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Network science offers a powerful language to represent and study complex systems composed of interacting elements — from the Internet to social and biological systems. A Guide to Temporal Networks presents recent theoretical and modelling progress in the emerging field of temporally varying networks and provides connections between the different areas of knowledge required to address this multi-disciplinary subject. After an introduction to key concepts on networks and stochastic dynamics, the authors guide the reader through a coherent selection of mathematical and computational tools for network dynamics. Perfect for students and professionals, this book is a gateway to an active field of research developing between the disciplines of applied mathematics, physics and computer science, with applications in others including social sciences, neuroscience and biology.This second edition extensively expands upon the coverage of the first edition as the authors expertly present recent theoretical and modelling progress in the emerging field of temporal networks, providing the keys to (and connections between) the different areas of knowledge required to address this multi-disciplinary problem.
Business sustainability and sustainable development are of great importance in modern-day socio-economic study. Despite this, the impact of recent contributions from systems and complexity sciences in addressing these issues has not yet filtered down into effective practice. This book argues that there is a need for urgency in the application of analytical tools which embody the principles of complexity management in sustainability research, in particular in the context of the global climate change. The approach presented is based on the concept of clusters of whole systems coming together through collaboration, in order to create larger wholes capable of dealing with the issues facing our socio-economic environmental systems.In this updated second edition, the authors further clarify the viability and sustainability (V&S) approach, and the criteria and framework needed for sustainable governance. It includes a more detailed perspective on the implications of the V&S approach to businesses and networks towards changes in structure, strategy and processes, inspired by specific case studies. Key additions include a criteria for designing more viable and sustainable self-governed organizations, the methodologies and tools to design and implement self-transformations towards sustainability, and how these tools support sustainability management individually and globally, for businesses and society.
This Element provides a tutorial on the Gillespie algorithms focusing on social multiagent dynamics and also review their recent extensions. The first main part focuses on simulation of social multiagent dynamics occurring in populations and networks, and the remainder reviews recent extensions of the Gillespie algorithms.
This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for epidemic modeling, optimization of transportation and logistics, as well as understanding biological phenomena. Over the past 20 years, network theory has proven to be one of the most powerful tools for studying and analyzing complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the “big data” sets. This book appeals to students, researchers, and professionals interested in theory and temporal networks—a field that has grown tremendously over the last decade. This second edition of Temporal Network Theory extends the first with three chapters highlighting recent developments in the interface with machine learning.
Drawing examples from real-world networks, this essential book traces the methods behind network analysis and explains how network data is first gathered, then processed and interpreted. The text will equip you with a toolbox of diverse methods and data modelling approaches, allowing you to quickly start making your own calculations on a huge variety of networked systems. This book sets you up to succeed, addressing the questions of what you need to know and what to do with it, when beginning to work with network data. The hands-on approach adopted throughout means that beginners quickly become capable practitioners, guided by a wealth of interesting examples that demonstrate key concepts. Exercises using real-world data extend and deepen your understanding, and develop effective working patterns in network calculations and analysis. Suitable for both graduate students and researchers across a range of disciplines, this novel text provides a fast-track to network data expertise.
This book explores social mechanisms that drive network change and link them to computationally sound models of changing structure to detect patterns. This text identifies the social processes generating these networks and how networks have evolved. Reviews: "this book is easy to read and entertaining, and much can be learned from it. Even if you know just about everything about large-scale and temporal networks, the book is a worthwhile read; you will learn a lot about SNA literature, patents, the US Supreme Court, and European soccer." (Social Networks) "a clear and accessible textbook, balancing symbolic maths, code, and visual explanations. The authors’ enthusiasm for the subject matter makes it enjoyable to read" (JASSS)
The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and conceptually more challenging. This book is intended as a first introduction and state-of-the art overview of this rapidly emerging field.
Music therapy as an intervention in medical, educational and many other environments has a rich and diverse history of methods, approaches and models. Consolidating the many components of music therapy, this completely updated edition of A Comprehensive Guide to Music Therapy covers everything students, teachers and practitioners of music therapy need to know. Building upon the work of Tony Wigram and developments within the field of music therapy over the last 15 years, this second edition looks at the theoretical foundation of music therapy, selected models and interventions, how it can be applied in clinical practice, and the recent progress made in research and evidence-based practice. Giving a complete picture of the multifaceted world of music therapy, it is a must-have for music therapy students, teachers and practitioners.
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Prepare for the CompTIA CySA+ certification exam with this fully updated self-study resource This highly effective self-study system provides complete coverage of every objective for the challenging CompTIA CySA+ Cybersecurity Analyst exam. You’ll find learning objectives at the beginning of each chapter, exam tips, in-depth explanations, and practice exam questions. All questions closely mirror those on the actual test in content, format, and tone. Designed to help you pass the CS0-002 exam with ease, this definitive guide also serves as an essential on-the-job reference. Covers all exam topics, including: Threat and vulnerability management Threat data and intelligence Vulnerability management, assessment tools, and mitigation Software and systems security Solutions for infrastructure management Software and hardware assurance best practices Security operations and monitoring Proactive threat hunting Automation concepts and technologies Incident response process, procedure, and analysis Compliance and assessment Data privacy and protection Support of organizational risk mitigation Online content includes: 200+ practice questions Interactive performance-based questions Test engine that provides full-length practice exams and customizable quizzes by exam objective