• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.286-297
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• 2020

This study explores how fear of isolation and willingness to speak out are affected by cultural values. The cross-cultural studies on the spiral of silent theory were conducted mostly in Eastern and Western countries and compared the results. It attributed to the results to the "individualist-collective" attitude difference. However, it did not explain the differences in the same individualism societies as well as in the collectivism societies. Thus, this study examined the impact of cultural values on the spiral of silence theory with 'individualism-collectivism' and 'uncertainty-avoidance'. To that end, the current study conducted online surveys in India, South Korea, the United States and Spain where have different levels of individualism, collectivism, and uncertainty-avoidance. As a result, individualism contributed to lower the fear of isolation, and collectivism and uncertainty avoidance have raised the fear of isolation. Besides, individualism and uncertainty avoidance also reinforce the willingness to speak out, while fear of social isolation has been shown to weaken the willingness to speak out. The study also found that fear of isolation has the mediated effect of individualism and collectivism on the willingness to speak out.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.18-25
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• 2012

IChinese postman problem is one of the classical combinatorial optimization problems with many applications. However, in application, some uncertain factors are frequently encountered. This paper employs uncertain programming to deal with Chinese postman problem with uncertain weight Within the framework of uncertainty theory, the concepts of expected shortest route, ${\alpha}$-shortest route, and distribution shortest route are proposed. After that, expected shortest model, and ${\alpha}$-shortest model are constructed. Taking advantage of properties of uncertainty theory, these models can be transf-ormed into their corresponding deterministic forms, which can be solved by classical algorithm..

• ETRI Journal
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• v.42 no.5
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• pp.799-804
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• 2020

Network security situation prediction is difficult due to its strong uncertainty, but DS evidence theory performs well in solving the problem of uncertainty. Based on DS evidence theory, this study analyzed the prediction of the network security situation, designed a prediction model based on the improved DS evidence theory, and carried out a simulation experiment. The experimental results showed that the improved method could predict accurately in the case of a large conflict, and had strong anti-jamming abilities as compared with the original method. The experimental results prove the effectiveness of the improved method in the prediction of the network security situation and provide some theoretical basis for the further application of DS evidence theory.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.270-276
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• 2014

This survey paper reviews robust control problems in both frequency domain and time domain. Robust control is focused on model uncertainties such as modeling error, system parameter variations, and disturbances. Robust control design problems are discussed according to parameter uncertainty, polytopic uncertainty, and norm-bounded uncertainty. Nowadays, robust control theory is combined with various control theory such as model predictive control, adaptive control, intelligent control, and time delay control.

• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.577-591
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• 2022

This paper develops a comparatively time-efficient methodology for performing seismic fragility analysis of the reinforced concrete (RC) buildings in the presence of uncertainty sources. It aims to appraise the effectiveness of any variation in the material's mechanical properties as epistemic uncertainty, and the record-to-record variation as aleatory uncertainty in structural response. In this respect, the fuzzy set theory, a well-known 𝛼-cut approach, and the Genetic Algorithm (GA) assess the median of collapse fragility curves as a fuzzy response. GA is requisite for searching the maxima and minima of the objective function (median fragility herein) in each membership degree, 𝛼. As this is a complicated and time-consuming process, the authors propose utilizing the Gene Expression Programming-based (GEP-based) equation for reducing the computational analysis time of the case study building significantly. The results indicate that the proposed structural analysis algorithm on the derived GEP model is able to compute the fuzzy median fragility about 33.3% faster, with errors less than 1%.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.902-907
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• 2005

This study was undertaken to develop a comprehensive scheduling method which applied the core concept(DBR) of TOC to PERT, and to combine Monte Carlo Simulation to revise the uncertainties of activities then to eliminate project duration uncertainty. Most of the project duration overlooks the fact that in spite of minimizing the project duration, the uncertainty of constrained resources still puts the reliability of project duration in jeopardy. For the contractor, however, the most important thing is to comply the project scheduling with the planning to reduce the uncertainty of the project activities, operational interaction and project duration. In order to demonstrate that the model can be used in construction project, the scheduling of a steel-structure project was used as a case study to verify the validity of this model.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.413-413
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• 2010

