WorldWideScience

Sample records for networked slepian-wolf theory

  1. Linear network theory

    CERN Document Server

    Sander, K F

    1964-01-01

    Linear Network Theory covers the significant algebraic aspect of network theory, with minimal reference to practical circuits. The book begins the presentation of network analysis with the exposition of networks containing resistances only, and follows it up with a discussion of networks involving inductance and capacity by way of the differential equations. Classification and description of certain networks, equivalent networks, filter circuits, and network functions are also covered. Electrical engineers, technicians, electronics engineers, electricians, and students learning the intricacies

  2. Network Theory and Religious Innovation

    DEFF Research Database (Denmark)

    Collar, Anna

    Collar, A. C. F. ‘Network Theory and Religious Innovation’. In Greek and Roman Networks in the Mediterranean, edited by I. Malkin, C. Constantakopoulou, K. Panagopoulou, 144-157. Abingdon: Routledge......Collar, A. C. F. ‘Network Theory and Religious Innovation’. In Greek and Roman Networks in the Mediterranean, edited by I. Malkin, C. Constantakopoulou, K. Panagopoulou, 144-157. Abingdon: Routledge...

  3. Theory of spatial networks

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, T

    1983-01-01

    A new framework of synchronous parallel processing systems called spatial networks is examined, in which the family of all cellular automata is included perfectly. This framework is free from the two restrictions of cellular automata of which one is the finiteness of the set of states of a cell and the other is the countability of an array space. Throughout this article, the relationships between function and structure of spatial networks are considered. First, the necessary and sufficient condition for spatial networks to be uniformly interconnected is given. That for spatial networks to be finitely interconnected is also given with a topological approach. The characterization theorem of cellular automata comes from these results. Second, it is shown that finitely and uniformly interconnected linear spatial networks can be characterized by the convolution form. Last, the conditions for their global mappings to be injective or surjective are discussed. 10 references.

  4. Quantum network theory

    International Nuclear Information System (INIS)

    Yurke, B.; Denker, J.S.

    1984-01-01

    A general approach, within the framework of canonical quantization, is described for analyzing the quantum behavior of complicated electronic circuits. This approach is capable of dealing with electrical networks having nonlinear or dissipative elements. The techniques are used to analyze a degenerate parametric amplifier, a device capable of generating squeezed coherent state signals. A circuit capable of performing back-action-evading electrical measurements is also discussed. (author)

  5. An Efficient SF-ISF Approach for the Slepian-Wolf Source Coding Problem

    Directory of Open Access Journals (Sweden)

    Tu Zhenyu

    2005-01-01

    Full Text Available A simple but powerful scheme exploiting the binning concept for asymmetric lossless distributed source coding is proposed. The novelty in the proposed scheme is the introduction of a syndrome former (SF in the source encoder and an inverse syndrome former (ISF in the source decoder to efficiently exploit an existing linear channel code without the need to modify the code structure or the decoding strategy. For most channel codes, the construction of SF-ISF pairs is a light task. For parallelly and serially concatenated codes and particularly parallel and serial turbo codes where this appear less obvious, an efficient way for constructing linear complexity SF-ISF pairs is demonstrated. It is shown that the proposed SF-ISF approach is simple, provenly optimal, and generally applicable to any linear channel code. Simulation using conventional and asymmetric turbo codes demonstrates a compression rate that is only 0.06 bit/symbol from the theoretical limit, which is among the best results reported so far.

  6. Rate-adaptive BCH coding for Slepian-Wolf coding of highly correlated sources

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Salmistraro, Matteo; Larsen, Knud J.

    2012-01-01

    This paper considers using BCH codes for distributed source coding using feedback. The focus is on coding using short block lengths for a binary source, X, having a high correlation between each symbol to be coded and a side information, Y, such that the marginal probability of each symbol, Xi in X......, given Y is highly skewed. In the analysis, noiseless feedback and noiseless communication are assumed. A rate-adaptive BCH code is presented and applied to distributed source coding. Simulation results for a fixed error probability show that rate-adaptive BCH achieves better performance than LDPCA (Low......-Density Parity-Check Accumulate) codes for high correlation between source symbols and the side information....

  7. Potential theory for directed networks.

    Directory of Open Access Journals (Sweden)

    Qian-Ming Zhang

    Full Text Available Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i We propose a new mechanism for the local organization of directed networks; (ii We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.

