During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing."

This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2012, held in Macau, China, in December 2012. The 34 revised full papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on computer science, information technology, artificial intelligence, web intelligence, cognitive science, neuroscience, medical science, life science, economics, data mining, data and knowledge engineering, intelligent agent technology, human computer interaction, complex systems, and system science.

During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing."

The denotational and expressive needs in cognitive informatics, computational intelligence, software engineering, and knowledge engineering have led to the development of new forms of mathematics collectively known as denotational mathematics. Denotational mathematics is a category of mathematical structures that formalize rigorous expressions and long-chain inferences of system compositions and behaviors with abstract concepts, complex relations, and dynamic processes. Typical paradigms of denotational mathematics are concept algebra, system algebra, Real-Time Process Algebra (RTPA), Visual Semantic Algebra (VSA), fuzzy logic, and rough sets. A wide range of applications of denotational mathematics have been identified in many modern science and engineering disciplines that deal with complex and intricate mathematical entities and structures beyond numbers, Boolean variables, and traditional sets. This issue of Springer's Transactions on Computational Science on Denotational Mathematics for Computational Intelligence presents a snapshot of current research on denotational mathematics and its engineering applications. The volume includes selected and extended papers from two international conferences, namely IEEE ICCI 2006 (on Cognitive Informatics) and RSKT 2006 (on Rough Sets and Knowledge Technology), as well as new contributions. The following four important areas in denotational mathem- ics and its applications are covered: Foundations and applications of denotational mathematics, focusing on: a) c- temporary denotational mathematics for computational intelligence; b) deno- tional mathematical laws of software; c) a comparative study of STOPA and RTPA; and d) a denotational mathematical model of abstract games.

This book constitutes the refereed proceedings of the 5th International Conference on Active Media Technology, AMT 2009, held in Beijing, China, in October 2009.

The 47 revised full papers and the 6 keynote talks were carefully reviewed and selected. The papers reflect the shared forum for researchers and practitioniers from diverse fields, such as computer science, information technology, artificial intelligence, media engineering, economics, data mining, data and knowledge engineering, intelligent agent technology, human computer interaction, complex systems and systems science.

It offered new insights into the main research challenges and development of AMT by revealing the interplay between the studies of human informatics and research of informatics on the Web/Internet, mobile and wireless centric intelligent information processing systems.

This volume contains the papers selected for presentation at the Third Inter- tional Conference on Rough Sets and Knowledge Technology (RSKT 2008) held in Chengdu, P. R. China, May 16-19, 2008. The RSKT conferences were initiated in 2006 in Chongqing, P. R. China. RSKT 2007 was held in Toronto, Canada, together with RSFDGrC 2007, as JRS 2007. The RSKT conferences aim to present state-of-the-art scienti?c - sults, encourage academic and industrial interaction, and promote collaborative research in rough sets and knowledge technology worldwide. They place emphasis on exploring synergies between rough sets and knowledge discovery, knowledge management, data mining, granular and soft computing as well as emerging application areas such as bioinformatics, cognitive informatics, and Web intel- gence, both at the level of theoretical foundations and real-life applications. RSKT 2008 focused on ?ve major research ?elds: computing theory and paradigms, knowledge technology, intelligent information processing, intelligent control, and applications. This was achieved by including in the conference program sessions on rough and soft computing, rough mereology with app- cations, dominance-based rough set approach, fuzzy-rough hybridization, gr- ular computing, logical and mathematical foundations, formal concept analysis, data mining, machine learning, intelligent information processing, bioinform- ics and cognitive informatics, Web intelligence, pattern recognition, and real-life applications of knowledge technology. A very strict quality control policy was adopted in the paper review process of RSKT 2008. Firstly, the PC Chairs - viewed all submissions.

This book constitutes the refereed proceedings of the Fourth International Conference on Rough Sets and Knowledge Technology, RSKT 2009, held in Gold Coast, Australia, in July 2009. The 85 revised full papers presented together with 3 keynote papers and 2 special sessions were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on rough sets and computing, rough sets and data reduction, data mining and knowledge discovery, granular computing and cognitive computing, fuzzy sets and computing, knowledge technology and intelligent systems, computational intelligence and applications, image processing and understanding, and formal concept analysis.