• Journal of Navigation and Port Research
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• v.30 no.2
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• pp.145-150
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• 2006

Recently we have seen a noticeable trend in ports to establish port clusters. Despite this trend, little research has actually been undertaken to fully define and analyse port clusters. A couple of exceptions have descriptively defined port clusters but the boundaries of port clusters are not apparent. Therefore, the aim of this paper is to define port clusters in terms of set theory and in particular look at them in terms of their distinct characteristics and system boundaries. The main concern of this paper is that there is a need to distinguish, from a system and a competition perspective, between port clusters, ports, maritime clusters and port ranges. This paper proposes a conceptual model relevant to the relationship among port clusters related assemblages and that has been applied to the north western europe region This model suggests six levels of competition that will help port authorities and government to develop appropriate policies and strategies for port operation and port industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.1-16
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• 2004

Critical success factors (CSFs) have been replicated and applied in a wide variety of settings for more than two decades. Most previous research on CSF have focused on identifying critical factors, based on the variance theory, in terms of the correlation between individual factor and Information system (IS) success. However, it is unknown how a set of critical factors Influence each other and lead to IS success, which means the process of IS implementation. in this research, we aim to understand how a set of critical factors influence each other and lead to IS success in the context of IS implementation for Customer Relationship Management based on the process theory. This research has implications In explaining a mechanism leading to CRM systems success based on the influencial relationships among the critical factors.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• Lingua Humanitatis
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• v.5
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• pp.221-264
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• 2003

This paper takes issue with the idea of language as a 'serial-time structure' as opposed to the 'real-time event' of speech, an idea entrenched in Chomskyan model of linguistic theory. The discussion centers around the leitmotif question: Is language constructed entirely from a finite set of apriori discrete symbol types, as the 'competence vs performance' dichotomy implies\ulcorner A set of linguistic patterns examined in this study, largely with regard to phonological considerations, points to the evidence to the contrary. That is, while the patterns may be said to be linguistically distinct, they are not discretely, different, i.e. not different enough to be reliably differentiated. It is demonstrated that much of current research in phonology, including the most recent Optimality Theory, is misdirected in that it falsely presupposes a discrete universal phonetic inventory. The main thrust of the present study is that there is no sharp boundary between 'competence' defined as the formal, symbolic, discrete time domain of language and human cognition on the one hand and 'performance' as the continuous, fuzzy, real-time domain of human physiology on the other.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1893-1896
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• 2002

Remediation Selection Expert System (RSES) is a rule-based expert system which is used far the selection of remediation techniques fur petroleum contaminated sites. In this paper, we describe a fuzzy logic-based sub-system: Site Characterization Sub-System (SCSS). It is an enhancement of the RSES, which is used to analyze the hydraulic properties of contaminated sites. This paper focuses on an explanation on how to apply fuzzy set theory for identification of soil types and hydraulic properties of a contaminated site. To illustrate application of fuzzy set theory to the problem, two sample cases are presented in detail.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.76-81
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• 1996

CFMS(Critical Function Monitering System)는 원자력발전소에서 비상시 제어실 운전원에게 원전의 안전상태에 대한 정보를 제공하는 기능을 갖는데, 원전의 안전성을 위해 인간공학적 확인 및 검증(V&V)이 요구된다. 본 연구에서는 CFMS 화면설계의 인간공학적 평가를 위하여, 원전의 안전성에 대한 평가항목들의 상대적 중요도를 구하고 최종적으로 설계의 적합성을 평 가하는 방법론을 제시하고자 한다. 본 연구에서는 CFMS 화면설계의 평가항목 및 평가기준 확립, 원전에서 인적오류발생 가능성에 대한 평가항목의 상대적 중요도 결정, 분석하고자 하는 CFMS 화면에 대한 각 평가항목들의 인간공학적 설계의 적합성 평가로구성된다. CFMS의 인간공학적 평가를 위한 방법론으로 Fuzzy Set Theory와 AHP(Analytic Hierarchical Process) 기법을 적용 한 방법론을 제시하였다. 최종적으로는 전문가의 평가를 통하여 국내 건설되는 원전의 실제적인 문제에 적용하고자 한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.139-141
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• 2016

With the introduction of national standards (KS) for call centers, customers are expected to have access to better-quality services in the future. The purpose of this study is to evaluate the relative importance of certification criteria for call center services using the Fuzzy AHP(Analytic Hierarchy Process) approach. Fuzzy AHP is the combination of the fuzzy set theory and AHP to deal with the uncertainty or ambiguousness of the decision-making process. The evaluation method proposed in this study can be applied to the KS services certification promoted by government.

• 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%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.21-22
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• 2021

Early academic warning is considered as an inherent problem in education data mining. Early and timely concern and guidance can save a student's university career. It is widely assumed as a multi-class classification system in view of machine learning. Therefore, An accurate and precise methodical solution is a complicated task to accomplish. For this issue, we present a hybrid model employing rough set theory with a back-propagation neural network to ameliorate the predictive capability of the system with an illustrative example. The experimental results show that it is an effective early academic warning model with an escalating improvement in predictive accuracy.