By Tetsuya Mizutani, Yuki Shinagawa, Naoki Murakami, Shigeru Igarashi (auth.), Jingsheng Lei, Fu Lee Wang, Hepu Deng, Duoqian Miao (eds.)
This quantity lawsuits comprises revised chosen papers from the 4th overseas convention on synthetic Intelligence and Computational Intelligence, AICI 2012, held in Chengdu, China, in October 2012. the whole of 163 high quality papers offered have been conscientiously reviewed and chosen from 724 submissions. The papers are prepared into topical sections on purposes of synthetic intelligence, functions of computational intelligence, facts mining and information discovery, evolution process, specialist and choice help platforms, fuzzy computation, info safety, clever keep an eye on, clever photograph processing, clever details fusion, clever sign processing, computer studying, neural computation, neural networks, particle swarm optimization, and development recognition.
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Additional info for Artificial Intelligence and Computational Intelligence: 4th International Conference, AICI 2012, Chengdu, China, October 26-28, 2012. Proceedings
The brands of the 8 mobile phones were Nokia, LG, Desay, ZTE, Haier, and Meizu. To eliminate the influence of different colors and materials on the perception, these samples were similar in color and material, which are illustrated in Fig. 1. Nokia E63 Nokia C6 Nokia 5310 LG GD300S Desay M800 ZTE U236 Fig. 1. 2 Y. Li and L. 83) were invited to participate in our experiment. All participants selected for the study had the experience using mobile phone at least 2 years. And they were college students receiving professional training in design, as it was felt that they would be more sensitive to kansei than average individuals and better able to concretely describe their thoughts about the product design.
Not only make product meet users’ emotional needs, pleasing user in visceral level, but also make product be easy to operate, satisfying user in behavioral level. In this way, the market competitiveness of product could be really enhanced. 6 Conclusions Kansei and usability are two important factors of products. To increase the market competitiveness of products, designers must take them into account. In this paper, we applied data mining method to study the relationship between kansei and usability.
Education input refers to all the human resources, funds and materials in which funds are human resources and materials in the currency form. Education investment can be divided into family and government education investment. And economic growth refers to the increase in funds in the economic system. Gross domestic product predigests GDP, Family_edu and Gov_edu separately predigest citizen education investment and government education investment. Establish linear model: LN (GDP) = a + b * family _ edu + c * gov _ edu , a , b and c is estimation parameters.