This is a volume consisting of selected papers that were presented at the 3rd St. Petersburg Workshop on Simulation held at St. Petersburg, Russia, during June 28-July 3, 1998. The Workshop is a regular international event devoted to mathematical problems of simulation and applied statistics organized by the Department of Stochastic Simulation at St. Petersburg State University in cooperation with INFORMS College on Simulation (USA). Its main purpose is to exchange ideas between researchers from Russia and from the West as well as from other coun tries throughout the World. The 1st Workshop was held during May 24-28, 1994, and the 2nd workshop was held during June 18-21, 1996. The selected proceedings of the 2nd Workshop was published as a special issue of the Journal of Statistical Planning and Inference. Russian mathematical tradition has been formed by such genius as Tchebysh eff, Markov and Kolmogorov whose ideas have formed the basis for contempo rary probabilistic models. However, for many decades now, Russian scholars have been isolated from their colleagues in the West and as a result their mathe matical contributions have not been widely known. One of the primary reasons for these workshops is to bring the contributions of Russian scholars into lime light and we sincerely hope that this volume helps in this specific purpose."

Revitalize your architectural visualizations by bringing new levels of realism to your day and night interior scenes. This book features full-color, step-by-step tutorials to develop a firm understanding of the processes and techniques involved in creating jaw-dropping 3d visualizations for top marketing agencies. This second volume includes day and night lighting of an atrium scene using seasoned tools and techniques to deploy V-Ray 5 and 3ds Max 2020. It has never been quicker and easier to create the industry's top-of-the-range 3d marketing visuals. The book starts with an overview of the best techniques to approach clients via emails, calls, meetings, and social media. There are also key insights into the best practices of handling projects, pricing, contracts, invoices, pre-production, production, post-production, etc. The subsequent step takes users through the installation of V-Ray 5 and the process of accessing the V-Ray Material browser dialog. Throughout the book, users are taken through VRayMtl functions such as Diffuse, Roughness, Reflect, Glossiness, Metalness, Refract, IOR, Abbe number, Fog color, Translucency, BRDF, Coat, Sheen and Bump. Users will also learn how to use procedural maps such as VRayBitmap, VRayTriplanarTex, Bricks, Metals, Carpaint, VRayDisplacementMod, VRayUVWRandomizer, VRayMultiSubTex, VRayPointCloudColor, VRayDirt, VRayAerialPersepective, VRayLightMtl, VRayMtlWrapper, VRayOverrideMtl, VRay2SidedMtl, VRayBlendMtl and VRayEdgesTex. Users will have a rare insight into all functionalities of a V-Ray camera, VRayLight objects, Render settings, Frame buffer, Global switches, IPR options, Bucket and Progressive image samplers, Image filters, Global DMC, Color mapping, Brute force GI, Light cache, Color management, Distributed rendering, Render elements, V-Ray image file format, VFB History settings, VFB Lens Effects, LightMix, Film tonemap, Hue/Saturation, Lookup Table and much more. Finally, users will embark on the amazing journey of utilizing the previous chapters to create eye-catching 3d marketing visuals through the meticulous process of pre-production, production and post-production of both day and night scenes/lighting. The tips and tricks section will extensively cover key sections about Verified views for planning applications, Parametric modeling with AdvArray, anima (R), project manager plug-in, Verge3d, Webrotate 360, Accucities 3d city models and much more.

Growth in the pharmaceutical market has slowed down - almost to a standstill. One reason is that governments and other payers are cutting costs in a faltering world economy. But a more fundamental problem is the failure of major companies to discover, develop and market new drugs. Major drugs losing patent protection or being withdrawn from the market are simply not being replaced by new therapies - the pharmaceutical market model is no longer functioning effectively and most pharmaceutical companies are failing to produce the innovation needed for success. This multi-authored new book looks at a vital strategy which can bring innovation to a market in need of new ideas and new products: Systems Biology (SB). Modeling is a significant task of systems biology. SB aims to develop and use efficient algorithms, data structures, visualization and communication tools to orchestrate the integration of large quantities of biological data with the goal of computer modeling. It involves the use of computer simulations of biological systems, such as the networks of metabolites comprise signal transduction pathways and gene regulatory networks to both analyze and visualize the complex connections of these cellular processes. SB involves a series of operational protocols used for performing research, namely a cycle composed of theoretical, analytic or computational modeling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.

