Kansei Engineering and Soft Computing: Theory and Practice
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Kansei Engineering and Soft Computing: Theory and Practice

Ying Dai (Iwate Pref. University, Japan), Basabi Chakraborty (Iwate Prefectural University, Japan) and Minghui Shi (Xiamen University, China)
Release Date: August, 2010|Copyright: © 2011 |Pages: 436
DOI: 10.4018/978-1-61692-797-4
ISBN13: 9781616927974|ISBN10: 1616927976|EISBN13: 9781616927998
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Description & Coverage
Description:

With the increasing concern regarding human factors in system development, the concepts of humanized technology and human-related systems have become the focus of more and more research.

Kansei Engineering and Soft Computing: Theory and Practice offers readers a comprehensive review of kansei engineering, soft computing techniques, and the fusion of these two fields from a variety of viewpoints. It explores traditional technologies, as well as solutions to real-world problems through the concept of kansei and the effective utilization of soft computing techniques. This publication is an essential read for professionals, researchers, and students in the field of kansei information processing and soft computing providing both theoretical and practical viewpoints of research in humanized technology.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • DNA Computing
  • Fuzzy Logic
  • High-dimensional Data Clustering
  • Humanoids
  • Kansei
  • Particle Swarm Optimizer
  • Physiological Measurement
  • Semantic Detection
  • Soft Computing
  • Text Mining
Table of Contents
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Editor Biographies
Ying Dai received her B.S. and M.S. degrees from Xian Jiaotong University, China in 1985 and 1988, respectively. After some years working in the same university, she attended Department of Information Engineering, Shinshu University, Japan in 1992. She had a Dr. Eng degree from Shinshu University in 1996. She was granted JSPS Research Fellowships for Young Scientists from 1995 to 1997. She joined the Iwate Pref. University in 1998. She has been an associate professor in the Faculty of Software and Information Science, Iwate Pref. University since 2002. Her main research interests are in the area of Pattern Recognition, Image Understanding, Kansei Information Processing, and Soft Computing Techniques. She is the member of IEEE, IEICE (the Institute of Electronics, Information and Communication Engineers), and JSKE (Japan Society of Kansei Engineering).
Basabi Chakraborty received B.Tech, M.Tech and Ph. D degrees in RadioPhysics and Electronics from Calcutta University, India. She worked in National Center for Knowledge based Computing Systems and Technology affiliated to Indian Statistical Institute, Calcutta, India until 1990. From 1991 to 1993 she worked as a part time researcher in Advanced Intelligent Communication Systems Laboratory in Sendai, Japan. She received another Ph. D in Information Science from Tohoku University, Sendai in 1996. From 1996 to 1998, she worked as a post doctoral research fellow in Research Institute of Electrical Communication, Tohoku University, Japan (under Telecommunication Advancement Organization (TAO) fellowship for a period of 10 months). In 1998 she joined as a faculty in Software and Information Science department of Iwate Prefectural University, Iwate, Japan and currently an Associate Professor in the same department. Her main research interests are in the area of Pattern Recognition, Image Processing, Soft Computing Techniques, Biometrics, Trust and Security in Computer Communication Network. She is a senior member of IEEE, member of ACM, Japanese Neural Network Society (JNNS) and Information Processing Society of Japan (IPSJ), executive committee member of IUPRAI (Indian Unit of Pattern Recognition and Artificial Intelligence), IEEE JC WIE (Women In Engineering) and ISAJ (Indian Scientists Association in Japan).
Minghui Shi received his M.S. degree in 2002 and Dr. degree in 2008 respectively from Jiangnan University and Xiamen University, China. He is currently an assistant professor at Xiamen University. In addition to working as a teacher, he is also a research member of Artificial Intelligence Institute of Xiamen University. His research interests involve Soft Computing Techniques, Machine Learning, Pattern Recognition, Information Processing in TCM (Traditional Chinese Medicine), and Feature Selection.
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Preface

With the increasing concern regarding human factors in system development, the concepts of humanized technology and human-related systems have become the focus of more and more research. Kansei engineering and soft computing are the most representative research fields in this area.

