• East Asian Economic Review
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• v.28 no.1
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• pp.95-140
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• 2024

This study empirically investigates the international transmission of China's uncertainty shocks. It estimates a time-varying parameter Bayesian global structural vector autoregressive model (TVP-BGVAR) using time series data for 33 countries to evaluate heterogeneous international linkage across countries and time. Uncertainty shocks are identified via sign restrictions. The empirical results reveal that an increase in uncertainty in China negatively affects the global economy, but those effects significantly vary over time. The effects of China's uncertainty shocks on the global economy have been significantly altered by China's WTO accession, the global financial crisis, and the recent US-China trade conflict. Furthermore, the effects of China's uncertainty shocks, typically on inflation, differ significantly across countries. Moreover, Trade openness appears crucial in explaining heterogeneous GDP responses across countries, whereas the international dimension of monetary policy appears to be important in explaining heterogeneous inflation responses across countries.

• Architectural research
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• v.8 no.2
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• pp.27-36
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• 2006

Structural uncertainties are generally modeled using probabilistic approaches in order to quantify uncertainties in behaviors of structures. This uncertainty results from the uncertainties of structural parameters. Monte Carlo methods have been usually carried out for analyses of uncertainty problems where no analytical expression is available for the forward relationship between data and model parameters. In such cases any direct mathematical treatment is impossible, however the forward relation materializes itself as an algorithm allowing data to be calculated for any given model. This study addresses a new method which is utilized as a basis for the uncertainty estimates of structural responses. It applies double uniform random numbers (i.e. DURN technique) to conventional Monte Carlo algorithm. In DURN method, the scenarios of uncertainties are sequentially selected and executed in its simulation. Numerical examples demonstrate the beneficial effect that the technique can increase uncertainty degree of structural properties with maintaining structural stability and safety up to the limit point of a breakdown of structural systems.

• Environmental and Resource Economics Review
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• v.14 no.1
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• pp.75-100
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• 2005

This study attempts to empirically investigate the respondents' preference uncertainty involved in stating their willingness to pay (WTP). In the contingent valuation (CV) survey, we employed two approaches using two split samples. The respondents of one sample were given the opportunity to express intensity of preference through polychotomous choice (PC) WTP question. Those of the other sample were given a follow-up question of confidence measure (0~100%). By incorporating the two elicited degrees of preference uncertainty into examining the WTP responses, we take a comparison of the two approaches in terms of the goodness-of-fit of the examination and the efficiency of the mean WTP estimates. In comparing the DC model with the PC models, the DC model provides more efficient estimates. Moreover, the conventional DC model give some gains in terms of the goodness-of-fit and efficiency in comparing with the PC model most similar to this model. In this specific study, incorporating the preference uncertainty in DC model results greater estimates than conventional DC model without loss of goodness-of-fit and efficiency. This implies that the consideration of preference uncertainty on DC model could correct underestimating. We conclude that DC model provides a better estimate of WTP and preference uncertainty could be a critical information on the DC-CV estimation.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.6
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• pp.838-844
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• 2022

In this paper, an experimental study was conducted on the energy efficiency ratio of performance for air source heat pump. The energy efficiency ratio presents the operating efficiency of heat pump performance. In order to improve reliability in the energy efficiency ratio test of air source heat pump, the measurement uncertainty of the instrument was estimated. Measurement uncertainty refers to the uncertainty of a measurement, estimates the range in which the expected value of the measurement can be within a certain confidence level, and suggests a range in which the measured representative value is incorrect. The measurement uncertainty for the energy efficiency ratio test of air source heat pump was calculated and the measured results were presented.

