Proceedings of the FISITA 2012 World Automotive Congress are selected from nearly 2,000 papers submitted to the 34th FISITA World Automotive Congress, which is held by Society of Automotive Engineers of China (SAE-China ) and the International Federation of Automotive Engineering Societies (FISITA). This proceedings focus on solutions for sustainable mobility in all areas of passenger car, truck and bus transportation. Volume 2: Advanced Internal Combustion Engines (II) focuses on: *Flow and Combustion Diagnosis *Engine Design and Simulation *Heat Transfer and Waste Heat Reutilization *Emission Standard and International Regulations Above all researchers, professional engineers and graduates in fields of automotive engineering, mechanical engineering and electronic engineering will benefit from this book. SAE-China is a national academic organization composed of enterprises and professionals who focus on research, design and education in the fields of automotive and related industries. FISITA is the umbrella organization for the national automotive societies in 37 countries around the world. It was founded in Paris in 1948 with the purpose of bringing engineers from around the world together in a spirit of cooperation to share ideas and advance the technological development of the automobile.

Achieving food security and economic developmental objectives in the face of climate change and rapid population growth requires systems modelling approaches, for example in the design of sustainable agriculture farming systems. Such approaches increase our understanding of system responses to different soil and climatic conditions, and provide insights into the effects of various variable climate change scenarios, providing valuable information for decision-makers. Further, in the agricultural sector, systems modelling can help optimise crop management and adaptation measures to boost productivity under variable climatic conditions. Presenting key outcomes from crop models used in agricultural systems this book is a valuable resource for professionals interested in using modelling approaches to manage the growth and improve the quality of various crops.

This book provides an introduction to fuzzy logic and surveys emerging research trends and the application of state-of-the-art fuzzy hybrid computing techniques in the field of construction engineering and management. Authors cover the theory and implementation of fuzzy hybrid computing methodologies for arithmetic, optimization, machine learning, multi-criteria decision-making, simulation, cognitive maps and data modelling. The practical application of these techniques to solve real-world problems across a wide range of construction engineering and management issues is also demonstrated and discussed. The completion of effectively planned, executed and controlled construction projects is dependent on numerous interacting factors and human activities, both of which introduce vagueness and subjective uncertainty into already complex processes. While expert knowledge is an essential component of effective decision-making, analysis and consideration of expert knowledge expressed in linguistic terms remains a challenging aspect of construction engineering and management. Fuzzy logic, which has applications in many disciplines, has the potential to address certain challenges inherent in construction engineering and management, in part because of its strengths in modelling human reasoning, dealing with subjective uncertainty and computing with linguistic terms. However, fuzzy logic alone has a number of limitations that can only be overcome by its integration with other, complementary methodologies, together leading to advanced and powerful fuzzy hybrid computing techniques. This book is of particular interest to students, researchers and practitioners who want to learn about the latest developments in fuzzy hybrid computing in construction engineering and management.

This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the surrounding world. It assumes that each phenomenon is driven by an underlying generative process that defines a joint distribution over random variables and their stochastic interactions, i.e., how events occur and in what order. The adjective "deep" comes from the fact that the distribution is parameterized using deep neural networks. There are two distinct traits of deep generative modeling. First, the application of deep neural networks allows rich and flexible parameterization of distributions. Second, the principled manner of modeling stochastic dependencies using probability theory ensures rigorous formulation and prevents potential flaws in reasoning. Moreover, probability theory provides a unified framework where the likelihood function plays a crucial role in quantifying uncertainty and defining objective functions. Deep Generative Modeling is designed to appeal to curious students, engineers, and researchers with a modest mathematical background in undergraduate calculus, linear algebra, probability theory, and the basics in machine learning, deep learning, and programming in Python and PyTorch (or other deep learning libraries). It will appeal to students and researchers from a variety of backgrounds, including computer science, engineering, data science, physics, and bioinformatics, who wish to become familiar with deep generative modeling. To engage the reader, the book introduces fundamental concepts with specific examples and code snippets. The full code accompanying the book is available on github. The ultimate aim of the book is to outline the most important techniques in deep generative modeling and, eventually, enable readers to formulate new models and implement them.

