Jyh-Rong Chou

Automatic design support and image evaluation of two-coloured products using colour association and colour harmony scales and genetic algorithm

Colour plays a key role in determining a consumers response to a products appearance. Accordingly, this study proposes an automatic design support system which enables a designer either to emulate the colour scheme of a two-coloured product and then to determine its corresponding image perception, or to search for the two-colour combination which most closely meets the required image perception. The proposed system combines a gray theory-based colour-association evaluation method and a colour-harmony-based aesthetic evaluation method to design and evaluate different product-colour schemes. Since colour-harmony theories cannot be implemented directly using the additive primaries (i.e. R (Red), G (Green) and B (Blue)) used in most computer-based colour emulations, this study develops a RGB-based colour-association and colour-harmony measurement scheme to evaluate the image perception of a particular product-colour scheme. In an inverse process, a genetic algorithm is applied to search for the near-optimal colour combination which satisfies the specified product colour-association goal and achieves a high degree of colour harmony. Various case studies involving the design and evaluation of a two-coloured thermos flask are provided for illustration purposes to demonstrate the effectiveness of the proposed method.

A linguistic evaluation approach for universal design

Universal design (UD) is an approach for developing products and environments that are usable by all people to the greatest extent possible. It benefits users of all ages and abilities without the need for adaptation or specialized design. Although a set of acknowledged principles has been developed and commonly used by industry and academia, it is difficult to quantitatively evaluate whether a product is indeed a good example of UD. This study improves the shortcomings of traditional analytical hierarchy process (AHP) methods in quantitative judgments, priority analysis, and aggregation performance, and proposes a linguistic evaluation approach for UD. The aims of this study are (1) to construct a hierarchy for evaluation using criteria against the UD principles, (2) to develop a convenient and effective eigenvalue algorithm for deriving the weights of criteria, and (3) to aggregate preference information and rank the order of decision alternatives by using linguistic variables associated with fuzzy weighted average techniques. An empirical study is conducted to illustrate the practicability of the proposed approach. In addition to UD, the proposed linguistic evaluation approach can be used to systematically assess alternatives from criteria that are relevant to a set of qualitative attributes.

On-line learning performance and computer anxiety measure for unemployed adult novices using a grey relation entropy method

On-line learning is an asynchronous computer-based learning mode that allows learners to learn anytime and anywhere in their own environment using information and communication technology. It can be considered as a way to bridge the digital gap. How a computer novice performs in such virtual and asynchronous learning environments is an interesting issue in human-computer interaction research. This paper presents the results of a study to investigate on-line learning performance and computer anxiety for unemployed adult novices. In this study, we propose a novel idea that integrates the concept of Shannon entropy into a grey relational analysis model. The proposed method was used to measure human information behavior in relation to on-line learning performance and computer anxiety. A total of 115 unemployed adults voluntarily participated in the experimental study. All experimental subjects were divided into groups according to individual differences in gender, age ranges, educational levels, and learning performances. Taking advantage of the grey relation entropy operation, we derived the perceptive correlations among different classified groups in terms of the accessibility of on-line learning and computer anxiety scales, respectively. Through the empirical study, certain on-line learning characteristics were also identified.

A Kansei evaluation approach based on the technique of computing with words

Abstract Kansei evaluation plays a vital role in the implementation of Kansei engineering; however, it is difficult to quantitatively evaluate customer preferences of a product’s Kansei attributes as such preferences involve human perceptual interpretation with certain subjectivity, uncertainty, and imprecision. An effective Kansei evaluation requires justifying the classification of Kansei attributes extracted from a set of collected Kansei words, establishing priorities for customer preferences of product alternatives with respect to each attribute, and synthesizing the priorities for the evaluated alternatives. Moreover, psychometric Kansei evaluation systems essentially require dealing with Kansei words. This paper presents a Kansei evaluation approach based on the technique of computing with words (CWW). The aims of this study were (1) to classify collected Kansei words into a set of Kansei attributes by using cluster analysis based on fuzzy relations; (2) to model Kansei preferences based on semantic labels for the priority analysis; and (3) to synthesize priority information and rank the order of decision alternatives by means of the linguistic aggregation operation. An empirical study is presented to demonstrate the implementation process and applicability of the proposed Kansei evaluation approach. The theoretical and practical implications of the proposed approach are also discussed.

An ideation method for generating new product ideas using TRIZ, concept mapping, and fuzzy linguistic evaluation techniques

This paper presents an ideation methodology for generating new product ideas.The Su-field enhanced concept mapping diagram is used to clarify potential problems.TRIZ methods are employed to abstract inventive problems and generate novel product ideas.Promising product ideas are determined using fuzzy linguistic evaluation techniques. The quality of initial ideas is considered a critical determinant for successful new product development (NPD). This study presents an ideation method for generating new product ideas. The aims of the proposed method are (1) to clarify and identify potential problems involved in the knowledge domain of the product design through the Su-field enhanced concept mapping diagram; (2) to abstract inventive problems and generate novel product ideas by means of the theory of inventive problem solving (TRIZ) methodology; and, (3) to develop an effective decision aiding method for evaluating alternative ideas and determining promising product ideas using fuzzy linguistic evaluation techniques. The applicability of the ideation method is demonstrated through a case study of an air purifier design. The theoretical and practical implications of the ideation method are also discussed.