This book focuses on the robustness analysis of high accuracy surface modeling method (HASM) to yield good performance of it. Understanding the sensitivity and uncertainty is important in model applications. The book aims to advance an integral framework for assessing model error that can demonstrate robustness across sets of possible controls, variable definitions, standard error, algorithm structure, and functional forms. It is an essential reference to the most promising numerical models. In areas where there is less certainty about models, but also high expectations of transparency, robustness analysis should aspire to be as broad as possible. This book also contains a chapter at the end featuring applications in climate simulation illustrating different implementations of HASM in surface modeling. The book is helpful for people involved in geographical information science, ecological informatics, geography, earth observation, and planetary surface modeling.

This book covers cutting-edge findings related to uncertainty quantification and optimization under uncertainties (i.e. robust and reliable optimization), with a special emphasis on aeronautics and turbomachinery, although not limited to these fields. It describes new methods for uncertainty quantification, such as non-intrusive polynomial chaos, collocation methods, perturbation methods, as well as adjoint based and multi-level Monte Carlo methods. It includes methods for characterization of most influential uncertainties, as well as formulations for robust and reliable design optimization. A distinctive element of the book is the unique collection of test cases with prescribed uncertainties, which are representative of the current engineering practice of the industrial consortium partners involved in UMRIDA, a level 1 collaborative project within the European Commission's Seventh Framework Programme (FP7). All developed methods are benchmarked against these industrial challenges. Moreover, the book includes a section dedicated to Best Practice Guidelines for uncertainty quantification and robust design optimization, summarizing the findings obtained by the consortium members within the UMRIDA project. All in all, the book offers a authoritative guide to cutting-edge methodologies for uncertainty management in engineering design, covers a wide range of applications and discusses new ideas for future research and interdisciplinary collaborations.

With the increasing popularization of the Internet, together with the rapid development of 3D scanning technologies and modeling tools, 3D model databases have become more and more common in fields such as biology, chemistry, archaeology and geography. People can distribute their own 3D works over the Internet, search and download 3D model data, and also carry out electronic trade over the Internet. However, some serious issues are related to this as follows: (1) How to efficiently transmit and store huge 3D model data with limited bandwidth and storage capacity; (2) How to prevent 3D works from being pirated and tampered with; (3) How to search for the desired 3D models in huge multimedia databases. This book is devoted to partially solving the above issues. Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space and transmission bandwidth. On the downside, compressed data must be decompressed to be used, and this extra processing may be detrimental to some applications. 3D polygonal mesh (with geometry, color, normal vector and texture coordinate information), as a common surface representation, is now heavily used in various multimedia applications such as computer games, animations and simulation applications. To maintain a convincing level of realism, many applications require highly detailed mesh models. However, such complex models demand broad network bandwidth and much storage capacity to transmit and store. To address these problems, 3D mesh compression is essential for reducing the size of 3D model representation.

The fields of computer vision and image processing are constantly evolving as new research and applications in these areas emerge. Staying abreast of the most up-to-date developments in this field is necessary in order to promote further research and apply these developments in real-world settings. Computer Vision: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material on development of computers for gaining understanding about videos and digital images. Highlighting a range of topics, such as computational models, machine learning, and image processing, this multi-volume book is ideally designed for academicians, technology professionals, students, and researchers interested in uncovering the latest innovations in the field.

Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds. The introduced methods improve the state of the art in various aspects, i.e. in the ability to handle inaccurate point tracks and 3D data with contaminations. NRSfM with shape priors obtained on-the-fly from several unoccluded frames of the sequence and the new gravitational class of methods for point set alignment represent the primary contributions of this book. About the Author: Vladislav Golyanik is currently a postdoctoral researcher at the Max Planck Institute for Informatics in Saarbrücken, Germany. The current focus of his research lies on 3D reconstruction and analysis of general deformable scenes, 3D reconstruction of human body and matching problems on point sets and graphs. He is interested in machine learning (both supervised and unsupervised), physics-based methods as well as new hardware and sensors for computer vision and graphics (e.g., quantum computers and event cameras).

This book introduces the concept of sensing, smart and sustainable systems (S3 systems) to support the design and redesign of products, services, business and manufacturing processes, manufacturing systems, and enterprises. The concept of S3 systems theory is introduced and explained in detail to support designers and engineers in their development task. This approach is embraced in the implementation of emergent Information and communication technologies and artificial intelligence techniques. The text helps the reader to understand the relationship between intelligent manufacturing, S3 systems and Industry 4.0. It presents a review of current approaches to design and development of technology-based products. Finally, it enlarges on the sensing, smart and sustainable systems theory to give examples of S3 systems as case studies.

Although GIS provides powerful functionality for spatial analysis, data overlay and storage, these spatially oriented systems lack the ability to represent temporal dynamics, which is a major impediment to its use in surface modeling. However, rapid development of computing technology in recent years has made real-time spatial analysis and real-time data visualization become realizable. Based on newly developed methods, Surface Modeling: High Accuracy and High Speed Methods explores solutions to big-error and slow-efficiency problems, two critical challenges that have long plagued those working in with geographical information system (GIS) and computer-aided design (CAD). By developing high accuracy and high speed methods for surface modeling, the book builds a bridge between the mathematical-oriented theory of surface modeling and the user-oriented application where the user is actually able to retrieve information on the method itself. The author examines a novel method of high accuracy surface modeling (HASM) in terms of the fundamental theorem of surfaces. He then analyzes the coefficient matrix and develops an adaptive method of HASM (HASM-AM), a multi-grade method of HASM (HASM-MG), and an adjustment method of HASM (HASM-AD). He uses numerical tests and real world studies to demonstrate that HASM-AM, HASM-MG, and HASM-AD have highly accelerated computational speed, especially for simulations with huge computational work. Building on this, the book discusses a HASM-based method for dynamic simulation (HASM-FDS), and then applies HASM methods to simulate terrains, climate change, ecosystem change, land cover, and soil properties. It demonstrates HASM's potential for simulating population distribution, human carrying capacity, ecosystem services, ecological diversity, change detection, and wind velocity. The book concludes with a discussion of the problems that exist in surface modeling on a global level and evaluates possible solutions to these problems.

The International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE), always sponsored by the International So- ety of Applied Intelligence (ISAI), emphasizes applications of applied intelligent systems to solve real-life problems in all areas. It is held every year and has become one of the biggest and most important academic activities concerning the theory and applications of intelligent systems in the world. The IEA/AIE 2009 conference was hosted by the National University of Tainan and National University of Kaohsiung in Taiwan. This was the first time that the IEA/AIE conference was held in Taiwan. We received 286 papers from all parts of the world. Only 84 papers were selected for publication in this volume of LNAI proceedings. Each paper was reviewed by at least two anonymous referees to assure the high quality. We would like to express our sincere thanks to the Program Committee members and all the reviewers for their hard work, which helped us to select the highest quality papers for the conference. These papers highlight opportunities and challenges for the next generation of applied int- ligence and reveal technological innovations in real applications.

This two-volume set CCIS 751 and CCIS 752 constitutes the proceedings of the 17th Asia Simulation Conference, AsiaSim 2017, held in Malacca, Malaysia, in August/September 2017. The 124 revised full papers presented in this two-volume set were carefully reviewed and selected from 267 submissions. The papers contained in these proceedings address challenging issues in modeling and simulation in various fields such as embedded systems; symbiotic simulation; agent-based simulation; parallel and distributed simulation; high performance computing; biomedical engineering; big data; energy, society and economics; medical processes; simulation language and software; visualization; virtual reality; modeling and Simulation for IoT; machine learning; as well as the fundamentals and applications of computing.