The book answers long-standing questions on scientific modeling and inference across multiple perspectives and disciplines, including logic, mathematics, physics and medicine. The different chapters cover a variety of issues, such as the role models play in scientific practice; the way science shapes our concept of models; ways of modeling the pursuit of scientific knowledge; the relationship between our concept of models and our concept of science. The book also discusses models and scientific explanations; models in the semantic view of theories; the applicability of mathematical models to the real world and their effectiveness; the links between models and inferences; and models as a means for acquiring new knowledge. It analyzes different examples of models in physics, biology, mathematics and engineering. Written for researchers and graduate students, it provides a cross-disciplinary reference guide to the notion and the use of models and inferences in science.

This book introduces state-of-the-art research on simulation and serious games for education. Based partially on work presented at the 3rd Asia-Europe Symposium on Simulation and Serious Games (3rd AESSSG) held in Zhuhai, China as part of the 2016 ACM SIGGRAPH International Conference on Virtual-Reality Consortium and Applications in Industry (VRACI 2016), it includes a selection of the best papers from both. The book is divided into three major domains of education applications that use simulation and serious games: science, technology, engineering and mathematics (STEM) education; special needs education; and humanity and social science education. A valuable resource for researchers and developers in simulation and serious games for education benefit from this book, it also offers educators and professionals involved in training insights into the possible applications of simulation and serious games in various areas.

Achieving value-based healthcare, increasing quality, reducing cost, and spreading access, has proven to be extremely challenging, in part due to research that is siloed and largely focused on singular risk factors, ineffective care coordination resulting from service fragmentation, and costly unintended consequences of reform that have emerged due to the complexity of healthcare systems. Understanding the behaviour of the overall system is becoming a major concern among healthcare managers and decision-makers intent on increasing value for their systems. This book fills a gap in the literature that is becoming more evident as reform efforts proliferate: a holistic Modeling and Simulation (M&S) approach to value-based healthcare within a framework that enables designing, testing and implementing concepts to integrate resource allocations, health phenomenon dynamics, individual behaviour, and population dynamics. It presents a pathways-based efficient coordination of care model involving all stakeholders including patients, providers, care deliverers, managers, and payers. It shows how M&S can help design a better service infrastructure and describes the information technologies that are necessary to implement it successfully. It also presents global and national healthcare perspectives from Europe, USA, Asia and Africa, as well as research directions needed to realize the value-based M&S healthcare vision.

With the increasing complexity and dynamism in today's machine design and development, more precise, robust and practical approaches and systems are needed to support machine design. Existing design methods treat the targeted machine as stationery. Analysis and simulation are mostly performed at the component level. Although there are some computer-aided engineering tools capable of motion analysis and vibration simulation etc., the machine itself is in the dry-run state. For effective machine design, understanding its thermal behaviours is crucial in achieving the desired performance in real situation. Dynamic Thermal Analysis of Machines in Running State presents a set of innovative solutions to dynamic thermal analysis of machines when they are put under actual working conditions. The objective is to better understand the thermal behaviours of a machine in real situation while at the design stage. The book has two major sections, with the first section presenting a broad-based review of the key areas of research in dynamic thermal analysis and simulation, and the second section presents an in-depth treatment of relevant methodology and algorithms, leading to better understanding of a machine in real situation. The book is a collection of novel ideas, taking into account the need for presenting intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students. Given the essential role of modern machines in factory automation and quality assurance, a book dedicated to the topic of dynamic thermal analysis, and its practical applications to machine design would be beneficial to readers of all design and manufacturing sectors, from machine design to automotive engineering, in better understanding the present challenges and solutions, as well as future research directions in this important area.

Soft computing, as an engineering science, and statistics, as a classical branch of mathematics, emphasize different aspects of data analysis.
Soft computing focuses on obtaining working solutions quickly, accepting approximations and unconventional approaches. Its strength lies in its flexibility to create models that suit the needs arising in applications. In addition, it emphasizes the need for intuitive and interpretable models, which are tolerant to imprecision and uncertainty.
Statistics is more rigorous and focuses on establishing objective conclusions based on experimental data by analyzing the possible situations and their (relative) likelihood. It emphasizes the need for mathematical methods and tools to assess solutions and guarantee performance.
Combining the two fields enhances the robustness and generalizability of data analysis methods, while preserving the flexibility to solve real-world problems efficiently and intuitively.