• Transactions of the Korean hydrogen and new energy society
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• v.32 no.6
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• pp.642-648
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• 2021

In this paper, an experimental study was conducted on the performance of the cooling tower. In order to improve reliability in the cooling tower performance test, the measurement uncertainty of the instrument was estimated. Measurement uncertainty refers to the uncertainty of a measurement, estimates the range in which the expected value of the measurement can be within a certain confidence level, and suggests a range in which the measured representative value is incorrect. Therefore, the measurement result of the performance experiment is not an actual value, but a reasonable estimated value. The measurement uncertainty for the test was calculated and the measured results were presented.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.2
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• pp.107-113
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• 2013

When the main spindle of high precision machine tools are run many hours, heat is generated in bearing parts of the inside of the spindle. Also, headstock is appeared distortion by inside and outside temperature difference of a machine. This paper studies method to measure behavior of machine tool about these thermal effects. In addition, it estimates measurement uncertainty factors which can be appeared in thermal effects measurement. Finding the factor of thermal affect measurement is important for estimation of measurement uncertainty. This paper measures thermal effects of high precision machine tools and evaluates the important factors of uncertainty.

• Transactions of the Korean hydrogen and new energy society
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• v.31 no.6
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• pp.630-636
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• 2020

This paper presents a experimental study on the performance of the heat pump. Uncertainty of measurement means the degree of uncertainty in the measurement. Therefore, it estimates a section where expected value of the measurement might be within a certain confidence level and suggests a range where measured representative value might be incorrect. Uncertainty of measurement is a parameter that shows characteristics of dispersion of measured value that was reasonably estimated from measured quantity. Measurement result of performance experiment is not a true value but estimated value that was estimated reasonably. Therefore, uncertainty of measurement needs to be calculated and presented with the result of measurement.

• Journal of Information Processing Systems
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• v.16 no.3
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• pp.588-598
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• 2020

An alternative state estimation filtering algorithm is designed for continuous time systems with noises as well as control input. Two kinds of estimation filters, which have different measurement memory structures, are operated selectively in order to use both filters effectively as needed. Firstly, the estimation filter with infinite memory structure is operated for a certain continuous time system. Secondly, the estimation filter with finite memory structure is operated for temporarily uncertain continuous time system. That is, depending on the presence of uncertainty, one of infinite memory structure and finite memory structure filtered estimates is operated selectively to obtain the valid estimate. A couple of test variables and declaration rule are developed to detect uncertainty presence or uncertainty absence, to operate the suitable one from two kinds of filtered estimates, and to obtain ultimately the valid filtered estimate. Through computer simulations for a continuous time aircraft engine system with different measurement memory lengths and temporary model uncertainties, the proposed state estimation filtering algorithm can work well in temporarily uncertain as well as certain continuous time systems. Moreover, the proposed state estimation filtering algorithm shows remarkable superiority to the infinite memory structure filtering when temporary uncertainties occur in succession.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.955-960
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• 2009

In this paper, we propose a novel approach to residual echo suppression (RES) algorithm based on tracking echo-presence uncertainty (TEPU) to improve the performance of acoustic echo suppression (AES) in the frequency domain. In the proposed method, the ratio of the microphone input and the echo-suppressed output signal power is employed as the threshold value for the decision rule to estimate the echo-presence uncertainty applied to the RES filter. The proposed RES scheme estimates the echo presence uncertainty in each frequency bin and effectively reduces residual echo signal in a simple fashion. The performance of the proposed algorithm is evaluated by the objective test and yields better results compared with the conventional schemes.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.813-826
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• 2018

Recently, weather radar system has been widely used for effectively monitoring near real-time weather conditions. The radar rainfall estimates are generally relies on the Z-R equation that is an indirect approximation of the empirical relationship. In this regards, the bias in the radar rainfall estimates can be affected by spatial-temporal variations in the radar profile. This study evaluates the uncertainty of the Z-R relationship while considering the rainfall types in the process of estimating the parameters of the Z-R equation in the context of stochastic approach. The radar rainfall estimates based on the Bayesian inference technique appears to be effective in terms of reduction in bias for a given season. The derived Z-R equation using Bayesian model enables us to better represent the hydrological process in the rainfall-runoff model and provide a more reliable forecast.