This book, on the general topic of hydroaerodynamics, investigates a number of exciting applications in this field, addressing specifically issues that allow seemingly paradoxical issues to be dealt with. The first part is devoted to the study of channel flows, in particular the lateral flow of a viscous and viscous-plastic liquid in a ring channel formed by coaxial cylinders. Specifically, the problem of dissipation of mechanical energy in channel flows of highly viscous liquids is addressed and solved. Furthermore, the mechanism leading to hydrodynamic erosion in intra-field pipelines (known as "channelized effect") is identified. Subsequently, a theory for channel flows with mass transfer through porous walls is developed. In the second part, viscous liquid free flows (jets) are investigated. In particular, a dispersion law for turbulent flow is derived and the existence of dynamic invariance in wake flows of variable density is demonstrated. The third part presents new insights from both theoretical and experimental research into concentrated vortex structure formation and development. The conditions for the existence of Taylor-Goertler vortices are determined and the mechanism for their formation is described. Last but not least, the theory of vortex rings, a particularly interesting problem in hydroaerodynamics, is introduced in the last section of this book. Care has been taken, when selecting original theoretical problems of interest, to make the link with related topics in the published literature. At the same time, all experimental research described in this book is given a meaningful physical interpretation and corroborated by suitable theoretical models and computations.

This book assesses the state-of-the-art in computational fluid dynamics (CFD) applied to ship hydrodynamics and provides guidelines for the future developments in the field based on the Gothenburg 2010 Workshop. It presents ship hull test cases, experimental data and submitted computational methods, conditions, grids and results. Analysis is made of errors for global (resistance, sinkage and trim and self-propulsion) and local flow (wave elevations and mean velocities and turbulence) variables, including standard deviations for global variables and propeller modeling for self-propulsion. The effects of grid size and turbulence models are evaluated for both global and local flow variables. Detailed analysis is made of turbulence modeling capabilities for capturing local flow physics. Errors are also analyzed for head-wave seakeeping and forward speed diffraction, and calm-water forward speed-roll decay. Resistance submissions are used to evaluate the error and uncertainty by means of a systematic verification and validation (V&V) study along with statistical investigations. Post-workshop experimental and computational studies are conducted and analyzed for evaluation of facility biases and to draw more concrete conclusions regarding the most reliable turbulence model, appropriate numerical methods and grid resolution requirements, respectively.

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe.

These papers on Intelligent Data Analysis and Management (IDAM) examine issues related to the research and applications of Artificial Intelligence techniques in data analysis and management across a variety of disciplines. The papers derive from the 2013 IDAM conference in Kaohsiung ,Taiwan. It is an interdisciplinary research field involving academic researchers in information technologies, computer science, public policy, bioinformatics, medical informatics, and social and behavior studies, etc. The techniques studied include (but are not limited to): data visualization, data pre-processing, data engineering, database mining techniques, tools and applications, evolutionary algorithms, machine learning, neural nets, fuzzy logic, statistical pattern recognition, knowledge filtering, and post-processing, etc.

This monograph addresses the state of the art of reduced order methods for modeling and computational reduction of complex parametrized systems, governed by ordinary and/or partial differential equations, with a special emphasis on real time computing techniques and applications in computational mechanics, bioengineering and computer graphics.

Several topics are covered, including: design, optimization, and control theory in real-time with applications in engineering; data assimilation, geometry registration, and parameter estimation with special attention to real-time computing in biomedical engineering and computational physics; real-time visualization of physics-based simulations in computer science; the treatment of high-dimensional problems in state space, physical space, or parameter space; the interactions between different model reduction and dimensionality reduction approaches; the development of general error estimation frameworks which take into account both model and discretization effects.

This book is primarily addressed to computational scientists interested in computational reduction techniques for large scale differential problems.

This book is concerned with recent advances in fitness landscapes. The concept of fitness landscapes originates from theoretical biology and refers to a framework for analysing and visualizing the relationships between genotypes, phenotypes and fitness. These relationships lay at the centre of attempts to mathematically describe evolutionary processes and evolutionary dynamics.

