• Journal of Distribution Science
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• v.11 no.9
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• pp.31-34
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• 2013

Purpose - This paper aims to explain that the Chinese distribution market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand. Research design, data, methodology - A survey was conducted on China's retail market data during 2012. By empirically analyzing the data for retail sales of online markets and franchises, we conclude that the online retail market in China will continue to grow. Results - Based on data from 2012, 2013 is expected to be a challenging year for the retail sector, as both external and internal pressure is likely to persist. This paper outlines some major challenges facing retailers in China. Conclusions - The study shows that retailers in the Chinese market will face some major challenges: 1) the Chinese retail market is considerably affected by an uncertain economic outlook 2) an unfair environment of competition exists and 3) product safety is a serious issue. However, in the future, China's retail market will continue to bring tremendous business opportunities to commercial enterprises, given the relatively strong economic fundamentals and substantial government-led measures to boost domestic demand.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.55-65
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• 2002

In this paper we present a Bayesian approach for determining an optimal maintenance policy following the expiration of warranty for a repairable system. We consider two types of warranty policies : non-renewing free replacement warranty (NFRW) and non-renewing pro-rata warranty (NPRW). The mathematical formula of the expected cost rate per unit time is obtained for NFRW and NPRW, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. We illustrate the use of our approach with simulated data.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.794-799
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• 1999

This study deals with robustness bounds estimation for uncertain linear systems with structured perturbations where the eigenvalues of the perturbed systems are guaranteed to stay in a prescribed region. Based upon the Lyapunov approach, new theorems to estimate allowable perturbation parameter bounds are derived. The theorems are referred to as the zero-order or first-order asymmetric robustness measure depending on the order of the P matrix in the sense of Taylor series expansion of perturbed Lyapunov equation. It is proven that Gao's theorem for the estimation of stability robustness bounds is a special case of proposed zero-order asymmetric robustness measure for eigenvalue assignment. Robustness bounds of perturbed parameters measured by the proposed techniques are asymmetric around the origin and less conservative than those of conventional methods. Numerical examples are given to illustrate proposed methods.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.225-229
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• 2012

We examine spectrum sensing in a situation of uncertain channel model. In particular, we assume that, besides additive noise, the observed signal contains an interference term whose probability distribution is unknown, and only its range and maximum power are known. We discuss the evaluation of the detector performance and its design in this situation. Although this paper specifically deals with the design of spectrum sensors, its scope is wider, as the applicability of its results extends to a general class of problems that may arise in the design of receivers whenever there is uncertainty about how to model the environment in which one is expected to operate. The theory expounded here allows one to determine the performance of a receiver, by combining the available (objective) probabilistic information with (subjective) information describing the designer's attitude.

• Journal of Korean Society for Quality Management
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• v.19 no.2
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• pp.96-107
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• 1991

At the design stage of a plant, the plausible causes and pathways of release of hazardous materials are not clearly known. Thus there exist large amount of uncertainties on the consequences resulting from the operation of a fusion plant. In order to better handle such uncertain circumstances, we utilize the Probabilistic Risk Assessment(PRA) for the safety analyses on fusion power plant. In this paper, we concentrate on the tritium release accident. We develop a simple model that describes the process and flow of tritium, by which we figure out the locations of tritium inventory and their vulnerability. We construct event tree models that lead to various levels of tritium release from abnormal initiating events. Branch parameters on the event tree are assessed from the fault tree analysis. Based on the event tree models we construct influence diagram models which are more useful for the parameter updating and analysis. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of consequences resulting from the operating a fusion power plant. We also discuss the way to utilize the results of testing on sub-systems to reduce the uncertain ties on over all system.

• Journal of the Korean Data and Information Science Society
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• v.17 no.3
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• pp.743-752
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• 2006

This paper considers a Bayesian approach to replacement policy model with minimal repair. We use the criterion based on the expected cost and the expected downtime to determine the optimal replacement period. To do so, we obtain the expected cost rate per unit time and the expected downtime per unit time, respectively. When the failure time is Weibull distribution with uncertain parameters, a Bayesian approach is established to formally express and update the uncertain parameters for determining an optimal maintenance policy. Especially, the overall value function suggested by Jiagn and Ji(2002) is applied to obtain the optimal replacement period. The numerical examples are presented for illustrative purpose.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1412-1420
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• 2018

An experiment was performed using the large-scale test facility (LSTF), which simulated a 1% vessel upper head small-break loss-of-coolant accident with an accident management (AM) measure under an assumption of total-failure of high-pressure injection (HPI) system in a pressurized water reactor (PWR). In the LSTF test, liquid level in the upper head affected break flow rate. Coolant was manually injected from the HPI system into cold legs as the AM measure when the maximum core exit temperature reached 623 K. The cladding surface temperature largely increased due to late and slow response of the core exit thermocouples. The AM measure was confirmed to be effective for the core cooling. The RELAP5/MOD3.3 code indicated insufficient prediction of primary coolant distribution. The author conducted uncertainty analysis for the LSTF test employing created phenomena identification and ranking table for each component. The author clarified that peak cladding temperature was largely dependent on the combination of multiple uncertain parameters within the defined uncertain ranges.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.395-399
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• 2016

Background: Whether ambient exposure to environmental pollutants leads to hematopoietic malignancies such as multiple myeloma (MM) remains to be ascertained. Therefore, we aimed to investigate the immunotyping distribution of serum monoclonal paraprotein and the environmental influence on MM and monoclonal gammopathy of uncertain significance (MGUS) in the Taiwanese population. Materials and Methods: Serum protein electrophoresis with immunosubtraction by the capillary zone electrophoresis method was performed as primary screening for MM and MGUS. Clinical, pathological, and residence data of patients were also obtained. Results: From August, 2013 to June, 2015, a total of 327 patients underwent serum protein electrophoresis with immunosubtraction. Among these, 281 demonstrated no remarkable findings or non-malignant oligoclonal gammopathy, 23 were detected to have MGUS, 18 were identified as MM, and a further 5 were found as other malignancies. The most frequent immunotyping distribution of serum monoclonal paraprotein was IgG kappa (54.3%, n=25), followed by IgA lambda (15.2%, n=7) and IgG lambda (10.9%, n=5) in subjects with gammopathy. Additionally, it was shown that the elderly (OR: 4.61, 95% CI: 1.88-11.30, P<0.01) and males (OR: 2.04, 95% CI: 1.04-4.02, P=0.04) had significantly higher risk of developing MM and MGUS. There was no obvious impact of environmental factors on the health risk of MM and MGUS evolution (OR: 0.77, 95% CI: 0.40-1.50, P=0.49). Conclusions: The most frequent immunotyping distribution of serum monoclonal paraprotein included IgG kappa, IgA lambda and IgG lambda in MM and MGUS in the Taiwanese population. The elderly and male subjects are at significantly higher risk of MM and MGUS development, but there was no obvious impact of environmental factors on risk.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.81-96
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• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.