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Book Multivariate Network Visualization

Download or read book Multivariate Network Visualization written by Andreas Kerren and published by Springer. This book was released on 2014-04-15 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the outcome of the Dagstuhl Seminar 13201 on Information Visualization - Towards Multivariate Network Visualization, held in Dagstuhl Castle, Germany in May 2013. The goal of this Dagstuhl Seminar was to bring together theoreticians and practitioners from Information Visualization, HCI and Graph Drawing with a special focus on multivariate network visualization, i.e., on graphs where the nodes and/or edges have additional (multidimensional) attributes. The integration of multivariate data into complex networks and their visual analysis is one of the big challenges not only in visualization, but also in many application areas. Thus, in order to support discussions related to the visualization of real world data, also invited researchers from selected application areas, especially bioinformatics, social sciences and software engineering. The unique "Dagstuhl climate" ensured an open and undisturbed atmosphere to discuss the state-of-the-art, new directions and open challenges of multivariate network visualization.

Book Network Analysis and Visualization in R

Download or read book Network Analysis and Visualization in R written by Alboukadel Kassambara and published by STHDA. This book was released on 2017-11-26 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social network analysis is used to investigate the inter-relationship between entities. Examples of network structures, include: social media networks, friendship networks and collaboration networks. This book provides a quick start guide to network analysis and visualization in R. You'll learn, how to: - Create static and interactive network graphs using modern R packages. - Change the layout of network graphs. - Detect important or central entities in a network graph. - Detect community (or cluster) in a network.

Book Visual Analysis of Multilayer Networks

Download or read book Visual Analysis of Multilayer Networks written by Fintan McGee and published by Morgan & Claypool Publishers. This book was released on 2021-06-10 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an overview and structured analysis of contemporary multilayer network visualization. It surveys techniques as well as tools, tasks, and analytics from within application domains. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them. Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains. The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization.

Book Fundamentals of Brain Network Analysis

Download or read book Fundamentals of Brain Network Analysis written by Alex Fornito and published by Academic Press. This book was released on 2016-03-04 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain

Book Multivariate Time Series Analysis in Climate and Environmental Research

Download or read book Multivariate Time Series Analysis in Climate and Environmental Research written by Zhihua Zhang and published by Springer. This book was released on 2017-11-09 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.

Book Graph Drawing Software

    Book Details:
  • Author : Michael Jünger
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 3642186386
  • Pages : 381 pages

Download or read book Graph Drawing Software written by Michael Jünger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: After an introduction to the subject area and a concise treatment of the technical foundations for the subsequent chapters, this book features 14 chapters on state-of-the-art graph drawing software systems, ranging from general "tool boxes'' to customized software for various applications. These chapters are written by leading experts: they follow a uniform scheme and can be read independently from each other. The text covers many industrial applications.

Book Statistical Analysis of Network Data with R

Download or read book Statistical Analysis of Network Data with R written by Eric D. Kolaczyk and published by Springer. This book was released on 2014-05-22 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

Book Lattice

    Book Details:
  • Author : Deepayan Sarkar
  • Publisher : Springer Science & Business Media
  • Release : 2008-02-15
  • ISBN : 0387759697
  • Pages : 283 pages

Download or read book Lattice written by Deepayan Sarkar and published by Springer Science & Business Media. This book was released on 2008-02-15 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by the author of the lattice system, this book describes lattice in considerable depth, beginning with the essentials and systematically delving into specific low levels details as necessary. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed. The book contains close to 150 figures produced with lattice. Many of the examples emphasize principles of good graphical design; almost all use real data sets that are publicly available in various R packages. All code and figures in the book are also available online, along with supplementary material covering more advanced topics.

Book The Oxford Handbook of Archaeological Network Research

Download or read book The Oxford Handbook of Archaeological Network Research written by Tom Brughmans and published by Oxford University Press. This book was released on 2023-11-23 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network research has recently been adopted as one of the tools of the trade in archaeology, used to study a wide range of topics: interactions between island communities, movements through urban spaces, visibility in past landscapes, material culture similarity, exchange, and much more. This Handbook is the first authoritative reference work for archaeological network research, featuring current topical trends and covering the archaeological application of network methods and theories. This is elaborately demonstrated through substantive topics and case studies drawn from a breadth of periods and cultures in world archaeology. It highlights and further develops the unique contributions made by archaeological research to network science, especially concerning the development of spatial and material culture network methods and approaches to studying long-term network change. This is the go-to resource for students and scholars wishing to explore how network science can be applied in archaeology through an up-to-date overview of the field.

