Functional And Shape Data Analysis

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Functional And Shape Data Analysis

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Author : Anuj Srivastava
language : en
Publisher: Springer
Release Date : 2016-10-03

Functional And Shape Data Analysis written by Anuj Srivastava and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-03 with Mathematics categories.

This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered—from introductory theory to algorithmic implementations and some statistical case studies—is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges. Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves—in one, two, and higher dimensions—both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.

Applied Functional Data Analysis

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Author : J.O. Ramsay
language : en
Publisher: Springer
Release Date : 2007-11-23

Applied Functional Data Analysis written by J.O. Ramsay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-23 with Mathematics categories.

This book contains the ideas of functional data analysis by a number of case studies. The case studies are accessible to research workers in a wide range of disciplines. Every reader should gain not only a specific understanding of the methods of functional data analysis, but more importantly a general insight into the underlying patterns of thought. There is an associated web site with MATLABr and S?PLUSr implementations of the methods discussed.

Mathematics Of Shapes And Applications

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Author : Sergey Kushnarev
language : en
Publisher: World Scientific
Release Date : 2019-11-20

Mathematics Of Shapes And Applications written by Sergey Kushnarev and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Mathematics categories.

Understanding how a single shape can incur a complex range of transformations, while defining the same perceptually obvious figure, entails a rich and challenging collection of problems, at the interface between applied mathematics, statistics and computer science. The program on Mathematics of Shapes and Applications, was held at the Institute for Mathematical Sciences at the National University of Singapore in 2016. It provided discussions on theoretical developments and numerous applications in computer vision, object recognition and medical imaging.The analysis of shapes is an example of a mathematical problem directly connected with applications while offering deep open challenges to theoretical mathematicians. It has grown, over the past decades, into an interdisciplinary area in which researchers studying infinite-dimensional Riemannian manifolds (global analysis) interact with applied mathematicians, statisticians, computer scientists and biomedical engineers on a variety of problems involving shapes.The volume illustrates this wealth of subjects by providing new contributions on the metric structure of diffeomorphism groups and shape spaces, recent developments on deterministic and stochastic models of shape evolution, new computational methods manipulating shapes, and new statistical tools to analyze shape datasets. In addition to these contributions, applications of shape analysis to medical imaging and computational anatomy are discussed, leading, in particular, to improved understanding of the impact of cognitive diseases on the geometry of the brain.

Big Data Analytics

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Author : Saumyadipta Pyne
language : en
Publisher: Springer
Release Date : 2016-10-12

Big Data Analytics written by Saumyadipta Pyne and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-12 with Computers categories.

This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

Advanced Business Analytics

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Author : Fausto Pedro García Márquez
language : en
Publisher: Springer
Release Date : 2015-01-24

Advanced Business Analytics written by Fausto Pedro García Márquez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-24 with Business & Economics categories.

The book describes advanced business analytics and shows how to apply them to many different professional areas of engineering and management. Each chapter of the book is contributed by a different author and covers a different area of business analytics. The book connects the analytic principles with business practice and provides an interface between the main disciplines of engineering/technology and the organizational, administrative and planning abilities of management. It also refers to other disciplines such as economy, finance, marketing, behavioral economics and risk analysis. This book is of special interest to engineers, economists and researchers who are developing new advances in engineering management but also to practitioners working on this subject.

Advances In Systems Computing Sciences And Software Engineering

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Author : Tarek Sobh
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-27

Advances In Systems Computing Sciences And Software Engineering written by Tarek Sobh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-27 with Technology & Engineering categories.

Advances in Systems, Computing Sciences and Software Engineering This book includes the proceedings of the International Conference on Systems, Computing Sciences and Software Engineering (SCSS’05). The proceedings are a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of computer science, software engineering, computer engineering, systems sciences and engineering, information technology, parallel and distributed computing and web-based programming. SCSS’05 was part of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE’05) (www. cisse2005. org), the World’s first Engineering/Computing and Systems Research E-Conference. CISSE’05 was the first high-caliber Research Conference in the world to be completely conducted online in real-time via the internet. CISSE’05 received 255 research paper submissions and the final program included 140 accepted papers, from more than 45 countries. The concept and format of CISSE’05 were very exciting and ground-breaking. The PowerPoint presentations, final paper manuscripts and time schedule for live presentations over the web had been available for 3 weeks prior to the start of the conference for all registrants, so they could choose the presentations they want to attend and think about questions that they might want to ask. The live audio presentations were also recorded and were part of the permanent CISSE archive, which also included all power point presentations and papers. SCSS’05 provided a virtual forum for presentation and discussion of the state-of the-art research on Systems, Computing Sciences and Software Engineering.

