This book provides novel concepts and techniques for air traffic management (ATM) and communications, navigation, and surveillance (CNS) systems. The book consists of selected papers from the 6th ENRI International Workshop on ATM/CNS (EIWAC2019) held in Tokyo in October 2019, the theme of which was "Exploring Ideas for World Aviation Challenges". Included are key topics to realize safer and more efficient skies in the future, linked to the integrated conference theme consisting of long-term visions based on presentations from various fields. The book is dedicated not only to researchers, academicians, and university students, but also to engineers in the industry, air navigation service providers (ANSPs), and regulators of aviation.

A concise and practical guide to financial modeling in Excel In The Essentials of Financial Modeling in Excel: A Concise Guide to Concepts and Methods, veteran quantitative modeling and business analysis expert Dr. Michael Rees delivers a practical and hands-on introduction to financial modeling in Excel. The author offers readers a well-structured and strategic toolkit to learn modeling from scratch, focusing on the core economic concepts and the structures commonly required within Excel models. Divided into six parts, the book discusses the use of models and the factors to consider when designing and building models so that they can be as powerful as possible, yet simple. . Readers will also find: The foundational structures and calculations most frequently used in modeling, including growth- and ratio-based methods, corkscrews, and waterfall analysis Walkthroughs of economic modeling, measurement, and evaluation, and the linking of these to the decision criteria. These include breakeven and payback analysis, compounding, discounting, calculation of returns, loan calculations, and others Structured approaches for modeling in corporate finance, including financial statement modeling, cash flow valuation, cost of capital, and ratio analysis Techniques to implement sensitivity and scenario analysis Core aspects of statistical analysis, including data preparation, manipulation, and integration The use of approximately 100 Excel functions within example modeling contexts Further Topics Sections, which introduce advanced aspects of many areas, in order to provide further benefit to more advance readers, whilst presenting the truly essential topics separately. Examples of these include introductions to PowerQuery and PowerPivot, as well as advanced waterfall structures An invaluable, all-in-one blueprint for learning financial modeling in Excel, this book is ideal for beginning and intermediate financial professionals and students seeking to build and reinforce essential topics in financial modeling.

This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g. streamflow and temperature) and environmental science (e.g. water quality). Deep learning is known as part of machine learning methodology based on the artificial neural network. Increasing data availability and computing power enhance applications of deep learning to hydrometeorological and environmental fields. However, books that specifically focus on applications to these fields are limited. Most of deep learning books demonstrate theoretical backgrounds and mathematics. However, examples with real data and step-by-step explanations to understand the algorithms in hydrometeorology and environmental science are very rare. This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN) as well as the conventional artificial neural network model.

This book presents innovative ideas and technical contributions in the area of metasurfaces and antenna technologies. On the one hand, it presents an effective method to analyze metasurfaces constituted by metallic texture with certain geometries. It shows how this method can be applied to the design of metasurface (MTS) antennas for deep space communications and other planar microwave devices. On the other hand, the book reports on a general methodology developed for analyzing flat devices realized by using modulated MTSs, which opens new design possibilities for a large number of microwave devices based on the manipulation of SWs. Finally, a novel approach of reconfigurability, which is based on a class of checkerboard MTS, is explored. All in all, this book covers important insights and significant results on the emerging topic of metasurfaces, from theoretical and computational aspects to experiments.

The investigation of the role of mechanical and mechano-chemical interactions in cellular processes and tissue development is a rapidly growing research field in the life sciences and in biomedical engineering. Quantitative understanding of this important area in the study of biological systems requires the development of adequate mathematical models for the simulation of the evolution of these systems in space and time. Since expertise in various fields is necessary, this calls for a multidisciplinary approach. This edited volume connects basic physical, biological, and physiological concepts to methods for the mathematical modeling of various materials by pursuing a multiscale approach, from subcellular to organ and system level. Written by active researchers, each chapter provides a detailed introduction to a given field, illustrates various approaches to creating models, and explores recent advances and future research perspectives. Topics covered include molecular dynamics simulations of lipid membranes, phenomenological continuum mechanics of tissue growth, and translational cardiovascular modeling. Modeling Biomaterials will be a valuable resource for both non-specialists and experienced researchers from various domains of science, such as applied mathematics, biophysics, computational physiology, and medicine.