  8. Potential Theory for Directed Networks

    Science.gov (United States)

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

    2013-01-01

    Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

  9. A Theory of Network Tracing

    Science.gov (United States)

    Acharya, Hrishikesh B.; Gouda, Mohamed G.

    Traceroute is a widely used program for computing the topology of any network in the Internet. Using Traceroute, one starts from a node and chooses any other node in the network. Traceroute obtains the sequence of nodes that occur between these two nodes, as specified by the routing tables in these nodes. Each use of Traceroute in a network produces a trace of nodes that constitute a simple path in this network. In every trace that is produced by Traceroute, each node occurs either by its unique identifier, or by the anonymous identifier"*". In this paper, we introduce the first theory aimed at answering the following important question. Is there an algorithm to compute the topology of a network N from a trace set T that is produced by using Traceroute in network N, assuming that each edge in N occurs in at least one trace in T, and that each node in N occurs by its unique identifier in at least one trace in T? We prove that the answer to this question is "No" if N is an even ring or a general network. However, it is "Yes" if N is a tree or an odd ring. The answer is also "No" if N is mostly-regular, but "Yes" if N is a mostly-regular even ring.

  10. Interdisciplinary and physics challenges of network theory

    Science.gov (United States)

    Bianconi, Ginestra

    2015-09-01

    Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.

  11. The tensor network theory library

    Science.gov (United States)

    Al-Assam, S.; Clark, S. R.; Jaksch, D.

    2017-09-01

    In this technical paper we introduce the tensor network theory (TNT) library—an open-source software project aimed at providing a platform for rapidly developing robust, easy to use and highly optimised code for TNT calculations. The objectives of this paper are (i) to give an overview of the structure of TNT library, and (ii) to help scientists decide whether to use the TNT library in their research. We show how to employ the TNT routines by giving examples of ground-state and dynamical calculations of one-dimensional bosonic lattice system. We also discuss different options for gaining access to the software available at www.tensornetworktheory.org.

  12. Networks and learning in game theory

    NARCIS (Netherlands)

    Kets, W.

    2008-01-01

    This work concentrates on two topics, networks and game theory, and learning in games. The first part of this thesis looks at network games and the role of incomplete information in such games. It is assumed that players are located on a network and interact with their neighbors in the network.

  13. Consumer culture theory (re)visits actor-network theory

    DEFF Research Database (Denmark)

    Bajde, Domen

    2013-01-01

    The vocabulary and tactics developed by actor-network theory (ANT) can shed light on several ontological and epistemological challenges faced by consumer culture theory. Rather than providing ready-made theories or methods, our translation of ANT puts forward a series of questions and propositions...

  14. Wireless network security theories and applications

    CERN Document Server

    Chen, Lei; Zhang, Zihong

    2013-01-01

    Wireless Network Security Theories and Applications discusses the relevant security technologies, vulnerabilities, and potential threats, and introduces the corresponding security standards and protocols, as well as provides solutions to security concerns. Authors of each chapter in this book, mostly top researchers in relevant research fields in the U.S. and China, presented their research findings and results about the security of the following types of wireless networks: Wireless Cellular Networks, Wireless Local Area Networks (WLANs), Wireless Metropolitan Area Networks (WMANs), Bluetooth

  15. Governance network theory: Past, present and future

    NARCIS (Netherlands)

    E-H. Klijn (Erik-Hans); J.F.M. Koppenjan (Joop)

    2012-01-01

    markdownabstract__Abstract__ This article argues that governance network theory (GNT) has developed into a fullyfledged theory that has gained prominence within public administration. The emergence of New Public Governance opens up new challenges, however, and instead of governance networks and

  16. Queuing theory and telecommunications networks and applications

    CERN Document Server

    Giambene, Giovanni

    2014-01-01

    This book provides a basic description of current networking technologies and protocols as well as important tools for network performance analysis based on queuing theory. The second edition adds selected contents in the first part of the book for what concerns: (i) the token bucket regulator and traffic shaping issues; (ii) the TCP protocol congestion control that has a significant part in current networking; (iii) basic satellite networking issues; (iv) adding details on QoS support in IP networks. The book is organized so that networking technologies and protocols (Part I) are first and are then followed by theory and exercises with applications to the different technologies and protocols (Part II). This book is intended as a textbook for master level courses in networking and telecommunications sectors.

