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Exploiting new advanced structures and electromechanical systems, e. g., adaptive structures, high-precision systems, micro electromechanical systems, distributed sensors/actuators, precision manipulation and controls, etc., has been becoming one of the mainstream research and development activities (structure & motion) in recent years. These new systems and devices could bring a new technological revolution in modern industries and further, directly or indirectly, impact human life. In the search for and research in innovative technologies, it is proved that piezoelectric materials are very versatile in both sensor and actuator applications. Consequently, piezoelectric technology has been widely applied to a large number of industrial applications and devices, varying from thin-film micro sensors/actuators to large space structures in addition to those relatively conventional applications, e. g., sensors, actuators, hydrophones, precision manipulators, mobile robots, micro motors, etc. There have been a few books on piezoelectricity published in the past; however, a unified presentation of piezoelectric shells and distributed senSing/control applications is still lacking. This book is intended to fill the gap and to pro~de practising engineers and researchers with an introduction to advanced piezoelectric shell theories and distributed sensor/actuator technologies in structural identification and control. This book represents a collection of the author's recent research and development on piezoelectric shells and related applications to distributed measurement and control of continuaj it reflects six best-paper awards, including [ xviii] • Contents. two ASME Best-Paper Awards in recent years.

A zero-suppressed decision diagram (ZDD) is a data structure to represent objects that typically contain many zeros. Applications include combinatorial problems, such as graphs, circuits, faults, and data mining. This book consists of four chapters on the applications of ZDDs. The first chapter by Alan Mishchenko introduces the ZDD. It compares ZDDs to BDDs, showing why a more compact representation is usually achieved in a ZDD. The focus is on sets of subsets and on sum-of-products (SOP) expressions. Methods to generate all the prime implicants (PIs), and to generate irredundant SOPs are shown. A list of papers on the applications of ZDDs is also presented. In the appendix, ZDD procedures in the CUDD package are described. The second chapter by Tsutomu Sasao shows methods to generate PIs and irredundant SOPs using a divide and conquer method. This chapter helps the reader to understand the methods presented in the first chapter. The third chapter by Shin-Ichi Minato introduces the''frontier-based''method that efficiently enumerates certain subsets of a graph. The final chapter by Shinobu Nagayama shows a method to match strings of characters. This is important in routers, for example, where one must match the address information of an internet packet to the proprer output port. It shows that ZDDs are more compact than BDDs in solving this important problem. Each chapter contains exercises, and the appendix contains their solutions. Table of Contents: Preface / Acknowledgments / Introduction to Zero-Suppressed Decision Diagrams / Efficient Generation of Prime Implicants and Irredundant Sum-of-Products Expressions / The Power of Enumeration--BDD/ZDD-Based Algorithms for Tackling Combinatorial Explosion / Regular Expression Matching Using Zero-Suppressed Decision Diagrams / Authors'and Editors'Biographies / Index

Compressed sensing (CS) allows signals and images to be reliably inferred from undersampled measurements. Exploiting CS allows the creation of new types of high-performance sensors including infrared cameras and magnetic resonance imaging systems. Advances in computer vision and deep learning have enabled new applications of automated systems. In this book, we introduce reconstruction-free compressive vision, where image processing and computer vision algorithms are embedded directly in the compressive domain, without the need for first reconstructing the measurements into images or video. Reconstruction of CS images is computationally expensive and adds to system complexity. Therefore, reconstruction-free compressive vision is an appealing alternative particularly for power-aware systems and bandwidth-limited applications that do not have on-board post-processing computational capabilities. Engineers must balance maintaining algorithm performance while minimizing both the number of measurements needed and the computational requirements of the algorithms. Our study explores the intersection of compressed sensing and computer vision, with the focus on applications in surveillance and autonomous navigation. Other applications are also discussed at the end and a comprehensive list of references including survey papers are given for further reading.

