• Title/Summary/Keyword: Kansei Engineering

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Incorporating "Kansei Engineering" Approach on Traditional Textiles - A Proposed Method for Identifying Multi-Sensorial Experiences on the Kansei Attributes of Traditional Textiles -

  • Syarief, Achmad
    • The Research Journal of the Costume Culture
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    • v.20 no.1
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    • pp.121-127
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    • 2012
  • When people are asked to described certain textiles, they frequently refer to the expressions of its properties such as attractiveness, uniqueness, shininess, robustness, comfortability, and so on. It shows how senses play important role in it. Human employs their senses when interacting with textiles, most notably visual and tactile/ haptic to absorb its expressive properties. Yet, our sensorial experiences may amplify when interacting with those of traditional textiles, such as batik, as we can entice sensations when seeing its motifs and patterns, smelling its materials, and touching its surfaces. The multi-sensorial importance of seeing, smelling, and touching in the interaction with and experience of textiles suggests that one should address senses in a systematic way when evaluating users' perception on traditional textiles. To address this issue, the paper proposes the incorporation of Kansei Engineering (KE) approach for identifying multi-sensorial experiences on the expressive properties of traditional textiles, using batik as a case of study. KE approach address person's psychological understanding when observing things in order to analyze and study the inherent relationship between person's perceptual knowledge and objects evaluated. This paper outlines the use of KE approach in correlating sensorial perceptions when experience with traditional textiles and ultimately expose users' preferences toward them. Background of KE approach on textiles will be explored and its application for the multi-sensorial investigation of traditional textiles will be discussed.

HIERARCHICAL CLUSTER ANALYSIS by arboART NEURAL NETWORKS and its APPLICATION to KANSEI EVALUATION DATA ANALYSIS

  • Ishihara, Shigekazu;Ishihara, Keiko;Nagamachi, Mitsuo
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.05a
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    • pp.195-200
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    • 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.

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A Study on the Methodologies of the Quality Assessment of the Mobile Telecommunication Units Using Kansei Engineering (감성공학을 이용한 이동통신기기의 품질평가 방법론에 관한 연구)

  • 김동남;조재립
    • Journal of Korean Society for Quality Management
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    • v.27 no.3
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    • pp.154-169
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    • 1999
  • In many fields, Kansei engineering, often called Human Sensibility Ergonomics, has been applied to the product development for customer's satisfaction. Also, it may use to a lot of products and environments related to human's convenient life. If the measurement and the validation of human sensibility are accomplished subjectively and qualitatively, then a good design is expected. This paper considers an application of one of the Kansei engineering's techniques, extraction and categorization of the sensory words, to the products of mobile telecommunication units. First, 1st sensory words were extracted from Korean dictionary, catalogues, pamphlets, etc. Second, 2nd sensory words were extracted from the questionnaires, elimination of synonym, advise of expert, etc. Third, final sensory words were extracted from questionnaires, etc. Fourth, ask to answer the questionnaires with the extracted words in the five-grade semantic differential. Finally, The factor analysis is used to categorize the extracted sensory words, and shows that the words can be grouped into some categories.

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A kansei engineering method to convert subjective customer requirements into product design functions (감성공학을 이용한 미래지향적 신제품개발에 관한 연구)

  • 이순요;권규식
    • Journal of the Ergonomics Society of Korea
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    • v.12 no.2
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    • pp.29-43
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    • 1993
  • This paper presents a conceptual approach to convert customer requirements expressed in ordinary language into a form of qualitative and quantitative functions for developing new products. This approach attempts to combine the concepts of the value engineering and the Kansei engineering. It emphasizes that customer require- ments should be interpreted and reflected on the design of new product. Specific are discussed for extracting subjective requirements and transforming them into qualitative and quantitative functions for product design. This approach is expected to provide the product designer with a systematic efficient tool for incorporating subjective requirements into a product design.

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EXPLORING THE MEANING OF COMFORTABILITY IN WEB SITES: THE KANSEI APPROACH

  • Okada, Roberto;Watanabe, Yuri
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.05a
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    • pp.51-56
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    • 2002
  • Information Technology is becoming ubiquitous. Our lifestyle is changing due to this digital revolution. Many researchers had been working on exploring the meaning and ways to realize the comfortability in physical sites. With the appearance of huge amount of Web sites, which provide a variety of services like electronic commerce, network game, search engines and so on, there are many researchers working on the definition of Web Usability. In this research, we go one step forward, by exploring the meaning of Web Comfortability, based on Kansei Engineering methods.

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A Method of Color KANSEI Information Extraction in Video Data (비디오 데이터에서의 컬러 감성 정보 추출 방법)

  • Choi, Jun-Ho;Hwangi, Myung-Gwon;Choi, Chang;Kim, Pan-Koo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.532-535
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    • 2008
  • The requirement of Digital Culture Content(Movie, Music, Animation, Digital TV, Exhibition and etc.) is increasing so variety and quantity of content is also increasing. The Movie what majority of the digital Content is developing of technology and data. In the result, the efficient retrieval service has required and user want to use a recommendation engine and semantic retrieval methods through the recommendation system. Therefore, this paper will suggest analysing trait element of digital content data, building of retrieval technology, analysing and retrieval technology base on KANSEI vocabulary and etc. For the these, we made a extraction technology of trait element based on semantics and KANSEI processing algorithm based on color information.

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EVALUATION OF COMFORT OR PAIN BY VIRTUAL HUMAN IN USING OF SOME PRODUCT

  • Maekawa, Yoshinori;Hasegawa, Bunzo
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.05a
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    • pp.34-38
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    • 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.

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A Human Sensibility Ergonomics Method for Vehicle Driving Simulator and Verbal Expressions Collected (자동차 주행 시뮬레이터의 운동감 재현 및 감성평가를 위한 감성어휘의 수집)

  • Jeong, Yeong-Hun;Eom, Seong-Suk;Son, Gwon;Choe, Gyeong-Hyeon
    • Journal of the Ergonomics Society of Korea
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    • v.19 no.2
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    • pp.1-14
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    • 2000
  • Driving simulators have been developed for evaluating users' reaction to various driving situations. Dynamic simulators have, however, limitations of the motion feedback in space. Therefore, this paper presents a driving simulator and suggests a human sensibility ergonomics (kansei engineering) method to be used in improving sense of motion through a vehicle simulator. Human sensibility ergonomics(kansei engineering) is defined as translating technology of the customer' feeling about a new product into design elements. Constituents of the simulator were defined and the virtual world was generated by the object modeling technique. Senses perceived were classified into feelings of velocity, acceleration, rotation, and vibration based on the human sensibility associated with driving. And the most frequent verbal expressions were collected from 17 male subjects to define complex human sensibility.

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A Study on Clustering Kansei Factors for the Surface Roughness of Materials

  • Jun, Chang Lim;Choi, Kyungmee
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.49-60
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    • 2003
  • The human sensibility product design requires information on consumer's emotions such as vision, auditory, olfactory, gustatory, or tactile perceptions. In this study, tactile sense which has not been well studied compared to other senses, is measured and statistically analysed. The emotional responses of 37 pairs of positive and negative adjectives describing tactile senses are collected and analysed through the questionnaire to find the correlation between adjectives and surface roughness of the sample. Mean ranks for 37 pairs of adjectives on four samples are obtained, and used to cluster these adjectives by factor analysis, multidimensional scaling, or cluster analysis.