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This monograph takes the reader through recent advances in data-driven methods and machine learning for problems in science—specifically in continuum physics. It develops the foundations and details a number of scientific machine learning approaches to enrich current computational models of continuum physics, or to use the data generated by these models to infer more information on these problems. The perspective presented here is drawn from recent research by the author and collaborators. Applications drawn from the physics of materials or from biophysics illustrate each topic. Some elements of the theoretical background in continuum physics that are essential to address these applications are developed first. These chapters focus on nonlinear elasticity and mass transport, with particular attention directed at descriptions of phase separation. This is followed by a brief treatment of the finite element method, since it is the most widely used approach to solve coupled partial differential equations in continuum physics. With these foundations established, the treatment proceeds to a number of recent developments in data-driven methods and scientific machine learning in the context of the continuum physics of materials and biosystems. This part of the monograph begins by addressing numerical homogenization of microstructural response using feed-forward as well as convolutional neural networks. Next is surrogate optimization using multifidelity learning for problems of phase evolution. Graph theory bears many equivalences to partial differential equations in its properties of representation and avenues for analysis as well as reduced-order descriptions--all ideas that offer fruitful opportunities for exploration. Neural networks, by their capacity for representation of high-dimensional functions, are powerful for scale bridging in physics--an idea on which we present a particular perspective in the context of alloys. One of the most compelling ideas in scientific machine learning is the identification of governing equations from dynamical data--another topic that we explore from the viewpoint of partial differential equations encoding mechanisms. This is followed by an examination of approaches to replace traditional, discretization-based solvers of partial differential equations with deterministic and probabilistic neural networks that generalize across boundary value problems. The monograph closes with a brief outlook on current emerging ideas in scientific machine learning.

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book.

This open access book constitutes the proceedings of the 31st European Symposium on Programming, ESOP 2022, which was held during April 5-7, 2022, in Munich, Germany, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2022. The 21 regular papers presented in this volume were carefully reviewed and selected from 64 submissions. They deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems.

This comprehensive book offers a clear account of the theory and applications of advanced metal forming. It provides a detailed discussion of specific forming processes, such as deep drawing, rolling, bending extrusion and stamping. The author highlights recent developments of metal forming technologies and explains sound, new and powerful expert system techniques for solving advanced engineering problems in metal forming. In addition, the basics of expert systems, their importance and applications to metal forming processes, computer-aided analysis of metalworking processes, formability analysis, mathematical modeling and case studies of individual processes are presented.

The theme of CUTE is focused on the various aspects of ubiquitous computing for advances in ubiquitous computing and provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of ubiquitous computing. Therefore this book will be include the various theories and practical applications in ubiquitous computing

th This volume is an edition of the papers selected from the 13 International Conference on Advanced Robotics, ICAR 2007, held in Jeju, Korea, August 22-25, 2007, with the theme: “Viable Robotics Service to Human. ” It is intended to deliver readers the most recent technical progress in robotics, in particular, toward the advancement of robotic service to human. To ensure its quality, this volume took only 28 papers out of the 214 papers accepted for publication for ICAR 2007. The selection was based mainly on the technical merit, but also took into consideration whether the subject represents a theme of current interest. For the final inclusion, authors of the selected papers were requested for another round of revision and expansion. In this volume, we organize the 28 contributions into three chapters. Chapter 1 covers Novel Mechanisms, Chapter 2 deals with perception guided navigation and manipulation, and Chapter 3 addresses human-robot interaction and intelligence. Chapters 1, 2 and 3 consist of 7, 13 and 8 contributions, respectively. For the sake of clarity, Chapter 2 is divided further into two parts with Part 1 for Perception Guided Navigation and Part 2 for Perception Guided Manipulation. Chapter 3 is also divided into two parts with Part 1 for Human- Robot Interaction and Part 2 for Intelligence. For the convenience of readers, a ch- ter summary is introduced as an overview in the beginning of each chapter. The chapter summaries were prepared by Dr. Munsang Kim for Chapter 1, Prof.

1 The International Workshop on Recon?gurable Computing (ARC) started in 2005 in Algarve, Portugal. The major motivation was to create an event where on-going research e?orts as well as more elaborated, interesting and hi- quality work on applied recon?gurable computing could be presented and d- cussed. Over the last couple of years recon?gurable computing has become a we- known and established research area producing interesting as well as important results in both general and embedded computing systems. It is also getting more and more interest from industry which is attracted by the (design and development)?exibility as well as the performance improvements that can be expected from this technology. As recon?gurablecomputing has blurred the gap between software and hardware, some even speak of a radical new programming paradigm opening a new realm of unseen applications and opportunities. The logo of the ARC workshop is the Nonius, a measurement instrument used in the Portuguese period of discoveries that was invented by Pedro Nunes, a Portuguesemathematician. As the logo suggests,the main motto of ARC is to help to navigate the world of recon?gurable computing. Driven by this motto, we hope ARC contributes to solid advances on recon?gurable computing.

This book constitutes the refereed proceedings of the 11th International Symposium on Static Analysis, SAS 2004, held in Verona, Italy in August 2004. The 23 revised full papers presented with an invited paper and abstracts of 3 invited talks were carefully reviewed and selected from 63 submissions. The papers are organized in topical sections on program and systems verification, security and safety, pointer analysis, abstract interpretation and algorithms, shape analysis, abstract domain and data structures, shape analysis and logic, and termination analysis.