The word kansei (derived from the Japanese ?? [kansei]), refers to human feelings, such as impressions, affect, and emotions, derived by observing the surrounding environment. Such feelings can arouse people to act instinctively—for example, just as happiness results in laughter, enjoying something will motivate an individual to obtain it. In this way, the concept of kansei consists of two distinct aspects: perception-generated feelings and feeling-driven action. Both aspects include issues of uncertainty, diversity, and dependence on the environment. Kansei engineering aims to solve these problems while bringing together culture and technology through the establishment of an information society based on the concept of kansei—in other words, the harmonization of the social, cultural, and natural sciences and technology with human skills, and the creation and promotion of human happiness [1]. With this goal in mind, kansei engineering focuses on the qualitative and quantitative evaluation of kansei, including the measurement and analysis of the impressions, emotions, and sense perceptions of groups and individuals, as well as the development of procedures for the representation, design and creation of products, machines and systems that embody the kansei of groups and individuals. The theories and technologies of soft computing are therefore essential developmental tools in kansei engineering.

Soft computing, a consortium of tools and techniques suitable for dealing with the uncertainty and imprecision of human-centric computing, comprises artificial neural networks, fuzzy logic, the rough set theory, evolutionary computation and other hybrid techniques. Recently, soft computing tools have been developed to solve many real-world problems involving human behavior. Until now, kansei engineering and soft computing have developed as two independent fields.

This book offers the reader a comprehensive review of kansei engineering, soft computing techniques, and the fusion of these two fields from a variety of viewpoints. After introducing the traditional technologies, the book’s focus shifts to the solution of real-world problems through the concept of kansei and the effective utilization of soft computing techniques, while such real world problems often involve uncertainty and imprecision, and are dependence on the context. Cutting-edge research on the measurement of kansei and its application in areas such as design, production, and healthcare is also introduced.

The book aims to reach professionals, researchers and students in the field of kansei information processing and soft computing, both in academia and industry. It will also serve as a reference book for professionals, researchers and students interested in studying existing kansei engineering and soft computing techniques from theoretical and practical viewpoints and obtaining insight into the application of kansei research in humanized technology or human-related systems.

The book is divided into two parts and comprises of 19 chapters. Part I, “Basic Concepts, Framework and Techniques”, consisting of 9 chapters, introduces the framework of soft computing, current soft computing techniques, the general process of constructing kansei retrieval systems, and the implementation of kansei factors in dynamic systems. Part II, “Measurement, Analysis, and Representation of Kansei”, consisting of 10 chapters, covers many critical kansei issues, such as the psychological and physiological measurement of kansei, representing kansei by analyzing the relationship between human’s feelings and physical attributes of entities, and the incorporation of kansei into product design.

The first chapter provides an introduction to the three essential paradigms of soft computing: neural network, fuzzy logic and evolutional computation. These paradigms are integrated to provide a framework for flexible information processing, which is useful for processing kansei-related issues. In particular, the notions, methodologies, and some algorithms of neural networks, fuzzy set theory, and heuristic search techniques, which are utilized throughout the book, are mainly introduced and discussed. Furthermore, methods for applying soft computing techniques to real-world problems involving uncertainty, including kansei-related issues, are presented.

Chapter 2 presents the utility and efficiency of the Particle Swarm Optimization (PSO) technique, a recently developed soft computing tool, in solving real-world humanistic problems. This chapter proposes novel PSO algorithms for clustering high-dimensional data and automatically determining the number of clusters in data mining applications, supported by the results of simulation experiments with synthetic data sets. This chapter is useful in handling optimization and search problems while dealing with kansei databases and categorizing concepts related to kansei.