These are the proceedings of the 25th International Conference on Domain Decomposition Methods in Science and Engineering, which was held in St. John's, Newfoundland, Canada in July 2018. Domain decomposition methods are iterative methods for solving the often very large systems of equations that arise when engineering problems are discretized, frequently using finite elements or other modern techniques. These methods are specifically designed to make effective use of massively parallel, high-performance computing systems. The book presents both theoretical and computational advances in this domain, reflecting the state of art in 2018.

The aim of this book is to unlock the power of the freeware R language to advanced university students and researchers dealing with whole-rock geochemistry of (meta-) igneous rocks. The first part covers data input/output, calculation of commonly used indexes and plotting in R. The core of the book then focusses on the presentation and practical implementations of modelling techniques used for fingerprinting processes such as partial melting, fractional crystallization, binary mixing or AFC using major-, trace-element and radiogenic isotope data. The reader will be given a firm theoretical basis for forward/reverse modelling, followed by exercises dealing with typical problems likely to be encountered in real life, and their solutions using R. The concluding sections demonstrate, using practical examples, how a researcher can proceed in developing a realistic model simulating natural systems. The appendices outline the fundamentals of the R language and provide a quick introduction to the open-source R-package GCDkit for interpretation of whole-rock geochemical data from igneous and metamorphic rocks.

This book offers an accessible guide to ubiquitous computing, with an emphasis on pervasive networking. It addresses various technical obstacles, such as connectivity, levels of service, performance, reliability and fairness. The focus is on describing currently available off-the-shelf technologies, novel algorithms and techniques in areas such as: underwater sensor networks, ant colony based routing, heterogeneous networks, agent based distributed networks, cognitive radio networks, real-time WSN applications, machine translation, intelligent computing and ontology based bit masking. By introducing the core topics and exploring assistive pervasive systems that draw on pervasive networking, the book provides readers with a robust foundation of knowledge on this growing field of research. Written in a straightforward style, the book is also accessible to a broad audience of researchers and designers who are interested in exploring pervasive computing further.

This book examines the use of agent-based modelling (ABM) in population studies, from concepts to applications, best practices to future developments. It features papers written by leading experts in the field that will help readers to better understand the usefulness of ABM for population projections, how ABM can be injected with empirical data to achieve a better match between model and reality, how geographic information can be fruitfully used in ABM, and how ABM results can be reported effectively and correctly. Coverage ranges from detailing the relation between ABM and existing paradigms in population studies to infusing agent-based models with empirical data. The papers show the benefits that ABM offers the field, including enhanced theory formation by better linking the micro level with the macro level, the ability to represent populations more adequately as complex systems, and the possibility to study rare events and the implications of alternative mechanisms in artificial laboratories. In addition, readers will discover guidelines and best practices with detailed examples of how to apply agent-based models in different areas of population research, including human mating behaviour, migration, and socio-structural determinants of health behaviours. Earlier versions of the papers in this book have been presented at the workshop "Recent Developments and Future Directions in Agent-Based Modelling in Population Studies," which took place at the University of Leuven (KU Leuven), Belgium, in September 2014. The book will contribute to the development of best practices in the field and will provide a solid point of reference for scholars who want to start using agent-based modelling in their own research.

Computational molecular and materials modeling has emerged to deliver solid technological impacts in the chemical, pharmaceutical, and materials industries. It is not the all-predictive science fiction that discouraged early adopters in the 1980s. Rather, it is proving a valuable aid to designing and developing new products and processes. People create, not computers, and these tools give them qualitative relations and quantitative properties that they need to make creative decisions.
With detailed analysis and examples from around the world, Applying Molecular and Materials Modeling describes the science, applications, and infrastructures that have proven successful. Computational quantum chemistry, molecular simulations, informatics, desktop graphics, and high-performance computing all play important roles. At the same time, the best technology requires the right practitioners, the right organizational structures, and - most of all - a clearly understood blend of imagination and realism that propels technological advances. This book is itself a powerful tool to help scientists, engineers, and managers understand and take advantage of these advances.

