This book offers a selection of the best articles presented at the CUPUM (Computers in Urban Planning and Urban Management) Conference, held in the second week of July 2017 at the University of South Australia in Adelaide. It provides a state-of-the-art overview of the availability and application of planning support systems (PSS) in the context of smart cities, big data, and urban futures. Rapid advances in computing, information, communication and web-based technologies are reaching into all facets of urban life, creating new and exciting urban futures. With the universal adoption of networked computing technologies, data generation is now so massive and all pervasive in society that it offers unprecedented technological solutions for planning and managing urban futures. These technologies are essential to effective urban planning and urban management in an increasingly challenging world, with socially disruptive changes, more complex and sophisticated urban lives and the need for resilience to deal with the possibility of adverse future environmental events and climate change. The book discusses examples of these technologies which encompass, inter alia: 'smart urban futures', where cities with myriad sensors are networked with communication technologies that enable the city planners to monitor well-being and be responsive to citizens' needs to allow dynamic management in real-time; PSS that encompass new hardware, develop new indicators, applications and innovative ways of facilitating public and community involvement in the management and planning of urban areas; and urban modelling that draws on theory and the richness of data from the growing range of urban sensing and communication technologies to build a better understanding of urban dynamics, trends and 'what-if' scenario investigations, and to provide better tools for planning and policymaking.

This contributed volume contains the conference proceedings of the Simulation of Urban Mobility (SUMO) conference 2014, Berlin. The included research papers cover a wide range of topics in traffic planning and simulation, including open data, vehicular communication, e-mobility, urban mobility, multimodal traffic as well as usage approaches. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.

This status report features the most recent developments in the field, spanning a wide range of topical areas in the computer simulation of condensed matter/materials physics. Both established and new topics are included, ranging from the statistical mechanics of classical magnetic spin models to electronic structure calculations, quantum simulations, and simulations of soft condensed matter.

1.1. INTRODUCTION Plastic covering, either framed or floating, is now used worldwide to protect crops from unfavorable growing conditions, such as severe weather and insects and birds. Protected cultivation in the broad sense, including mulching, has been widely spread by the innovation of plastic films. Paper, straw, and glass were the main materials used before the era of plastics. Utilization of plastics in agriculture started in the developed countries and is now spreading to the developing countries. Early utilization of plastic was in cold regions, and plastic was mainly used for protection from the cold. Now plastic is used also for protection from wind, insects and diseases. The use of covering techniques started with a simple system such as mulching, then row covers and small tunnels were developed, and finally plastic houses. Floating mulch was an exception to this sequence: it was introduced rather recently, although it is a simple structure. New development of functional and inexpensive films triggered widespread use of floating mulch. Table 1.1. The use a/plastic mulch in the world (after Jouet, 2001).

Changes and additions are sprinkled throughout. Among the significant new features are: * Markov-chain simulation (Sections 1. 3, 2. 6, 3. 6, 4. 3, 5. 4. 5, and 5. 5); * gradient estimation (Sections 1. 6, 2. 5, and 4. 9); * better handling of asynchronous observations (Sections 3. 3 and 3. 6); * radically updated treatment of indirect estimation (Section 3. 3); * new section on standardized time series (Section 3. 8); * better way to generate random integers (Section 6. 7. 1) and fractions (Appendix L, program UNIFL); * thirty-seven new problems plus improvements of old problems. Helpful comments by Peter Glynn, Barry Nelson, Lee Schruben, and Pierre Trudeau stimulated several changes. Our new random integer routine extends ideas of Aarni Perko. Our new random fraction routine implements Pierre L'Ecuyer's recommended composite generator and provides seeds to produce disjoint streams. We thank Springer-Verlag and its late editor, Walter Kaufmann-Bilhler, for inviting us to update the book for its second edition. Working with them has been a pleasure. Denise St-Michel again contributed invaluable text-editing assistance. Preface to the First Edition Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences.

This book offers a new, theoretical approach to information dynamics, i.e., information processing in complex dynamical systems. The presentation establishes a consistent theoretical framework for the problem of discovering knowledge behind empirical, dynamical data and addresses applications in information processing and coding in dynamical systems. This will be an essential reference for those in neural computing, information theory, nonlinear dynamics and complex systems modeling.