Expert Trading Systems "This book is an excellent introduction to advanced statistical modeling of financial markets. Wolberg’s explanation of kernel regression is lucid and direct. The author carefully leads readers through each stage of a trade system design and points out to them any potential difficulties they might encounter along the way. In addition, the examples give a concrete grasp of the subject without getting tangled up in any lengthy mathematical derivation." —Peter F. Borish, President, Computer Trading Corporation "The successful application of advanced modeling methods to the development of expert trading systems and financial market forecasting models requires both theoretical and practical knowledge. Wolberg was a pioneer in the development and application of kernel regression modeling to this area, and his book displays both deep theoretical understanding and practical knowledge in a highly readable how-to manner. Moreover, Wolberg’s advanced kernel regression algorithm is orders of magnitude faster than existing methods, thus broadening its application tremendously. I highly recommend this book to any practitioner in this area." —David Aronson, President, Raden Research Group Inc. "Kernel regression is a powerful statistical modeling technique that gives excellent performance in a wide variety of applications, including financial market prediction. Its use has traditionally been limited by its potentially overwhelming computational requirements, but Wolberg provides an effective algorithm that speeds computation by orders of magnitude, making it universally available." —Timothy Masters, author of Neural, Novel & Hybrid Algorithms for Time Series Prediction "This book presents an excellent overview of nonlinear modeling techniques used to build predictive models for financial time series. It is suitable both as a text for a financial modeling course or for a financial analyst who wants to use kernel methods for modeling. Wolberg describes his innovative approach to speeding up kernel regression, which allows these methods to be applied to a more complex set of problems. His software can be used to develop, test, and generate technical trading systems with more flexibility than other software that is commonly available." —Sandor Straus, PhD, Merfin, LLC, former partner of Renaissance Technology Corp.

Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: * Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. * The most innovative developments in the different steps of the kriging process. * An up-to-date account of strategies for dealing with data evolving in space and time. * An accompanying website featuring R code and examples

This book is based on a two-day symposium at the Paris Institute of Advanced Study titled "space-time geometries and movement in the brain and the arts". It includes over 20 chapters written by the leading scientists and artists who presented their related research studies at the symposium and includes six sections; the first three focus on space-time geometries in perception, action and memory while the last three focus on specific artistic domains: drawing and painting, dance, music, digital arts and robotics. The book is accompanied by a dedicated webpage including related images and videos. There is an ever-growing interest in the topics covered by this book. Space and time are of fundamental importance for our understanding of human perception, action, memory and cognition, and are entities which are equally important in physics, biology, neuroscience and psychology. Highly prominent scientists and mathematicians have expressed their belief that our bodies and minds shape the ways we perceive space and time and the physical laws we formulate. Understanding how the brain perceives motion and generates -bodily movements is of great significance. There is also growing interest in studying how space, time and movement subserve artistic creations in different artistic modalities (e.g., fine arts, digital and performing arts and music). This interest is inspired by the idea that artists make intuitive use of the principles and simplifying strategies used by the brain in movement generation and perception. Building upon new understanding of the spatio-temporal geometries subserving movement generation and perception by the brain we can start exploring how artists make use of such neuro --geometrical and neuro-dynamic representations in order to express artistic concepts and emotionally affect the human observers and listeners. Scientists have also started formulating new ideas of how aesthetic judgements emerge from the principles and brain mechanisms subserving motor control and motion perception. Covering novel and multidisciplinary topics, this advanced book will be of interest to neuroscientists, behavioral scientists, artificial intelligence and robotics experts, students and artists.

Written by one of the world's foremost authorities in time series modelling, this book explores goodness of fit tests in time series analysis. Starting with linear models, the author proceeds to nonlinear modelling with extensions to long-memory and generalized linear models--all areas of interest and activity. The focus is firmly on practical matters, and the author presents a range of applications, particularly from the financial arena. Until now, published work in this area has been scattered throughout the literature. Researchers and practitioners alike will welcome this book as a reference that will guide them through the final stages of their modelling tasks.