The book will cover the past, present and future developments of field theory and computational electromagnetics. The first two chapters will give an overview of the historical developments and the present the state-of-the-art in computational electromagnetics. These two chapters will set the stage for discussing recent progress, new developments, challenges, trends and major directions in computational electromagnetics with three main emphases:

a. Modeling of ever larger structures with multi-scale dimensions and multi-level descriptions (behavioral, circuit, network and field levels) and transient behaviours

b. Inclusions of physical effects other than electromagnetic: quantum effects, thermal effects, mechanical effects and nano scale features

c. New developments in available computer hardware, programming paradigms (MPI, Open MP, CUDA and Open CL) and the associated new modeling approaches

These are the current emerging topics in the area of computational electromagnetics and may provide readers a comprehensive overview of future trends and directions in the area.

The book iswritten for students, research scientists, professors, design engineers and consultants who engaged in the fields ofdesign, analysis and research of the emerging technologies related to computational electromagnetics, RF/microwave, optimization, new numerical methods, as well as accelerator simulator, dispersive materials, nano-antennas, nano-waveguide, nano-electronics, terahertz applications, bio-medical and material sciences.The book may also be used for those involved in commercializing electromagnetic and related emerging technologies, sensors and the semiconductor industry. The book can be used as a reference book for graduates and post graduates. It can also be used as a text book for workshops and continuing education for researchers and design engineers."

Here is a comprehensive guide to the incorporation of computer simulation in all levels of the planning function of an organization. Writing for managers of planning, planners, and programmers, the author enables readers to gain an overall understanding of the potential role of simulation in planning, to apply simulation to their own particular needs, and to translate planning concepts into computer instructions. Nersesian demonstrates that for manager, planner, and programmer alike, simulation is not difficult in concept nor complicated to put into practice. The author argues that simulation is a necessary activity in a planning environment characterized by uncertain futures and rapidly changing conditions.

The book is organized into separate chapters, each of which acts as a case study of an aspect in the use of simulation. The synopsis that begins every chapter provides the manager of a planning operation with an appreciation of the general application of simulation to one facet of planning. The chapters themselves focus on particular situations which might befall a planner within the general application of simulation to the planning process. Special appendices--designed to aid programmers who have not had much previous experience in setting up simulation programs--follow each chapter and provide descriptive material and the applicable simulation program. As a comprehensive yet easily understood guide to the benefits of utilizing simulation in the planning process, this book will be an invaluable resource for planners, corporate executives, and programmers.

This book presents the latest in decision-making tools, techniques, and solutions for policy makers to utilize in overcoming the challenges faced by healthcare systems. With contributions from experts world-wide, an array of healthcare management models, techniques, and integrative solutions are presented, drawing on econometric, system dynamics, and agent-based models as well as state-of-the-art empirical studies. As total healthcare spending (both total expenditures on health as a percentage of GDP and average spending on per capita) increases across most of the world's economies, healthcare systems continue to face challenges in terms of cost, quality, and access, as a result of its fragmented nature. Consequently, healthcare managers and policy makers require innovative integrative approaches and solutions to better manage complex, dynamic healthcare systems. This volume offers researchers and policy makers an insightful and critical review of the state of the art in healthcare modeling, with a particular focus on system dynamics, agent-based models, and modern empirical studies. It will be of interest to those in the fields of health, business management, and information systems.

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.

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduce the evolving area of static and dynamic simulation-based optimization. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms. Key features of this revised and improved Second Edition include: * Extensive coverage, via step-by-step recipes, of powerful new algorithms for static simulation optimization, including simultaneous perturbation, backtracking adaptive search and nested partitions, in addition to traditional methods, such as response surfaces, Nelder-Mead search and meta-heuristics (simulated annealing, tabu search, and genetic algorithms) * Detailed coverage of the Bellman equation framework for Markov Decision Processes (MDPs), along with dynamic programming (value and policy iteration) for discounted, average, and total reward performance metrics * An in-depth consideration of dynamic simulation optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via API, Q-P-Learning, actor-critics, and learning automata * A special examination of neural-network-based function approximation for Reinforcement Learning, semi-Markov decision processes (SMDPs), finite-horizon problems, two time scales, case studies for industrial tasks, computer codes (placed online) and convergence proofs, via Banach fixed point theory and Ordinary Differential Equations Themed around three areas in separate sets of chapters - Static Simulation Optimization, Reinforcement Learning and Convergence Analysis - this book is written for researchers and students in the fields of engineering (industrial, systems, electrical and computer), operations research, computer science and applied mathematics.

