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Intelligent Nanotechnology: Merging Nanoscience and Artificial Intelligence provides an overview of advances in science and technology made possible by the convergence of nanotechnology and artificial intelligence (AI). Sections focus on AI-enhanced design, characterization and manufacturing and the use of AI to improve important material properties, with an emphasis on mechanical, photonic, electronic and magnetic properties. Designing benign nanomaterials through the prediction of their impact on biology and the environment is also discussed. Other sections cover the use of AI in the acquisition and analysis of data in experiments and AI technologies that have been enhanced through nanotechnology platforms. Final sections review advances in applications enabled by the merging of nanotechnology and artificial intelligence, including examples from biomedicine, chemistry and automated research. - Includes recent advances on AI-enhanced design, characterization and the manufacturing of nanomaterials - Reviews AI technologies that have been enabled by nanotechnology - Discusses potentially world-changing applications that could ensue as a result of merging these two fields
The book builds on the analogy between social groups and assemblies of molecules to introduce the concepts of statistical mechanics, machine learning and data science. Applying a data analytics approach to molecular systems, we show how individual (molecular) features and interactions between molecules, or "communication" processes, allow for the prediction of properties and collective behavior of molecular systems - just as polling and social networking shed light on the behavior of social groups. Applications to systems at the cutting-edge of research for biological, environmental, and energy applications are also presented. Key features: Draws on a data analytics approach of molecular systems. Covers hot topics such as artificial intelligence and machine learning of molecular trends. Contains applications to systems at the cutting-edge of research for biological, environmental and energy applications. Discusses molecular simulation and links with other important, emerging techniques and trends in computational sciences and society. Authors have a well-established track record and reputation in the field.
This book introduces various coverage control problems for mobile sensor networks including barrier, sweep and blanket. Unlike many existing algorithms, all of the robotic sensor and actuator motion algorithms developed in the book are fully decentralized or distributed, computationally efficient, easily implementable in engineering practice and based only on information on the closest neighbours of each mobile sensor and actuator and local information about the environment. Moreover, the mobile robotic sensors have no prior information about the environment in which they operation. These various types of coverage problems have never been covered before by a single book in a systematic way. Another topic of this book is the study of mobile robotic sensor and actuator networks. Many modern engineering applications include the use of sensor and actuator networks to provide efficient and effective monitoring and control of industrial and environmental processes. Such mobile sensor and actuator networks are able to achieve improved performance and efficient monitoring together with reduction in power consumption and production cost.
Safe Robot Navigation Among Moving and Steady Obstacles is the first book to focus on reactive navigation algorithms in unknown dynamic environments with moving and steady obstacles. The first three chapters provide introduction and background on sliding mode control theory, sensor models, and vehicle kinematics. Chapter 4 deals with the problem of optimal navigation in the presence of obstacles. Chapter 5 discusses the problem of reactively navigating. In Chapter 6, border patrolling algorithms are applied to a more general problem of reactively navigating. A method for guidance of a Dubins-like mobile robot is presented in Chapter 7. Chapter 8 introduces and studies a simple biologically-inspired strategy for navigation a Dubins-car. Chapter 9 deals with a hard scenario where the environment of operation is cluttered with obstacles that may undergo arbitrary motions, including rotations and deformations. Chapter 10 presents a novel reactive algorithm for collision free navigation of a nonholonomic robot in unknown complex dynamic environments with moving obstacles. Chapter 11 introduces and examines a novel purely reactive algorithm to navigate a planar mobile robot in densely cluttered environments with unpredictably moving and deforming obstacles. Chapter 12 considers a multiple robot scenario. For the Control and Automation Engineer, this book offers accessible and precise development of important mathematical models and results. All the presented results have mathematically rigorous proofs. On the other hand, the Engineer in Industry can benefit by the experiments with real robots such as Pioneer robots, autonomous wheelchairs and autonomous mobile hospital. - First book on collision free reactive robot navigation in unknown dynamic environments - Bridges the gap between mathematical model and practical algorithms - Presents implementable and computationally efficient algorithms of robot navigation - Includes mathematically rigorous proofs of their convergence - A detailed review of existing reactive navigation algorithm for obstacle avoidance - Describes fundamentals of sliding mode control
Chaired by K Wüthrich (Nobel Laureate in Chemistry, 2002) and co-chaired by B Weckhuysen, this by-invitation-only conference has gathered 39 participants — who are leaders in the field of computational modeling and its applications in Chemistry, Material Sciences and Biology. Highlights of the Conference Proceedings are short, prepared statements by all the participants and the records of lively discussions on the current and future perspectives in the field of computational modeling, from chemistry to materials to biology.
"A short, provocative manifesto for the programmable materials revolution from the visionary founder of MIT's Self-Assembly Lab"--
This book discusses the latest advances in research and development, design, operation and analysis of transportation systems and their complementary infrastructures. It reports on both theories and case studies on road and rail, aviation and maritime transportation. The book covers a wealth of topics, from accident analysis, vehicle intelligent control, and human-error and safety issues to next-generation transportation systems, model-based design methods, simulation and training techniques, and many more. A special emphasis is given to smart technologies and automation in transport, as well as to user-centered, ergonomic and sustainable design of transport systems. The book, which is based on the AHFE 2017 International Conference on Human Factors in Transportation, held on July 17–21, Los Angeles, California, USA, mainly addresses transportation system designers, industrial designers, human–computer interaction researchers, civil and control engineers, as well as vehicle system engineers. Moreover, it represents a timely source of information for transportation policy-makers and social scientists dealing with traffic safety, management, and sustainability issues in transport.