  17. Matching theory for wireless networks

    CERN Document Server

    Han, Zhu; Saad, Walid

    2017-01-01

    This book provides the fundamental knowledge of the classical matching theory problems. It builds up the bridge between the matching theory and the 5G wireless communication resource allocation problems. The potentials and challenges of implementing the semi-distributive matching theory framework into the wireless resource allocations are analyzed both theoretically and through implementation examples. Academics, researchers, engineers, and so on, who are interested in efficient distributive wireless resource allocation solutions, will find this book to be an exceptional resource. .

  18. Framing labor contracts : Contract versus network theories

    NARCIS (Netherlands)

    Knegt, R.

    2016-01-01

    Since the 18th century the ‘contractual model’ has become both a paradigm of social theories (f.i. ‘rational choice’) and a dominant model of structuring labour relations. Its presupposition of the subjectivity of individual actors as a given is criticized with reference to network-based theories

  19. Network location theory and contingency planning

    Energy Technology Data Exchange (ETDEWEB)

    Hakimi, S L

    1983-08-01

    A brief survey of results in network location theory is first presented. Then, a systems view of contingency planning is described. Finally, some results in location theory are re-examined and it is shown that they are motivated by contingency planning considerations. Some new issues and problems in location theory are described, which, if properly tackled, will have a substantial impact on contingency planning in transportation.

  20. Remarks on network public theory

    OpenAIRE

    Marcin Brol; Slawomir Czetwertynski

    2013-01-01

    This paper is a trial of capturing of a relation between traditional public sphere atrophy and the augmentation of a network public sphere. A thesis is advanced that the traditional public sphere is subject of the atrophy, however, the entire network public sphere is subject of the augmentation process. Such a formulated thesis forces a choice between two following issues. The first of them regards a relation between factors, which stimulate the atrophy and the augmentation. The second issue ...

  1. A first course in network theory

    CERN Document Server

    Estrada, Ernesto

    2015-01-01

    The study of network theory is a highly interdisciplinary field, which has emerged as a major topic of interest in various disciplines ranging from physics and mathematics, to biology and sociology. This book promotes the diverse nature of the study of complex networks by balancing the needs of students from very different backgrounds. It references the most commonly used concepts in network theory, provides examples of their applications in solving practicalproblems, and clear indications on how to analyse their results.In the first part of the book, students and researchers will discover the

  2. Mathematical theories of distributed sensor networks

    CERN Document Server

    Iyengar, Sitharama S; Balakrishnan, N

    2014-01-01

    Mathematical Theory of Distributed Sensor Networks demonstrates how mathematical theories can be used to provide distributed sensor modeling and to solve important problems such as coverage hole detection and repair. The book introduces the mathematical and computational structure by discussing what they are, their applications and how they differ from traditional systems. The text also explains how mathematics are utilized to provide efficient techniques implementing effective coverage, deployment, transmission, data processing, signal processing, and data protection within distributed sensor networks. Finally, the authors discuss some important challenges facing mathematics to get more incite to the multidisciplinary area of distributed sensor networks.

  3. COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks

    NARCIS (Netherlands)

    Sie, Rory

    2012-01-01

    Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.

  4. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  5. Information theory perspective on network robustness

    International Nuclear Information System (INIS)

    Schieber, Tiago A.; Carpi, Laura; Frery, Alejandro C.; Rosso, Osvaldo A.; Pardalos, Panos M.; Ravetti, Martín G.

    2016-01-01

    A crucial challenge in network theory is the study of the robustness of a network when facing a sequence of failures. In this work, we propose a dynamical definition of network robustness based on Information Theory, that considers measurements of the structural changes caused by failures of the network's components. Failures are defined here as a temporal process defined in a sequence. Robustness is then evaluated by measuring dissimilarities between topologies after each time step of the sequence, providing a dynamical information about the topological damage. We thoroughly analyze the efficiency of the method in capturing small perturbations by considering different probability distributions on networks. In particular, we find that distributions based on distances are more consistent in capturing network structural deviations, as better reflect the consequences of the failures. Theoretical examples and real networks are used to study the performance of this methodology. - Highlights: • A novel methodology to measure the robustness of a network to component failure or targeted attacks is proposed. • The use of the network's distance PDF allows a precise analysis. • The method provides a dynamic robustness profile showing the response of the topology to each failure event. • The measure is capable to detect network's critical elements.