The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo simulation in statistical physics, which deals with the computer simulation of many-body systems in condensed matter physics and related fields of physics and beyond (traffic flows, stock market fluctuations, etc.). Using random numbers generated by a computer, these powerful simulation methods calculate probability distributions, making it possible to estimate the thermodynamic properties of various systems. The book describes the theoretical background of these methods, enabling newcomers to perform such simulations and to analyse their results. It features a modular structure, with two chapters providing a basic pedagogic introduction plus exercises suitable for university courses; the remaining chapters cover major recent developments in the field. This edition has been updated with two new chapters dealing with recently developed powerful special algorithms and with finite size scaling tools for the study of interfacial phenomena, which are important for nanoscience. Previous editions have been highly praised and widely used by both students and advanced researchers.

Computational Creativity, Concept Invention, and General Intelligence in their own right all are flourishing research disciplines producing surprising and captivating results that continuously influence and change our view on where the limits of intelligent machines lie, each day pushing the boundaries a bit further. By 2014, all three fields also have left their marks on everyday life - machine-composed music has been performed in concert halls, automated theorem provers are accepted tools in enterprises' R&D departments, and cognitive architectures are being integrated in pilot assistance systems for next generation airplanes. Still, although the corresponding aims and goals are clearly similar (as are the common methods and approaches), the developments in each of these areas have happened mostly individually within the respective community and without closer relationships to the goings-on in the other two disciplines. In order to overcome this gap and to provide a common platform for interaction and exchange between the different directions, the International Workshops on "Computational Creativity, Concept Invention, and General Intelligence" (C3GI) have been started. At ECAI-2012 and IJCAI-2013, the first and second edition of C3GI each gathered researchers from all three fields, presenting recent developments and results from their research and in dialogue and joint debates bridging the disciplinary boundaries. The chapters contained in this book are based on expanded versions of accepted contributions to the workshops and additional selected contributions by renowned researchers in the relevant fields. Individually, they give an account of the state-of-the-art in their respective area, discussing both, theoretical approaches as well as implemented systems. When taken together and looked at from an integrative perspective, the book in its totality offers a starting point for a (re)integration of Computational Creativity, Concept Invention, and General Intelligence, making visible common lines of work and theoretical underpinnings, and pointing at chances and opportunities arising from the interplay of the three fields.

This edited volume focuses on how we can protect our environment and enhance environmental sustainability when faced with changes and pressures imposed by our expansive needs. The volume unites multiple subject areas within sustainability, enabling the techniques and philosophy in the chapters to be applied to research areas in environmental science, plant sciences, energy, biodiversity and conservation. The chapters from expert contributors cover topics such as mathematical modelling tools used to monitor diversity of plant species, and the stability of ecosystem services such as biogeochemical cycling. Empirical research presented here also brings together mathematical developments in the important fields of robotics including kinematics, dynamics, path planning, control, vision, and swarmanoids. Through this book readers will also discover about rainfall-runoff modelling which will give them a better idea of the effects of climate change on the sustainability of water resources at the watershed scale. Modelling approaches will also be examined that maximize readers insights into the global problem of energy transition, i.e. the switch to an energy production system using renewable resources only. Collective and discrete insights are made to assist with synergy which should progress well beyond this book. Insight is also given to assist policy formations, development and implementations. The book has a strong multi-disciplinary nature at its core, and will appeal to both generalist readers and specialists in information technology, mathematics, biology, physics, chemistry and environmental sciences.

Object-Oriented Computer Simulation of Discrete-Event Systems offers a comprehensive presentation of a wide repertoire of computer simulation techniques available to the modelers of dynamic systems. Unlike other books on simulation, this book includes a complete and balanced description of all essential issues relevant to computer simulation of discrete event systems, and it teaches simulation users how to design, program and exploit their own computer simulation models. In addition, it uses the object-oriented methodology throughout the book as its main programming platform. The reader is expected to have some background in the theory of probability and statistics and only a little programming experience in C++, as the book is not tied down to any particular simulation language. The book also provides 50 complete simulation problems to assist with writing such simulation programs. Object-Oriented Computer Simulation of Discrete-Event Systems demonstrates the basic and generic concepts used in computer simulation of discrete-event systems in a comprehensive, uniform and self-contained manner.