Since its inception, the Tutorial Guides in Electronic Engineering series has met with great success among both instructors and students. Designed for first- and second-year undergraduate courses, each text provides a concise list of objectives at the beginning of every chapter, key definitions and formulas highlighted in margin notes, and references to other texts in the series. With emphasis on the fundamental ideas and applications of modelling and design, Control Engineering imparts a thorough understanding of the principles of feedback control. Simple but detailed design examples used throughout the book illustrate how various classical feedback control techniques can be employed for single-input, single-output systems. Noting the interdisciplinary nature of control engineering, the author makes the text equally relevant to students whose interests lie outside of electronics by concentrating on general systems characteristics rather than on specific implementations. The author assumes students are familiar with complex numbers, phasors, and elementary calculus, and while a knowledge of simple linear differential equations would be useful, this treatment has few other mathematical requirements. With its clear explanations, copious illustrations, well-chosen examples, and end-of-chapter exercises, Control Engineering forms an outstanding first-course textbook.

This book discusses systems of damage detection and structural health monitoring in mechanical, civil, and aerospace structures. It utilizes principles of fuzzy logic, probability theory, and signal processing to develop systems and approaches that are robust in the presence of both noise in the data and variations in properties of materials which are intrinsic to the process of mass production. This volume will be useful to graduate students, researchers, and engineers working in this area, especially those looking to understand and address model uncertainty in their algorithms.

This book presents the refereed proceedings of the 13th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held at the University of Rennes, France, and organized by Inria, in July 2018. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all theoretical aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems, arising, in particular, in finance, statistics and computer graphics.

This two-volume set constitutes the refereed post-conference proceedings of the 12th International Conference on Simulation Tools and Techniques, SIMUTools 2020, held in Guiyang, China, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 125 revised full papers were carefully selected from 354 submissions. The papers focus on simulation methods, simulation techniques, simulation software, simulation performance, modeling formalisms, simulation verification and widely used frameworks.

This research monograph brings AI to the field of Customer Relationship Management (CRM) to make a customer experience with a product or service smart and enjoyable. AI is here to help customers to get a refund for a canceled flight, unfreeze a banking account or get a health test result. Today, CRM has evolved from storing and analyzing customers' data to predicting and understanding their behavior by putting a CRM system in a customers' shoes. Hence advanced reasoning with learning from small data, about customers' attitudes, introspection, reading between the lines of customer communication and explainability need to come into play. Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers' frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently. Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.

This comprehensive volume covers both elementary and advanced analog and digital circuit simulation using PSpice. The text includes many worked examples, circuit diagrams, tables, and code listings. It also compares practical results with those obtained from simulation.

This book provides an insight in advanced methods and concepts for structural analysis and design against seismic loading. The book consists of 25 chapters dealing with a wide range of timely issues in contemporary Earthquake Engineering. In brief, the topics covered are: collapse assessment, record selection, effect of soil conditions, problems in seismic design, protection of monuments, earth dam structures and liquid containers, numerical methods, lifetime assessment, post-earthquake measures. A common ground of understanding is provided between the communities of Earth Sciences and Computational Mechanics towards mitigating seismic risk. The topic is of great social and scientific interest, due to the large number of scientists and practicing engineers currently working in the field and due to the great social and economic consequences of earthquakes.

Models and simulations of all kinds are tools for dealing with reality. Humans have always used mental models to better understand the world around them: to make plans, to consider different possibilities, to share ideas with others, to test changes, and to determine whether or not the development of an idea is feasible. The book Modeling and Simulation uses exactly the same approach except that the traditional mental model is translated into a computer model, and the simulations of alternative outcomes under varying conditions are programmed on the computer. The advantage of this method is that the computer can track the multitude of implications and consequences in complex relationships much more quickly and reliably than the human mind. This unique interdisciplinary text not only provides a self contained and complete guide to the methods and mathematical background of modeling and simulation software (SIMPAS) and a collection of 50 systems models on an accompanying diskette. Students from fields as diverse as ecology and economics will find this clear interactive package an instructive and engaging guide.

This edited volume brings together the state of the art in polymer nanocomposite theory and modeling, creating a roadmap for scientists and engineers seeking to design new advanced materials. The book opens with a review of molecular and mesoscale models predicting equilibrium and non-equilibrium nanoscale structure of hybrid materials as a function of composition and, especially, filler types. Subsequent chapters cover the methods and analyses used for describing the dynamics of nanocomposites and their mechanical and physical properties. Dedicated chapters present best practices for predicting materials properties of practical interest, including thermal and electrical conductivity, optical properties, barrier properties, and flammability. Each chapter is written by leading academic and industrial scientists working in each respective sub-field. The overview of modeling methodology combined with detailed examples of property predictions for specific systems will make this book useful for academic and industrial practitioners alike.