The book addresses recent advances in the understanding of fitness landscapes in evolutionary biology and evolutionary computation. In the volume, experts in the field of fitness landscapes present these findings in an integrated way to make it accessible to a number of audiences: senior undergraduate and graduate students in computer science, theoretical biology, physics, applied mathematics and engineering, but also researcher looking for a reference or/and entry point into using fitness landscapes for analysing algorithms. Also practitioners wanting to employ fitness landscape techniques for evaluating bio- and nature-inspired computing algorithms can find valuable material in the book. For teaching proposes, the book could also be used as a reference handbook.

The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel(r) Xeon Phi series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors first-hand optimization experience.

The material is organized in three sections. The first section, Basics of MIC, introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment. Next, the section on Performance Optimization explains general MIC optimization techniques, which are then illustrated step-by-step using the classical parallel programming example of matrix multiplication. Finally, Project development presents a set of practical and experience-driven methods for using parallel computing in application projects, including how to determine if a serial or parallel CPU program is suitable for MIC and how to transplant a program onto MIC.

This book appeals to two main audiences: First, software developers for HPC applications it will enable them to fully exploit the MIC architecture and thus achieve the extreme performance usually required in biological genetics, medical imaging, aerospace, meteorology and other areas of HPC. Second, students and researchers engaged in parallel and high-performance computing it will guide them on how to push the limits of system performance for HPC applications. "

Data-Based Controller Design presents a comprehensive analysis of data-based control design. It brings together the different data-based design methods that have been presented in the literature since the late 1990's. To the best knowledge of the author, these data-based design methods have never been collected in a single text, analyzed in depth or compared to each other, and this severely limits their widespread application. In this book these methods will be presented under a common theoretical framework, which fits also a large family of adaptive control methods: the MRAC (Model Reference Adaptive Control) methods. This common theoretical framework has been developed and presented very recently.

The book is primarily intended for PhD students and researchers - senior or junior - in control systems. It should serve as teaching material for data-based and adaptive control courses at the graduate level, as well as for reference material for PhD theses. It should also be useful for advanced engineers willing to apply data-based design. As a matter of fact, the concepts in this book are being used, under the author's supervision, for developing new software products in a automation company. The book will present simulation examples along the text. Practical applications of the concepts and methodologies will be presented in a specific chapter.

In this book international expert authors provide solutions for modern fundamental problems including the complexity of computing of critical points for set-valued mappings, the behaviour of solutions of ordinary differential equations, partial differential equations and difference equations, or the development of an abstract theory of global attractors for multi-valued impulsive dynamical systems. These abstract mathematical approaches are applied to problem-solving in solid mechanics, hydro- and aerodynamics, optimization, decision making theory and control theory. This volume is therefore relevant to mathematicians as well as engineers working at the interface of these fields.

This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and "applied science" is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as "Statistics for Engineers and Scientists" without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes. Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models. Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation) Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process. Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter. The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.

The book is intended as a textbook providing a deliberately simple introduction to finite element methods in a way that should be readily understandable to engineers, both students and practicing professionals. Only the very simplest elements are considered, mainly two-dimensional three-noded constant strain triangles, with simple linear variation of the relevant variables. Chapters of the book deal with structural problems (beams), classification of a broad range of engineering into harmonic and biharmonic types, finite element analysis of harmonic problems, finite element analysis of biharmonic problems (plane stress and plane strain). Full FORTRAN programs are listed and explained in detail, and a range of practical problems solved in the text. Despite being somewhat unfashionable for general programming purposes, the FORTRAN language remains very widely used in engineering. The programs listed, which were originally developed for use on mainframe computers, have been thoroughly updated for use on desktops and laptops. Unlike the first edition, the new edition has Problems (with Solutions) at the end of each chapter. Electronic copies of the programs should be freely available for download from the internet.

If your students struggle with standard deviation or statistical tests, this is the book for them. This textbook companion will help improve their essential maths skills for psychology, whichever awarding body specification you're following. You can use it throughout the course, whenever you feel they need some extra help. - Develop understanding of both maths and psychology with all worked examples and questions within a psychology context - Improve confidence with a step-by-step approach to every maths skill - Measure progress with guided and non-guided questions - Understand misconceptions with full worked solutions to every question - Feel confident in expert guidance from experienced teacher and examiner Molly Marshall, reviewed by Dorothy Coombs, Editor of ATP Today, former Chair of the Association for the Teaching of Psychology and experienced biology, psychology and FSMQ Statistics teacher

This book brings together a rich selection of studies in mathematical modeling and computational intelligence, with application in several fields of engineering, like automation, biomedical, chemical, civil, electrical, electronic, geophysical and mechanical engineering, on a multidisciplinary approach. Authors from five countries and 16 different research centers contribute with their expertise in both the fundamentals and real problems applications based upon their strong background on modeling and computational intelligence. The reader will find a wide variety of applications, mathematical and computational tools and original results, all presented with rigorous mathematical procedures. This work is intended for use in graduate courses of engineering, applied mathematics and applied computation where tools as mathematical and computational modeling, numerical methods and computational intelligence are applied to the solution of real problems.