Sir Francis Crick would undoubtedly be at the front of the line ordering this fascinating book. Being one of the discoverers of DNA, he would be amazed at how his work has been applied to mankind's most important invention, the computer. In this excellent text, the reader is given a comprehensive introduction to the field of DNA computing. The book emphasizes computational methods to tackle central problems of DNA computing, such as controlling living cells, building patterns, and generating nanomachines. It also includes laboratory-scale human-operated models of computation, as well as a description of the first experiment of DNA computation conducted by Adleman in 1994.

This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.

Calculated Bets describes a gambling system that works. Steven Skiena, a jai-alai enthusiast and computer scientist, documents how he used computer simulations and modeling techniques to predict the outcome of jai-alai matches and increased his initial stake by 544% in one year. Skiena demonstrates how his jai-alai system functions like a stock trading system, and includes examples of how gambling and mathematics interact in program trading systems, how mathematical models are used in political polling, and what the future holds for Internet gambling. With humor and enthusiasm, Skiena explains computer predictions used in business, sports, and politics, and the difference between correlation and causation. An unusual presentation of how mathematical models are designed, built, and validated, Calculated Bets also includes a list of modeling projects with online data sources. Steven Skiena, Associate Professor of Computer Science at SUNY Stony Brook, is the author of The Algorithm Design Manual (Springer-Verlag, 1997) and the EDUCOM award-winning Computational Discrete Mathematics. He is the recipient of the ONR Young Investigator's Award and the Chancellor's Award for Excellence in Teaching at Stony Brook. His research interests include discrete mathematics and its applications, particularly the design of graph, string, and geometric algorithms.

Rubinstein is the pioneer of the well-known score function and cross-entropy methods.

Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.

In 1982, Professor Pawlak published his seminal paper on what he called "rough sets" - a work which opened a new direction in the development of theories of incomplete information. Today, a decade and a half later, the theory of rough sets has evolved into a far-reaching methodology for dealing with a wide variety of issues centering on incompleteness and imprecision of information - issues which playa key role in the conception and design of intelligent information systems. "Incomplete Information: Rough Set Analysis" - or RSA for short - presents an up-to-date and highly authoritative account of the current status of the basic theory, its many extensions and wide-ranging applications. Edited by Professor Ewa Orlowska, one of the leading contributors to the theory of rough sets, RSA is a collection of nineteen well-integrated chapters authored by experts in rough set theory and related fields. A common thread that runs through these chapters ties the concept of incompleteness of information to those of indiscernibility and similarity.

This text compiles research from a vibrant social simulation community of researchers who have developed unique and innovative approaches to social simulation.

Agent-based modeling/simulation is an emergent approach to the analysis of social and economic systems. It provides a bottom-up experimental method to be applied to social sciences such as economics, management, sociology, and politics as well as some engineering fields dealing with social activities. This book includes selected papers presented at the Fifth International Workshop on Agent-Based Approaches in Economic and Social Complex Systems held in Tokyo in 2007. It contains two invited papers given as the plenary and invited talks in the workshop and 21 papers presented in the six regular sessions: Organization and Management; Fundamentals of Agent-Based and Evolutionary Approaches; Production, Services and Urban Systems; Agent-Based Approaches to Social Systems; and Market and Economics I and II. The research presented here shows the state of the art in this rapidly growing field.

Collecting the work of the foremost scientists in the field, Discrete-Event Modeling and Simulation: Theory and Applications presents the state of the art in modeling discrete-event systems using the discrete-event system specification (DEVS) approach. It introduces the latest advances, recent extensions of formal techniques, and real-world examples of various applications. The book covers many topics that pertain to several layers of the modeling and simulation architecture. It discusses DEVS model development support and the interaction of DEVS with other methodologies. It describes different forms of simulation supported by DEVS, the use of real-time DEVS simulation, the relationship between DEVS and graph transformation, the influence of DEVS variants on simulation performance, and interoperability and composability with emphasis on DEVS standardization. The text also examines extensions to DEVS, new formalisms, and abstractions of DEVS models as well as the theory and analysis behind real-world system identification and control. To support the generation and search of optimal models of a system, a framework is developed based on the system entity structure and its transformation to DEVS simulation models. In addition, the book explores numerous interesting examples that illustrate the use of DEVS to build successful applications, including optical network-on-chip, construction/building design, process control, workflow systems, and environmental models. A one-stop resource on advances in DEVS theory, applications, and methodology, this volume offers a sampling of the best research in the area, a broad picture of the DEVS landscape, and trend-setting applications enabled by the DEVS approach. It provides the basis for future research discoveries and encourages the development of new applications.