This book gathers the outcomes of the second ECCOMAS CM3 Conference series on transport, which addressed the main challenges and opportunities that computation and big data represent for transport and mobility in the automotive, logistics, aeronautics and marine-maritime fields. Through a series of plenary lectures and mini-forums with lectures followed by question-and-answer sessions, the conference explored potential solutions and innovations to improve transport and mobility in surface and air applications. The book seeks to answer the question of how computational research in transport can provide innovative solutions to Green Transportation challenges identified in the ambitious Horizon 2020 program. In particular, the respective papers present the state of the art in transport modeling, simulation and optimization in the fields of maritime, aeronautics, automotive and logistics research. In addition, the content includes two white papers on transport challenges and prospects. Given its scope, the book will be of interest to students, researchers, engineers and practitioners whose work involves the implementation of Intelligent Transport Systems (ITS) software for the optimal use of roads, including safety and security, traffic and travel data, surface and air traffic management, and freight logistics.

This book discusses all the major nature-inspired algorithms with a focus on their application in the context of solving navigation and routing problems. It also reviews the approximation methods and recent nature-inspired approaches for practical navigation, and compares these methods with traditional algorithms to validate the approach for the case studies discussed. Further, it examines the design of alternative solutions using nature-inspired techniques, and explores the challenges of navigation and routing problems and nature-inspired metaheuristic approaches.

Discrete Event Simulation is a process-oriented text/reference that utilizes an eleven-step model to represent the simulation process from problem formulation to implementation and documentation. The book presents the necessary level of detail required to fully develop a model that produces meaningful results and considers the tools necessary to interpret those results. Sufficient background information is provided so that the underlying concepts of simulation are understood. Major topics covered in Discrete Event Simulation include probability and distributional theory, statistical estimation and inference, the generation of random variates, verification and validation techniques, time management methods, experimental design, and programming language considerations. The book also examines distributed simulation and issues related to distributing the physical process over a network of tightly coupled processors. Topics covered in this area include deadlock, synchronization, rollback, event management, and communication processes. Fully worked examples and numerous practical exercises have been drawn from the engineering disciplines and computer science, although they have been structured so that they will be useful as well to other disciplines such as economics, business administration, and management science. The presentation of techniques and methods in Discrete Event Simulation make it an ideal text/reference for all practitioners of discrete event simulation.

This book presents the state of the art in High Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general, as well as the future of High Performance Computing systems and heterogeneous architectures. The contributions cover a broad range of topics, from improved system management to Computational Fluid Dynamics, High Performance Data Analytics, and novel mathematical approaches for large-scale systems. In addition, they explore innovative fields like coupled multi-physics and multi-scale simulations. All contributions are based on selected papers presented at the 26th and 28th Workshops on Sustained Simulation Performance, held at the High Performance Computing Center, University of Stuttgart, Germany, in October 2017 and 2018, and the 27th and 29th Workshops on Sustained Simulation Performance, held at the Cyberscience Center, Tohoku University, Japan, in March 2018 and 2019.

This self-contained, interdisciplinary book encompasses mathematics, physics, computer programming, analytical solutions and numerical modelling, industrial computational fluid dynamics (CFD), academic benchmark problems and engineering applications in conjunction with the research field of anisotropic turbulence. It focuses on theoretical approaches, computational examples and numerical simulations to demonstrate the strength of a new hypothesis and anisotropic turbulence modelling approach for academic benchmark problems and industrially relevant engineering applications. This book contains MATLAB codes, and C programming language based User-Defined Function (UDF) codes which can be compiled in the ANSYS-FLUENT environment. The computer codes help to understand and use efficiently a new concept which can also be implemented in any other software packages. The simulation results are compared to classical analytical solutions and experimental data taken from the literature. A particular attention is paid to how to obtain accurate results within a reasonable computational time for wide range of benchmark problems. The provided examples and programming techniques help graduate and postgraduate students, engineers and researchers to further develop their technical skills and knowledge.

