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Lecture Notes in Computational Science and Engineering

Emerging Technologies in Computational
Sciences for Industry, Sustainability a

Emerging Technologies in Computational Sciences for Industry, Sustainability and Innovation

Math to Product

Selected Papers from the ICOSAHOM Conference, Seoul, Korea, August 14 – 18, 2023

Spectral and High-Order Methods for Partial Differential Equations ICOSAHOM 2023

This book gathers outstanding papers presented at the European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2023. The conference was held in Lisbon, Portugal, in September 2023. Leading experts in the field presented the latest results and ideas regarding the design, implementation and analysis of numerical algorithms, as well as their applications to relevant societal problems.
ENUMATH is a series of conferences held every two years to provide a forum for discussing basic aspects and new trends in numerical mathematics and its scientific and industrial applications, all examined at the highest level of international expertise. The first ENUMATH was held in Paris in 1995, with successive installments at various sites across Europe, including Heidelberg (1997), Jyvaskyla (1999), lschia Porto (2001), Prague (2003), Santiago de Compostela (2005), Graz (2007), Uppsala (2009), Leicester (2011), Lausanne (2013), Ankara (2015), Bergen (2017), and Egmond aan Zee (2019).

European Conference, September 4-8, Lisbon, Portugal

Numerical Mathematics and Advanced Applications ENUMATH 2023, Volume 2

Numerical Mathematics and Advanced Applications ENUMATH 2023, Volume 1

This volume presents a selection of papers presented at the 11th International Conference on Numerical Geometry, Grid Generation, and Scientific Computing held December 12–14, 2022 in memory of Sergei Alexandrovich Ivanenko.&nbsp; The conference focuses on Voronoi-Delaunay theory and algorithms for tilings and partitions, mesh deformation and optimization, equidistribution principle, error analysis, discrete differential geometry, duality in mathematical programming and numerical geometry, mesh-based optimization and optimal control methods, iterative solvers for variational problems, as well as algorithm and software development.The book provides an overview of recent advances in mesh generation and adaptation in terms of mathematical foundations, algorithm and software development, and applications.

Proceedings of the 11th International NUMGRID Conference, 2022

Numerical Geometry, Grid Generation and Scientific Computing

The focus of these conference proceedings is on research, development, and applications in the fields of numerical geometry, scientific computing and numerical simulation, particularly in mesh generation and related problems. In addition, this year’s special focus is on Voronoi diagrams and their applications, celebrating the 150th&nbsp;birthday of G.F. Voronoi.In terms of content, the book strikes a balance between engineering algorithms and mathematical foundations.&nbsp;It presents an overview of recent advances in numerical geometry, grid generation and adaptation in terms of mathematical foundations, algorithm and software development and applications.The specific topics covered include: quasi-conformal and quasi-isometric mappings, hyperelastic deformations, multidimensional generalisations of the equidistribution principle, discrete differential geometry, spatial and metric encodings, Voronoi-Delaunay theory for tilings and partitions, duality in mathematical programming and numerical geometry, mesh-based optimisation and optimal control methods.&nbsp; Further aspects examined include iterative solvers for variational problems and algorithm and software development. The applications of the methods discussed are multidisciplinary and include problems from mathematics, physics, biology, chemistry, material science, and engineering.

Proceedings of the 9th International Conference, NUMGRID 2018 / Voronoi 150, Celebrating the 150th Anniversary of G.F. Voronoi, Moscow, Russia, December 2018

This book introduces readers to one of the first methods developed for the numerical treatment of boundary value problems on polygonal and polyhedral meshes, which it subsequently analyzes and applies in various scenarios. The BEM-based finite element approaches employs implicitly defined trial functions, which are treated locally by means of boundary integral equations. A detailed construction of high-order approximation spaces is discussed and applied to uniform, adaptive and anisotropic polytopal meshes. The main benefits of these general discretizations are the flexible handling they offer for meshes, and their natural incorporation of hanging nodes. This can especially be seen in adaptive finite element strategies and when anisotropic meshes are used. Moreover, this approach allows for problem-adapted approximation spaces as presented for convection-dominated diffusion equations. All theoretical results and considerations discussed in the book are verified and illustrated by several numerical examples and experiments. &nbsp;Given its scope, the book will be of interest to mathematicians in the field of boundary value problems, engineers with a (mathematical) background in finite element methods, and advanced graduate students. &nbsp;

BEM-based Finite Element Approaches on Polytopal Meshes

Finite element methods are the most popular methods for solving partial differential equations numerically, and despite having a history of more than 50 years, there is still active research on their analysis, application and extension. This book features overview papers and original research articles from participants of the 30th Chemnitz Finite Element Symposium, which itself has a 40-year history. Covering topics including numerical methods for equations with fractional partial derivatives;&nbsp;isogeometric analysis and other novel discretization methods, like space-time finite elements and boundary elements;&nbsp;analysis of a posteriori error estimates and adaptive methods;&nbsp;enhancement of efficient solvers of the resulting systems of equations, discretization methods for partial differential equations on surfaces;&nbsp;and methods adapted to applications in solid and fluid mechanics, it offers readers insights into the latest results.