Mastering modelling, and in particular numerical models, is becoming a crucial and central question in modern computational mechanics. Various tools, able to quantify the quality of a model with regard to another one taken as the reference, have been derived. Applied to computational strategies, these tools lead to new computational methods which are called "adaptive." The present book is concerned with outlining the state of the art and the latest advances in both these important areas.

Papers are selected from a Workshop (Cachan 17-19 September 1997) which is the third of a series devoted to Error Estimators and Adaptivity in Computational Mechanics. The Cachan Workshop dealt with latest advances in adaptive computational methods in mechanics and their impacts on solving engineering problems. It was centered too on providing answers to simple questions such as: what is being used or can be used at present to solve engineering problems? What should be the state of art in the year 2000? What are the new questions involving error estimators and their applications?

This contributed volume contains the conference proceedings of the Simulation of Urban Mobility (SUMO) conference 2015, Berlin. The included papers cover a wide range of topics in traffic planning and simulation, including intermodal simulation, intermodal transport, vehicular communication, modeling urban mobility, open data as well as autonomous driving. The target audience primarily comprises researchers and experts in the field of mobility research, but the book may also be beneficial for graduate students.

This unique book brings together a comprehensive set of papers on the background, theory, technical issues and applications of agent-based modelling (ABM) within geographical systems. This collection of papers is an invaluable reference point for the experienced agent-based modeller as well those new to the area. Specific geographical issues such as handling scale and space are dealt with as well as practical advice from leading experts about designing and creating ABMs, handling complexity, visualising and validating model outputs. With contributions from many of the world's leading research institutions, the latest applied research (micro and macro applications) from around the globe exemplify what can be achieved in geographical context.

This book is relevant to researchers, postgraduate and advanced undergraduate students, and professionals in the areas of quantitative geography, spatial analysis, spatial modelling, social simulation modelling and geographical information sciences.

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The problem of robotic and virtual interaction with physical objects has been the subject of research for many years in both the robotic manipulation and haptics communities. Both communities have focused much attention on human touch-based perception and manipulation, modelling contact between real or virtual hands and objects, or mechanism design. However, as a whole, these problems have not yet been addressed from a unified perspective. This edited book is the outcome of a well-attended workshop which brought together leading scholars from various branches of the robotics, virtual-reality, and human studies communities during the 2004 IEEE International Conference on Robotics and Automation. It covers some of the most challenging problems on the forefront of today 's research on physical interaction with real and virtual objects, with special emphasis on modelling contacts between objects, grasp planning algorithms, haptic perception, and advanced design of hands, devices and interfaces.

A Toolbox for Digital Twins: From Model-Based to Data-Driven brings together the mathematical and numerical frameworks needed for developing digital twins (DTs). Starting from the basics-probability, statistics, numerical methods, optimization, and machine learning-and moving on to data assimilation, inverse problems, and Bayesian uncertainty quantification, the book provides a comprehensive toolbox for DTs. Readers will find guidelines and decision trees to help the reader choose the right tools for the job, emphasis on the design process, denoted as the "inference cycle," whose aim is to propose a global methodology for complex problems, a comprehensive reference section with all recent methods, covering both model-based and data-driven approaches, and a vast selection of examples and all accompanying code. A Toolbox for Digital Twins: From Model-Based to Data-Driven is for researchers and engineers, engineering students, and scientists in any domain where data and models need to be coupled to produce digital twins.

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.

Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm optimization, artificial immune systems, artificial life, genetic programming, etc.