In semiconductor manufacturing field, all equipments have various sensors to diagnosis the situations of processes. For increasing the accuracy of diagnosis, hundreds of sensors are emplyed. As sensors provide millions of data, the process diagnosis from them are unrealistic. Besides, in some cases, the results from some data which have same conditions are different. We want to find some information, such as data and knowledge, from the data. Nowadays, fault detection and classification (FDC) has been concerned to increasing the yield. Certain faults and no-faults can be classified by various FDC tools. The uncertainty in semiconductor manufacturing, no-faulty in faulty and faulty in no-faulty, has been caused the productivity to decreased. From the uncertainty, the rough set theory is a viable approach for extraction of meaningful knowledge and making predictions. Reduction of data sets, finding hidden data patterns, and generation of decision rules contrasts other approaches such as regression analysis and neural networks. In this research, a RGB sensor was used for diagnosis plasma instead of optical emission spectroscopy (OES). RGB data has just three variables (red, green and blue), while OES data has thousands of variables. RGB data, however, is difficult to analyze by human's eyes. Same outputs in a variable show different outcomes. In other words, RGB data includes the uncertainty. In this research, by rough set theory, decision rules were generated. In decision rules, we could find the hidden data patterns from the uncertainty. RGB sensor can diagnosis the change of plasma condition as over 90% accuracy by the rough set theory. Although we only present a preliminary research result, in this paper, we will continuously develop uncertainty problem solving data mining algorithm for the application of semiconductor process diagnosis.

• Korean Journal of Adult Nursing
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• v.13 no.2
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• pp.200-208
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• 2001

The purpose of this study was to understand the nature and structure of "uncertainty of chronically ill patients" by explaining it more scientifically. This study is based on the unique experiences, which individual uncertainty experiences differ from others. In this sense, Q-methodology which includes self-psychology and abductive logics is applied to the study. The results indicate that there are six types of uncertainty of chronically ill patients : my own fault, self-esteem loss, self-care determination, cure-doubt, reality-restructure, and past-tenacity reality-absence. Thus, "uncertainty of chronically ill patients" is defined from the study as the process in which continuous transition and evaluation of possibility cause changes in human recognition, attitude, action, etc.. The significance of the study is threefold : (1) discovery of six types of uncertainty of chronically ill patients in Korean people, (2) the better understanding of "uncertainty of chronically ill patients", (3) possible developments of nursing concept and assessment and intervention technique based on the new dimension of the understanding in uncertainty for nursing of chronically ill patients from this research.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.521-528
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• 2005

The evaluation process of rock mass properties intrinsically contains some uncertainty due to the inhomogeneity of rock mass and the measurement error. Although various empirical methods for the determination of rock mass properties were suggested, there is no way of integrating various information on rock mass properties except averaging. For these reasons, this research introduces evidence theory which can model epistemic uncertainty and yield reasonable rock mass properties through combining various information such as empirical equations, in-situ test results, and so on. Through the application of evidence theory to the real site investigation and in situ experiment results, an interval of deformation modulus, cohesion and friction angle of rock mass were obtained. The ratios between lower and upper bound of those properties ranges from 1.6 to 3.6. Numerical analyses of circular hole using the properties for TYPE-2 rock mass were carried out. The magnitude or size of plastic region and radial displacement in case of lower bound properties is about 4 times larger than that of upper bound properties.

• Communications of the Korean Mathematical Society
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• v.28 no.2
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• pp.419-423
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• 2013

In this paper we present a robust duality theory for generalized convex programming problems under data uncertainty. Recently, Jeyakumar, Li and Lee [Nonlinear Analysis 75 (2012), no. 3, 1362-1373] established a robust duality theory for generalized convex programming problems in the face of data uncertainty. Furthermore, we extend results of Jeyakumar, Li and Lee for an uncertain multiobjective robust optimization problem.