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Understanding Criminal Networks is a short methodological primer for those interested in studying illicit, deviant, covert, or criminal networks using social network analysis (SNA). Accessibly written by Gisela Bichler, a leading expert in SNA for dark networks, the book is chock-full of graphics, checklists, software tips, step-by-step guidance, and straightforward advice. Covering all the essentials, each chapter highlights three themes: the theoretical basis of networked criminology, methodological issues and useful analytic tools, and producing professional analysis. Unlike any other book on the market, the book combines conceptual and empirical work with advice on designing networking studies, collecting data, and analysis. Relevant, practical, theoretical, and methodologically innovative, Understanding Criminal Networks promises to jumpstart readers’ understanding of how to cross over from conventional investigations of crime to the study of criminal networks.
Most of the articles in this book deal with static or point-to-pointInterconnection Networks. In particular, new constructions are proposed basedon different tools from discrete mathematics. Many new records have beenestablished in the table of the maximum number of vertices of graphs withmaximum degree &Dgr; and diameter D. Properties of thesenetworks (and of more classical ones) are analyzed in many of the otherpapers. About 40% of the articles deal with fault tolerance orvulnerability properties using either combinatorial tools or probabilisticones.
Now reissued by Cambridge University Press, the updated second edition of this definitive textbook provides an unrivaled introduction to the theoretical and practical fundamentals of wireless communications. Key technical concepts are developed from first principles, and demonstrated to students using over 50 carefully curated worked examples. Over 200 end-of-chapter problems, based on real-world industry scenarios, help cement student understanding. The book provides a thorough coverage of foundational wireless technologies, including wireless local area networks (WLAN), 3G systems, and Bluetooth along with refreshed summaries of recent cellular standards leading to 4G and 5G, insights into the new areas of mobile satellite communications and fixed wireless access, and extra homework problems. Supported online by a solutions manual and lecture slides for instructors, this is the ideal foundation for senior undergraduate and graduate courses in wireless communications.
This book constitutes the refereed proceedings of the 7th International Conference on Ad-Hoc, Mobile, and Wireless Networks, ADHOC-NOW 2008, held in Sophia-Antipolis, France, September 2008. The 40 revised full papers and the 15 poster presentations were carefully reviewed and selected from 110 submissions. The papers deal with advances in Ad-Hoc networks, i.e. wireless, self-organizing systems formed by co-operating nodes within communication range of each other that form temporary networks. Their topology is dynamic, decentralized, ever changing and the nodes may move around arbitrarily.
Teachers use e-learning systems to develop course notes and web-based activities to communicate with learners on one side and monitor and classify their progress on the other. Learners use it for learning, communication, and collaboration. Adaptive e-learning systems often employ learner models, and the behavior of an adaptive system varies depending on the data from the learner model and the learner's profile. Without knowing anything about the learner who uses the system, a system would behave in exactly the same way for all learners. Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems: Emerging Research and Opportunities is a collection of research on the use of Bayesian networks and methods as a probabilistic formalism for the management of the learner model in adaptive hypermedia. It specifically discusses comparative studies, transformation rules, and case diagrams that support all phases of the learner model and the use of Bayesian networks and multi-entity Bayesian networks to manage dynamic aspects of this model. While highlighting topics such as developing the learner model, learning management systems, and modeling techniques, this book is ideally designed for instructional designers, course administrators, educators, researchers, and professionals.
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 constitutes the refereed proceedings of the 6th EAI International Conference on Industrial Networks and Intelligent Systems, INISCOM 2020, held in Hanoi, Vietnam, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 26 full papers were selected from 59 submissions and are organized thematically in tracks on telecommunications systems and networks; hardware, software and application designs; information processing and data analysis; industrial networks and intelligent systems; security and privacy.
Network diasporas are but the latest bridge connecting developing economy insiders, with their risk-mitigating knowledge and connections, to outsiders in command of technical know-how and investment capital. This book examines the interaction of expatriate talent with institutions in expatriates' countries of origin in an attempt to make the potential of diasporas and their knowledge a reality. The question of how to trigger and sustain such a virtuous cycle is a central concern of this book. The focus is on the "how to" details of how to design effective diaspora networks and transform brain drain into brain gain.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the X International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2021). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks, and technological networks.