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 496 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. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - 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

Download or read book Centrality Metrics for Complex Network Analysis Emerging Research and Opportunities written by Meghanathan, Natarajan and published by IGI Global. This book was released on 2018-04-05 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization. Centrality Metrics for Complex Network Analysis: Emerging Research and Opportunities is a pivotal reference source for the latest research findings on centrality metrics and their broader applications for different categories of networks including wireless sensor networks, curriculum networks, social networks etc. Featuring extensive coverage on relevant areas, such as complex network graphs, node centrality metrics, and mobile sensor networks, this publication is an ideal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.

Download or read book STACS 2005 written by Volker Diekert and published by Springer. This book was released on 2005-02-02 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd Annual Symposium on Theoretical Aspects of Computer Science, STACS 2005, held in Stuttgart, Germany in February 2005. The 54 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 217 submissions. A broad variety of topics from theoretical computer science are addressed, in particular complexity theory, algorithmics, computational discrete mathematics, automata theory, combinatorial optimization and approximation, networking and graph theory, computational geometry, grammar systems and formal languages, etc.

Download or read book Complex Networks written by Vito Latora and published by Cambridge University Press. This book was released on 2017-09-28 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to the theory and applications of complex network science, complete with real-world data sets and software tools.

Download or read book Network Analysis written by Ulrik Brandes and published by Springer. This book was released on 2005-02-02 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: ‘Network’ is a heavily overloaded term, so that ‘network analysis’ means different things to different people. Specific forms of network analysis are used in the study of diverse structures such as the Internet, interlocking directorates, transportation systems, epidemic spreading, metabolic pathways, the Web graph, electrical circuits, project plans, and so on. There is, however, a broad methodological foundation which is quickly becoming a prerequisite for researchers and practitioners working with network models. From a computer science perspective, network analysis is applied graph theory. Unlike standard graph theory books, the content of this book is organized according to methods for specific levels of analysis (element, group, network) rather than abstract concepts like paths, matchings, or spanning subgraphs. Its topics therefore range from vertex centrality to graph clustering and the evolution of scale-free networks. In 15 coherent chapters, this monograph-like tutorial book introduces and surveys the concepts and methods that drive network analysis, and is thus the first book to do so from a methodological perspective independent of specific application areas.

Download or read book Handbook of Graphs and Networks in People Analytics written by Keith McNulty and published by CRC Press. This book was released on 2022-06-19 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.

Download or read book Graph Theory and Complex Networks written by Maarten van Steen and published by Maarten Van Steen. This book was released on 2010 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to explain the basics of graph theory that are needed at an introductory level for students in computer or information sciences. To motivate students and to show that even these basic notions can be extremely useful, the book also aims to provide an introduction to the modern field of network science. Mathematics is often unnecessarily difficult for students, at times even intimidating. For this reason, explicit attention is paid in the first chapters to mathematical notations and proof techniques, emphasizing that the notations form the biggest obstacle, not the mathematical concepts themselves. This approach allows to gradually prepare students for using tools that are necessary to put graph theory to work: complex networks. In the second part of the book the student learns about random networks, small worlds, the structure of the Internet and the Web, peer-to-peer systems, and social networks. Again, everything is discussed at an elementary level, but such that in the end students indeed have the feeling that they: 1.Have learned how to read and understand the basic mathematics related to graph theory. 2.Understand how basic graph theory can be applied to optimization problems such as routing in communication networks. 3.Know a bit more about this sometimes mystical field of small worlds and random networks. There is an accompanying web site www.distributed-systems.net/gtcn from where supplementary material can be obtained, including exercises, Mathematica notebooks, data for analyzing graphs, and generators for various complex networks.

