• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Information Systems Review
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• v.15 no.1
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• pp.45-68
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• 2013

Despite improved technologies, procedures, and regulations, consumers are still uncertain about purchasing online. The objective of this study is to understand uncertainty factors in online shopping and their relationships with the consumers' intention to purchase. For this objective we derived seller anonymity, lack of product transparency, and lack of process transparency as uncertainty factors from previous researches which may affect consumers' perceived uncertainty on online shopping. Then, a causal model was developed to conceptualize the relationships between these uncertainty factors as antecedent variables and consumer's intention to purchase as consequent variable with perceived uncertainty as an intermediary variable. Purchase involvement was used as a moderating variable on the relationship between perceived uncertainty and the intention to purchase online. The model was tested empirically to find meaningful relationships among these variables. The findings indicate that all antecedent variables affect perceived uncertainty significantly and perceived uncertainty negatively affects consumers' intention to purchase. Moreover, the results of analysis show purchase involvement has a significant moderating effect on the relationship between perceived uncertainty and intention to purchase online.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.860-865
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• 2021

A data-based model, such as an AAKR model is widely used for monitoring the drifts of sensors in nuclear power plants. However, since a training dataset and a test dataset for a data-based model cannot be constructed with the data from all the possible states, the model uncertainty cannot be good enough to represent the uncertainty of estimations. In fact, the errors of estimation grow much bigger if the incoming data come from inexperienced states. To overcome this limitation of the model uncertainty, a new measure of uncertainty for a data-based model is developed and the predicted uncertainty is introduced. The predicted uncertainty is defined in every estimation according to the incoming data. In this paper, the AAKR model is used as a data-based model. The predicted uncertainty is similar in magnitude to the model uncertainty when the estimation is made for the incoming data from the experienced states but it goes bigger otherwise. The characteristics of the predicted model uncertainty are studied and the usefulness is demonstrated with the pressure signals measured in the flow-loop system. It is expected that the predicted uncertainty can quite reduce the false alarm by using the variable threshold instead of the fixed threshold.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.10
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• pp.1388-1398
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• 2000

A pipe prover is a flowmeter calibrator used in flow measurement field. Gravimetric and volumetric methods were applied to determine the basic volume of the pipe prover. Uncertainty of its basic volume measurement was evaluated in accordance with the procedure recommended by International Organization for Standardization. The combined standard uncertainty of determining the basic volume was estimated from the sensitivity coefficient and the standard uncertainty of independent variables. It was found that the uncertainties of the weighing and volume measurements have dominant influence on that of the basic volume determination. With the quantitative analysis of the sensitivity coefficient, the contribution of the each variable uncertainty to the combined standard uncertainty of the basic volume is shown clearly.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.4
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• pp.561-571
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• 2001

The standard uncertainty of flowrate measurement is obtained by combining that of independent variables. Gravimetric and volumetric method were applied to determine the flowrate and the standard uncertainties of flowrate measurement by both methods were evaluated in accordance with the procedure recommended by International Organization for Standardization. The combined standard uncertainties of determining the flowrate were estimated from the sensitivity coefficient and the standard uncertainty of independent variables. For practical application, the methods for evaluating and expressing uncertainty in flow measurement were discussed. It was found that the uncertainties of the weighing and time measurement in gravimetric method, the volume and time measurement in volumetric method have dominant influence on that of flowrate measurement. With the quantitative analysis of the sensitivity coefficient, the contribution of the each variable uncertainty to the combined standard uncertainty of flowrate measurement is shown clearly.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.119-123
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• 2009

Recently, a MEMS gyroscope has been broadly fabricated and used due to development of a micromachining. However, there is a difference between the modeling design and the actual product and this difference can lead to the performance variation of a MEMS gyroscope. A classical design method does not exactly estimate the performance of a MEMS gyroscope. Therefore a design process considering the design variable uncertainty has to be employed to design MEMS gyroscope model. In this paper, the equation of motion of a MEMS gyroscope model is obtained to analyze the performance of a MEMS gyroscope and the effects of the design variables on the MEMS gyroscope performance are investigated. Finally the performance of MEMS gyroscope is estimated through a statistical analysis based on sample statistics.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.452-461
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• 2007

Adaptive anti-sway and trajectory tracking control of overhead crane is presented, which utilizes Fuzzy Uncertainty Observer(FUO) and Fuzzy based Variable Structure Control(FVSC). We consider an overhead crane system which can be decoupled into the actuated and unactuated subsystems with its own lumped uncertainty such as parameter uncertainties and external disturbance. First, a new method for anti-sway control using FVSC is proposed to improve the conventional method based on Lyapunov direct method, while a conventional trajectory tracking control law using feedback linearization is directly adopted. Second, FUO is designed to estimate one of the two lumped uncertainties which can compensate both of them, based on the fact that two lumped uncertainties are coupled with each other. Then, an adaptive anti-sway control is proposed by incorporating the proposed FVSC and FUO. Under the condition that the observation error is Uniformly Ultimately Bounded(UUB) within an arbitrarily shrinkable region, the overall closed-loop system is shown to be Globally Uniformly Ultimately Bounded(GUUB). In addition, the Global Asymptotic Stability(GAS) of it is shown under the vanishing disturbance assumption. Finally, the effectiveness of the proposed scheme has been confirmed by numerical simulations.

• Journal of IKEEE
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• v.13 no.1
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• pp.30-35
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• 2009

A new controller which can achieve the asymptotic tracking is proposed for the nonlinear system having a uncertainty in the input coefficient. A high gain observer is used to estimate the state variables when the nonlinear system has a modeling uncertainty. A variable structure control is used to achieve an asymptotic tracking, while ultimate boundness was achieved in the previous work. A Lyapunov analysis is used to justify the our proposal. The performance of proposed method is demonstrated via simulation.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.1982-1984
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• 1997

In this paper, adaptive variable structure control is proposed for Electromagnetic Suspension(EMS). Although variable structure control shows excellent robustness to unstructured modelling uncertainty, such as flux leakage and saturation, it has several drawbacks that severely limit practical applicability such as high control activity and control chattering. To minimize these effects, the mass of the electromagnet and efficiency of levitation force are estimated on-line to reduce the range of system uncertainty. The effectiveness of the proposed control scheme is verified by experimental results using a 1.5kg electromagnet and DSP (TMS320C31).

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.658-663
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• 2003

In deterministic design of feedback controllers for uncertain dynamic systems, the upper bound of the uncertainty is very important to guarantee the stability of the closed loop system. In this paper, we assume that the upper bound of the uncertainty is formulated using a Fredholm integral equation of the first kind, that is, an integral of the product of a predefined kernel with an unknown influence function. We propose an adaptation law that is capable of estimating this upper bound. Using this adaptive upper bound, we design an adaptive variable structure control (AVSC), which guarantees asymptotic stability/ultimate boundedness of uncertain dynamic systems. The illustrative example shows the proposed AVSC is effective for uncertain dynamic systems.