0.085 mm (-1.010 to 0.084 mm). Intra- and inter-observer differences were found in measurements with the manual method, but not with the deep learning method. The measurement time with the deep learning method was markedly shorter than with the manual method (21.7 ± 1.1 vs. 82.5 ± 16.1 minutes, p < 0.001). Conclusion: The performance of efficient segmentation and diameter measurement of TBADs based on the 3D deep CNN was both accurate and stable. This method is promising for evaluating aortic morphology automatically and alleviating the workload of radiologists in the near future.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1479-1484
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• 2009

It is commonly recognized to need performance management for successful construction project. PPC measurement of Last Planner System is one of construction project measurement method. PPC measurement is quantitatively assessment to go through construction, and that is not completely to be trusted when compare a project with another or an individual case work with another in same project. According to, purpose of this study is comparison indicator establishment that compare project with another or an individual case work with another it is not use PPC measurement for quantitatively assessment to go through construction. The procedure of this study is derive of the point at issue of existing PPC measurement for a aim PPC measurement in this study expenditure and select weight about that and it is applied to actually construction.