Download or read book Graphs and Networks written by S. R. Kingan and published by John Wiley & Sons. This book was released on 2022-04-28 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphs and Networks A unique blend of graph theory and network science for mathematicians and data science professionals alike. Featuring topics such as minors, connectomes, trees, distance, spectral graph theory, similarity, centrality, small-world networks, scale-free networks, graph algorithms, Eulerian circuits, Hamiltonian cycles, coloring, higher connectivity, planar graphs, flows, matchings, and coverings, Graphs and Networks contains modern applications for graph theorists and a host of useful theorems for network scientists. The book begins with applications to biology and the social and political sciences and gradually takes a more theoretical direction toward graph structure theory and combinatorial optimization. A background in linear algebra, probability, and statistics provides the proper frame of reference. Graphs and Networks also features: Applications to neuroscience, climate science, and the social and political sciences A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels A large selection of primary and secondary sources for further reading Historical notes that hint at the passion and excitement behind the discoveries Practice problems that reinforce the concepts and encourage further investigation and independent work

Download or read book Graphs and Networks written by S. R. Kingan and published by John Wiley & Sons. This book was released on 2022-05-03 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphs and Networks A unique blend of graph theory and network science for mathematicians and data science professionals alike. Featuring topics such as minors, connectomes, trees, distance, spectral graph theory, similarity, centrality, small-world networks, scale-free networks, graph algorithms, Eulerian circuits, Hamiltonian cycles, coloring, higher connectivity, planar graphs, flows, matchings, and coverings, Graphs and Networks contains modern applications for graph theorists and a host of useful theorems for network scientists. The book begins with applications to biology and the social and political sciences and gradually takes a more theoretical direction toward graph structure theory and combinatorial optimization. A background in linear algebra, probability, and statistics provides the proper frame of reference. Graphs and Networks also features: Applications to neuroscience, climate science, and the social and political sciences A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels A large selection of primary and secondary sources for further reading Historical notes that hint at the passion and excitement behind the discoveries Practice problems that reinforce the concepts and encourage further investigation and independent work

Download or read book Applying Graph Theory in Ecological Research written by Mark R.T. Dale and published by Cambridge University Press. This book was released on 2017-11-09 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book clearly describes the many applications of graph theory to ecological questions, providing instruction and encouragement to researchers.

Download or read book Algorithms and Models for Network Data and Link Analysis written by François Fouss and published by Cambridge University Press. This book was released on 2016-07-12 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network data are produced automatically by everyday interactions - social networks, power grids, and links between data sets are a few examples. Such data capture social and economic behavior in a form that can be analyzed using powerful computational tools. This book is a guide to both basic and advanced techniques and algorithms for extracting useful information from network data. The content is organized around 'tasks', grouping the algorithms needed to gather specific types of information and thus answer specific types of questions. Examples include similarity between nodes in a network, prestige or centrality of individual nodes, and dense regions or communities in a network. Algorithms are derived in detail and summarized in pseudo-code. The book is intended primarily for computer scientists, engineers, statisticians and physicists, but it is also accessible to network scientists based in the social sciences. MATLAB®/Octave code illustrating some of the algorithms will be available at: http://www.cambridge.org/9781107125773.

Download or read book Constitutional Calculus written by Jeff Suzuki and published by JHU Press. This book was released on 2015-03 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: How math trumps tradition in promoting justice, fairness, and a more stable democracy. How should we count the population of the United States? What would happen if we replaced the electoral college with a direct popular vote? What are the consequences of allowing unlimited partisan gerrymandering of congressional districts? Can six-person juries yield verdicts consistent with the needs of justice? Is it racist to stop and frisk minorities at a higher rate than non-minorities? These and other questions have long been the subject of legal and political debate and are routinely decided by lawyers, politicians, judges, and voters, mostly through an appeal to common sense and tradition. But mathematician Jeff Suzuki asserts that common sense is not so common, and traditions developed long ago in what was a mostly rural, mostly agricultural, mostly isolated nation of three million might not apply to a mostly urban, mostly industrial, mostly global nation of three hundred million. In Constitutional Calculus, Suzuki guides us through the U.S. Constitution and American history to show how mathematics reveals our flaws, finds the answers we need, and moves us closer to our ideals. From the first presidential veto to the debate over mandatory drug testing, the National Security Agency's surveillance program, and the fate of death row inmates, Suzuki draws us into real-world debates and then reveals how math offers a superior compass for decision-making. Relying on iconic cases, including the convictions of the Scottsboro boys, League of United Latin American Citizens v. Perry, and Floyd v. City of New York, Suzuki shows that more math can lead to better justice, greater fairness, and a more stable democracy. Whether you are fascinated by history, math, social justice, or government, your interest will be piqued and satisfied by the convincing case Suzuki makes.