Chapter 3 introduces basic text mining techniques that help to analyze interviews and questionnaires, including keyword extraction, word graphs, clustering of text and association rule mining. In addition, a case study using text mining for the analysis of interviews and questionnaires revealing the opinions, concerns and needs of subjects is presented. This chapter is useful for learning the basics of text mining and how to use it to extract information such as the concerns and needs of subjects from questionnaire data.

Chapter 4 demonstrates an application of a human cognitive behavior model in developing an automatic biometric authentication system. Using set estimation, the authors developed a novel threshold selection technique for identifying individuals who are learned by the system, and differentiating humans from no-humans. This chapter deals with an important subset of cognitive system design involving human factors and demonstrates the possibility of successful design of such systems through simulation experiments in a real-world environment.

Chapter 5 introduces DNA computing, another emerging computational technique encompassing computer science, biological science and engineering. DNA computing, a variant of biomolecular computation, is now widely accepted as a new computing model for future computing devices. This chapter describes the theoretical framework and formal models of DNA computation and presents several DNA computing models used to solve real-world problems. DNA encoding may play a crucial role in designing successful human-centric computational paradigms that might be useful in kansei engineering.

Chapter 6 summarizes the general flow of kansei retrieval systems and presents the structure of a typical kansei database. Indexing technologies for kansei retrieval are then described and discussed. In particular, in order to speed up the retrieval process, the author proposes an original adaptive R*-tree method that is quite appropriated for the kansei database. This chapter not only helps readers to understand the mechanisms and methodology of kansei retrieval, but also to realize the importance of considering efficiency when constructing a kansei database and performing kansei retrieval.

Human moods are influenced by the multiple forms of media that surround us. Detection of emotions elicited by various media has emerged as an area of active research area in the past few decades. Chapter 7 surveys advances in this area, including a general overview of research on affective analysis of multimedia contents, recent research on detecting emotional semantics from images, videos and music, three typical archetypal systems related to the three fields of images, videos and music, several critical problems, and strategies for problem resolution. This chapter is helpful in understanding state-of-the-art research on kansei analysis regarding multimedia and the critical hurdles to overcome in constructing a kansei-based multimedia retrieval system.

Chapter 8 reviews the fundamental concepts of non-smooth dynamical systems, together with examples showing the diversity of their nonlinear behaviors, and introduces a Takagi-Sugeno fuzzy modeling concept, demonstrating how it could be extended to represent a non-smooth system and applied to a stability analysis to predict the onset of structural instability in the evolution of a dynamical system. This interesting topic implies the potentiality of inferring the bifurcation of kansei evaluation in processes such as product design, painting, or music video production, because they can be considered non-smooth dynamic systems following fuzzy decision rules.

Humanoid and android robots are expected to be one of the greatest new industries of the 21st century. We can therefore anticipate the presence of more and more robots not only in factories but also in our daily lives. Chapter 9 discusses the future relationship between humans and humanoid and android robots. How will robots change human society? Will the robots endanger us? How should we regulate the development of humanoid robots? This chapter is valuable for researchers and engineers who aim to explore the potential of robotic technology from the perspective of kansei.

Chapter 10 and Chapter 11 present the typical processing flow of kansei engineering by measuring and analyzing subjects’ psychological states. After reviewing kansei engineering research on music, which is classified into six categories (kansei evaluation methodology, music psychological research, physiological measurement, music theoretical research, kansei music system and recommendation system), Chapter 10 presents approaches for kansei research on melody and rhythm from the perspective of music theory. Methods for analyzing relations between modes, melodic ranges, or rhythms and kansei evaluation based on principal component analysis are introduced, and how the arrangements of modes affects human impressions and feelings is revealed and applied in a real-time melody recognition system. This chapter helps readers to understand the basis of kansei engineering and how various approaches are applied.