Book Big Data of Complex Networks

Download or read book Big Data of Complex Networks written by Matthias Dehmer and published by CRC Press. This book was released on 2016-08-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.

Book Methods of Multivariate Analysis

Download or read book Methods of Multivariate Analysis written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2003-04-14 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Methods of Multivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit, it is often necessary to analyze the variables simultaneously, rather than isolate them and consider them individually. Multivariate analysis enables researchers to explore the joint performance of such variables and to determine the effect of each variable in the presence of the others. The Second Edition of Alvin Rencher's Methods of Multivariate Analysis provides students of all statistical backgrounds with both the fundamental and more sophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author provides examples and exercises based on fifty-nine real data sets from a wide variety of scientific fields. Rencher takes a "methods" approach to his subject, with an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. The Second Edition contains revised and updated chapters from the critically acclaimed First Edition as well as brand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers and hints in the appendix, providing students the opportunity to test and extend their understanding of the subject. Methods of Multivariate Analysis provides an authoritative reference for statistics students as well as for practicing scientists and clinicians.

Book Doing Meta Analysis with R

Download or read book Doing Meta Analysis with R written by Mathias Harrer and published by CRC Press. This book was released on 2021-09-15 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

Book Egocentric Network Analysis

Download or read book Egocentric Network Analysis written by Brea L. Perry and published by Structural Analysis in the Soc. This book was released on 2018-03-22 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth, comprehensive and practical guide to egocentric network analysis, focusing on fundamental theoretical, research design, and analytic issues.

Book An Introduction to Applied Multivariate Analysis with R

Download or read book An Introduction to Applied Multivariate Analysis with R written by Brian Everitt and published by Springer Science & Business Media. This book was released on 2011-04-23 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

Book Proceedings of the Symposium on Applied Computing

Download or read book Proceedings of the Symposium on Applied Computing written by Sung Y. Shin and published by . This book was released on 2017-04-03 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: SAC 2017: Symposium on Applied Computing Apr 03, 2017-Apr 07, 2017 Marrakech, Morocco. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Book Future of Airplane Factory

Download or read book Future of Airplane Factory written by George Nicholas Bullen and published by SAE International. This book was released on 2019-05-28 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Future of Airplane Factory: Digitally Optimized Intelligent Airplane Factory defines the architecture, key building blocks, and roadmap for actualizing a future airplane factory (FAF) that is digitally optimized for intelligent airplane assembly. They fit and integrate with other FAF building blocks that aggregate to a Digitally Optimized Intelligent Airplane Factory (DOIAF). The word "intelligent" refers to the ability of a system to make right decisions and take right action in the highly dynamic and fluid environment of the modern airplane manufacturing space. The event-driven dynamics inherent in the complexity of this environment drive the need for expert knowledge which resides in intelligence systems incorporating the experience of experts. Expert knowledge need not be smart, brilliant, or possess genius as long as the outcomes are derived from right decisions resulting in right actions-applied rapidly to sustain an optimized factory enterprise. Complete factory enterprise visibility requires a higher order of decision capability that current operating systems do not have. A highly visible factory collects and displays data and information as it happens-at a rate beyond the ability of humans and current systems to analyze, process, decide, and act upon. Expert systems are constructed to present humans with right decisions in the form of optimal choices for right actions by incorporating the knowledge of experts into the logic for the decision. Structured Knowledge-Based Expert Systems (SKBES) are incorporated in this book and defined as a critical component for full enterprise actionable visibility. The power of the Digitally Optimized Intelligent Airplane Factory not only is found in its ability to unify the factory, reduce touch labor, improve quality, and streamline throughput but it also enables a significant reduction in above-the-shop-floor support and management. Such an ecosystem frees the human to focus on the complexity of interpersonal responsibilities. If the use of a DOIAF can be viewed as a holistic mechanism, then the human can be the agent engaging with that mechanism; improving negotiations for pricing, contracts, or other person-to-person events that require instinct and relationship.

Book Visualization Analysis and Design

Download or read book Visualization Analysis and Design written by Tamara Munzner and published by CRC Press. This book was released on 2014-12-01 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques