Recent Advances in Numerical Methods features contributions from distinguished researchers, focused on significant aspects of current numerical methods and computational mathematics. The increasing necessity to present new computational methods that can solve complex scientific and engineering problems requires the preparation of this volume with actual new results and innovative methods that provide numerical solutions in effective computing times. Each chapter will present new and advanced methods and modern variations on known techniques that can solve difficult scientific problems efficiently.

In the theory of splines, a function is approximated piece-wise by (usually cubic) polynomials. Quasi-splines is the natural extension of this, allowing us to use any useful class of functions adapted to the problem.
Approximation with Quasi-Splines is a detailed account of this highly useful technique in numerical analysis.
The book presents the requisite approximation theorems and optimization methods, developing a unified theory of one and several variables. The author applies his techniques to the evaluation of definite integrals (quadrature) and its many-variables generalization, which he calls "cubature."
This book should be required reading for all practitioners of the methods of approximation, including researchers, teachers, and students in applied, numerical and computational mathematics.

This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale network optimization problems.

This book includes selected contributions on applied mathematics, numerical analysis, numerical simulation and scientific computing related to fluid mechanics problems, presented at the FEF-"Finite Element for Flows" conference, held in Rome in spring 2017. Written by leading international experts and covering state-of-the-art topics in numerical simulation for flows, it provides fascinating insights into and perspectives on current and future methodological and numerical developments in computational science. As such, the book is a valuable resource for researchers, as well as Masters and Ph.D students.

This book presents the bending theory of hyperelastic beams in the context of finite elasticity. The main difficulties in addressing this issue are due to its fully nonlinear framework, which makes no assumptions regarding the size of the deformation and displacement fields. Despite the complexity of its mathematical formulation, the inflexion problem of nonlinear beams is frequently used in practice, and has numerous applications in the industrial, mechanical and civil sectors. Adopting a semi-inverse approach, the book formulates a three-dimensional kinematic model in which the longitudinal bending is accompanied by the transversal deformation of cross-sections. The results provided by the theoretical model are subsequently compared with those of numerical and experimental analyses. The numerical analysis is based on the finite element method (FEM), whereas a test equipment prototype was designed and fabricated for the experimental analysis. The experimental data was acquired using digital image correlation (DIC) instrumentation. These two further analyses serve to confirm the hypotheses underlying the theoretical model. In the book's closing section, the analysis is generalized to the case of variable bending moment. The governing equations then take the form of a coupled system of three equations in integral form, which can be applied to a very wide class of equilibrium problems for nonlinear beams.

Finite volume methods are used for various applications in fluid dynamics, magnetohydrodynamics, structural analysis or nuclear physics. A closer look reveals many interesting phenomena and mathematical or numerical difficulties, such as true error analysis and adaptivity, modelling of multi-phase phenomena or fitting problems, stiff terms in convection/diffusion equations and sources. To overcome existing problems and to find solution methods for future applications requires many efforts and always new developments. The goal of The International Symposium on Finite Volumes for Complex Applications VI is to bring together mathematicians, physicists and engineers dealing with Finite Volume Techniques in a wide context. This book, divided in two volumes, brings a critical look at the subject (new ideas, limits or drawbacks of methods, theoretical as well as applied topics).

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

Covid-19 has shown us the importance of mathematical and statistical models to interpret reality, provide forecasts, and explore future scenarios. Algorithms, artificial neural networks, and machine learning help us discover the opportunities and pitfalls of a world governed by mathematics and artificial intelligence.

Advances in Discrete Tomography and its Applications is a unified presentation of new methods, algorithms, and select applications that are the foundations of multidimensional image construction and reconstruction. The self-contained survey chapters, written by leading mathematicians, engineers, and computer scientists, present cutting-edge research and results in the field. Three main areas are covered: theoretical results, algorithms, and practical applications. Following an historical and introductory overview of the field, the book explores various mathematical and computational problems of discrete tomography with an emphasis on new applications. Topics and features include: historical overview and summary chapter; uniqueness and complexity in discrete tomography; 3-D tomographic reconstruction from radiographic data; symbolic projections; and, applications to neutron tomography. Professionals, researchers, practitioners, and students in mathematics, computer imaging, biomedical imaging, computer engineering, and image processing will find the book to be a useful guide and reference to state-of-the-art research, methods, and applications.