Selected Papers from the 30th Chemnitz Finite Element Symposium 2017

Advanced Finite Element Methods with Applications

This volume collects selected papers presented at the Ninth International Workshop on Meshfree Methods held in Bonn, Germany in September 2017. They address various aspects of this very active research field and cover topics from applied mathematics, physics and engineering. The numerical treatment of partial differential equations with meshfree discretization techniques has been a very active research area in recent years. While the fundamental theory of meshfree methods has been developed and considerable advances of the various methods have been made, many challenges in the mathematical analysis and practical implementation of meshfree methods remain. This symposium aims to promote collaboration among engineers, mathematicians, and computer scientists and industrial researchers to address the development, mathematical analysis, and application of meshfree and particle methods especially to multiscale phenomena. It continues the 2-year-cycled Workshops on Meshfree Methods for Partial Differential Equations.

Meshfree Methods for Partial Differential Equations IX

This book provides state-of-the-art and interdisciplinary topics on solving matrix eigenvalue problems, particularly by using recent petascale and upcoming post-petascale supercomputers. It gathers selected topics presented at the International Workshops on Eigenvalue Problems: Algorithms; Software and Applications, in Petascale Computing (EPASA2014 and EPASA2015), which brought together leading researchers working on the numerical solution of matrix eigenvalue problems to discuss and exchange ideas – and in so doing helped to create a community for researchers in eigenvalue problems. The topics presented in the book, including novel numerical algorithms, high-performance implementation techniques, software developments and sample applications, will contribute to various fields that involve solving large-scale eigenvalue problems.

EPASA 2015, Tsukuba, Japan, September 2015

Eigenvalue Problems: Algorithms, Software and Applications in Petascale Computing

Isogeometric Analysis is a groundbreaking computational approach that promises the possibility of integrating the finite element&nbsp; method into conventional spline-based CAD design tools. It thus bridges the gap between numerical analysis and geometry, and moreover it allows to tackle new cutting edge applications at the frontiers of research in science and engineering. This proceedings volume contains a selection of outstanding research papers presented at the second International Workshop on Isogeometric Analysis and Applications, held at Annweiler, Germany, in April 2014.

Isogeometric Analysis and Applications 2014

Sparse grids are a popular tool for the numerical treatment of high-dimensional problems. Where classical numerical discretization schemes fail in more than three or four dimensions, sparse grids, in their different flavors, are frequently the method of choice.This volume of LNCSE presents selected papers from the proceedings of the fourth workshop on sparse grids and applications, and demonstrates once again the importance of this numerical discretization scheme. The articles present recent advances in the numerical analysis of sparse grids in connection with a range of applications including computational chemistry, computational fluid dynamics, and big data analytics, to name but a few.

Sparse Grids and Applications - Miami 2016

This book provides a snapshot of the state of the art of the rapidly evolving field of integration of geometric data in finite element computations.The contributions to this volume, based on research presented at the UCL workshop on the topic in January 2016, include three review papers on core topics such as fictitious domain methods for elasticity, trace finite element methods for partial differential equations defined on surfaces, and Nitsche’s method for contact problems. Five chapters present original research articles on related theoretical topics, including Lagrange multiplier methods, interface problems, bulk-surface coupling, and approximation of partial differential equations on moving domains. Finally, two chapters discuss advanced applications such as crack propagation or flow in fractured poroelastic media. This is the first volume that provides a comprehensive overview of the field of unfitted finite element methods, including recent techniques such as cutFEM, traceFEM, ghost penalty, and augmented Lagrangian techniques. It is aimed at researchers in applied mathematics, scientific computing or computational engineering.

Proceedings of the UCL Workshop 2016

Geometrically Unfitted Finite Element Methods and Applications

ICT in Asset Management

This book provides insights on how to approach and utilise data science tools, technologies/methodologies related to artificial intelligence in industrial context including their essence and inter-connections. Description of technology/methodology approaches, their purpose and benefits when developing AI-solution is given with case studies.

