Iterating Infusion: Clearer Views of Objects, Classes, and Systems is a one-of-a-kind book, not dependent on any single technology. Rather, it provides a way to integrate the most efficient techniques from a variety of programming methods, in a manner that makes designing and programming software look easy. Iterating Infusion presents comprehensive tools for you to best manage and work with object orientation. These include simplified fundamental concepts, popular language comparisons, advanced designing strategies, a broad usage progression, thorough design notations (interaction algebra), and data-oriented (fundamentally-OO) languages. The title, Iterating Infusion, alludes to the fact that any system has multiple, coexisting functional levels and that new levels—both lower and higher—are continually added to the same functional area. The practical effect is to bring processes into focus, always clarifying the vague. The extreme form of this is when separate but compatible technologies are brought together to create advancements; these can be baby-steps or great leaps, with varying amounts of effort. In more general terms, the same thing in a different context can take on much more power. And actually, this phenomenon is at the heart of object-oriented software. Readers have been confirming that, compared to books on just low-level details, Iterating Infusion presents cohesive insights that allow you to solve more problems with the same effort in more key places.

This book constitutes the thoroughly refereed post-proceedings of the 9th International Workshop on Radical Innovations of Software and Systems Engineering in the Future, RISSEF 2002, held in Venice, Italy, in October 2002. The 24 revised full papers presented were carefully reviewed and selected from the 36 invited workshop presentations. The authors evaluate all major paradigms and conceptual issues in software and systems design and analysis, especially regarding their potential for modifications to cope with future needs.

Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.

This volume discusses advances in applied nonlinear optimal control, comprising both theoretical analysis of the developed control methods and case studies about their use in robotics, mechatronics, electric power generation, power electronics, micro-electronics, biological systems, biomedical systems, financial systems and industrial production processes. The advantages of the nonlinear optimal control approaches which are developed here are that, by applying approximate linearization of the controlled systems’ state-space description, one can avoid the elaborated state variables transformations (diffeomorphisms) which are required by global linearization-based control methods. The book also applies the control input directly to the power unit of the controlled systems and not on an equivalent linearized description, thus avoiding the inverse transformations met in global linearization-based control methods and the potential appearance of singularity problems. The method adopted here also retains the known advantages of optimal control, that is, the best trade-off between accurate tracking of reference setpoints and moderate variations of the control inputs. The book’s findings on nonlinear optimal control are a substantial contribution to the areas of nonlinear control and complex dynamical systems, and will find use in several research and engineering disciplines and in practical applications.

In the highly specialized field of caring for children in the PICU, Fuhrman and Zimmerman's Pediatric Critical Care is the definitive reference for all members of the pediatric intensive care team. Drs. Jerry J. Zimmerman and Alexandre T. Rotta, along with an expert team of editors and contributors from around the world, have carefully updated the 6th Edition of this highly regarded text to bring you the most authoritative and useful information on today's pediatric critical care—everything from basic science to clinical applications. - Contains highly readable, concise chapters with hundreds of useful photos, diagrams, algorithms, and clinical pearls. - Uses a clear, logical, organ-system approach that allows you to focus on the development, function, and treatment of a wide range of disease entities. - Features more international authors and expanded coverage of global topics including pandemics, sepsis treatment in underserved communities, specific global health concerns by region. - Covers current trends in sepsis-related mortality and acute care after sepsis, as well as new device applications for pediatric patients. - Provides ultrasound videos and more than 500 board-style review questions and answers on Expert Consult. - Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.

What does a probabilistic program actually compute? How can one formally reason about such probabilistic programs? This valuable guide covers such elementary questions and more. It provides a state-of-the-art overview of the theoretical underpinnings of modern probabilistic programming and their applications in machine learning, security, and other domains, at a level suitable for graduate students and non-experts in the field. In addition, the book treats the connection between probabilistic programs and mathematical logic, security (what is the probability that software leaks confidential information?), and presents three programming languages for different applications: Excel tables, program testing, and approximate computing. This title is also available as Open Access on Cambridge Core.