This book introduces game theory as a means to conceptualize, model, and analyze cyber deception. Drawing upon a collection of deception research from the past 10 years, the authors develop a taxonomy of six species of defensive cyber deception. Three of these six species are highlighted in the context of emerging problems such as privacy against ubiquitous tracking in the Internet of things (IoT), dynamic honeynets for the observation of advanced persistent threats (APTs), and active defense against physical denial-of-service (PDoS) attacks. Because of its uniquely thorough treatment of cyber deception, this book will serve as a timely contribution and valuable resource in this active field. The opening chapters introduce both cybersecurity in a manner suitable for game theorists and game theory as appropriate for cybersecurity professionals. Chapter Four then guides readers through the specific field of defensive cyber deception. A key feature of the remaining chapters is the development of a signaling game model for the species of leaky deception featured in honeypots and honeyfiles. This model is expanded to study interactions between multiple agents with varying abilities to detect deception. Game Theory for Cyber Deception will appeal to advanced undergraduates, graduate students, and researchers interested in applying game theory to cybersecurity. It will also be of value to researchers and professionals working on cybersecurity who seek an introduction to game theory.

Features Minimal pre-requisites beyond a solid background in calculus, such as a calculus I course. Suitable for upper division mathematics and sciences students and graduate-level biology students. Provides sample MATLAB codes and instruction in Appendices.

The book describes currently applied and newly developed advanced numerical methods for wave-induced ship motions and loads. Besides well-established computational methods based on strip theory, panel methods and finite volume methods for unsteady Reynolds-averaged Navier-Stokes equations (URANS), recent advances like a fully nonlinear Rankine panel method, URANS calculations including elastic hull deformations, and an improved method to predict added resistance in waves are explained in detail. Furthermore, statistical methods to assess extreme motions and loads are described both for linear and nonlinear responses in a stationary seaway as well as during long-term ship operations. Results of motions and loads, computed using the various methods, are compared with each other and with results of model experiments. Introductory chapters on fluid dynamics, motions of rigid and elastic ship hulls, numerical methods to compute fluid flows associated with wind waves, and the development and simulation of seaways complement the volume. The book will be of interest to post-graduate students, PhD candidates, as well as engineers in the field of naval architecture, ocean, and marine engineering.

This book features recent research in mathematical modeling of indirectly and directly transmitted infectious diseases in humans, animals, and plants. It compiles nine not previously published studies that illustrate the dynamic spread of infectious diseases, offering a broad range of models to enrich understanding. It demonstrates the capability of mathematical modeling to capture disease spread and interaction dynamics as well as the complicating factors of various evolutionary processes. In addition, it presents applications to real-world disease control by commenting on key parameters and dominant pathways related to transmission. While aimed at early-graduate level students, the book can also provide insights to established researchers in that it presents a survey of current topics and methodologies in a constantly evolving field.

The Springer Handbook of Spacetime is dedicated to the ground-breaking paradigm shifts embodied in the two relativity theories, and describes in detail the profound reshaping of physical sciences they ushered in. It includes in a single volume chapters on foundations, on the underlying mathematics, on physical and astrophysical implications, experimental evidence and cosmological predictions, as well as chapters on efforts to unify general relativity and quantum physics. The Handbook can be used as a desk reference by researchers in a wide variety of fields, not only by specialists in relativity but also by researchers in related areas that either grew out of, or are deeply influenced by, the two relativity theories: cosmology, astronomy and astrophysics, high energy physics, quantum field theory, mathematics, and philosophy of science. It should also serve as a valuable resource for graduate students and young researchers entering these areas, and for instructors who teach courses on these subjects.

The Handbook is divided into six parts. Part A: Introduction to Spacetime Structure. Part B: Foundational Issues. Part C: Spacetime Structure and Mathematics. Part D: Confronting Relativity theories with observations. Part E: General relativity and the universe. Part F: Spacetime beyond Einstein.

This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2020), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during 8-9 July 2020. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.

This book contains a selection of revised and extended research articles written by prominent researchers participating in the 27th World Congress on Engineering and Computer Science (WCECS 2019) which was held in San Francisco, USA, on October 22-24, 2019. Topics covered include engineering mathematics, electrical engineering, communications systems, computer science, chemical engineering, systems engineering, manufacturing engineering, and industrial applications. With contributions carefully chosen to represent the most cutting-edge research presented during the conference, the book contains some of the state-of-the-art in engineering technologies and the physical sciences and their applications and serves as a useful reference for researchers and graduate students working in these fields.