Theories, Applications and Case Studies

AI Factory

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

An essential guide for tackling outliers and anomalies in machine learning and data science. In recent years, machine learning (ML) has transformed virtually every area of research and technology, becoming one of the key tools for data scientists. Robust machine learning is a new approach to handling outliers in datasets, which is an often-overlooked aspect of data science. Ignoring outliers can lead to bad business decisions, wrong medical diagnoses, reaching the wrong conclusions or incorrectly assessing feature importance, just to name a few. Fundamentals of Robust Machine Learning offers a thorough but accessible overview of this subject by focusing on how to properly handle outliers and anomalies in datasets. There are two main approaches described in the book: using outlier-tolerant ML tools, or removing outliers before using conventional tools. Balancing theoretical foundations with practical Python code, it provides all the necessary skills to enhance the accuracy, stability and reliability of ML models. Fundamentals of Robust Machine Learning readers will also find: <ul><li>A blend of robust statistics and machine learning principles</li><li>Detailed discussion of a wide range of robust machine learning methodologies, from robust clustering, regression and classification, to neural networks and anomaly detection</li><li>Python code with immediate application to data science problems</li></ul> Fundamentals of Robust Machine Learning is ideal for undergraduate or graduate students in data science, machine learning, and related fields, as well as for professionals in the field looking to enhance their understanding of building models in the presence of outliers.

Handling Outliers and Anomalies in Data Science

Fundamentals of Robust Machine Learning

Lecture Notes on Data Engineering and Communications Technologies

This book presents the proceedings of the 4th International Conference on Advanced Computing and Informatics (ICACIn’24). The conference, held on December 16–17, 2024, at STEAMhouse, Birmingham City University (UK), with a parallel session at Hassan II University (Morocco), attracted submissions by researchers in 20 countries. Out of 91 submissions, 46 high-quality papers were selected, presenting the latest advancements and cutting-edge developments in computing and informatics. The book covers a wide range of advanced computing topics, including data science, big data analytics, the Internet of Things (IoT), smart computing, artificial intelligence, machine learning, cybersecurity, intelligent communication systems, health informatics, and information systems. Designed for researchers, practitioners, and graduate students, this book serves as a valuable resource for exploring advanced intelligent computing techniques and their real-world applications.

Proceedings of the 4th International Conference of Advanced Computing and Informatics (ICACIN 2024), Volume 2

Advances on Intelligent Computing and Data Science II

Medical and Technical Analysis and Signal Processing Perspectives

Exploring Infant Cry

Springer Handbooks of Computational Statistics

Handbook of Blockchain Analytics

Springer Water

This book explains the most recent methods in Geographic Information Systems (GIS) and geostatistics as they apply to groundwater through complete case studies that demonstrate actual remote sensing applications in this field.&nbsp;This book&nbsp; covers a wide range of geospatial health-related topics and methods, including climate change, healthcare utilization, health disparities, air quality assessment, asthma, water quality assessment, and machine learning. It also advances scientific understanding, development, and application of geospatial technologies related to water resource management.&nbsp;This book concentrates on the most recent studies and uses of geospatial methods in water resource management, offering insights into the difficulties and possibilities of applying these methods to solve practical issues.&nbsp;&nbsp;Objectives:&nbsp;This book brings together academics, practitioners, and decision-makers from many fields to discuss and present the most recent advancements in the field of geospatial applications/ approaches/ tools for water resource management. The goal of the book is to give a thorough review of the most recent methods and uses of geospatial technology in the management of water resources, including resource estimation, quality assessment, and quality control. The book discusses the advantages and drawbacks of using geospatial approaches to manage water resources, points out knowledge gaps, and suggests future research avenues.&nbsp;Scope and Structure:&nbsp;The book consists of chapters contributed by leading experts in the field of geospatial water resource management.

A Geospatial Approach: Volume 1

Groundwater Resource Management Planning Strategies

Modeling and Simulation in Science, Engineering and Technology

A Chronological Catalog of Unconventional Methods and First-of-Its-Kind Solutions

Space–Time Computational Flow Analysis

Communications in Computer and Information Science

9th International Conference, CVIP 2024, Chennai, India, December 19–21, 2024, Revised Selected Papers, Part I

Computer Vision and Image Processing

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

Lecture Notes in Computer Science

16th TPC Technology Conference, TPCTC 2024, Guangzhou, China, August 30, 2024, Revised Selected Papers

Performance Evaluation and Benchmarking

9th International Conference, CVIP 2024, Chennai, India, December 19–21, 2024, Revised Selected Papers, Part III

Emerging Technologies in Computational Sciences for Industry, ...

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