• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.45-71
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• 1997

There has been considerable research recently on uncertainty handling in the fields of artificial intelligence and knowledge-based system. Various numerical and non-numerical methods have been proposed for representing and propagating uncertainty in knowledge-based system. The Bayesian method, the Dempster-Shafer's Evidence Theory, the Certainty Factor model and the Fuzzy Set Theory are most frequently appeared in the knowledge-based system. Each of these four methods views uncertainty from a different perspective and propagates it differently. There is no single method which can handle uncertainty properly in all kinds of knowledge-based systems' domain. Therefore a knowledge-based system will work more effectively when the uncertainty handling method in the system fits to the system's environment. This paper proposed a framework for selecting proper uncertainty handling methods in knowledge-based system with respect to characteristics of problem domain and cognitive styles of experts. A schema with strategic/operational and unstructured/structured classification is employed to differenciate domain. And a schema with systematic/intuitive and preceptive/receptive classification is employed to differenciate experts' cognitive style. The characteristics of uncertainty handling methods are compared with characteristics of problem domains and cognitive styles respectively. Then a proper uncertainty handling method is proposed for each category.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.10 s.241
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• pp.1130-1138
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• 2005

A national standard system for the petroleum field has been developed to calibrate and test the oil flow meters in Korea. The operating system and the uncertainty of the system were evaluated by the peer reviewers of foreign national metrology institutes in 2002. Since the characteristics of the system might be changed by time, the uncertainty of the system is reevaluated with the consideration of the long term stability of the system. It is found that the system has a relative expanded uncertainty of 0.048 $\%$ in the range of $15\~120\;m^3/h$. According to the uncertainty budget, the uncertainties of the fluid density and the final mass measurement, which are temperature dependent, contribute about $94\%$ of the total uncertainty in the oil flow standard system

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.7
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• pp.919-926
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• 2012

In order to control a LTI(Linear Time Invariant) system subjected to system noise and measurement noise, first of all, it is necessary to estimate the state of system with reliability. Kalman filtering technique has been widely used to estimate the state of the stochastic LTI system with stationary noise characteristics because of its estimation ability versus algorithm simplicity. However, it often fails to estimate the state of the LTI system of which system parameter uncertainty exists partly and/or input uncertainty exists. In this paper, a new estimation technique based on Kalman filter is suggested for stochastic LTI system under parameter uncertainty and/or input uncertainty. A fuzzy estimation algorithm against uncertainties is introduced so as to compensate the state estimate filtered by Kalman filter. In order to verify the state estimation performance of the suggested technique, several simulations are accomplished.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.7
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• pp.781-786
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• 2016

All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty. By international agreement, this uncertainty has a probabilistic basis and reflects incomplete knowledge of the quantity value. The "Guide to the Expression of Uncertainty in Measurement", commonly known as the GUM, is the definitive document on this subject. The requirements for estimation of measurement uncertainty apply to all results provided by calibration laboratories and results produced by testing laboratories under the optional circumstances. In this paper, a procedure for estimation of measurement uncertainty from vibration testing is proposed on KS F 2868:2003 as an example. Both Type A and Type B evaluation of uncertainty are considered to calculate the combined standard uncertainty and expanded uncertainty.

• International Journal of Contents
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• v.5 no.3
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• pp.40-49
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• 2009

While numerous studies have suggested the significance of uncertainty during the process of information-seeking, less research has investigated user uncertainty in the actual search process using a real system. This study investigated user perceptions of uncertainty in the process of the selection of information retrieval system in the real information-seeking process. Considering the role of commercial Web search engines as supplementary tools for traditional bibliographic databases in academic research environments, this study analyzed the selection behavior of scholarly researchers, who use such search tools for their academic study. The researchers were limited to the discipline of science in order to understand user perceptions in this field. The findings revealed various dimensions, types, and incidents of uncertainty. Variations appeared in different incidents of uncertainty relating to the unique characteristics of the subjects' information-seeking context. The identification of three principal origins of uncertainty based on the different types of uncertainty generated implications to improve information systems and services.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.791-798
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• 2011

All mechanical-system parameters have uncertainty, and this uncertainty directly affects system performances and results in a decrease in the manufacturing outputs. In particular, since the size of a MEMS system is extremely small, the manufacturing tolerances of a MEMS system are relatively large when compared to the tolerances of a macro-scale system. High manufacturing tolerances result from an increase in the uncertainty of the system parameters, thereby affecting the performances and manufacturing yields. In this paper, the performance uncertainty of a MEMS accelerometer due to system parameter uncertainty is analyzed by using several uncertainty analysis methods. Finally, the performance distributions and manufacturing yields of the MEMS accelerometer are predicted.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.5
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• pp.596-608
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• 2018

The present study aims to assess test uncertainty assessment method of nominal wake field measurement by a Stereoscopic Particle Image Velocimetry (SPIV) system in a towing tank. The systematic uncertainty of the SPIV system was estimated from repeated uniform flow measurements. In the uniform flow measurement case, time interval between image frames and uniform flow speed were varied to examine the effects of particle displacement and flow around the SPIV system on the systematic standard uncertainty. The random standard uncertainty was assessed by repeating nominal wake field measurements and the estimated random standard uncertainty was compared with that of laser Doppler velocimetry. The test uncertainty assessment method was applied to nominal wake measurement tests of a very large crude oil carrier model ship. The nominal wake measurement results were compared with existing experimental database by other measurement methods, with its assessed uncertainty.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.27 no.8
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• pp.1071-1080
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• 2003

A national standard system was developed in order to calibrate and test the oil flowmeters for the petroleum field. A stop valve and a gyroscopic weighing scale were employed for the primary standard of the flow quantity. It is operated by the standing start and finish mode and the static weighing method. The model equation for uncertainty evaluation was based on the calibration principle of standard system. The sources of the uncertainties were quantified and combined according to the GUM(Guide to the Expression of Uncertainty in Measurement). It was found that the standard system had the relative expanded uncertainty of 0.04 % in the range of 18 - 350 ㎥/ｈ. According to the uncertainty budget, the uncertainties of the fluid density and the volume of pipeline, which were temperature dependent, contributed 92% of final uncertainty in the oil flow standard system.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.105-117
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• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• Applied Science and Convergence Technology
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• v.23 no.3
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• pp.103-112
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• 2014

The Korea Research Institute of Standards and Science (KRISS) has three major vacuum systems: an ultrasonic interferometer manometer (UIM; Section II, Figs. 1 and 2) for a low vacuum, a static expansion system (SES; Section III, Figs. 3 and 4) for a medium vacuum, and an orifice-type dynamic expansion system (DES, Section IV, Figs. 5 and 6) for high and ultra-high vacuum systems. For each system, explicit measurement model equations with multiple variables are given. According to ISO standards, all of these system variable errors were used to calculate the expanded uncertainty (U). For each system, the expanded uncertainties (k = 1, confidence level = 95%) and relative expanded uncertainty (expanded uncertainty/generated pressure) levels are summarized in Table 4. Within the uncertainty limits, our bilateral and key comparisons [CCM.P-K4 (10 Pa to 1 kPa)] are extensive and in good agreement with those of other nations (Fig. 8 and Table 5).