Continuum Models for Phase Transitions and Twinning in Crystals presents the fundamentals of a remarkably successful approach to crystal thermomechanics. Developed over the last two decades, it is based on the mathematical theory of nonlinear thermoelasticity, in which a new viewpoint on material symmetry, motivated by molecular theories, plays a central role.

This is the first organized presentation of a nonlinear elastic approach to twinning and displacive phase transition in crystalline solids. The authors develop geometry, kinematics, and energy invariance in crystals in strong connection and with the purpose of investigating the actual mechanical aspects of the phenomena, particularly in an elastostatics framework based on the minimization of a thermodynamic potential. Interesting for both mechanics and mathematical analysis, the new theory offers the possibility of investigating the formation of microstructures in materials undergoing martensitic phase transitions, such as shape-memory alloys.

Although phenomena such as twinning and phase transitions were once thought to fall outside the range of elastic models, research efforts in these areas have proved quite fruitful. Relevant to a variety of disciplines, including mathematical physics, continuum mechanics, and materials science, Continuum Models for Phase Transitions and Twinning in Crystals is your opportunity to explore these current research methods and topics.

In this book, a number of experts from various disciplines take a look at three different strands in learning to model. They examine the activity of modeling from disparate theoretical standpoints, taking into account the individual situation of the individuals involved. The chapters seek to bridge the modeling of communication and the modeling of particular scientific domains. In so doing, they seek to throw light on the educational communication that goes on in conceptual learning.
Taken together, the chapters brought together in this volume illustrate the diversity and vivacity of research on a relatively neglected, yet crucially important aspect of education across disciplines: learning to model. A common thread across the research presented is the view that communication and interaction, as fundamental to most educational practices and as a repository of conceptual understanding and a learning mechanism in itself, is intimately linked to elaborating meaningful, coherent, and valid representations of the world.
The editors hope this volume will contribute to both the fundamental research in its field and ultimately provide results that can be of practical value in designing new situations for teaching and learning modeling, particularly those involving computers.

Social life of bacteria is in the focus of recent research. Bacteria are simple enough to be accessible by science, but still complex enough to show cooperation, division of labor, bet-hedging, cross-talk and synchronized activities, and a rich variety of social traits. A central question of evolutionary theory is the explanation why this social life did develop, and why these systems are evolutionary stable. This book introduces the reader into the theory of evolution, covering classical models and as well as recent developments. The theory developed is used to represent the up-to-date understanding of social bacteria.This book will be useful for students and lecturers interested in mathematical evolutionary theory, as well as for researchers as a reference.

Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods.

The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The applications discussed center primarily, but not exclusively, on developmental toxicity, which leads naturally to discussion of other methodologies, including risk assessment and dose-response modelling.

Clearly written, Topics in Modelling of Clustered Data offers a practical, easily accessible survey of important modelling issues. Overview models give structure to a multitude of approaches, figures help readers visualize model characteristics, and a generous use of examples illustrates all aspects of the modelling process.

This book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.

Mathematical modeling is becoming increasingly versatile and multi-disciplinary. This text demonstrates the broadness of this field as the authors consider the principles of model construction and use common approaches to build models from a range of subject areas. The book reflects the interests and experiences of the authors, but it explores mathematical modeling across a wide range of applications, from mechanics to social science. A general approach is adopted, where ideas and examples are favored over rigorous mathematical procedures. This insightful book will be of interest to specialists, teachers, and students across a wide range of disciplines..

Particle methods have seen increasing use in several engineering and scientific fields, both because of their unique modelling capabilities and the availability of the necessary computational power. This title focuses on their theory and application.

This book provides an overview of power electronic converters for numerical simulations based on DIgSILENT PowerFactory. It covers the working principles, key assumptions and implementation of models of different types of these power systems. The book is divided into three main parts: the first discusses high-voltage direct currents, while the second part examines distribution systems and micro-grids. Lastly, the third addresses the equipment and technologies used in modelling and simulation. Each chapter includes practical examples and exercises, and the accompanying software illustrates essential models, principles and performance using DIgSILENT PowerFactory. Exploring various current topics in the field of modelling power systems, this book will appeal to a variety of readers, ranging from students to practitioners.

This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable.

It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques.

Each chapter features:

• a minimum discussion of mathematical detail;
• an empirical example applying the technique; and
• a discussion of the software related to that technique.

Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.