Graphs In Biomedical Image Analysis Computational Anatomy And Imaging Genetics

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Author : M. Jorge Cardoso
language : en
Publisher: Springer
Release Date : 2017-09-06

Graphs In Biomedical Image Analysis Computational Anatomy And Imaging Genetics written by M. Jorge Cardoso and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-06 with Computers categories.

This book constitutes the refereed joint proceedings of the First International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, the 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017, and the Third International Workshop on Imaging Genetics, MICGen 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 7 full papers presented at GRAIL 2017, the 10 full papers presented at MFCA 2017, and the 5 full papers presented at MICGen 2017 were carefully reviewed and selected. The GRAIL papers cover a wide range of graph based medical image analysis methods and applications, including probabilistic graphical models, neuroimaging using graph representations, machine learning for diagnosis prediction, and shape modeling. The MFCA papers deal with theoretical developments in non-linear image and surface registration in the context of computational anatomy. The MICGen papers cover topics in the field of medical genetics, computational biology and medical imaging.

Handbook Of Variational Methods For Nonlinear Geometric Data

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Author : Philipp Grohs
language : en
Publisher: Springer Nature
Release Date : 2020-04-03

Handbook Of Variational Methods For Nonlinear Geometric Data written by Philipp Grohs and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-03 with Mathematics categories.

This book covers different, current research directions in the context of variational methods for non-linear geometric data. Each chapter is authored by leading experts in the respective discipline and provides an introduction, an overview and a description of the current state of the art. Non-linear geometric data arises in various applications in science and engineering. Examples of nonlinear data spaces are diverse and include, for instance, nonlinear spaces of matrices, spaces of curves, shapes as well as manifolds of probability measures. Applications can be found in biology, medicine, product engineering, geography and computer vision for instance. Variational methods on the other hand have evolved to being amongst the most powerful tools for applied mathematics. They involve techniques from various branches of mathematics such as statistics, modeling, optimization, numerical mathematics and analysis. The vast majority of research on variational methods, however, is focused on data in linear spaces. Variational methods for non-linear data is currently an emerging research topic. As a result, and since such methods involve various branches of mathematics, there is a plethora of different, recent approaches dealing with different aspects of variational methods for nonlinear geometric data. Research results are rather scattered and appear in journals of different mathematical communities. The main purpose of the book is to account for that by providing, for the first time, a comprehensive collection of different research directions and existing approaches in this context. It is organized in a way that leading researchers from the different fields provide an introductory overview of recent research directions in their respective discipline. As such, the book is a unique reference work for both newcomers in the field of variational methods for non-linear geometric data, as well as for established experts that aim at to exploit new research directions or collaborations. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com.

Data Analysis In Bi Partial Perspective Clustering And Beyond

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Author : Jan W. Owsiński
language : en
Publisher: Springer
Release Date : 2019-03-23

Data Analysis In Bi Partial Perspective Clustering And Beyond written by Jan W. Owsiński and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-23 with Computers categories.

This book presents the bi-partial approach to data analysis, which is both uniquely general and enables the development of techniques for many data analysis problems, including related models and algorithms. It is based on adequate representation of the essential clustering problem: to group together the similar, and to separate the dissimilar. This leads to a general objective function and subsequently to a broad class of concrete implementations. Using this basis, a suboptimising procedure can be developed, together with a variety of implementations. This procedure has a striking affinity with the classical hierarchical merger algorithms, while also incorporating the stopping rule, based on the objective function. The approach resolves the cluster number issue, as the solutions obtained include both the content and the number of clusters. Further, it is demonstrated how the bi-partial principle can be effectively applied to a wide variety of problems in data analysis. The book offers a valuable resource for all data scientists who wish to broaden their perspective on basic approaches and essential problems, and to thus find answers to questions that are often overlooked or have yet to be solved convincingly. It is also intended for graduate students in the computer and data sciences, and will complement their knowledge and skills with fresh insights on problems that are otherwise treated in the standard “academic” manner.

Harnessing Data Science For Sustainable Agriculture And Natural Resource Management

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Author : Mehul S. Raval
language : en
Publisher: Springer Nature
Release Date : 2024-12-19

Harnessing Data Science For Sustainable Agriculture And Natural Resource Management written by Mehul S. Raval and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-19 with Computers categories.

This book is a comprehensive resource that handles the issues of sustainable agriculture and natural resource management, aligned with the United Nations' Sustainable Development Goals (SDGs). The book is organized into five sections, Understanding the Problem, Data Collection and Cleaning, Exploratory Data Analysis and Visualization, Model Building, and Model Deployment. Each section covers a critical aspect of data science in this context and addresses specific SDGs 2—zero hunger, 6—clean water and sanitation, 12—responsible consumption and production, 13—climate action, and 15—Life on land. The organized sections are arranged to seamlessly follow the data science pipeline and provide practical guidance from problem understanding to its model deployment and stakeholder management. The book is useful for researchers, students, practitioners, and policymakers.