Intelligent systems are now being used more commonly than in the past. These involve cognitive, evolving and artificial-life, robotic, and decision making systems, to name a few. Due to the tremendous speed of development, on both fundamental and technological levels, it is virtually impossible to offer an up-to-date, yet comprehensive overview of this field. Nevertheless, the need for a volume presenting recent developments and trends in this domain is huge, and the demand for such a volume is continually increasing in industrial and academic engineering 1 communities. Although there are a few volumes devoted to similar issues, none offer a comprehensive coverage of the field; moreover they risk rapidly becoming obsolete. The editors of this volume cannot pretend to fill such a large gap. However, it is the editors' intention to fill a significant part of this gap. A comprehensive coverage of the field should include topics such as neural networks, fuzzy systems, neuro-fuzzy systems, genetic algorithms, evolvable hardware, cellular automata-based systems, and various types of artificial life-system implementations, including autonomous robots. In this volume, we have focused on the first five topics listed above. The volume is composed of four parts, each part being divided into chapters, with the exception of part 4. In Part 1, the topics of "Evolvable Hardware and GAs" are addressed. In Chapter 1, "Automated Design Synthesis and Partitioning for Adaptive Reconfigurable Hardware," Ranga Vemuri and co-authors present state-of-the-art adaptive architectures, their classification, and their applications."

The focus of this volume is comprised of the fundamentals, models, and information technologies (IT) methods and tools for disaster prediction and mitigation. A more detailed list of topics includes mathematical and computational modeling of processes leading to or producing disasters, modeling of disaster effects, IT means for disaster mitigation, including data mining tools, knowledge-based and expert systems for use in disaster circumstances, GIS-based systems for disaster prevention and mitigation and equipment for disaster-prone areas. A specific type or class of disasters (natural or human-made), however will not be part of the main focus of this work. Instead, this book was conceived to offer a comprehensive, integrative view on disasters, seeking to determine what various disasters have in common. Because disaster resilience and mitigation involve humans, societies and cultures, not only technologies and economic models, special attention was paid in this volume to gain a comprehensive view on these issues, as a foundation of the IT tool design.

Computational intelligence techniques are gaining momentum in the medical prognosis and diagnosis. This volume presents advanced applications of machine intelligence in medicine and bio-medical engineering. Applied methods include knowledge bases, expert systems, neural networks, neuro-fuzzy systems, evolvable systems, wavelet transforms, and specific internet applications. The volume is written in view of explaining to the practitioner the fundamental issues related to computational intelligence paradigms and to offer a fast and friendly-managed introduction to the most recent methods based on computer intelligence in medicine.

This volume offers comprehensive coverage of intelligent systems, including fundamental aspects, software-, sensors-, and hardware-related issues. Moreover, the contributors to this volume provide, beyond a systematic overview of intelligent interfaces and systems, deep, practical knowledge in building and using intelligent systems in various applications. Special emphasis is placed on specific aspects and requirements in applications.

Intelligent systems and technologies are increasing finding their ways in our daily lives. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems; A Fuzzy Density Analysis of Subgroups by means of DNA Oligonucleotides; Evolution of Cooperating Classification Rules with an Archiving Strategy to Underpin Collaboration; Designing Agents with Dynamic Capability; Localized versus Locality Preserving Representation Methods in Face Recognition Tasks; Invariance Properties of Recurrent Neural Networks; Solving Bioinformatics Problems by Soft Computing Techniques; Transforming an Interactive Expert Code into a Statefull Service and a Multicoreenabled System; Ro-WordNet with Paradigmatic Morphology and Subjectivity Mark-up; Special Cases of Relative Object Qualification using the AMONG Operator; Effective Speaker Tracking Strategies for Multi-party Human-Computer Dialogue; The Fuzzy Interpolative Control for Passive Greenhouses; GPS safety system for airplanes; 3D Collaborative Interfaces for E-learning; Open Projects in Contemporary E-Learning; Software Platform for Archaeological Patrimony Inventory and Management. The book is directed to the graduate students, researchers, professors and the practitioner of intelligent systems.

The focus of this volume is comprised of the fundamentals, models, and information technologies (IT) methods and tools for disaster prediction and mitigation. A more detailed list of topics includes mathematical and computational modeling of processes leading to or producing disasters, modeling of disaster effects, IT means for disaster mitigation, including data mining tools, knowledge-based and expert systems for use in disaster circumstances, GIS-based systems for disaster prevention and mitigation and equipment for disaster-prone areas. A specific type or class of disasters (natural or human-made), however will not be part of the main focus of this work. Instead, this book was conceived to offer a comprehensive, integrative view on disasters, seeking to determine what various disasters have in common. Because disaster resilience and mitigation involve humans, societies and cultures, not only technologies and economic models, special attention was paid in this volume to gain a comprehensive view on these issues, as a foundation of the IT tool design.