  6. Network Security Validation Using Game Theory

    Science.gov (United States)

    Papadopoulou, Vicky; Gregoriades, Andreas

    Non-functional requirements (NFR) such as network security recently gained widespread attention in distributed information systems. Despite their importance however, there is no systematic approach to validate these requirements given the complexity and uncertainty characterizing modern networks. Traditionally, network security requirements specification has been the results of a reactive process. This however, limited the immunity property of the distributed systems that depended on these networks. Security requirements specification need a proactive approach. Networks' infrastructure is constantly under attack by hackers and malicious software that aim to break into computers. To combat these threats, network designers need sophisticated security validation techniques that will guarantee the minimum level of security for their future networks. This paper presents a game-theoretic approach to security requirements validation. An introduction to game theory is presented along with an example that demonstrates the application of the approach.

  7. Fuzzy neural network theory and application

    CERN Document Server

    Liu, Puyin

    2004-01-01

    This book systematically synthesizes research achievements in the field of fuzzy neural networks in recent years. It also provides a comprehensive presentation of the developments in fuzzy neural networks, with regard to theory as well as their application to system modeling and image restoration. Special emphasis is placed on the fundamental concepts and architecture analysis of fuzzy neural networks. The book is unique in treating all kinds of fuzzy neural networks and their learning algorithms and universal approximations, and employing simulation examples which are carefully designed to he

  8. Psychology and social networks: a dynamic network theory perspective.

    Science.gov (United States)

    Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

    2014-04-01

    Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

  9. Linear control theory for gene network modeling.

    Science.gov (United States)

    Shin, Yong-Jun; Bleris, Leonidas

    2010-09-16

    Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  10. Towards an Information Theory of Complex Networks

    CERN Document Server

    Dehmer, Matthias; Mehler, Alexander

    2011-01-01

    For over a decade, complex networks have steadily grown as an important tool across a broad array of academic disciplines, with applications ranging from physics to social media. A tightly organized collection of carefully-selected papers on the subject, Towards an Information Theory of Complex Networks: Statistical Methods and Applications presents theoretical and practical results about information-theoretic and statistical models of complex networks in the natural sciences and humanities. The book's major goal is to advocate and promote a combination of graph-theoretic, information-theoreti

  11. Dobrushin's approach to queueing network theory

    Directory of Open Access Journals (Sweden)

    F. I. Karpelevich

    1996-01-01

    Full Text Available R.L. Dobrushin (1929-1995 made substantial contributions to Queueing Network Theory (QNT. A review of results from QNT which arose from his ideas or were connected to him in other ways is given. We also comment on various related open problems.

  12. Nonequilibrium landscape theory of neural networks.

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-11-05

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

  13. Nonequilibrium landscape theory of neural networks

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  14. Formulation and applications of complex network theory

    Science.gov (United States)

    Park, Juyong

    In recent years, there has been a great surge of interest among physicists in modeling social, technological, or biological systems as networks. Analyses of large-scale networks such as the Internet have led to discoveries of many unexpected network properties, including power-law degree distributions. These discoveries have prompted physicists to devise novel ways to model networks, both computational and theoretical. In this dissertation, we present several network models and their applications. First, we study the theory of Exponential Random Graphs. We derive it from the principle of maximum entropy, thereby showing that it is the equivalent of the Gibbs ensemble for networks. Using tools of statistical physics, we solve well-known and new examples that include power-law networks and the two-star model. Our solutions confirm the existence of a first-order phase transition for the latter whose exact behavior has not been presented previously. We also study degree correlations and clustering in networks. Degrees of adjacent vertices are positively correlated in social networks, whereas they are negatively correlated in other types of networks. We demonstrate that a negative degree correlation is a more natural state of a network, and therefore that social networks are an exception. We argue that variations in the number of vertices in social groups cause positive degree correlations, and analyze a model that incorporates such a mechanism. The model indeed shows a high level of degree correlation and clustering that is similar in value to those of real networks. Finally, we develop algorithms for ranking vertices in networks that represent pairwise comparisons. The first algorithm is based on the familiar concept of indirect wins and losses. The second algorithm is based on the concept of retrodictive accuracy, which is maximized by positioning as many winners above the losers as possible. We compare the rankings of American college football teams generated by our

