• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.1 s.106
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• pp.40-49
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• 2006

A novel disturbance measurement method, model based disturbance observer (MBDO) for optical disk drives (ODDs), is proposed and the disturbance analysis using the proposed method is performed under various conditions. In ODDs, the quantitative and qualitative analysis for the generated disturbance during normal operation is very important to successful servo loop design. However, the disturbance measurement is difficult, and high precision measurement is necessary. Furthermore, the conventional disturbance measurement method using a LDV (laser Doppler vibrometer) has many difficulties in eccentricity direction due to the vertical movement of an optical disk. To solve this problem, the MBDO is proposed. First, the relationship between the servo loop for ODDs and the generated disturbance are briefly reviewed. Second, the principle of the MBDO is introduced, and the disturbance measurement results, which are measured by the MBDO and a LDV, are compared. In these experiments, test DVD-ROM disks are used to generate quantitative/qualitative disturbance. Then, the disturbance analysis under various conditions is performed using waterfall technique. This technique clearly shows the disturbance trend from the inner part of an optical disk to the outer part of it. Finally, the various disturbances measurement results are summarized and some remarks for it are commented.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.953-958
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• 2013

This study suggests a measurement error model based on skewed normal distribution instead of normal distribution to identify slope parameter properties in a simple liner regression model. We prove that the slope parameter in a simple linear regression model is underestimated.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.39-44
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• 2021

Since the recent Corona 19, the importance of cloud computing is increasing, and at the same time, competition among clouds is intensifying. Cloud companies are competing for survival by promoting various management innovation methods for continuous growth and development amid a rapidly changing business environment. They are also increasingly interested in performance management in their operations and growth. In this paper, we propose Cloud BSC, an IT BSC-based performance measurement model for cloud enterprise performance management. The validity of the proposed model is verified through statistical analysis and causal analysis. Eventually, the proposed model is expected to be utilized as a management evaluation tool that can provide useful performance analysis information to cloud companies.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.38-42
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• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

• Proceedings of the Korean Geotechical Society Conference
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• 1994.09a
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• pp.235-246
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• 1994

At pre-construction design stage, most of the design data are based on the site investigation results or property estimation which often does not provide satisfactory output for the tunnel analysis. Nonlinear FEM tunnel analysis was cariied out by Hoek-Brown model which is principly semi-empirical design method based on insitu rock descriptions, rock test results as well as field measurement data. The results of the analytical methods from Hoek-Brown model and Mohr-Coulomb model are compared with the sige measurement data from two-NATM tunnel construction sites. It was found that the Hoek-Brown model can be satisfactorily adopted as a feed back analysis technique in order to examin the safety of NATM tunnel at any construction stage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8753-8759
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• 2015

Establishment of analysis procedures and validated performance measurements for generator output is required to maintain stable management of generator output in turbine power generation cycle. We developed turbine expansion model and measurement validation model for the performance calculation of generator using turbine output based on ASME (American Society of Mechanical Engineers) PTC (Performance Test Code). We also developed verification model for uncertain measurement data related to the turbine and generator output. Although the model in previous researches was developed using artificial neural network and kernel regression, the verification model in this paper was based on algorithms through Support Vector Machine (SVM) model to overcome the problems of unmeasured data. The selection procedures of related variables and data window for verification learning was also developed. The model reveals suitability in the estimation procss as the learning error was in the range of about 1%. The learning model can provide validated estimations for corrective performance analysis of turbine cycle output using the predictions of measurement data loss.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.229-239
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• 2008

This study aims to suggest a performance measurement model reflecting the characteristics of safety evaluation system, especially the model for return manufacturing related to safety, and to develop the S-BSC(Safety-Balanced ScoreCard) measurement model using a weight lifetime value to which a relative weight is applied by using AHP based on the BSC.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.408-410
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• 2009

We present an efficient and robust measurement model for visual tracking. This approach builds on and extends work on subspace representations of measurement model. Subspace-based tracking algorithms have been introduced to visual tracking literature for a decade and show considerable tracking performance due to its robustness in matching. However the measures used in their measurement models are often restricted to few approaches. We propose a novel measure of object matching using Angle In Feature Space, which aims to improve the discriminability of matching in subspace. Therefore, our tracking algorithm can distinguish target from similar background clutters which often cause erroneous drift by conventional Distance From Feature Space measure. Experiments demonstrate the effectiveness of the proposed tracking algorithm under severe cluttered background.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.148-154
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• 2012

The purpose of this study is to develop measurement items for quality cost in service industries. Quality cost is necessary in order to evaluate quality management activities. It is clear that the quality cost in service industry is different from manufacturing industry. Generally, in service industries, quality cost is very difficult to assess because it has a unique characteristics. This paper proposes an effective method for measuring quality cost in service industries. Based on the PAF (Prevention, Appraisal, Failure) cost model, we utilizes the concept of five demensions in SERVQUAL which are tangibles, reliability, responsiveness, assurance, empathy. This paper also presents to a standard model for quality cost measurement in service industries.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.485-499
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• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.