This volume offers comprehensive coverage of intelligent systems, including fundamental aspects, software-, sensors-, and hardware-related issues. Moreover, the contributors to this volume provide, beyond a systematic overview of intelligent interfaces and systems, deep, practical knowledge in building and using intelligent systems in various applications. Special emphasis is placed on specific aspects and requirements in applications.

Intelligent systems and technologies are increasing finding their ways in our daily lives. This book presents a sample of recent research results from key researchers. The contributions include: Introduction to intelligent systems; A Fuzzy Density Analysis of Subgroups by means of DNA Oligonucleotides; Evolution of Cooperating Classification Rules with an Archiving Strategy to Underpin Collaboration; Designing Agents with Dynamic Capability; Localized versus Locality Preserving Representation Methods in Face Recognition Tasks; Invariance Properties of Recurrent Neural Networks; Solving Bioinformatics Problems by Soft Computing Techniques; Transforming an Interactive Expert Code into a Statefull Service and a Multicoreenabled System; Ro-WordNet with Paradigmatic Morphology and Subjectivity Mark-up; Special Cases of Relative Object Qualification using the AMONG Operator; Effective Speaker Tracking Strategies for Multi-party Human-Computer Dialogue; The Fuzzy Interpolative Control for Passive Greenhouses; GPS safety system for airplanes; 3D Collaborative Interfaces for E-learning; Open Projects in Contemporary E-Learning; Software Platform for Archaeological Patrimony Inventory and Management. The book is directed to the graduate students, researchers, professors and the practitioner of intelligent systems.

Computational intelligence techniques are gaining momentum in the medical prognosis and diagnosis. This volume presents advanced applications of machine intelligence in medicine and bio-medical engineering. Applied methods include knowledge bases, expert systems, neural networks, neuro-fuzzy systems, evolvable systems, wavelet transforms, and specific internet applications. The volume is written in view of explaining to the practitioner the fundamental issues related to computational intelligence paradigms and to offer a fast and friendly-managed introduction to the most recent methods based on computer intelligence in medicine.

Intelligent systems are now being used more commonly than in the past. These involve cognitive, evolving and artificial-life, robotic, and decision making systems, to name a few. Due to the tremendous speed of development, on both fundamental and technological levels, it is virtually impossible to offer an up-to-date, yet comprehensive overview of this field. Nevertheless, the need for a volume presenting recent developments and trends in this domain is huge, and the demand for such a volume is continually increasing in industrial and academic engineering 1 communities. Although there are a few volumes devoted to similar issues, none offer a comprehensive coverage of the field; moreover they risk rapidly becoming obsolete. The editors of this volume cannot pretend to fill such a large gap. However, it is the editors' intention to fill a significant part of this gap. A comprehensive coverage of the field should include topics such as neural networks, fuzzy systems, neuro-fuzzy systems, genetic algorithms, evolvable hardware, cellular automata-based systems, and various types of artificial life-system implementations, including autonomous robots. In this volume, we have focused on the first five topics listed above. The volume is composed of four parts, each part being divided into chapters, with the exception of part 4. In Part 1, the topics of "Evolvable Hardware and GAs" are addressed. In Chapter 1, "Automated Design Synthesis and Partitioning for Adaptive Reconfigurable Hardware," Ranga Vemuri and co-authors present state-of-the-art adaptive architectures, their classification, and their applications."

The focus of this volume is comprised of the fundamentals, models, and information technologies (IT) methods and tools for disaster prediction and mitigation. A more detailed list of topics includes mathematical and computational modeling of processes leading to or producing disasters, modeling of disaster effects, IT means for disaster mitigation, including data mining tools, knowledge-based and expert systems for use in disaster circumstances, GIS-based systems for disaster prevention and mitigation and equipment for disaster-prone areas. A specific type or class of disasters (natural or human-made), however will not be part of the main focus of this work. Instead, this book was conceived to offer a comprehensive, integrative view on disasters, seeking to determine what various disasters have in common. Because disaster resilience and mitigation involve humans, societies and cultures, not only technologies and economic models, special attention was paid in this volume to gain a comprehensive view on these issues, as a foundation of the IT tool design.