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Public and private managers who are looking for sustainable development have to implement innovative solutions in a complex field of action. Joint action is needed, but the existing power networks within and between public and private domains tend to frustrate joint innovations. This book analyzes how public and private managers deal with energy transitions by creating innovative networks capable of co-ordinated action. A case study shows how separated power networks in the field of mobility, energy and environment, which are spread over the public and private world as well as civil society, are becoming more interconnected
Adaptive Networks by Thilo Gross,Hiroki Sayama Pdf
Adding one and one makes two, usually. But sometimes things add up to more than the sum of their parts. This observation, now frequently expressed in the maxim “more is different”, is one of the characteristic features of complex systems and, in particular, complex networks. Along with their ubiquity in real world systems, the ability of networks to exhibit emergent dynamics, once they reach a certain size, has rendered them highly attractive targets for research. The resulting network hype has made the word “network” one of the most in uential buzzwords seen in almost every corner of science, from physics and biology to economy and social sciences. The theme of “more is different” appears in a different way in the present v- ume, from the viewpoint of what we call “adaptive networks.” Adaptive networks uniquely combine dynamics on a network with dynamical adaptive changes of the underlying network topology, and thus they link classes of mechanisms that were previously studied in isolation. Here adding one and one certainly does not make two, but gives rise to a number of new phenomena, including highly robust se- organization of topology and dynamics and other remarkably rich dynamical beh- iors.
Self-Organization in Continuous Adaptive Networks by Anne-Ly Do,Thilo Gross Pdf
In the last years, adaptive networks have been discovered simultaneously in different fields as a universal framework for the study of self-organization phenomena. Understanding the mechanisms behind these phenomena is hoped to bring forward not only empirical disciplines such as biology, sociology, ecology, and economy, but also engineering disciplines seeking to employ controlled emergence in future technologies. This volume presents new analytical approaches, which combine tools from dynamical systems theory and statistical physics with tools from graph theory to address the principles behind adaptive self-organization. It is the first class of approaches that is applicable to continuous networks. The volume discusses the mechanisms behind three emergent phenomena that are prominently discussed in the context of biological and social sciences:• synchronization,• spontaneous diversification, and• self-organized criticality.Self-organization in continuous adaptive networks contains extended research papers. It can serve as both, a review of recent results on adaptive self-organization as well as a tutorial of new analytical methodsSelf-organization in continuous adaptive networks is ideal for academic staff and master/research students in complexity and network sciences, in engineering, physics and maths.
Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models by Jan Treur Pdf
This book addresses the challenging topic of modeling adaptive networks, which often manifest inherently complex behavior. Networks by themselves can usually be modeled using a neat, declarative, and conceptually transparent Network-Oriented Modeling approach. In contrast, adaptive networks are networks that change their structure; for example, connections in Mental Networks usually change due to learning, while connections in Social Networks change due to various social dynamics. For adaptive networks, separate procedural specifications are often added for the adaptation process. Accordingly, modelers have to deal with a less transparent, hybrid specification, part of which is often more at a programming level than at a modeling level. This book presents an overall Network-Oriented Modeling approach that makes designing adaptive network models much easier, because the adaptation process, too, is modeled in a neat, declarative, and conceptually transparent Network-Oriented Modeling manner, like the network itself. Thanks to this approach, no procedural, algorithmic, or programming skills are needed to design complex adaptive network models. A dedicated software environment is available to run these adaptive network models from their high-level specifications. Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily. For example, this can be applied to model metaplasticity in cognitive neuroscience, or second-order adaptation in biological and social contexts. The book illustrates the usefulness of this approach via numerous examples of complex (higher-order) adaptive network models for a wide variety of biological, mental, and social processes. The book is suitable for multidisciplinary Master’s and Ph.D. students without assuming much prior knowledge, although also some elementary mathematical analysis is involved. Given the detailed information provided, it can be used as an introduction to Network-Oriented Modeling for adaptive networks. The material is ideally suited for teaching undergraduate and graduate students with multidisciplinary backgrounds or interests. Lecturers will find additional material such as slides, assignments, and software.
Reviews of Nonlinear Dynamics and Complexity by Heinz Georg Schuster Pdf
Adopting a cross-disciplinary approach, the review character of this monograph sets it apart from specialized journals. The editor is advised by a first-class board of international scientists, such that the carefully selected and invited contributions represent the latest and most relevant findings.
Handbook on Biological Networks by Stefano Boccaletti Pdf
Networked systems are all around us. The accumulated evidence of systems as complex as a cell cannot be fully understood by studying only their isolated constituents, giving rise to a new area of interest in research OCo the study of complex networks . In a broad sense, biological networks have been one of the most studied networks, and the field has benefited from many important contributions. By understanding and modeling the structure of a biological network, a better perception of its dynamical and functional behavior is to be expected. This unique book compiles the most relevant results and novel insights provided by network theory in the biological sciences, ranging from the structure and dynamics of the brain to cellular and protein networks and to population-level biology. Sample Chapter(s). Chapter 1: Introduction (61 KB). Contents: Networks at the Cellular Level: The Structural Network Properties of Biological Systems (M Brilli & P Li); Dynamics of Multicellular Synthetic Gene Networks (E Ullner et al.); Boolean Networks in Inference and Dynamic Modeling of Biological Systems at the Molecular and Physiological Level (J Thakar & R Albert); Complexity of Boolean Dynamics in Simple Models of Signaling Networks and in Real Genetic Networks (A D az-Guilera & R ulvarez-Buylla); Geometry and Topology of Folding Landscapes (L Bongini & L Casetti); Elastic Network Models for Biomolecular Dynamics: Theory and Application to Membrane Proteins and Viruses (T R Lezon et al.); Metabolic Networks (M C Palumbo et al.); Brain Networks: The Human Brain Network (O Sporns); Brain Network Analysis from High-Resolution EEG Signals (F De Vico Fallani & F Babiloni); An Optimization Approach to the Structure of the Neuronal layout of C elegans (A Arenas et al.); Cultured Neuronal Networks Express Complex Patterns of Activity and Morphological Memory (N Raichman et al.); Synchrony and Precise Timing in Complex Neural Networks (R-M Memmesheimer & M Timme); Networks at the Individual and Population Levels: Ideas for Moving Beyond Structure to Dynamics of Ecological Networks (D B Stouffer et al.); Evolutionary Models for Simple Biosystems (F Bagnoli); Evolution of Cooperation in Adaptive Social Networks (S Van Segbroeck et al.); From Animal Collectives and Complex Networks to Decentralized Motion Control Strategies (A Buscarino et al.); Interplay of Network State and Topology in Epidemic Dynamics (T Gross). Readership: Advanced undergraduates, graduate students and researchers interested in the study of complex networks in a wide range of biological processes and systems."