In this book the author investigates the impact of demographic change on economic growth. As a result of the current financial crisis, a new view on economics has been demanded by various scientists. The author provides such a new view on economic growth, using a methodology of system dynamics. By applying this method, the author focuses on characteristics of complex systems and analyzes aging and shrinking processes, and not only positive growth. Delays and feedback processes are also considered. This leads to deeper and revealing insights into economic behavior. In doing so, a new semi-endogenous growth model is developed by introducing a specific and detailed population sector (demographic growth model). The book shows and analyzes the behavior of such a model and tests several policy scenarios in a transfer chapter to apply the new theoretical approach on real world problems. The major results are summarized in 15 principles of demographic growth.

Modeling of photovoltaic sources and their emulation by means of power electronic converters are challenging issues. The former is tied to the knowledge of the electrical behavior of the PV generator; the latter consists in its realization by a suitable power amplifier. This extensive introduction to the modeling of PV generators and their emulation by means of power electronic converters will aid in understanding and improving design and set up of new PV plants. The main benefit of reading Photovoltaic Sources is the ability to face the emulation of photovoltaic generators obtained by the design of a suitable equipment in which voltage and current are the same as in a real source. This is achieved according to the following steps: the source electrical behavior modeling, the power converter design, including its control, for the laboratory emulator. This approach allows the reader to cope with the creation of an indoor virtual photovoltaic plant, in which the environmental conditions can be imposed by the user, for testing real operation including maximum power point tracking, partial shading, control for the grid or load interfacing, etc. Photovoltaic Sources is intended to meet the demands of postgraduate level students, and should prove useful to professional engineers and researchers dealing with the problems associated with modeling and emulation of photovoltaic sources.

This book provides tips to teachers for moving toward active learning by using simulation and gaming. The book is a rare reference for teachers who wish to initiate active learning by applying many real experiences from world experts in simulation and gaming. This cumulative wisdom comes from cutting-edge trials reported at the 49th International Simulation and Gaming Association's annual conference in Thailand 9-13 July 2018. The importance of changing teachers' one-way lecture approach to that of active learning has been commonly understood for several decades and has been promoted especially in recent years in Asian universities. Simulation and gaming meets the requirements of such teaching programs, especially for active learning, but there are few books or references on how to gamify a lecture. This book serves as a guide to facilitate that change. The author recognizes the duty to provide readers with fixed directions toward simulation and gaming in the next generation, which have still not been fully elucidated. Developing a simulation and gaming culture and making it sustainable in the next decade are the purpose of this book.

Disaster management is a process or strategy that is implemented when any type of catastrophic event takes place. The process may be initiated when anything threatens to disrupt normal operations or puts the lives of human beings at risk. Governments on all levels as well as many businesses create some sort of disaster plan that make it possible to overcome the catastrophe and return to normal function as quickly as possible. Response to natural disasters (e.g., floods, earthquakes) or technological disaster (e.g., nuclear, chemical) is an extreme complex process that involves severe time pressure, various uncertainties, high non-linearity and many stakeholders. Disaster management often requires several autonomous agencies to collaboratively mitigate, prepare, respond, and recover from heterogeneous and dynamic sets of hazards to society. Almost all disasters involve high degrees of novelty to deal with most unexpected various uncertainties and dynamic time pressures. Existing studies and approaches within disaster management have mainly been focused on some specific type of disasters with certain agency oriented. There is a lack of a general framework to deal with similarities and synergies among different disasters by taking their specific features into account. This book provides with various decisions analysis theories and support tools in complex systems in general and in disaster management in particular. The book is also generated during a long-term preparation of a European project proposal among most leading experts in the areas related to the book title. Chapters are evaluated based on quality and originality in theory and methodology, application oriented, relevance to the title of the book.