The gathering and storage of data indexed in space and time are experiencing unprecedented growth, demanding for advanced and adapted tools to analyse them. This thesis deals with the exploration and modelling of complex high-frequency and non-stationary spatio-temporal data. It proposes an efficient framework in modelling with machine learning algorithms spatio-temporal fields measured on irregular monitoring networks, accounting for high dimensional input space and large data sets. The uncertainty quantification is enabled by specifying this framework with the extreme learning machine, a particular type of artificial neural network for which analytical results, variance estimation and confidence intervals are developed. Particular attention is also paid to a highly versatile exploratory data analysis tool based on information theory, the Fisher-Shannon analysis, which can be used to assess the complexity of distributional properties of temporal, spatial and spatio-temporal data sets. Examples of the proposed methodologies are concentrated on data from environmental sciences, with an emphasis on wind speed modelling in complex mountainous terrain and the resulting renewable energy assessment. The contributions of this thesis can find a large number of applications in several research domains where exploration, understanding, clustering, interpolation and forecasting of complex phenomena are of utmost importance.

This introductory textbook is designed for a one-semester course on the use of the matrix and analytical methods for the performance analysis of telecommunication systems. It provides an introduction to the modelling and analysis of telecommunication systems for a broad interdisciplinary audience of students in mathematics and applied disciplines such as computer science, electronics engineering, and operations research.

Model based predictive control (MBPC) is arguably the most important approach to the advance control of complex interacting industrial processes. Unique among modern theories, MBPC can handle real-time state and actuator constraints in a natural way, enabling plants to maximize their profits. In addition, the wide range of model structures, prediction horizons, and optimization criteria allows for tailor-made MBPC applications--whether they be for high-speed machine tools or large-scale industrial processes. This timely edited volume, based on a conference held at Oxford University and devoted exclusively to MBPC, brings the field up to date with the latest theoretical and practical advances. Topics include how MBPC is expanding to include variants in the basic themes (such as new prediction and optimization approaches, nonlinear models, and two-dimensional problems), general stabilization ideas for constrained plant, and unsolved problems in MBPC. This excellent volume is the introduction to the theory, current applications, and hot research areas in MBPC that students and professionals in control systems have been waiting for.

This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.

Software, Animation and the Moving Image brings a unique perspective to the study of computer-generated animation by placing interviews undertaken with animators alongside an analysis of the user interface of animation software. Wood develops a novel framework for considering computer-generated images found in visual effects and animations.

At the intersection of astronautics, computer science, and social science, this book introduces the challenges and insights associated with computer simulation of human society in outer space, and of the dynamics of terrestrial enthusiasm for space exploration. Never before have so many dynamic representations of space-related social systems existed, some deeply analyzing the logical implications of social-scientific theories, and others open for experience by the general public as computer-generated virtual worlds. Fascinating software ranges from multi-agent artificial intelligence models of civilization, to space-oriented massively multiplayer online games, to educational programs suitable for schools or even for the world's space exploration agencies. At the present time, when actual forays by humans into space are scarce, computer simulations of space societies are an excellent way to prepare for a renaissance of exploration beyond the bounds of Earth.

This book systematically introduces readers to the finite element analysis software DIANA (DIsplacement ANAlyzer) and its applications in civil engineering. Developed by TNO Corporation in the 1970s, DIANA is frequently used in civil engineering and engineering mechanics. Unlike the software user's manual, which provides a comprehensive introduction and theoretical analysis, this book presents a simplified overview of the basic background theory to help beginners master the software quickly. It also discusses GUI operation and the command console in Python language, and includes examples involving classical modeling operations to help readers review each section. Both the book and DIANA itself are valuable resources for students and researchers in all the structural engineering fields, such as civil engineering, bridge engineering, geotechnical engineering, tunnel engineering, underground structural engineering, irrigation, municipal engineering and fire engineering.

In this self-consistent monograph, the author gathers and describes different mathematical techniques and combines all together to form practical procedures for the inverse analyses. It puts together topics coming from mathematical programming, with soft computing and Proper Orthogonal Decomposition, in order to show, in the context of structural analyses, how the things work and what are the main problems one needs to tackle.

Throughout the book a number of examples and exercises are worked out in order to make reader practically familiar with discussed topics.