Nomination of Benjamin A. Powell to be General Counsel of the Office of the Director of National Intelligence by United States. Congress. Senate. Select Committee on Intelligence Pdf
Fuzzy Logic-Based Modeling in Collaborative and Blended Learning by Hadjileontiadou, Sofia J. Pdf
Technology has dramatically changed the way in which knowledge is shared within and outside of traditional classroom settings. The application of fuzzy logic to new forms of technology-centered education has presented new opportunities for analyzing and modeling learner behavior. Fuzzy Logic-Based Modeling in Collaborative and Blended Learning explores the application of the fuzzy set theory to educational settings in order to analyze the learning process, gauge student feedback, and enable quality learning outcomes. Focusing on educational data analysis and modeling in collaborative and blended learning environments, this publication is an essential reference source for educators, researchers, educational administrators and designers, and IT specialists. This premier reference monograph presents key research on educational data analysis and modeling through the integration of research on advanced modeling techniques, educational technologies, fuzzy concept maps, hybrid modeling, neuro-fuzzy learning management systems, and quality of interaction.
Neural Networks for Control by W. Thomas Miller,Richard S. Sutton,Paul J. Werbos Pdf
Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Advances in Computer Communications and Networks From Green, Mobile, Pervasive Networking to Big Data Computing by Kewei Sha,Aaron Striegel,Min Song Pdf
Recent developments in computer communications and networks have enabled the deployment of exciting new areas such as Internet of Things and collaborative big data analysis. The design and implementation of energy efficient future generation communication and networking technologies also require the clever research and development of mobile, pervasive, and large-scale computing technologies. Advances in Computer Communications and Networks: from Green, Mobile, Pervasive Networking to Big Data Computing studies and presents recent advances in communication and networking technologies reflecting the state-of-the-art research achievements in novel communication technology and network optimization. Technical topics discussed in the book include: Data Center NetworksMobile Ad Hoc NetworksMultimedia NetworksInternet of ThingsWireless SpectrumNetwork Optimization.This book is ideal for personnel in computer communication and networking industries as well as academic staff and collegial, master, Ph.D. students in computer science, computer engineering, electrical engineering and telecommunication systems.
Patterns of Synchrony in Complex Networks of Adaptively Coupled Oscillators by Rico Berner Pdf
The focus of this thesis is the interplay of synchrony and adaptivity in complex networks. Synchronization is a ubiquitous phenomenon observed in different contexts in physics, chemistry, biology, neuroscience, medicine, socioeconomic systems, and engineering. Most prominently, synchronization takes place in the brain, where it is associated with cognitive capacities like learning and memory, but is also a characteristic of neurological diseases like Parkinson and epilepsy. Adaptivity is common in many networks in nature and technology, where the connectivity changes in time, i.e., the strength of the coupling is continuously adjusted depending upon the dynamic state of the system, for instance synaptic neuronal plasticity in the brain. This research contributes to a fundamental understanding of various synchronization patterns, including hierarchical multifrequency clusters, chimeras and other partial synchronization states. After a concise survey of the fundamentals of adaptive and complex dynamical networks and synaptic plasticity, in the first part of the thesis the existence and stability of cluster synchronization in globally coupled adaptive networks is discussed for simple paradigmatic phase oscillators as well as for a more realistic neuronal oscillator model with spike-timing dependent plasticity. In the second part of the thesis the interplay of adaptivity and connectivity is investigated for more complex network structures like nonlocally coupled rings, random networks, and multilayer systems. Besides presenting a plethora of novel, sometimes intriguing patterns of synchrony, the thesis makes a number of pioneering methodological advances, where rigorous mathematical proofs are given in the Appendices. These results are of interest not only from a fundamental point of view, but also with respect to challenging applications in neuroscience and technological systems.
Computational Social Networks by My T. Thai,Nam P. Nguyen,Huawei Shen Pdf
This book constitutes the refereed proceedings of the 4th International Conference on Computational Social Networks, CSoNet 2015, held in Beijing, China, in August 2015. The 23 revised full papers and 3 short papers presented together with 2 extended abstracts were carefully reviewed and selected from 101 submissions and cover topics on social information diffusion; network clustering and community structure; social link prediction and recommendation; and social network structure analysis.
Complex Networks and Their Applications VII by Luca Maria Aiello,Chantal Cherifi,Hocine Cherifi,Renaud Lambiotte,Pietro Lió,Luis M. Rocha Pdf
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, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and 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.
Complex Networks & Their Applications IX by Rosa M. Benito,Chantal Cherifi,Hocine Cherifi,Esteban Moro,Luis Mateus Rocha,Marta Sales-Pardo Pdf
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 IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). 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.