This book examines air pollution of a big city using multi-year and multi-season data from ground-based air monitoring stations and satellite sounding data, which provides more clear and detailed information on the main sources of air pollution, the long-term trend of pollution, the influence of meteorological parameters on pollution levels, and trajectories of polluted air masses. For example, the book shows that particulate matter from local sources is transported from deserts to create air quality challenges. It also analyzes the effects of desert and semi-desert landscapes on high concentrations of pollutants.

The Discrete Element Method (DEM) has emerged as a solution to predicting load capacities of masonry structures. As one of many numerical methods and computational solutions being applied to evaluate masonry structures, further research on DEM tools and methodologies is essential for further advancement. Computational Modeling of Masonry Structures Using the Discrete Element Method explores the latest digital solutions for the analysis and modeling of brick, stone, concrete, granite, limestone, and glass block structures. Focusing on critical research on mathematical and computational methods for masonry analysis, this publication is a pivotal reference source for scholars, engineers, consultants, and graduate-level engineering students.

This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.

A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement. This book contains methodology for the analysis of data that arise from such multiscale processes. The book brings together a number of recent developments and makes them accessible to a wider audience. Taking a Bayesian approach allows for full accounting of uncertainty, and also addresses the delicate issue of uncertainty at multiple scales. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice.

The book is aimed at statisticians, applied mathematicians, and engineers working on problems dealing with multiscale processes in time and/or space, such as in engineering, finance, and environmetrics. The book will also be of interest to those working on multiscale computation research. The main prerequisites are knowledge of Bayesian statistics and basic Markov chain Monte Carlo methods. A number of real-world examples are thoroughly analyzed in order to demonstrate the methods and to assist the readers in applying these methods to their own work. To further assist readers, the authors are making source code (for R) available for many of the basic methods discussed herein.

"Current Topics in Membranes" provides a systematic, comprehensive, and rigorous approach to specific topics relevant to the study of cellular membranes. Each volume is a guest edited compendium of membrane biology.
*Discusses the current stat of electrostatics in biomolecular simulations and future directions
*Includes information on time and length scales in lipid bilayer simulations
*Includes a chapter on the nature of lipid rafts

This volume brings together, in a central text, chapters written by leading scholars working at the intersection of modeling, the natural and social sciences, and public participation. This book presents the current state of knowledge regarding the theory and practice of engaging stakeholders in environmental modeling for decision-making, and includes basic theoretical considerations, an overview of methods and tools available, and case study examples of these principles and methods in practice. Although there has been a significant increase in research and development regarding participatory modeling, a unifying text that provides an overview of the different methodologies available to scholars and a systematic review of case study applications has been largely unavailable. This edited volume seeks to address a gap in the literature and provide a primer that addresses the growing demand to adopt and apply a range of modeling methods that includes the public in environmental assessment and management. The book is divided into two main sections. The first part of the book covers basic considerations for including stakeholders in the modeling process and its intersection with the theory and practice of public participation in environmental decision-making. The second part of the book is devoted to specific applications and products of the various methods available through case study examination. This second part of the book also provides insight from several international experts currently working in the field about their approaches, types of interactions with stakeholders, models produced, and the challenges they perceived based on their practical experiences.

This book highlights recent developments in the field, presented at the Social Simulation 2015 conference in Groningen, The Netherlands. It covers advances both in applications and methods of social simulation. Societal issues addressed range across complexities in economic systems, opinion dynamics and civil violence, changing mobility patterns, different land-use, transition in the energy system, food production and consumption, ecosystem management and historical processes. Methodological developments cover how to use empirical data in validating models in general, formalization of behavioral theory in agent behavior, construction of artificial populations for experimentation, replication of models, and agent-based models that can be run in a web browser. Social simulation is a rapidly evolving field. Social scientists are increasingly interested in social simulation as a tool to tackle the complex non-linear dynamics of society. Furthermore, the software and hardware tools available for social simulation are becoming more and more powerful. This book is an important source for readers interested in the newest developments in the ways in which the simulation of social interaction contributes to our understanding and managing of complex social phenomena.

