• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.99-106
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• 2020

The purpose of this study is to find out whether image similarity between celebrities and brands on social network service be a determinant to predict advertising effectiveness. To this end, an advertising effect prediction model for celebrity endorsed advertising was created and its validity was verified through a machine learning method which is a big data analysis technique. Firstly, the celebrity-brand image similarity, which was used as an independent variable, was quantified by the association network theory with social big data, and secondly a multiple regression model which used data representing advertising effects as a dependent variable was repeatedly conducted to generate an advertising effect prediction model. The accuracy of the prediction model was decided by comparing the prediction results with the survey outcomes. As for a result, it was proved that the validity of the predictive modeling of advertising effects was secured since the classification accuracy of 75%, which is a criterion for judging validity, was shown. This study suggested a new methodological alternative and direction for big data-based modeling research through celebrity-brand image similarity structure based on social network theory, and effect prediction modeling by machine learning.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.206-211
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• 2006

The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

• Journal of Educational Research in Mathematics
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• v.20 no.1
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• pp.57-71
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• 2010

Similarity between concept and concept, principle and principle, theory and theory is known as a strong motivation to mathematical knowledge construction. Metaphor and analogy are reasoning skills based on similarity. These two reasoning skills have been introduced as useful not only for mathematicians but also for students to make meaningful conjectures, by which mathematical knowledge is constructed. However, there has been lack of researches connecting the two reasoning skills. In particular, no research focused on the interplay between the two in didactic transposition. This study investigated the process of knowledge construction by metaphor and analogy and their roles in didactic transposition. In conclusion, three kinds of models using metaphor and analogy in didactic transposition were elaborated.

• ETRI Journal
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• v.25 no.5
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• pp.401-406
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• 2003

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non-registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well-defined method based on a statistical test theory. Our computational experiments on real-world data show that the proposed method has potential for coping with the actual difficulties in biometrics.

• Journal of the Korea Society of Computer and Information
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• v.14 no.4
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• pp.153-160
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• 2009

This study investigated what factors influence the knowledge contribution in online communities. Based on the theoretical framework like self-presentation theory and organizational citizenship behavior theory, we developed the research model and proposed four hypotheses. In order to test our hypotheses with an empirical study, we have conducted a survey which resulted in 192 valid responses in the final sample. The PLS analysis results indicate that knowledge contribution is influenced by self-presentation, innovation, organizational citizenship behavior, and affection similarity of online community users. Practical implications of these findings and future research implications are also discussed.

• Journal of the Korea Fashion and Costume Design Association
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• v.18 no.3
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• pp.165-181
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• 2016

This study looks into the Korean traditional costume formation and the thoughts of the Korean people that form the foundation of that Korean traditional costume formation. And the goal of this study is in linking the thoughts and formative characteristics reflected in the Korean traditional costume formation to the fractal geometry, in an attempt to reveal correlation between Korean traditional costume formation which have existed for thousands of years to contemporary science of the West. The fractal theory that appeared as the new paradigm of contemporary science displayed similarities with the traditional ideologies of Korea, and the fact that formation principles of fractal appear in the formation of Korean costume, formed based on the Korean ideologies, show magnanimous capacity of the traditional Korean culture. When we look at the concept of fractal, the word fractal refers to the structure in which the shape repeats, where small structure is similar to the whole structure in form in endlessly repeating structure. In other words, 'fractal' means a structure that geometrically untangles the concept of 'self-similarity' which possesses the same shape in parts and in whole, and its major characteristics include 'self-similarity', 'circularity' and 'repeatability'. Korean costumes were formed based on the Han-thoughts, with a structure that possesses parts within the whole and the whole within parts, in accordance with the self-similarity theory of 'fractal'. This study compared studied fractal phenomenon which appear in formation characteristics of Korean traditional costume, which were formed based on the Korean traditional ideology, in other words, Korean costume formation and formation principles of fractal geometry were compared studied.

• Advances in materials Research
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• v.8 no.3
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• pp.155-177
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• 2019

In this paper, a new displacement based high-order shear deformation theory is introduced for the static response of functionally graded sandwich plate with new definition of porosity distribution taking into account composition and the scheme of the sandwich plate. Unlike any other theory, the number of unknown functions involved is only four, as against five in case of other shear deformation theories. The theory presented is variationally consistent, has strong similarity with classical plate theory in many aspects, does not require shear correction factor, and gives rise to transverse shear stress variation such that the transverse shear stresses vary parabolically across the thickness satisfying shear stress free surface conditions. Material properties of FGM layers are assumed to vary continuously across the plate thickness according to either power-law or sigmoid function in terms of the volume fractions of the constituents. The face layers are considered to be FG across each face thickness while the core is made of a ceramic homogeneous layer. Governing equations are derived from the principle of virtual displacements. The closed-form solution of a simply supported rectangular plate subjected to sinusoidal loading has been obtained by using the Navier method. Numerical results are presented to show the effect of the material distribution, the sandwich plate geometry and the porosity on the deflections and stresses of FG sandwich plates. The validity of the present theory is investigated by comparing some of the present results with other published results.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.17-35
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• 2011

The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.491-495
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• 1993

In this paper, we present a methodology to model an indoor environment of a mobile robot using fuzzy numbers and to make a global map of the robot environment using graph theory. We describe any geometric primitive of robot environment as a parameter vector in parameter space and represent the ill-known values of the prameterized geometric primitive by means of fuzzy numbers restricted to appropriate membership functions. Also we describe the spatial relations between geometric prinitives using graph theory for local maps. For making the global map of the mobile robot environment, the correspondence problem between local maps is solved using a fuzzy similarity measure and a Bipartite graph matching technique.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.489-492
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• 2004

In this paper, we propose a representation method of emotions in RIDE(Robot Intelligence with Digital Emotion) project. The method used in RIDE not only represents the emotional state in James-Lange Theory but also represents that of the Cannon-Bard Theory. Furthermore, our method allow the memorization of an emotion so as to process the self-inflicting emotion mentioned in the Schafter-Singer Theory. We also allow the similarity and differences in the characteristics by compaing of two emotions.