It emphasises the initiative ideas of the algorithm, contains discussions in the contexts, and suggests further readings and possible research projects. All the methods form a pedagogical way to make EAs easy and interesting.

This textbook also introduces the applications of EAs as many as possible. At least one real-life application is introduced by the end of almost every chapter. The authors focus on the kernel part of applications, such as how to model real-life problems, how to encode and decode the individuals, how to design effective search operators according to the chromosome structures, etc.

This textbook adopts pedagogical ways of making EAs easy and interesting. Its methods include an introduction at the beginning of each chapter, emphasising the initiative, discussions in the contexts, summaries at the end of every chapter, suggested further reading, exercises, and possible research projects.

Introduction to Evolutionary Algorithms will enable students to:

establish a strong background on evolutionary algorithms;

appreciate the cutting edge of EAs;

perform their own research projects by simulating the application introduced in the book; and

apply their intuitive ideas to academic search.

This book is aimed at senior undergraduate students or first-year graduate students as a textbook or self-study material."

Researchers develop simulation models that emulate real-world situations. While these simulation models are simpler than the real situation, they are still quite complex and time consuming to develop. It is at this point that metamodeling can be used to help build a simulation study based on a complex model. A metamodel is a simpler, analytical model, auxiliary to the simulation model, which is used to better understand the more complex model, to test hypotheses about it, and provide a framework for improving the simulation study. The use of metamodels allows the researcher to work with a set of mathematical functions and analytical techniques to test simulations without the costly running and re-running of complex computer programs. In addition, metamodels have other advantages, and as a result they are being used in a variety of ways: model simplification, optimization, model interpretation, generalization to other models of similar systems, efficient sensitivity analysis, and the use of the metamodel's mathematical functions to answer questions about different variables within a simulation study.

Employing computer simulations for the study of the evolution of altruism has been popular since Axelrod's book "The Evolution of Cooperation". But have the myriads of simulation studies that followed in Axelrod's footsteps really increased our knowledge about the evolution of altruism or cooperation? This book examines in detail the working mechanisms of simulation based evolutionary explanations of altruism. It shows that the "theoretical insights" that can be derived from simulation studies are often quite arbitrary and of little use for the empirical research. In the final chapter of the book, therefore, a set of epistemological requirements for computer simulations is proposed and recommendations for the proper research design of simulation studies are made.

This book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems. Drawing on the authors' extensive experience within the field of reliability engineering, it addresses and discusses a variety of topics, including: * Background and overview of safety and dependability studies; * Explanation and critical analysis of definitions related to core concepts; * Risk identification through qualitative approaches (preliminary hazard analysis, HAZOP, FMECA, etc.); * Modelling of industrial systems through static (fault tree, reliability block diagram), sequential (cause-consequence diagrams, event trees, LOPA, bowtie), and dynamic (Markov graphs, Petri nets) approaches; * Probabilistic calculations through state-of-the-art analytical or Monte Carlo simulation techniques; * Analysis, modelling, and calculations of common cause failure and uncertainties; * Linkages and combinations between the various modelling and calculation approaches; * Reliability data collection and standardization. The book features illustrations, explanations, examples, and exercises to help readers gain a detailed understanding of the topic and implement it into their own work. Further, it analyses the production availability of production systems and the functional safety of safety systems (SIL calculations), showcasing specific applications of the general theory discussed. Given its scope, this book is a valuable resource for engineers, software designers, standard developers, professors, and students.

In the last decade parallel computing has been put forward as the only computational answer to the increasing computational needs arising from very large and complex fluid dynamic problems. Considerable efforts are being made to use parallel computers efficiently to solve several fluid dynamic problems originating in aerospace, climate modelling and environmental applications.

Parallel CFD Conferences are international and aim to increase discussion among researchers worldwide.

Topics covered in this particular book include typical CFD areas such as turbulence, Navier-Stokes and Euler solvers, reactive flows, with a good balance between both university and industrial applications. In addition, other applications making extensive use of CFD such as climate modelling and environmental applications are also included.

Anyone involved in the challenging field of Parallel Computational Fluid Dynamics will find this volume useful in their daily work.