The applications involving electromagnetic fields are so pervasive that it is difficult to estimate their contribution to the industrial output: generation of electricity, power transmission lines, electric motors, actuators, relays, radio, TV and microwave transmission and reception, magnetic storage, and even the mundane little magnet used to hold a paper note on the refrigerator are all electromagnetic in nature. One would be hard pressed to find a device that works without relaying on any electromagnetic principle or effect. This text provides a good theoretical understanding of the electromagnetic field equations but also treats a large number of applications. In fact, no topic is presented unless it is directly applicable to engineering design or unless it is needed for the understanding of another topic. In electrostatics, for example, the text includes discussions of photocopying, ink-jet printing, electrostatic separation and deposition, sandpaper production, paint spraying, and powder coating. In magnetics, the applications discussed include electric motors, implantable magnets, nuclear magnetic resonance, magnetic stirring of molten materials, and electromagnetic braking and bearings. Electric motors and transformers are used to demonstrate the ideas of magnetic forces and torques and of induction; the applications discussed include the new super-efficient electric drives, linear induction motors, and implantable transformers to power life-sustaining devices. The discussion of wave-propagation phenomena will include applications of new materials to aerospace systems, such as the so-called stealth materials, as well as the use of electromagnetic weaves for materials processing, such as grain drying with microwaves, microwave detection of explosives, and remote sensing of the earth and its resources.

Micro-TAS'98 is the third of a series of symposia initiated by MBSA (University of Twente) in 1994, on the subject of miniaturizing, and integrating within a monolithic structure, the chemical, biochemical and biological procedures commonly used for analysis and synthesis. The primary tool used to develop micro-total analysis systems (mu- TAS) has been micro-photolithographic patterning and micromachining. These powerful tools of Micro System Technology (MST or MEMS) have been applied in highly imaginative ways to develop microchip chemical arrays, fully integrated pump and fluid manifolds, and electrokinetically driven micro-channel systems to be used for genetic analysis, clinical diagnostics and environmental monitoring, and to integrate reactions as diverse as the polymerase chain reaction (PCR) and the large volume, partial oxidation of ammonia. This text illustrates the rapid expansion of the field, the extensive industrial involvement, the increasing number of participating researchers, the expanding range of concepts and applications that utilize MST and microfluidic devices, and new MST-compatible plastic micro-machining to meet the needs of the life science community. This volume contains the proceedings of the Third International Symposium on Micro-Total Analysis Systems, mu-TAS'98, held on October 13-16 in Banff, Alberta, Canada. State-of-the-art invited and contributed papers presented by the world's leading mu- TAS research groups provide a highly informative picture of the growth since 1994 and of the promising future of this exciting and rapidly growing field.

During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland.The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.

A reactive system is one that is in continual interaction with its environment and executes at a pace determined by that environment. Examples of reactive systems are network protocols, air-traffic control systems, industrial-process control systems etc. Reactive systems are ubiquitous and represent an important class of systems. Due to their complex nature, such systems are extremely difficult to specify and implement. Many reactive systems are employed in highly-critical applications, making it crucial that one considers issues such as reliability and safety while designing such systems. The design of reactive systems is considered to be problematic, and p.oses one of the greatest challenges in the field of system design and development. In this paper, we discuss specification-modeling methodologies for reactive systems. Specification modeling is an important stage in reactive system design where the designer specifies the desired properties of the reactive system in the form of a specification model. This specification model acts as the guidance and source for the implementation. To develop the specification model of complex systems in an organized manner, designers resort to specification modeling methodologies. In the context of reactive systems, we can call such methodologies reactive-system specification modeling methodologies.