  15. Linear control theory for gene network modeling.

    Directory of Open Access Journals (Sweden)

    Yong-Jun Shin

    Full Text Available Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain and linear state-space (time domain can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  16. Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

    Directory of Open Access Journals (Sweden)

    Nai-Ru Xu

    2016-01-01

    Full Text Available The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

  17. Wireless sensor networks from theory to applications

    CERN Document Server

    El Emary, Ibrahiem M M

    2013-01-01

    Although there are many books available on WSNs, most are low-level, introductory books. The few available for advanced readers fail to convey the breadth of knowledge required for those aiming to develop next-generation solutions for WSNs. Filling this void, Wireless Sensor Networks: From Theory to Applications supplies comprehensive coverage of WSNs. In order to provide the wide-ranging guidance required, the book brings together the contributions of domain experts working in the various subfields of WSNs worldwide. This edited volume examines recent advances in WSN technologies and consider

  18. Game theory in communication networks cooperative resolution of interactive networking scenarios

    CERN Document Server

    Antoniou, Josephina

    2012-01-01

    A mathematical tool for scientists and researchers who work with computer and communication networks, Game Theory in Communication Networks: Cooperative Resolution of Interactive Networking Scenarios addresses the question of how to promote cooperative behavior in interactive situations between heterogeneous entities in communication networking scenarios. It explores network design and management from a theoretical perspective, using game theory and graph theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities. The book promotes the use of Game T

  19. The Economics of Networks: theory and empirics

    NARCIS (Netherlands)

    M.J. van der Leij (Marco)

    2006-01-01

    textabstractWherever we are, networks are all around us. The roads that we travel form a network. The websites that we visit form an enormous information network. But, above all, we are part of a network ourselves, the network of social contacts and relations. These networks play an

  20. Networking of theories as a research practice in mathematics education

    CERN Document Server

    Bikner-Ahsbahs, Angelika

    2014-01-01

    How can we deal with the diversity of theories in mathematics education This was the main question that led the authors of this book to found the Networking Theories Group. Starting from the shared assumption that the existence of different theories is a resource for mathematics education research, the authors have explored the possibilities of interactions between theories, such as contrasting, coordinating, and locally integrating them. The book explains and illustrates what it means to network theories; it presents networking as a challenging but fruitful research practice and shows how the Group dealt with this challenge considering five theoretical approaches, namely the approach of Action, Production, and Communication (APC), the Theory of Didactical Situations (TDS), the Anthropological Theory of the Didactic (ATD), the approach of Abstraction in Context (AiC), and the Theory of Interest-Dense Situations (IDS). A synthetic presentation of each theory and their connections shows how the activity of netw...

  1. How Might Better Network Theories Support School Leadership Research?

    Science.gov (United States)

    Hadfield, Mark; Jopling, Michael

    2012-01-01

    This article explores how recent research in education has applied different aspects of "network" theory to the study of school leadership. Constructs from different network theories are often used because of their perceived potential to clarify two perennial issues in leadership research. The first is the relative importance of formal and…

  2. Understanding Social Networks: Theories, Concepts, and Findings

    Science.gov (United States)

    Kadushin, Charles

    2012-01-01

    Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…

  3. Adaptive Networks Theory, Models and Applications

    CERN Document Server

    Gross, Thilo

    2009-01-01

    With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.

  4. A Preliminary Theory of Dark Network Resilience

    Science.gov (United States)

    Bakker, Rene M.; Raab, Jorg; Milward, H. Brinton

    2012-01-01

    A crucial contemporary policy question for governments across the globe is how to cope with international crime and terrorist networks. Many such "dark" networks--that is, networks that operate covertly and illegally--display a remarkable level of resilience when faced with shocks and attacks. Based on an in-depth study of three cases…

  5. Essays on Networks: Theory and Applications

    NARCIS (Netherlands)

    A.M. Babus (Ana Maria)

    2008-01-01

    textabstractNetworks have proven to be a useful representation of various systems. Social and economic interactions, biological and ecological systems, the internet can be understood better if modelled as networks. Intuitively, a network describes a collection of nodes and the links between them.