Download or read book Centrality Measures in Transportation Networks written by Tulsi Bora and published by Mohammed Abdul Sattar. This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphs. Most people identify this phrase with a statistical graph, such as a bar, line, circle or a graph of a function. But, the analysis of graphs is referred to as graph theory in mathematics. Graphs are a central topic in discrete mathematics. Graphs, which are comprised of vertices (nodes or actors) and edges (links), are used as models in graph theory. These mathematical models represent real-world problems and circumstances. The concept of graph theory is derived from a mathematical depiction of this type of situation. In mathematics, graph theory is an exciting and dynamic field. It is used to examine real-world challenges in various fields ranging from chemistry to linguistics, geography to sociology, transportation to infrastructure networks, social science to biological networks and so on. Graphs are mathematical constructions used to represent pair wise relationships between objects. They can be found on maps, in constellations and in the design and drafting process. Graphs highlight various computer applications that enable modem communication and technological processes. They serve to strengthen logical and abstract thinking. Graph theory emerged as an academic discipline in 1736, when Leonhard Euler solved the renowned Konigsberg bridge issue. Euler solved the Konigsberg bridge problem by expressing it as a graph theory problem, with the land areas represented as vertices and the bridges as edges. Euler introduced the concept of degree by stating that if a graph has no more than two odd vertices, then there exists some path that traverses each edge once. Complex network graphs differ greatly from ordinary graphs. Network science is the study of complex networks, which can represent any distinct system, from different interaction networks to social networks. Over the last two decades, network research has contributed to the identification of universal and surprising patterns in a wide range of domains, from ecological and social systems to technical and biological systems. From the research of last two decades in various domains, it will help to create innovative multidisciplinary tools for transforming many real world problems into models so that it can easily solvable.

Download or read book Handbook of Research on Advanced Applications of Graph Theory in Modern Society written by Pal, Madhumangal and published by IGI Global. This book was released on 2019-08-30 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the world of mathematics and computer science, technological advancements are constantly being researched and applied to ongoing issues. Setbacks in social networking, engineering, and automation are themes that affect everyday life, and researchers have been looking for new techniques in which to solve these challenges. Graph theory is a widely studied topic that is now being applied to real-life problems. The Handbook of Research on Advanced Applications of Graph Theory in Modern Society is an essential reference source that discusses recent developments on graph theory, as well as its representation in social networks, artificial neural networks, and many complex networks. The book aims to study results that are useful in the fields of robotics and machine learning and will examine different engineering issues that are closely related to fuzzy graph theory. Featuring research on topics such as artificial neural systems and robotics, this book is ideally designed for mathematicians, research scholars, practitioners, professionals, engineers, and students seeking an innovative overview of graphic theory.

Download or read book Cybersecurity and Applied Mathematics written by Leigh Metcalf and published by Syngress. This book was released on 2016-06-07 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cybersecurity and Applied Mathematics explores the mathematical concepts necessary for effective cybersecurity research and practice, taking an applied approach for practitioners and students entering the field. This book covers methods of statistical exploratory data analysis and visualization as a type of model for driving decisions, also discussing key topics, such as graph theory, topological complexes, and persistent homology. Defending the Internet is a complex effort, but applying the right techniques from mathematics can make this task more manageable. This book is essential reading for creating useful and replicable methods for analyzing data. - Describes mathematical tools for solving cybersecurity problems, enabling analysts to pick the most optimal tool for the task at hand - Contains numerous cybersecurity examples and exercises using real world data - Written by mathematicians and statisticians with hands-on practitioner experience

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Download or read book OECD Patent Statistics Manual written by OECD and published by OECD Publishing. This book was released on 2009-02-05 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This manual provides guiding principles for the use of patent data in the context of S&T measurement, and recommendations for the compilation and interpretation of patent indicators in this context.