The second volume of this research monograph describes a number of applications of Artificial Intelligence in the field of Customer Relationship Management with the focus of solving customer problems. We design a system that tries to understand the customer complaint, his mood, and what can be done to resolve an issue with the product or service. To solve a customer problem efficiently, we maintain a dialogue with the customer so that the problem can be clarified and multiple ways to fix it can be sought. We introduce dialogue management based on discourse analysis: a systematic linguistic way to handle the thought process of the author of the content to be delivered. We analyze user sentiments and personal traits to tailor dialogue management to individual customers. We also design a number of dialogue scenarios for CRM with replies following certain patterns and propose virtual and social dialogues for various modalities of communication with a customer. After we learn to detect fake content, deception and hypocrisy, we examine the domain of customer complaints. We simulate mental states, attitudes and emotions of a complainant and try to predict his behavior. Having suggested graph-based formal representations of complaint scenarios, we machine-learn them to identify the best action the customer support organization can chose to retain the complainant as a customer.

This book presents selected papers from The 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2019). Focusing on novel architecture theories, tools, methods, and procedures for digital design and construction in architecture, it promotes dialogs between architecture, engineer, computer science, robotics, and other relevant disciplines to establish a new way of production in the building industry in the digital age. The contents make valuable contributions to academic researchers and engineers in the industry. At the same time, it offers readers new ideas for the application of digital technology.

This comprehensive book examines a range of examples, prepared by a diverse group of academic and industry practitioners, which demonstrate how cloud-based simulation is being extensively used across many disciplines, including cyber-physical systems engineering. This book is a compendium of the state of the art in cloud-based simulation that instructors can use to inform the next generation. It highlights the underlying infrastructure, modeling paradigms, and simulation methodologies that can be brought to bear to develop the next generation of systems for a highly connected society. Such systems, aptly termed cyber-physical systems (CPS), are now widely used in e.g. transportation systems, smart grids, connected vehicles, industrial production systems, healthcare, education, and defense. Modeling and simulation (M&S), along with big data technologies, are at the forefront of complex systems engineering research. The disciplines of cloud-based simulation and CPS engineering are evolving at a rapid pace, but are not optimally supporting each other's advancement. This book brings together these two communities, which already serve multi-disciplinary applications. It provides an overview of the simulation technologies landscape, and of infrastructure pertaining to the use of cloud-based environments for CPS engineering. It covers the engineering, design, and application of cloud simulation technologies and infrastructures applicable for CPS engineering. The contributions share valuable lessons learned from developing real-time embedded and robotic systems deployed through cloud-based infrastructures for application in CPS engineering and IoT-enabled society. The coverage incorporates cloud-based M&S as a medium for facilitating CPS engineering and governance, and elaborates on available cloud-based M&S technologies and their impacts on specific aspects of CPS engineering.

Diving the Thistlegorm is a unique in-depth look at one of the world's best-loved shipwrecks, the World War II British Merchant Navy steamship, featuring award-winning underwater photography. In this highly visual guide, cutting edge photographic methods enable views of the famous wreck and its fascinating cargo which were previously impossible. Sitting upright in 30m of clear, inviting Red Sea waters, the ship is packed with the materials of war. Largely complete lorries, trucks, motorbikes, aircraft spares and airfield equipment are crammed into the forward holds and the remains of other vehicles lie amongst boxes of ammunition in the exploded aft holds. Often referred to as an underwater museum, the wreck fascinates visitors for dive after dive. The book is the culmination of decades of experience, archaeological and photographic expertise, many hours underwater, months of computer processing time, and days spent researching and verifying the history of the ship and its cargo. For the first time, Diving the Thistlegorm brings the rich and complex contents of the wreck together, identifying individual items and illustrating where they can be found. As the expert team behind the underwater photography, reconstructions and explanations take you through the wreck in incredible detail, you will discover not only what has been learned but also what mysteries are still to be solved. Limited run of hardbacks.

This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.

This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.

This book describes the development of a constitutive modeling platform for soil testing, which is one of the key components in geomechanics and geotechnics. It discusses the fundamentals of the constitutive modeling of soils and illustrates the use of these models to simulate various laboratory tests. To help readers understand the fundamentals and modeling of soil behaviors, it first introduces the general stress-strain relationship of soils and the principles and modeling approaches of various laboratory tests, before examining the ideas and formulations of constitutive models of soils. Moving on to the application of constitutive models, it presents a modeling platform with a practical, simple interface, which includes various kinds of tests and constitutive models ranging from clay to sand, that is used for simulating most kinds of laboratory tests. The book is intended for undergraduate and graduate-level teaching in soil mechanics and geotechnical engineering and other related engineering specialties. Thanks to the inclusion of real-world applications, it is also of use to industry practitioners, opening the door to advanced courses on modeling within the industrial engineering and operations research fields.