• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.175-177
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• 2002

This paper presents a methodology for analyzing individual differences on Kansei evaluation for a set of product samples. This analysis divides subjects into several groups by each subject's Kansei evaluation data according to what kinds of Kansei are related on what kinds of design elements. The basic idea is to classify the results of cluster analysis in individual subject's ranges. A similarity matrix of subject is computed by comparing dendrogram of each subjects. The methodology is applied to analyzing evaluation data of cellular phone design.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.201-204
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• 2002

Kansei design knowledge acquisition stage is a crucial stage in kansei designing process and kansei engineering (KE) methodology. In kansei engineering methodology, it is essential to extract design knowledge or rules on relationships between customer's kansei and product design element. We attempt to construct a more powerful melted for extracting the design rules from kansei expremental data. We constucted a kansei experiment concerning color kansei evaluation, and analyzed the sane data by both conventional quantification theory type I and rough set theory. Finally, we compared the effectiveness of both methods for extracting rules and examined the extensions of rough set theory in kansei engineering.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05d
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• pp.1040-1045
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• 2002

This paper described the developed website usability evaluation system in terms of Kansei engineering using neural network. Developed system simultaneously operates with the MS Internet Explorer by entering the target URL for usability evaluation, and the results are learned using neural network. We firstly derived the Kansei adjectives and website usability factors and they were matched by the correspondence analysis. Then, highly corresponded adjectives were implemented on the system for the Kansei evaluation. Finally, the results showed the appropriate efficiency of developed algorithm and system for the website evaluation. If more subjects were used for the system learning, the efficiency of system could be improved.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.230-234
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• 2000

Thermal comfort by wearing clothes is the important element which gives influence to a clothing comfort. The thermal comfort of clothes have been evaluated by sensory test and physical property of clothes material. To evaluate a thermophysiological comfort. a new evaluation method which measures the physiological response such as electroencephalogram(EEG) is attracting the attention of many people. In the chilly environment, the EEGs in t재 kinds of thermal conditions : with and without clothes were measured. By utilizing the chaos analysis, the behavior of the obtained EEGs were quantiatively expressed in the correlation dimension. As a result, the correlation dimension of the EEGs in being thermal comfortable feeling by putting on clothes, was bigger than the correlation dimension of the EEGs in being cold and discomfort. These results suggest that chaotic analysis of EEG is effective to the quantitative evaluation of thermal esthesis.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2004.11a
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• pp.22-22
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• 2004

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.129-141
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• 2001

Kansei engineering or image technology is a tool to analyze relation between product design components and the impression or feeling of human for physical products. This paper attempts to construct the designer\`s aid tool for developing corporate identity(CI) symbol mark based on the hybrid Kansei engineering. It combines the forward Kansei engineering for translating consumer\`s feeling into design components of CI symbol mark and the backward Kansei engineering for evaluating consumer\`s feeling for CI symbol mark. The semantic differential(SD) evaluation experiment is carried out to find the relations between image and design. The backward Kansei engineering system is modelled by fuzzy neural network. This research is expected to contribute to the development of CI symbol mark that correspond to comsumer\`s image.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.20-23
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• 2002

In Japan, deodorizing airflesheners are very popular to make air flesh by deodorizing odor in rooms, toilet as well as inside a car. There are in different features in deodorizing material of Gel and Liquid, in a shape of bottle from tall to low height, in bottle color and so on. These different features will influence the customer's feeling to the products of deodorizing airfleshener. This paper deals with the psychological evaluation of the features of deodorizing airfleshener on the SD scale with kansei words. The evaluated data were analyzed by Quantification Theory Type I that leads to the relational rules between the product feature and the kansei words. The beautiful and graceful kansei consists of low height, middle width deformed round shape, but easy operational feature is based on tall shape design. These results are helpful to develop a new product of deodorizing airfleshener.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.271-279
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• 2022

In the discipline of design science, the integration of cognitive, semantic, and affective elements is crucial in the conception and development of a product. Affective components in IT artefacts have attracted researchers' attention, but little attention has been given to Geographic Information Systems (GIS). This research was conducted to identify emotions in web-based GIS, and determine design influences on the emotions using Kansei engineering (KE). In the evaluation procedure, ten web-based GIS were used as specimens, and 20 Kansei words were used as emotional descriptors in the Kansei checklist. 50 participants were asked to rate their emotional responses towards the specimens on the Kansei checklist. Principal Component Analysis was used to discover the semantic structure of Kansei, in which dynamism and spaciousness were identified. Significant Kansei concepts were identified using Factor Analysis, in which dynamic & well-organized, refreshing, spacious, professional, and nautical-look were identified. Partial Least Square analysis has assisted the research in discovering the significant design influence to the Kansei. These findings provide designers and other stakeholders with valuable knowledge for strategizing future web-based GIS designs that incorporate user emotions.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.16.2-16
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• 2001

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.161-172
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• 2006

This study aims to compare and contrast the Kansei modeling methods for building a luxuriousness model that people feel about appearance of mobile phones. For the evaluation based on Kansei engineering approaches, 15 participants were employed to evaluate 18 mobile phones using a questionnaire. The results of evaluation were analyzed to build luxuriousness models through quantification I method, neural network, and decision tree method, respectively. The performance of Kansei modeling methods was compared and contrasted in terms of accuracy and predictability. The result of comparison of modeling methods indicated that model accuracy and predictability was closely related to the number of variables and data size. It was also revealed that quantification I method was the best in terms of model accuracy while decision tree method was the best modeling method with small variance in terms of predictability. However, it was empirically found that quantification I method showed extremely unstable predictability with small number of data. Consequently, it is expected that the research findings of this study might be utilized as a guideline for selecting proper Kansei modeling method.