Visualisation and Processing of Tensor Fields provides researchers an inspirational look at how to process and visualize complicated 2D and 3D images known as tensor fields. Tensor fields are the natural representation for many physical quantities; they can describe how water moves around in the brain, how gravity varies around the earth, or how materials are stressed and deformed. With its numerous color figures, this book helps the reader understand both the underlying mathematics and the applications of tensor fields. The reader also will learn about the most recent research topics and open research questions.

In this book we gather recent mathematical developments and engineering applications of Trefftz methods, with particular emphasis on the Method of Fundamental Solutions (MFS). These are true meshless methods that have the advantage of avoiding the need to set up a mesh altogether, and therefore going beyond the reduction of the mesh to a boundary. These Trefftz methods have advantages in several engineering applications, for instance in inverse problems where the domain is unknown and some numerical methods would require a remeshing approach. Trefftz methods are also known to perform very well with regular domains and regular data in boundary value problems, achieving exponential convergence. On the other hand, they may also under certain conditions, exhibit instabilities and lead to ill-conditioned systems. This book is divided into ten chapters that illustrate recent advances in Trefftz methods and their application to engineering problems. The first eight chapters are devoted to the MFS and variants whereas the last two chapters are devoted to related meshless engineering applications. Part of these selected contributions were presented in the 9th International Conference on Trefftz Methods and 5th International Conference on the MFS, held in 2019, July 29-31, in Lisbon, Portugal.

This book introduces an interesting and alternative way to design absorbing boundary conditions (ABCs) for quantum wave equations, basically the nonlinear Schroedinger equation. The focus of this book is the application of the phase space filter approach to derive accurate radiation conditions for Schroedinger equations. Researchers who are interested in partial differential equations and mathematical physics might find this book appealing.

This book presents a detailed description of a robust pseudomultigrid algorithm for solving (initial-)boundary value problems on structured grids in a black-box manner. To overcome the problem of robustness, the presented Robust Multigrid Technique (RMT) is based on the application of the essential multigrid principle in a single grid algorithm. It results in an extremely simple, very robust and highly parallel solver with close-to-optimal algorithmic complexity and the least number of problem-dependent components. Topics covered include an introduction to the mathematical principles of multigrid methods, a detailed description of RMT, results of convergence analysis and complexity, possible expansion on unstructured grids, numerical experiments and a brief description of multigrid software, parallel RMT and estimations of speed-up and efficiency of the parallel multigrid algorithms, and finally applications of RMT for the numerical solution of the incompressible Navier Stokes equations. Potential readers are graduate students and researchers working in applied and numerical mathematics as well as multigrid practitioners and software programmers. Contents Introduction to multigrid Robust multigrid technique Parallel multigrid methods Applications of multigrid methods in computational fluid dynamics

Special numerical techniques are already needed to deal with nxn matrices for large n.Tensor data are of size nxnx...xn=n DEGREESd, where n DEGREESd exceeds the computer memory by far. They appear for problems of high spatial dimensions. Since standard methods fail, a particular tensor calculus is needed to treat such problems. The monograph describes the methods how tensors can be practically treated and how numerical operations can be performed. Applications are problems from quantum chemistry, approximation of multivariate functions, solution of pde, e.g., with stochastic coefficie

This proceedings volume convenes selected, peer-reviewed papers presented at the 3rd International Conference on Mathematics and its Applications in Science and Engineering - ICMASE 2022, which was held on July 4-7, 2022 by the Technical University of Civil Engineering of Bucharest, Romania. Works in this volume cover new developments in applications of mathematics in science and engineering, with emphasis on mathematical and computational modeling of real-world problems. Topics range from the use of differential equations to model mechanical structures to the employ of number theory in the development of information security and cryptography. Educational issues specific to the acquisition of mathematical competencies by engineering and science students at all university levels are also touched on. Researchers and university students are the natural audiences for this book, which can be equally appealing to practitioners seeking up-to-date techniques in mathematical applications to different contexts and disciplines.