The first edition of "Geometric Morphometrics for Biologists" has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses.
Contains updated coverage of methods, especially for sampling complex curves and 3D forms and a new chapter on applications of geometric morphometrics to forensicsOffers a reorganization of chapters to streamline learning basic conceptsPresents detailed instructions for conducting analyses with freely available, easy to use software Provides numerous illustrations, including graphical presentations of important theoretical concepts and demonstrations of alternative approaches to presenting results

The book integrates theoretical analysis, numerical simulation and modeling approaches for the treatment of singular phenomena. The projects covered focus on actual applied problems, and develop qualitatively new and mathematically challenging methods for various problems from the natural sciences. Ranging from stochastic and geometric analysis over nonlinear analysis and modelling to numerical analysis and scientific computation, the book is divided into the three sections: A) Scaling limits of diffusion processes and singular spaces, B) Multiple scales in mathematical models of materials science and biology and C) Numerics for multiscale models and singular phenomena. Each section addresses the key aspects of multiple scales and model hierarchies, singularities and degeneracies, and scaling laws and self-similarity.

This book addresses the basics of interval/fuzzy set theory, artificial neural networks (ANN) and computational methods. It presents step-by-step modeling for application problems along with simulation and numerical solutions. In general, every science and engineering problem is inherently biased by uncertainty, and there is often a need to model, solve and interpret problems in the world of uncertainty. At the same time, exact information about models and parameters of practical applications is usually not known and precise values do not exist. This book discusses uncertainty in both data and models. It consists of seven chapters covering various aspects of fuzzy uncertainty in application problems, such as shallow water wave equations, static structural problems, robotics, radon diffusion in soil, risk of invasive alien species and air quality quantification. These problems are handled by means of advanced computational and fuzzy theory along with machine intelligence when the uncertainties involved are fuzzy. The proposed computational methods offer new fuzzy computing methods that help other areas of knowledge construction where inexact information is present.

Radiation from spectral lines can be absorbed and re- emitted many times in atomic vapours before it reaches the boundaries of the container encasing the vapour. This effect is known as radiation trapping. It plays an important role practically everywhere where atomic vapours occur, e.g. in spectroscopy, in gas lasers, in atomic line filters, in the determination of atomic lifetimes, in measurements of atomic interaction potentials, and in electric discharge lamps. This book for the first time assembles all the information necessary for a treatment of practical problems, emphasizing both physical insights and mathematical methods. After an introduction that reviews resonance radiation and collisional processes in atomic vapours, physical effects and mathematical methods for various types of problems (e.g. with or without saturation, particle diffusion, reflecting cell walls, etc.) are explained in detail. The last part of the book describes the applications of these methods to a variety of practical problems like cross-section measurements or the design of discharge lamps.

Nonlinear matrix equations arise frequently in applied science and engineering. This is the first book to provide a unified treatment of structure-preserving doubling algorithms, which have been recently studied and proven effective for notoriously challenging problems, such as fluid queue theory and vibration analysis for high-speed trains. The authors present recent developments and results for the theory of doubling algorithms for nonlinear matrix equations associated with regular matrix pencils, and highlight the use of these algorithms in achieving robust solutions for notoriously challenging problems that other methods cannot. Structure-Preserving Doubling Algorithms for Nonlinear Matrix Equations is intended for researchers and computational scientists. Graduate students may also find it of interest.

