• Journal of Industrial Convergence
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• v.12 no.2
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• pp.40-52
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• 2014

I present a theoretical analysis of the charismatic leadership and the follower's role. I distinguish between two types of charismatic relationships and present general propositions about how followers' self-concepts may dertermine the type of charismatic relationship they form with the leader. I conclude by suggesting further the study.

• Journal for History of Mathematics
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• v.34 no.1
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• pp.1-20
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• 2021

Logic and intuition are considered as the opposite extremes of teaching geometry, and any teaching method of geometry is to be placed between these extremes. The purpose of this study is to identify the characteristics of logical and intuitive approaches for teaching geometry and to derive didactical implications by taking Euclid's Elements and Clairaut's Elements respectively representing the extremes. To this end, comparing the composition and contents of each book, we analyze which propositions Clairaut chose from Euclid's Elements, how their approaches differ in definitions, proofs, and geometrical constructions, and what unique approaches Clairaut took. The results reveal that Clairaut mainly chose propositions from Euclid's books 1, 3, 6, 11, and 12 to provide the contexts that show why such ideas were needed, rather than the sudden appearance of abstract and formal propositions, and omitted or modified the process of justification according to learners' levels. These propose a variety of intuitive strategies in line with trends of teaching geometry towards emphasis on conceptual understanding and different levels of justification. Specifically, such as the general principle of similarity and the infinite geometric approach shown in Clairaut's Elements, we could confirm that intuition-based geometry does not necessarily aim for tasks with low cognitive demand, but must be taught in a way that learners can understand.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.1
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• pp.1-13
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• 2010

This study analyzes the innovation process of the value chain in the fashion industry. It examines the differences between traditional and FF-based methods that include value chain processes such as design, production, and distribution-sales process. In the literature review and case studies, general propositions were drawn from each innovative stage by a comparison analysis. First, design speed is the main factor to explain the impact of IT in the design process. Second, small quantity batch production becomes main stream by the adoption of a computer-integrated manufacturing system in the production process. Third, cost reduction and speedup improvement are results of innovation in the distribution process. Last, a customized interface provides important information that can integrate the value chain and make useful customer relationships in the sales process. Fast fashion is the best product of these procedural innovations in the overall value chain. Consequently, this study confirmed that the general propositions referred above were acceptable and adaptable in the case of ZARA in terms of fast fashion strategy.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.105-121
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• 2005

Ubiquitous computing(UC) is an emerging paradigm. Its arrival as a mainstream is expected to trigger innovative UC-driven business models (UCBMs). Currently, there is no Parsimonious methodology to analyze and provide diagnostics for UCBMs. With this research, we propose a analytical architecture that enables the assessment of an UCBM in its structural strengths and weaknesses. With value logic as the cornerstone, the architecture is composed of value actors, value assets, value context, business value Propositions, customer value propositions, value creation logics, and value assumptions. Dimensional variables are initially Identified based on the review of business model literature. Then, their significance is empirically examined through 14 UCBM scenarios, and variables that are expected to Play an important role in the UCBM assessment are decided. Finally, by analyzing the scenarios in terms of the dimensional variables, we attempted to summarize general characteristics of emerging UCBMs.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.559-566
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• 2004

In general, the certainty factors of the fuzzy production rules and the certainty factors of fuzzy propositions appearing in the rules are represented by real values between zero and one. If it can allow the certainty factors of the fuzzy production rules and the certainty factors of fuzzy propositions to be represented by interval -valued fuzzy sets, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more flexible manner. This paper presents fuzzy Petri nets and proposes an interval-valued fuzzy backward reasoning algorithm for rule-based systems based on fuzzy Petri nets Fuzzy Petri nets model the fuzzy production rules in the knowledge base of a rule-based system, where the certainty factors of the fuzzy propositions appearing in the fuzzy production rules and the certainty factors of the rules are represented by interval-valued fuzzy sets. The algorithm we proposed generates the backward reasoning path from the goal node to the initial nodes and then evaluates the certainty factor of the goal node. The proposed interval-valued fuzzy backward reasoning algorithm can allow the rule-based systems to perform fuzzy backward reasoning in a more flexible and human-like manner.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.625-631
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• 2004

In general, the certainty factors of the fuzzy production rules and the certainty factors of fuzzy Propositions appearing in the rules are represented by real values between zero and one. If it can allow the certainty factors of the fuzzy production rules and the certainty factors of fuzzy propositions to be represented by interval-valued fuzzy sets, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more flexible manner(15). This paper presents a fuzzy Petri nets and proposes an interval-valued fuzzy reasoning algorithm for rule-based systems based on fuzzy Petri nets. Fuzzy Petri nets model the fuzzy production rules in the knowledge base of a rule-based system, where the certainty factors of the fuzzy Propositions appearing in the furry production rules and the certainty factors of the rules are represented by interval-valued fuzzy sets. The proposed interval-valued fuzzy set reasoning algorithm can allow the rule-based systems to perform fuzzy reasoning in a more flexible manner.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.685-693
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• 2005

An aperiodic perfect map(APM) is an array with the property that every array of certain size, called a window, arises exactly once as a contiguous subarray in the array. In this article, we deal with the generalization of APM in higher dimensional arrays. First, we reframe all known definitions onto the generalized n-dimensional arrays. Next, some elementary known results on arrays are generalized to propositions on n-dimensional arrays. Finally, with some devised integer representations, two constructions of infinite family of n-dimensional APMs are generalized from known 2-dimensional constructions in [7].

• Journal of Distribution Science
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• v.17 no.11
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• pp.53-62
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• 2019

Purpose: This research aims to study the internal and external social practices of supply chain management along with economic and social performance of eight Portuguese companies from different industrial sectors. Through empirical data derived from eight case studies, five research propositions are suggested and tested. Research, design, data and methodology: The data was collected through 22 semi-structured interviews with general, procurement, and environmental/safety managers from eight companies from different industrial sectors. Secondary data was collected from reports, websites, and companies' internal documentation. Results: The analysis identifies the most important social practices considered by managers, as well as the performance measures that are most appropriate and most widely used to evaluate the influence of social practices on corporate economic and social performance. The results support four of the five propositions of this research. Companies' economic and social performance are affected by the implementation of social practices into the supply chain, namely the internal social practices. Conclusions: The findings confirmed that there is a positive relationship between internal social practices and economic performance. Internal social supply chain practices contribute to improve social performance. It also identifies the social practices which have negative effects on focal company performance.

• Journal of The Korean Association For Science Education
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• v.26 no.5
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• pp.637-645
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• 2006

This study reviewed and discussed the nature of scientific hypothesis described in philosophy, the philosophy of science, science, and science education. In these descriptions, a hypothesis was defined as one of five types: hypothesis as an assumption, hypothesis as a prediction, hypothesis as a tentative explanation, hypothesis as a tentative law, and hypothesis as a tentative causal explanation. Most scholars agreed that a hypothesis is a proposition or a set of propositions proposed as an explanation for an observed situation. In this view, a hypothesis is a possible answer to or an explanation of a question that accounts for all the observed facts. Also, it is a statement that explains why things happen in nature or an explanation for an observation that can be tested. In the five types of hypothesis meanings, a tentative explanation includes a tentative law and a tentative causal explanation. However, tentative laws are not explanation but description which are general statements drawn from specific experiences by way of a process known as induction. A number of studies also have distinguished hypothesis from assumption, tentative explanation, tentative law, and prediction. Therefore, a hypothesis is concluded to be a proposition or a set of propositions proposed as a tentative causal explanation for an observed situation.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.