The genesis of this book goes back to the conference held at the University of Bologna, June 1999, on collaborative work between the University of California at Berkeley and the University of Bologna. The book, in its present form, is a compilation of some of the recent work using geometric partial differential equations and the level set methodology in medical and biomedical image analysis.The book not only gives a good overview on some of the traditional applications in medical imagery such as, CT, MR, Ultrasound, but also shows some new and exciting applications in the area of Life Sciences, such as confocal microscope image understanding.

This thesis make significant contributions to both the numerical and analytical aspects of particle physics, reducing the noise associated with matrix calculations in quantum chromodynamics (QCD) and modeling multi-quark mesonic matters that could be used to investigate particles previously unseen in nature. Several methods are developed that can reduce the statistical uncertainty in the extraction of hard-to-detect lattice QCD signals from disconnected diagrams. The most promising technique beats competing methods by 1700 percent, leading to a potential decrease in the computation time of quark loop quantities by an order of magnitude. This not only increases efficiency but also works for QCD matrices with almost-zero eigenvalues, a region where most QCD algorithms break down. This thesis also develops analytical solutions used to investigate exotic particles, specifically the Thomas-Fermi quark model, giving insight into possible new states formed from mesonic matter. The main benefit of this model is that it can work for a large number of quarks which is currently almost impossible with lattice QCD. Patterns of single-quark energies are observed which give the first a priori indication that stable octa-quark and hexadeca-quark versions of the charmed and bottom Z-meson exist.

This book systematically analyses the latest insights into night vision imaging processing and perceptual understanding as well as related theories and methods. The algorithm model and hardware system provided can be used as the reference basis for the general design, algorithm design and hardware design of photoelectric systems. Focusing on the differences in the imaging environment, target characteristics, and imaging methods, this book discusses multi-spectral and video data, and investigates a variety of information mining and perceptual understanding algorithms. It also assesses different processing methods for multiple types of scenes and targets.Taking into account the needs of scientists and technicians engaged in night vision optoelectronic imaging detection research, the book incorporates the latest international technical methods. The content fully reflects the technical significance and dynamics of the new field of night vision. The eight chapters cover topics including multispectral imaging, Hadamard transform spectrometry; dimensionality reduction, data mining, data analysis, feature classification, feature learning; computer vision, image understanding, target recognition, object detection and colorization algorithms, which reflect the main areas of research in artificial intelligence in night vision. The book enables readers to grasp the novelty and practicality of the field and to develop their ability to connect theory with real-world applications. It also provides the necessary foundation to allow them to conduct research in the field and adapt to new technological developments in the future.

This volume contains the extended version of selected talks given at the international research workshop "Coping with Complexity: Model Reduction and Data Analysis," Ambleside, UK, August 31 - September 4, 2009. The book is deliberately broad in scope and aims at promoting new ideas and methodological perspectives. The topics of the chapters range from theoretical analysis of complex and multiscale mathematical models to applications in e.g., fluid dynamics and chemical kinetics.

Fractal structures or geometries currently play a key role in all models for natural and industrial processes that exhibit the formation of rough surfaces and interfaces. Computer simulations, analytical theories and experiments have led to significant advances in modeling these phenomena across wild media. Many problems coming from engineering, physics or biology are characterized by both the presence of different temporal and spatial scales and the presence of contacts among different components through (irregular) interfaces that often connect media with different characteristics. This work is devoted to collecting new results on fractal applications in engineering from both theoretical and numerical perspectives. The book is addressed to researchers in the field.

