• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.195-200
• /
• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.301-305
• /
• 2000

The present study is part of the Special Research Project for the Construction of a Kansei Sensory Evaluation Model that is currently underway at the University of Tsukuba. In this study, a robot was operated by remote control at an actual art museum as part of a preliminary experiment. The results obtained therefrom were used to consider how people might view exhibits. In a previous study, a standard lens and s wide-angle lens were used to analyze differences in sensory-based movements, while VRML was used to analyze differences in these movements between a virtual and an actual museum. In the present study, the time delay in remote operation, which is currently unavoidable, placed some restrictions on the degree of freedom with which exhibits could be viewed, but it was apparent that sensory evaluation could be possible depending on the search behavior and viewing time. Furthermore specific viewing behaviors using the robot were observed, suggesting that new Kansei sensory perceptions were derived from these behaviors.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.34-38
• /
• 2002

A virtual human which can evaluate Kansei such as comfort, pain, etc. when the virtual human uses some product is developed. In this paper, method of the evaluation of Kansei by the virtual human is presented. The body of our virtual human is modeled as an uniform non-linear elastic one with a skeleton. The deformation of the body on the contact with some product is simulated using a FEM analysis, and by using of the simulated results (load distribution, strain, etc.) on the contact surface the Kansei is predicted. As examples of the application, comfort of buttocks on seating and pain of arm on hanging of bag are shown. This virtual human can apply for the design of virtual products and also the simulation of medical care.

• Journal of the Ergonomics Society of Korea
• /
• v.25 no.2
• /
• pp.187-196
• /
• 2006

This study aims to develop luxuriousness models based on both users' subjective feelings and objective material characteristics of automobile crash pad using Kansei engineering approach. Based on the results of literature survey and FGI, 12 Kansei variables describing look-and-feel and touch feel and crash pad design variables were extracted for systematically developing both a conceptual model of luxuriousness and a questionnaire for Kansei evaluation. A total of 41 various crash pad samples and 60 participants(customers: 30, designers: 30) were employed to evaluate the crash pad samples using the questionnaire with 9-point semantic differential scale and 100-point modified magnitude estimate scale. Based on the survey results, luxuriousness models were developed by using regression and quantification I method. In addition, they were compared and contrasted with respect to the relative importance of Kansei variables. Consequently, the developed luxurious model could suggest the preferred combination of material properties of crash pad.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.240-243
• /
• 2000

An apparel products retrieval system was proposed in which users can refer to products using Kansei evaluation values. The system adopts relevance feedback using history of the retrieval to learn the tendency of user evaluation. The system is based on a vector space retrieval model using products images expression as semantic scales. The system makes a query from user inputting information and retrieves closest products from the database. Revising algorithms of the difference method. linear multiple regression performed to investigate the effectiveness and criteria of the search. As a result of evaluation of the accuracy, it was found that the linear multiple regression and the neural network models are effective for the retrieval considering the individual Kansei.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2011.05a
• /
• pp.25-26
• /
• 2011

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2001.10a
• /
• pp.7.2-7
• /
• 2001

• Journal of Korean Society of Transportation
• /
• v.28 no.3
• /
• pp.39-49
• /
• 2010

Provision of in-vehicle warning information is of keen interest since it can be effectively used to prevent traffic accident on the road. This study evaluates the effectiveness of information provision modalities based on kansei engineering. Various warning information scenarios using different modalities are devised for the evaluation. Statistical data analysis techniques including factor analysis, correlation analysis, and the general linear model are used to assess the user's affect for information modalities. The evaluation result shows that the provision of visual information consisted of 'text and pictogram' leads to higher understandability. The combination of beep sound and voice message' was identified as a more effective modality for auditory warning. In addition, the red color for the blinking warning signal was preferred by users.

• Journal of Korean Institute of Industrial Engineers
• /
• v.33 no.4
• /
• pp.393-401
• /
• 2007

Affective aspects of design attributes such as color, Pattern, and texture are important to the overall impression and the success of interior products. Among all the interior materials, wallpapers and flooring materials take up largest construction area and they are main components in creating affective impression for customers. This study aims to investigate the relationship between luxuriousness and related affective variables and design elements of wallpapers and flooring materials. The approach consists of 3 steps: (1) selecting related affective features and product design attributes through a literature survey, opinion of expert panel, and focus group interview, (2) conducting evaluation experiments, and (3) developing Kansei models using multivariate statistical analysis and analyzing critical attributes. Evaluation experiment was conducted using a questionnaire made up of 7-point scale and 100-point scale and 30 housewives and 20 interior designers participated in the evaluation experiment. The result of evaluation was analyzed through principal component regression and quantification I analysis. As a result of analyzing the survey data, the relationship between luxuriousness and related affective features and product design attributes was identified, moreover a optimal combination of the design component was identified. Consequently, it is expected that the results of the study would be a basis of the concept of emotion-based design by giving insights about how customers perceive the luxuriousness and suggesting the optimal combination, and providing specific quantitative design guidelines.

• Science of Emotion and Sensibility
• /
• v.12 no.1
• /
• pp.77-86
• /
• 2009

A comfort evaluation of car seat clothing has been proposed for high comforts interior seat clothing. Car seat covers have received wide spread attention due to their man-machine interface working. And then, it will be necessary for measurements on delicate basic mechanical-properties, which closely relate with human touch feeling of its materials. In this research, we have utilized $KES-FB^{(R)}$(Kawabata Evaluation System) series, $^ST300{(R)}$ analogue softness tester and friction tester for measurement a physical properties. In order to consider both kansei and physical properties on interior seat covers, we firstly have established subjective words of judgement for the seat covers. Secondly, related them to the objective measurement of physical properties. Each kansei-language has clearly defined as 'Softness', 'Elasticity', 'Volume' and 'Stickiness' for the adjectives of leather car seat covers. These technical terms have correlated to physical properties in other words, h (mm), bending moment ($gf^*$cm/cm), To-Tm (mm) and ${\mu}$. At this time, fuzzy logic has utilized to predict the value of kansei language through physical values. On the basis of this result, finally it is possible to predict quality index of car seat covers using neural networks technique. In short, we develop a quality evaluation system of car seat clothing combining four physical quantities with kansei engineering.