• Computational Structural Engineering : An International Journal
• /
• v.1 no.2
• /
• pp.81-87
• /
• 2001

A framework for reliability analysis of structural components and systems under conditions of statistical and model uncertainty is presented. The Bayesian parameter estimation method is used to derive the posterior distribution of model parameters reflecting epistemic uncertainties. Point, predictive and bound estimates of reliability accounting for parameter uncertainties are derived. The bounds estimates explicitly reflect the effect of epistemic uncertainties on the reliability measure. These developments are enhance-ments of second-moment uncertainty analysis methods developed by A. H-S. Ang and others three decades ago.

• Journal of Distribution Science
• /
• v.9 no.2
• /
• pp.123-129
• /
• 2011

The restaurant franchise industry is one that could benefit significantly from the use of intranet technology, from its potential for improving communications between franchisors and franchisees, to providing easier inventory and ordering processes. However, there is a level of trepidation among potential users about whether the technology would improve their work performance. This study sought to examine the relationships between perceived uncertainty and perceived usefulness of intranet technology in the restaurant franchise industry. Through a review of available literature, 10 sub-dimensions of perceived uncertainty (Duncan, 1972) and six sub-dimensions of perceived usefulness (Davis, 1989) were derived. Canonical correlation analysis was used to examine the relationships between these concepts using data collected from 163 franchising restaurant managers in South Korea. Findings from the data analysis demonstrates two negative factors and one positive factor in perceived uncertainty that influence perceived usefulness, thus offering some implications of what to consider when implementing an intranet system in a restaurant franchise.

• Journal of Environmental Science International
• /
• v.20 no.12
• /
• pp.1541-1551
• /
• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

• Korea Trade Review
• /
• v.44 no.3
• /
• pp.25-42
• /
• 2019

This research examined the mediation effect of Workforce Agility (WA) on the relationship between environmental uncertainty and operational performance. We manipulated the control variables that are known to be affected by employment flexibility. Employment flexibility is caused by idiosyncratic characteristics of Korean port system. The analysis was tested by Baron & Kenny's method. The result indicates that each path of the proposed model is significant. Furthermore, the mediation effect was checked with the Sobel Test. The research revealed that environment uncertainty poses an indirect effect on operational performance. Both supply/demand uncertainty and technological uncertainty affected operational performance through the mediation effect of WA. Most of the distribution centers located in Busan Newport Distripark are operated in a bimodal labor (human resource) system which includes both permanent employees (workers) and temporary employees (workers). This empirical research provides theoretical and managerial implications by suggesting ways to increase efficiency in distribution center operation through WA enhancement, and to improve the unloading labor system.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 2005.04a
• /
• pp.316-319
• /
• 2005

Contaminated area should be identified for designing polluted groundwater cleanup plan. A methodology was suggested to identify a contaminant plume distribution geostatistically. James & Gorelick (1994) suggested a methodology to evaluate data worth as expected reducing remediation cost. In this study, their methodology was modified to evaluate data worth as expected reducing uncertainty of the contaminant plume distribution. In suggested methodology, the source identification model by Mahar & Datta (2001) using a forward solute transport model is integrated. Suggested methodology was assessed by two simple example problems and its result represented reducing uncertainties of contaminant plume distribution successfully.

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

• Journal of Distribution Science
• /
• v.16 no.12
• /
• pp.5-11
• /
• 2018

Purpose - We investigate the relationship between economic policy uncertainty (EPU) of the US and China and housing distribution economy in Korea using EPU indexes of two countries and the economic indicators in Korea. Research design, data, and methodology - We use the data such as the Korean housing price stability index (HPSI), housing purchase price index (HPPI), housing lease price index (HLPI), banking stock index (BSI), and consumer price index (CPI) with EPU indexes from January 1999 to December 2017. As an empirical methodology, we select the vector error correction model (VECM) due to the existence of cointegration. Result - As results of the impulse response function, the impact of the US EPU index has initially a negative response on the Korean HPSI, HPPI, and HLPI referring the housing distribution market including the economic variables, BSI, and CPI. Likewise, the impact of index in China has initially a negative response on economic indicators except the BSI in Korea. Conclusions - This study shows that the EPU index of the US has significantly negative relationships on all economic indicators in Korea. In this study, we reveal EPU of the US and China has dynamic impact on housing distribution economy returns in Korea.

• Journal of the Institute of Convergence Signal Processing
• /
• v.10 no.3
• /
• pp.198-206
• /
• 2009

This paper presents the reduction of the positional uncertainty of an ultrasonic sensor ring with overlapped beam pattern for the efficient obstacle detection of a mobile robot. Basically, it is assumed that a relatively small number of inexpensive low directivity ultrasonic sensors are installed at regular spacings along the side of a circular mobile robot with their beams overlapped. First, for both single and double obstacles, we show that the positional uncertainty inherent to an ultrasonic sensor can be reduced using the overlapped beam pattern, and also quantify the relative improvement in positional uncertainty. Second, given measured distance data from one or two ultrasonic sensors, we devise the geometric method to determine the position of an obstacle with respect to the center of a mobile robot. Third, we examine and compare existing ultrasonic sensor models, including Gaussian distribution, parabolic distribution, uniform distribution, and impulse, and then build the sensor model of overlapped ultrasonic sensors, adequate for obstacle detection in terms of positional uncertainty and computational requirement. Finally, through experiments using our prototype ultrasonic sensor ring, the validity of overlapped beam pattern for reduced positional uncertainty and efficient obstacle detection is demonstrated.

• Journal of Wetlands Research
• /
• v.11 no.1
• /
• pp.49-64
• /
• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Proceedings of the KIEE Conference
• /
• 2005.11b
• /
• pp.139-141
• /
• 2005

For the reliable evaluation of the distribution and power transformer no-load loss measurement, measurement uncertainty of the transformer measuring system, consisted of current transformer, potential transformer and power metering equipment is required. In this paper, we describe the uncertainty of transformer measuring system based on ANSI/IEEE C57.12.90.