One of the most elementary questions in mathematics is whether an area minimizing surface spanning a contour in three space is immersed or not; i.e. does its derivative have maximal rank everywhere. The purpose of this monograph is to present an elementary proof of this very fundamental and beautiful mathematical result. The exposition follows the original line of attack initiated by Jesse Douglas in his Fields medal work in 1931, namely use Dirichlet's energy as opposed to area. Remarkably, the author shows how to calculate arbitrarily high orders of derivatives of Dirichlet's energy defined on the infinite dimensional manifold of all surfaces spanning a contour, breaking new ground in the Calculus of Variations, where normally only the second derivative or variation is calculated. The monograph begins with easy examples leading to a proof in a large number of cases that can be presented in a graduate course in either manifolds or complex analysis. Thus this monograph requires only the most basic knowledge of analysis, complex analysis and topology and can therefore be read by almost anyone with a basic graduate education.

Perturbation methods are widely used in the study of physically significant differential equations, which arise in Applied Mathematics, Physics and Engineering.; Background material is provided in each chapter along with illustrative examples, problems, and solutions.; A comprehensive bibliography and index complete the work.; Covers an important field of solutions for engineering and the physical sciences.; To allow an interdisciplinary readership, the book focuses almost exclusively on the procedures and the underlying ideas and soft pedal the proofs; Dr. Bhimsen K. Shivamoggi has authored seven successful books for various publishers like John Wiley & Sons and Kluwer Academic Publishers.

Techniques of optimization are applied in many problems in economics, automatic control, engineering, etc. and a wealth of literature is devoted to this subject. The first computer applications involved linear programming problems with simp- le structure and comparatively uncomplicated nonlinear pro- blems: These could be solved readily with the computational power of existing machines, more than 20 years ago. Problems of increasing size and nonlinear complexity made it necessa- ry to develop a complete new arsenal of methods for obtai- ning numerical results in a reasonable time. The lineariza- tion method is one of the fruits of this research of the last 20 years. It is closely related to Newton's method for solving systems of linear equations, to penalty function me- thods and to methods of nondifferentiable optimization. It requires the efficient solution of quadratic programming problems and this leads to a connection with conjugate gra- dient methods and variable metrics. This book, written by one of the leading specialists of optimization theory, sets out to provide - for a wide readership including engineers, economists and optimization specialists, from graduate student level on - a brief yet quite complete exposition of this most effective method of solution of optimization problems.

The book presents high quality research papers presented at International Conference on Computational Intelligence (ICCI 2020) held at Indian Institute of Information Technology, Pune, India during 12-13 December, 2020. The topics covered are artificial intelligence, neural network, deep learning techniques, fuzzy theory and systems, rough sets, self-organizing maps, machine learning, chaotic systems, multi-agent systems, computational optimization ensemble classifiers, reinforcement learning, decision trees, support vector machines, hybrid learning, statistical learning. metaheuristics algorithms: evolutionary and swarm-based algorithms like genetic algorithms, genetic programming, differential evolution, particle swarm optimization, whale optimization, spider monkey optimization, firefly algorithm, memetic algorithms. And also machine vision, Internet of Things, image processing, image segmentation, data clustering, sentiment analysis, big data, computer networks, signal processing, supply chain management, web and text mining, distributed systems, bioinformatics, embedded systems, expert system, forecasting, pattern recognition, planning and scheduling, time series analysis, human-computer interaction, web mining, natural language processing, multimedia systems, and quantum computing.

This volume contains the articles presented at the 20th International Meshing Roundtable (IMR) organized, in part, by Sandia National Laboratories and was held in Paris, France on Oct 23-26, 2011. This is the first year the IMR was held outside the United States territory. Other sponsors of the 20th IMR are Systematic Paris Region Systems & ICT Cluster, AIAA, NAFEMS, CEA, and NSF. The Sandia National Laboratories started the first IMR in 1992, and the conference has been held annually since. Each year the IMR brings together researchers, developers, and application experts, from a variety of disciplines, to present and discuss ideas on mesh generation and related topics. The topics covered by the IMR have applications in numerical analysis, computational geometry, computer graphics, as well as other areas, and the presentations describe novel work ranging from theory to application.