To investigate the relationship between people’s perceptions of sidewalk environments and their component elements, Chapter 11 adopts factor analysis and the rough sets approach to determine the most important attributes to people’s perceptions, minimal attribute sets without redundancy, and a series of decision rules that represent the relationships between perceptions and the physical components of sidewalk environments. The analytical approach promotes better understanding of people’s perceptions of sidewalk environments and then establishes a useful and constructive framework for discussion of walking environment design and management.

As an example of the application of kansei engineering, the development of a kansei communication robot, Ifbot, is presented in Chapter 12. Ifbot communicates with people by expressing emotions through facial expressions. Here, the authors present their development approach, including the association of facial expressions with human emotions using an auto-associative neural network, a soft computing tool. In addition, methods for generating expressive faces that convey human emotion in order to enhance the quality of human-robot communication are discussed. A method for creating personality through facial expressions has also been proposed. This study and its application represent an important development in the cooperation between kansei engineering and soft computing.

Chapter 13 describes how several color sequences (temporal or spatial) affect human impressions, and demonstrates how to develop a color sequence that reminds viewers of the natural world. A number of experiments have investigated the different effects of spatial (or temporal) ordered color sequences on the naturalness by calculating the projected route area and route complexity of a hexagonal diagram comprising six color sequences. Then, a simple fuzzy model of the colors used to give an impression of naturalness is achieved. The proposed techniques are also useful for investigating the effects of color order on other impressions, which play an important role in product design.

Chapter 14 examines how a particular narrative can become the narrative of an entire community, and thereby influence or control the behavior of all members of that community. This research extracts its hypothesis from the narrative theory of scenery, which holds that narratives are distinct with different work experiences and can be shared by people in the same community. These shared normative scenery narratives subsequently influence community members’ behavior. Normative scenery narratives can be viewed as products of the general kansei of farmers in a community. This chapter helps readers to understand how general kansei is formed through sharing of group members’ experiences and feelings, and how it controls the behaviors of the group.

An overview of the emerging approaches for incorporating kansei (human feelings) into system design is presented in Chapter 15. Three approaches involving the relationship between psychophysiology and the design process have been studied. Tools and methods are developed with a psychological basis with respect to human inspiration, behavior and mental images of the design process and requirements. Each of the proposed approaches is supported by real-world examples and applications. This chapter is highly educational in developing the field of kansei design.

Chapter 16 represents another application of a human cognitive action model in designing a person authentication system. This chapter focuses on handwriting as a primary coordinated activity of human movement and, with the help of soft computing tools, presents a framework for tacit handwriting skill analysis for the extraction of embedded knowledge. A technique for detecting human identity by analyzing handwriting captured by a computer writing pad is also presented and is supported by simulation experiments with benchmark data.

Chapter 17 and 18 introduce methods for measuring physiological signals and utilizing these signals to assess human mental states, such as stress, mood, or feelings. Chapter 17 explores salivary biomarkers and their potential to reveal the degree of stress accumulation, while Chapter 18 presents bioelectric signals and their application in estimating human mood states in combination with PCA, HMM and NN approaches . The contents of these two chapters demonstrate the possibility of measuring and analyzing kansei using physiological signals.

Chapter 19 presents a 4-year research project (2008-2011) currently underway at Xiamen University, China, to build China’s first artificial brain. The project takes an “evolutionary engineering” approach, effectively evolving tens of thousands of neural net modules (or “agents” in the sense of Minsky’s “Society of Mind”) and connecting them to make artificial brains. These modules are evolved rapidly and are then connected according to the artificial brain designs of human “brain architects” (BAs). The artificial brain will eventually contain thousands of pattern recognizer modules and hundreds of decision modules that, when suitably combined, will be able to control the hundreds of behaviors of a robot. As a general research report, this chapter is worth reading to understand the construction of a system that is expected to develop functions rivaling the human brain in complexity.

We are confident that professionals, researchers and students in the fields of kansei information processing and soft computing will be able to use this book to learn more about the ways in which kansei research can be applied to different environments.


[1] Japan Society of Kansei Engineering, http://www.jske.org/historical/main_e.html