Over the last decades Discrete Event Simulation has conquered many different application areas. This trend is, on the one hand, driven by an ever wider use of this technology in different fields of science and on the other hand by an incredibly creative use of available software programs through dedicated experts. This book contains articles from scientists and experts from 10 countries. They illuminate the width of application of this technology and the quality of problems solved using Discrete Event Simulation. Practical applications of simulation dominate in the present book. The book is aimed to researchers and students who deal in their work with Discrete Event Simulation and which want to inform them about current applications. By focusing on discrete event simulation, this book can also serve as an inspiration source for practitioners for solving specific problems during their work. Decision makers who deal with the question of the introduction of discrete event simulation for planning support and optimization this book provides a contribution to the orientation, what specific problems could be solved with the help of Discrete Event Simulation within the organization.

This volume contains the articles presented at the 21st International Meshing Roundtable (IMR) organized, in part, by Sandia National Laboratories and was held on October 7-10, 2012 in San Jose, CA, USA. The first IMR was held in 1992, and the conference series has been held annually since. Each year the IMR brings together researchers, developers, and application experts in a variety of disciplines, from all over the world, to present and discuss ideas on mesh generation and related topics. The technical papers in this volume present theoretical and novel ideas and algorithms with practical potential, as well as technical applications in science and engineering, geometric modeling, computer graphics, and visualization.

Systems for Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) are currently separate. The potential of the latest technologies and changes in operational and analytical applications over the last decade have given rise to the unification of these systems, which can be of benefit for both workloads. Research and industry have reacted and prototypes of hybrid database systems are now appearing.

Benchmarks are the standard method for evaluating, comparing and supporting the development of new database systems. Because of the separation of OLTP and OLAP systems, existing benchmarks are only focused on one or the other. With the rise of hybrid database systems, benchmarks to assess these systems will be needed as well.

Based on the examination of existing benchmarks, a new benchmark for hybrid database systems is introduced in this book. It is furthermore used to determine the effect of adding OLAP to an OLTP workload and is applied to analyze the impact of typically used optimizations in the historically separate OLTP and OLAP domains in mixed-workload scenarios.

Modeling is a key component to sciences from mathematics to life science, including environmental and ecological studies. By looking at the underlying concepts of the software, we can make sure that we build mathematically feasible models and that we get the most out of the data and information that we have. This book shows how models can be analyzed using simple math and software to generate meaningful qualitative descriptions of system dynamics. This book shows that even without a full analytical, mathematically rigorous analysis of the equations, there may be ways to derive some qualitative understanding of the general behavior of a system. By relating some of the modeling approaches and systems theory to real-world examples the book illustrates how these approaches can help understand concepts such as sustainability, peak oil, adaptive management, optimal harvest and other practical applications.
* Relates modeling approaches and systems theory to real-world examples
* Teaches students to build mathematically feasible models and get the most out of the data and information available
* Wide range of applications in hydrology, population dynamics, market cycles, sustainability theory, management, and more

This book commemorates the 65th birthday of Dr. Boris Kovalerchuk, and reflects many of the research areas covered by his work. It focuses on data processing under uncertainty, especially fuzzy data processing, when uncertainty comes from the imprecision of expert opinions. The book includes 17 authoritative contributions by leading experts.

Particle models play an important role in many applications in physics, chemistry and biology. They can be studied on the computer with the help of molecular dynamics simulations. This book presents in detail both the necessary numerical methods and techniques (linked-cell method, SPME-method, tree codes, multipole technique) and the theoretical background and foundations. It illustrates the aspects modelling, discretization, algorithms and their parallel implementation with MPI on computer systems with distributed memory. Furthermore, detailed explanations are given to the different steps of numerical simulation, and code examples are provided. With the description of the algorithms and the presentation of the results of various simulations from the areas material science, nanotechnology, biochemistry and astrophysics, the reader of this book will be able to write his own programs for molecular dynamics step by step and to run successful experiments.