Models in system design follow the general tendency in electronics in terms of size, complexity and difficulty of maintenance. While a model should be a manageable representation of a system, this increasing complexity sometimes forces current CAD-tool designers and model writers to apply modeling techniques to the model itself. Model writers are interested in instrumenting their model, so as to extract critical information before the model is complete. CAD tools designers use internal representations of the design at various stages. The complexity has also led CAD-tool developers to develop formal tools, theories and methods to improve relevance, completeness and consistency of those internal representations. Information modeling involves the representation of objects, their properties and relationships. Performance Modeling When it comes to design choices and trade-offs, performance is generally the final key. However performance estimations have to be extracted at a very early stage in the system design. Performance modeling concerns the set of tools and techniques that allow or help the designer to capture metrics relating to future architectures. Performance modeling encompasses the whole system, including software modeling. It has a strong impact on all levels of design choices, from hardware/software partitioning to the final layout. Information Modeling Specification and formalism have in the past traditionally played little part in the design and development of EDA systems, their support environments, languages and processes. Instead, EDA system developers and EDA system users have seemed to be content to operate within environments that are often extremely complex and may be poorly tested and understood. This situation has now begun to change with the increasing use of techniques drawn from the domains of formal specification and database design. This section of this volume addresses aspects of the techniques being used. In particular, it considers a specific formalism, called information modeling, which has gained increasing acceptance recently and is now a key part of many of the proposals in the EDA Standards Roadmap, which promises to be of significance to the EDA industry. In addition, the section looks at an example of a design system from the point of view of its underlying understanding of the design process rather than through a consideration of particular CAD algorithms. Meta-Modeling: Performance and Information Modeling contains papers describing the very latest techniques used in meta-modeling. It will be a valuable text for researchers, practitioners and students involved in Electronic Design Automation.

Integral Equation Methods for Electromagnetic and Elastic Waves is an outgrowth of several years of work. There have been no recent books on integral equation methods. There are books written on integral equations, but either they have been around for a while, or they were written by mathematicians. Much of the knowledge in integral equation methods still resides in journal papers. With this book, important relevant knowledge for integral equations are consolidated in one place and researchers need only read the pertinent chapters in this book to gain important knowledge needed for integral equation research. Also, learning the fundamentals of linear elastic wave theory does not require a quantum leap for electromagnetic practitioners. Integral equation methods have been around for several decades, and their introduction to electromagnetics has been due to the seminal works of Richmond and Harrington in the 1960s. There was a surge in the interest in this topic in the 1980s (notably the work of Wilton and his coworkers) due to increased computing power. The interest in this area was on the wane when it was demonstrated that differential equation methods, with their sparse matrices, can solve many problems more efficiently than integral equation methods. Recently, due to the advent of fast algorithms, there has been a revival in integral equation methods in electromagnetics. Much of our work in recent years has been in fast algorithms for integral equations, which prompted our interest in integral equation methods. While previously, only tens of thousands of unknowns could be solved by integral equation methods, now, tens of millions of unknowns can be solved with fast algorithms. This has prompted new enthusiasm in integral equation methods. Table of Contents: Introduction to Computational Electromagnetics / Linear Vector Space, Reciprocity, and Energy Conservation / Introduction to Integral Equations / Integral Equations for Penetrable Objects / Low-Frequency Problems in Integral Equations / Dyadic Green's Function for Layered Media and Integral Equations / Fast Inhomogeneous Plane Wave Algorithm for Layered Media / Electromagnetic Wave versus Elastic Wave / Glossary of Acronyms

The idea for this book originated during the workshop “Model order reduction, coupled problems and optimization” held at the Lorentz Center in Leiden from S- tember 19–23, 2005. During one of the discussion sessions, it became clear that a book describing the state of the art in model order reduction, starting from the very basics and containing an overview of all relevant techniques, would be of great use for students, young researchers starting in the?eld, and experienced researchers. The observation that most of the theory on model order reduction is scattered over many good papers, making it dif?cult to?nd a good starting point, was supported by most of the participants. Moreover, most of the speakers at the workshop were willing to contribute to the book that is now in front of you. The goal of this book, as de?ned during the discussion sessions at the workshop, is three-fold:?rst, it should describe the basics of model order reduction. Second, both general and more specialized model order reduction techniques for linear and nonlinear systems should be covered, including the use of several related numerical techniques. Third, the use of model order reduction techniques in practical appli- tions and current research aspects should be discussed. We have organized the book according to these goals. In Part I, the rationale behind model order reduction is explained, and an overview of the most common methods is described.