This book covers a wide spectrum of systems such as linear and nonlinear multivariable systems as well as control problems such as disturbance, uncertainty and time-delays. The purpose of this book is to provide researchers and practitioners a manual for the design and application of advanced discrete-time controllers. The book presents six different control approaches depending on the type of system and control problem. The first and second approaches are based on Sliding Mode control (SMC) theory and are intended for linear systems with exogenous disturbances. The third and fourth approaches are based on adaptive control theory and are aimed at linear/nonlinear systems with periodically varying parametric uncertainty or systems with input delay. The fifth approach is based on Iterative learning control (ILC) theory and is aimed at uncertain linear/nonlinear systems with repeatable tasks and the final approach is based on fuzzy logic control (FLC) and is intended for highly uncertain systems with heuristic control knowledge. Detailed numerical examples are provided in each chapter to illustrate the design procedure for each control method. A number of practical control applications are also presented to show the problem solving process and effectiveness with the advanced discrete-time control approaches introduced in this book.

The book discusses essential topics in industrial and applied mathematics such as image processing with a special focus on medical imaging, biometrics and tomography. Applications of mathematical concepts to areas like national security, homeland security and law enforcement, enterprise and e-government services, personal information and business transactions, and brain-like computers are also highlighted. These contributions - all prepared by respected academicians, scientists and researchers from across the globe - are based on papers presented at the international conference organized on the occasion of the Silver Jubilee of the Indian Society of Industrial and Applied Mathematics (ISIAM) held from 29 to 31 January 2016 at Sharda University, Greater Noida, India. The book will help young scientists and engineers grasp systematic developments in those areas of mathematics that are essential to properly understand challenging contemporary problems.

The contributions gathered here provide an overview of current research projects and selected software products of the Fraunhofer Institute for Algorithms and Scientific Computing SCAI. They show the wide range of challenges that scientific computing currently faces, the solutions it offers, and its important role in developing applications for industry. Given the exciting field of applied collaborative research and development it discusses, the book will appeal to scientists, practitioners, and students alike. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI combines excellent research and application-oriented development to provide added value for our partners. SCAI develops numerical techniques, parallel algorithms and specialized software tools to support and optimize industrial simulations. Moreover, it implements custom software solutions for production and logistics, and offers calculations on high-performance computers. Its services and products are based on state-of-the-art methods from applied mathematics and information technology.

This book presents cutting-edge developments in the advanced mathematical theories utilized in computer graphics research - fluid simulation, realistic image synthesis, and texture, visualization and digital fabrication. A spin-off book from the International Symposium on Mathematical Progress in Expressive Image Synthesis in 2016 and 2017 (MEIS2016/2017) held in Fukuoka, Japan, it includes lecture notes and an expert introduction to the latest research presented at the symposium. The book offers an overview of the emerging interdisciplinary themes between computer graphics and driven mathematic theories, such as discrete differential geometry. Further, it highlights open problems in those themes, making it a valuable resource not only for researchers, but also for graduate students interested in computer graphics and mathematics.

This book is a source of valuable and useful information on the topics of dynamics of number systems and scientific computation with arbitrary precision. It is addressed to scholars, scientists and engineers, and graduate students. The treatment is elementary and self-contained with relevance both for theory and applications. The basic prerequisite of the book is linear algebra and matrix calculus.

The new book series "The Science and Art of Simulation" (SAS) addresses computer simulations as a scientific activity and engineering artistry (in the sense of a techne). The first volume is devoted to three topics: 1. The Art of Exploring Computer Simulations Philosophy began devoting attention to computer simulations at a relatively early stage. Since then, the unquestioned point of view has been that computer simulation is a new scientific method; the philosophy of simulation is therefore part of the philosophy of science. The first section of this volume discusses this implicit, unchallenged assumption by addressing, from different perspectives, the question of how to explore (and how not to explore) research on computer simulations. Scientists discuss what is still lacking or considered problematic, while philosophers draft new directions for research, and both examine the art of exploring computer simulations. 2. The Art of Understanding Computer Simulations The results of computer simulations are integrated into both political and social decisions. It is implicitly assumed that the more detailed, and consequently more realistic, a computer simulation is, the more useful it will be in decision-making. However, this idea is by no means justified. Different types of computer simulations have to be differentiated, which in turn requires the specific skill of understanding computer simulation results. The articles in this section examine the capabilities and limits of simulation results in political and social contexts, exploring the art of understanding computer simulation results. 3. The Art of Knowing through Computer Simulations? The advent of computer simulation in today's scientific practices challenges the order of science. What kind of knowledge is gained through computer simulations is the key question in this section. Computer simulations are often compared to experiments or to arguments, and the transformation of our traditional scientific notions might be more challenging than expected - these Ideas are put forward in the third section to conceptualize the art of knowing through computer simulations.