Implicit objects have gained increasing importance in geometric modeling, visualisation, animation, and computer graphics, because their geometric properties provide a good alternative to traditional parametric objects. This book presents the mathematics, computational methods and data structures, as well as the algorithms needed to render implicit curves and surfaces, and shows how implicit objects can easily describe smooth, intricate, and articulatable shapes, and hence why they are being increasingly used in graphical applications.

Divided into two parts, the first introduces the mathematics of implicit curves and surfaces, as well as the data structures suited to store their sampled or discrete approximations, and the second deals with different computational methods for sampling implicit curves and surfaces, with particular reference to how these are applied to functions in 2D and 3D spaces.

This book includes selected peer-reviewed papers presented at the International Conference on Modeling, Simulation and Optimization (CoMSO 2021), organized by National Institute of Technology, Silchar, Assam, India, during December 16-18, 2021. The book covers topics of modeling, simulation and optimization, including computational modeling and simulation, system modeling and simulation, device/VLSI modeling and simulation, control theory and applications, modeling and simulation of energy systems and optimization. The book disseminates various models of diverse systems and includes solutions of emerging challenges of diverse scientific fields.

This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648 "Software for Exascale Computing" (SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dresden during October 21-23, 2019. In that respect, it both represents a continuation of Vol. 113 in Springer's series Lecture Notes in Computational Science and Engineering, the corresponding report of SPPEXA's first funding phase, and provides an overview of SPPEXA's contributions towards exascale computing in today's sumpercomputer technology. The individual chapters address one or more of the research directions (1) computational algorithms, (2) system software, (3) application software, (4) data management and exploration, (5) programming, and (6) software tools. The book has an interdisciplinary appeal: scholars from computational sub-fields in computer science, mathematics, physics, or engineering will find it of particular interest.

This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python. Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge-Kutta, and shooting methods; presents largely self-contained chapters, arranged in a logical order suitable for an introductory course on scientific computing. Undergraduate students embarking on a first course on numerical methods or scientific computing will find this textbook to be an invaluable guide to the field, and to the application of these methods across such varied disciplines as computer science, engineering, mathematics, economics, the physical sciences, and social science.

"Multi-finger Haptic Interaction "presents a panorama of technologies and methods for multi-finger haptic interaction, together with an analysis of the benefits and implications of adding multiple-fingers to haptic applications.

Research topics covered include: design and control of advanced haptic devices;multi-contact point simulation algorithms;interaction techniques and implications in human perception when interacting with multiple fingers.

These multi-disciplinary results are integrated into applications such as medical simulators for training manual skills, simulators for virtual prototyping and precise manipulations in remote environments.

"Multi-finger Haptic Interaction "presents the current and potential applications that can be developed with these systems, and details the systems' complexity. The research is focused on enhancing haptic interaction by providing multiple contact points to the user.

This state-of-the-art volume is oriented towards researchers who are involved in haptic device design, rendering methods and perception studies, as well as readers from different disciplines who are interested in applying multi-finger haptic technologies and methods to their field of interest.

A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.

This book, which is the first to be published in the emerging field of farm-level microsimulation, highlights the different methodological components of microsimulation modelling: hypothetical, static, dynamic, behavioural, spatial and macro-micro. The author applies various microsimulation-based methodological tools to farms in a consistent manner and, supported by a set of Stata codes, undertakes analysis of a wide range of farming systems from OECD countries. To these case studies, O'Donoghue incorporates farming policies such as CAP income support payments, agri-environmental schemes, forestry planting incentives and biomass incentives - in doing so, he illuminates the merits of microsimulation in this environment.

This book describes, from a computer science viewpoint the software, methods of simulating and analysing crowds with a particular focus on the effects of panic in emergency situations. The power of modern technology impacts on modern life in multiple ways every day. A variety of scientific models and computational tools have been developed to improve human safety and comfort in built environments. In particular, understanding pedestrian behaviours during egress situations is of considerable importance in such contexts. Moreover, some places are built for large numbers of people (such as train stations and airports and high volume special activities such as sporting events). Simulating Crowds in Egress Scenarios discusses the use of computational crowd simulation to reproduce and evaluate egress performance in specific scenarios. Several case studies are included, evaluating the work and different analyses, and comparisons of simulation data versus data obtained from real-life experiments are given.

The first step in making your ideas a reality SketchUp offers a vast array of tools that help you get your building, woodworking, and design plans out of your head and into a real model. Even if you've never dabbled in the software, SketchUp All-in-One For Dummies makes it easy to get started as quickly as the ideas pop into your head! Providing real-world insight from top SketchUp insiders, these six-books-in-one teach you how to tackle the basics of the program and apply those skills to real-world projects. You'll discover the basics of modeling as they apply to either free or paid versions of SketchUp before diving into creating models to use for making objects, constructing buildings, or redesigning interiors. Navigate the SketchUp product mix Get familiar with the basics of modeling View and share your models Make your architecture, interior design, and woodworking dreams a reality You have tons of great ideas--and now you can harness this powerful software to bring them to life.

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 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."

This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.

Theoretical molecular spectroscopy has been the subject of intense activity in the last decade as a result of the increasing availability of powerful computers. Computational Molecular Spectroscopy is the first book ever to provide a comprehensive treatment of modern compuational techniques for predicting/interpreting molecular spectra.
Comprised essentially of four main parts, the book is a must for research workers in high resolution molecular spectroscopy and in quantum chemistry. It is also highly useful to undergraduate and postgraduate students of physics and chemistry, who are just starting out in the field.
The four main areas covered include:

• Ab initio calculation of potential energy surfaces and other electronic properties of molecules
• Perturbation-theory-based and variational approaches to the calculation of spectroscopic data
• Theory of calculating rovibronic energies, including the Renner and Jahn-Teller effects
• Special topics of high current interest: highly excited states and local modes, semi-classical approaches, time-dependent phenomena, and the Carr-Parrinello approach.

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.

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.

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.

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.

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.

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.

Systems Architecture Modeling with the Arcadia Method is an illustrative guide for the understanding and implementation of model-based systems and architecture engineering with the Arcadia method, using Capella, a new open-source solution. More than just another systems modeling tool, Capella is a comprehensive and extensible Eclipse application that has been successfully deployed in a wide variety of industrial contexts. Based on a graphical modeling workbench, it provides systems architects with rich methodological guidance using the Arcadia method and modeling language. Intuitive model editing and advanced viewing capabilities improve modeling quality and productivity, and help engineers focus on the design of the system and its architecture. This book is the first to help readers discover the richness of the Capella solution.

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.