Cognitive Techniques In Visual Data Interpretation

The extremely rapid progress of science dealing with the design of new computer systems and the development of intelligent algorithmic solutions for solving c- plex problems has become apparent also in the field of computational intelligence and cognitive informatics methods. The progress of these new branches of inf- matics has only started a few years ago, but they are already making a very s- nificant contribution to the development of modern technologies, and also forming the foundations for future research on building an artificial brain and systems i- tating human thought processes. We are already able to build robots with basic machine intelligence, which can sometimes perform complex actions and also - erate by adapting to changing conditions of their surroundings. This very impr- sive development of intelligent systems is manifested in the creation of robotic devices which use artificial intelligence algorithms in their operations, mo- ments, when solving difficult problems or communicating with humans. It is also evidenced by the introduction of new methods of reasoning about and interpreting objects or events surrounding the system. One of the fields in which the need to deploy such modern solutions is obvious are cognitive vision systems used both in mobile robots and in computer systems which recognise or interpret the meaning of recorded signals or patterns.

The extremely rapid progress of science dealing with the design of new computer systems and the development of intelligent algorithmic solutions for solving c- plex problems has become apparent also in the field of computational intelligence and cognitive informatics methods. The progress of these new branches of inf- matics has only started a few years ago, but they are already making a very s- nificant contribution to the development of modern technologies, and also forming the foundations for future research on building an artificial brain and systems i- tating human thought processes. We are already able to build robots with basic machine intelligence, which can sometimes perform complex actions and also - erate by adapting to changing conditions of their surroundings. This very impr- sive development of intelligent systems is manifested in the creation of robotic devices which use artificial intelligence algorithms in their operations, mo- ments, when solving difficult problems or communicating with humans. It is also evidenced by the introduction of new methods of reasoning about and interpreting objects or events surrounding the system. One of the fields in which the need to deploy such modern solutions is obvious are cognitive vision systems used both in mobile robots and in computer systems which recognise or interpret the meaning of recorded signals or patterns.

The extremely rapid progress of science dealing with the design of new computer systems and the development of intelligent algorithmic solutions for solving c- plex problems has become apparent also in the field of computational intelligence and cognitive informatics methods. The progress of these new branches of inf- matics has only started a few years ago, but they are already making a very s- nificant contribution to the development of modern technologies, and also forming the foundations for future research on building an artificial brain and systems i- tating human thought processes. We are already able to build robots with basic machine intelligence, which can sometimes perform complex actions and also - erate by adapting to changing conditions of their surroundings. This very impr- sive development of intelligent systems is manifested in the creation of robotic devices which use artificial intelligence algorithms in their operations, mo- ments, when solving difficult problems or communicating with humans. It is also evidenced by the introduction of new methods of reasoning about and interpreting objects or events surrounding the system. One of the fields in which the need to deploy such modern solutions is obvious are cognitive vision systems used both in mobile robots and in computer systems which recognise or interpret the meaning of recorded signals or patterns.

The development of computer science is now so rapid that we, the readers, in-creasingly receive technology news about new solutions and applications which very often straddle the border between the real and the virtual worlds. Computer science is also the area in which cognitive science is witnessing a renaissance, be-cause its combination with technical sciences has given birth to a broad scientific discipline called cognitive informatics. And it is this discipline which has become the main theme of this monograph, which is also to serve as a kind of guide to cognitive informatics problems. This book is the result of work on systems for the cognitive analysis and inter-pretation of various data. The purpose of such an analytical approach is to show that for an in-depth analysis of data, the layers of semantics contained in these sets must be taken into account. The interdisciplinary nature of the solutions proposed means that the subject of cognitive systems forming part of cognitive informatics becomes a new challenge for the research and application work carried out. The authors of this monograph hope that it will guide Readers on an interesting and accurate journey through the intricacies of information and cognitive science.

Security-enriched urban computing and smart grids are areas that attracted many a- demic and industry professionals to research and develop. The goal of this conference was to bring together researchers from academia and industry as well as practitioners to share ideas, problems and solutions relating to the multifaceted aspects of urban computing and the smart grid. This conference includes the following special sessions: Signal Processing, Image Processing, Pattern Recognition and Communications (SIPC 2010), Networking, Fault-tolerance and Security For Distributed Computing Systems (NFSDCS 2010), Security Technology Application (STA 2010), Electric Transportation (ElecTrans 2010), Techniques of Bi-directional Power Computing in High Voltage Power Supply (TBPC 2010), Low Power IT and Applications (LPITA 2010), Computational Intel- gence and Soft Computing (CISC 2010), Distributed Computing and Sensor Networks (DCSN 2010), Advanced Fusion IT (AFIT 2010), Social Media and Social Netwo- ing (SMSN 2010), Software Engineering and Medical Information Engineering (SEMIE 2010), Human-Centered Advanced Research/Education (HuCARE 2010), Database Integrity and Security (DIS 2010), Ubiquitous IT Application (UITA 2010) and Smart Grid Applications (SGA 2010). We would like to express our gratitude to all of the authors of the submitted papers and to all attendees, for their contributions and participation. We believe in the need for continuing this undertaking in the future.

The importance of visual data mining, as a strong sub-discipline of data mining, had already been recognized in the beginning of the decade. In 2005 a panel of renowned individuals met to address the shortcomings and drawbacks of the current state of visual information processing. The need for a systematic and methodological development of visual analytics was detected. This book aims at addressing this need. Through a collection of 21 contributions selected from more than 46 submissions, it offers a systematic presentation of the state of the art in the field. The volume is structured in three parts on theory and methodologies, techniques, and tools and applications.

This volume constitutes the refereed proceedings of the Third International Conference on Advanced Science and Technology, AST 2011, held in Seoul, South Korea, in September 2011. The 37 revised full papers presented in this volume were carefully reviewed and selected from numerous submissions. The papers feature ideas, problems and solutions relating to the multifaceted aspects of the Advanced Science and Technology, such as communication and networking; ubiquitous multimedia computing; security technology and information assurance; computer science, software engineering and applications thereof; bio-science and bio-technology; u- and e-service, science and technology; database theory and application; control and automation; signal processing, image processing and pattern recognition; as well as grid and distributed computing.

Cognitive Informatics (CI) is the science of cognitive information processing and its applications in cognitive computing. CI is a transdisciplinary enquiry of computer science, information science, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain. Advances and engineering applications of CI have led to the emergence of cognitive computing and the development of Cognitive Computers (CCs) that reason and learn. As initiated by Yingxu Wang and his colleagues, CC has emerged and developed based on the transdisciplinary research in CI, abstract intelligence (aI), and denotational mathematics after the inauguration of the series of IEEE International Conference on Cognitive Informatics since 2002 at Univ. of Calgary, Stanford Univ., and Tsinghua Univ., etc. This volume in LNCS (subseries of Computational Intelligence), LNCI 323, edited by Y. Wang, D. Zhang, and W. Kinsner, presents the latest development in cognitive informatics and cognitive computing. The book focuses on the explanation of cognitive models of the brain, the layered reference model of the brain, the fundamental mechanisms of abstract intelligence, and the implementation of computational intelligence by autonomous inference and learning engines based on CCs.