This volume is the proceedings of the workshop ?Next Generation Design and Verification Methodologies for Distributed Embedded Control Systems? organised by General Motors R&D, India Science Lab. The workshop was held on January 5-6 2007 at the NIAS auditorium, IISc campus, Bangalore, India. This workshop is the first of its kind to be organised by an automotive major to bring together the leaders in the field of embedded systems development to present state-of-the-art work, and to discuss future strategies for addressing the increasing complexity of embedded control systems. The workshop consisted of invited talks given by leading experts and researchers from academic and industrial organizations. The workshop covered all areas of embedded systems development and in particular: Formal specification and verification of distributed, heterogeneous, embedded systems Formal semantics of modeling languages Model-based specification and testing Formal approach to component based development Software product line engineering Automatic code generation for distributed, embedded systems.

This book covers the start-of-the-art research and development for the emerging area of autonomous and intelligent systems. In particular, the authors emphasize design and validation methodologies to address the grand challenges related to safety. This book offers a holistic view of a broad range of technical aspects (including perception, localization and navigation, motion control, etc.) and application domains (including automobile, aerospace, etc.), presents major challenges and discusses possible solutions.

Changing climate in micro and macro level attribute to influence and bring changes in productivity and production trend of every industry including agriculture and its ecosystem. The influence of climate change and its environmental impact on coastal ecosystem greatly influence the life and livelihood of agrarian communities and people involved in allied industries. The book has been authored with objectives of providing understanding on the environmental problems, features of coastal ecosystem, advanced strategies for environmental protection, mitigation strategies for environmental problems in coastal areas and augmenting agriculture income from coastal areas. Note: T&F does not sell or distribute the hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. This title is co-published with NIPA.

This volume is the proceedings of a workshop organized by General Motors research and development laboratory in Bangalore, India. It was the first of its kind to be run by an automotive major to bring together the leaders in the field of embedded systems development to present state-of-the-art work, and to discuss future strategies for addressing the increasing complexity of embedded control systems. The workshop consisted of invited talks given by leading experts and researchers from academic and industrial organizations. It covered all areas of embedded systems development.

This book constitutes the refereed proceedings of the 17th International Conference on Foundations of Software Technology and Theoretical Computer Science, FSTTCS'97. The 18 revised full papers presented were selected from a total of 68 submissions. Also included are five invited papers by Ed Clarke, Deepak Kapur, Madhu Sudan, Vijaya Ramachandran, and Moshe Vardi. Among the topics addressed are concurrency, Petri nets, graph computations, program verification, model checking, recursion theory, rewriting, and error-correcting codes.

Machine Intelligence in Mechanical Engineering explains the latest applications of machine intelligence and data-driven decision-making in mechanical engineering industries. By providing introductory theory, trouble-shooting case studies, detailed algorithms and implementation instructions, this interdisciplinary book will help readers explore additional applications in their own fields. Those with a mechanical background will learn the important tasks related to preprocessing of datasets, feature extraction, verification and validation of machine learning models which unlock these new methods. Machine Intelligence is currently a key topic in industrial automation, enabling machines to solve complex engineering tasks and driving efficiencies in the smart production line. Smart preventative maintenance systems can prevent machine downtime, smart monitoring and control can produce more effective workflows with less human intervention.