  6. Application of random matrix theory to biological networks

    Energy Technology Data Exchange (ETDEWEB)

    Luo Feng [Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, SC 29634 (United States); Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhong Jianxin [Department of Physics, Xiangtan University, Hunan 411105 (China) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhongjn@ornl.gov; Yang Yunfeng [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Scheuermann, Richard H. [Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhou Jizhong [Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019 (United States) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhouj@ornl.gov

    2006-09-25

    We show that spectral fluctuation of interaction matrices of a yeast protein-protein interaction network and a yeast metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we demonstrate that while the global biological networks evaluated belong to GOE, removal of interactions between constituents transitions the networks to systems of isolated modules described by the Poisson distribution. Our results indicate that although biological networks are very different from other complex systems at the molecular level, they display the same statistical properties at network scale. The transition point provides a new objective approach for the identification of functional modules.

  7. Network analysis and synthesis a modern systems theory approach

    CERN Document Server

    Anderson, Brian D O

    2006-01-01

    Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations

  8. Modern temporal network theory: a colloquium

    Science.gov (United States)

    Holme, Petter

    2015-09-01

    The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.

  9. Ad hoc networks telecommunications and game theory

    CERN Document Server

    Benslama, Malek; Batatia, Hadj

    2015-01-01

    Random SALOHA and CSMA protocols that are used to access MAC in ad hoc networks are very small compared to the multiple and spontaneous use of the transmission channel. So they have low immunity to the problems of packet collisions. Indeed, the transmission time is the critical factor in the operation of such networks. The simulations demonstrate the positive impact of erasure codes on the throughput of the transmission in ad hoc networks. However, the network still suffers from the intermittency and volatility of its efficiency throughout its operation, and it switches quickly to the satura

  10. Control theory of digitally networked dynamic systems

    CERN Document Server

    Lunze, Jan

    2013-01-01

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

  11. Actor/Actant-Network Theory as Emerging Methodology for ...

    African Journals Online (AJOL)

    4carolinebell@gmail.com

    2005-01-31

    Jan 31, 2005 ... to trace relationships, actors, actants and actor/actant-networks .... associated with a particular type of social theory (Latour, 1987; ..... the Department of Environmental Affairs and Tourism, Organised Business and Organised.

  12. Renormalization group theory for percolation in time-varying networks.

    Science.gov (United States)

    Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M

    2018-05-22

    Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.

  13. The cooperative game theory of networks and hierarchies

    CERN Document Server

    Gilles, Robert P

    2010-01-01

    This book details standard concepts in cooperative game theory with applications to the analysis of social networks and hierarchical authority organizations. It covers the multi-linear extension, the Core, the Shapley value, and the cooperative potential.

  14. A preliminary theory of dark network resilience

    NARCIS (Netherlands)

    Bakker, R.M.; Raab, J.; Milward, H.B.

    2012-01-01

    A crucial contemporary policy question for governments across the globe is how to cope with international crime and terrorist networks. Many such “dark” networks—that is, networks that operate covertly and illegally—display a remarkable level of resilience when faced with shocks and attacks. Based

  15. Detection of network attacks based on adaptive resonance theory

    Science.gov (United States)

    Bukhanov, D. G.; Polyakov, V. M.

    2018-05-01

    The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

  16. Neutral theory of chemical reaction networks

    International Nuclear Information System (INIS)

    Lee, Sang Hoon; Holme, Petter; Minnhagen, Petter; Bernhardsson, Sebastian; Kim, Beom Jun

    2012-01-01

    To what extent do the characteristic features of a chemical reaction network reflect its purpose and function? In general, one argues that correlations between specific features and specific functions are key to understanding a complex structure. However, specific features may sometimes be neutral and uncorrelated with any system-specific purpose, function or causal chain. Such neutral features are caused by chance and randomness. Here we compare two classes of chemical networks: one that has been subjected to biological evolution (the chemical reaction network of metabolism in living cells) and one that has not (the atmospheric planetary chemical reaction networks). Their degree distributions are shown to share the very same neutral system-independent features. The shape of the broad distributions is to a large extent controlled by a single parameter, the network size. From this perspective, there is little difference between atmospheric and metabolic networks; they are just different sizes of the same random assembling network. In other words, the shape of the degree distribution is a neutral characteristic feature and has no functional or evolutionary implications in itself; it is not a matter of life and death. (paper)

  17. Social Capital Theory: Implications for Women's Networking and Learning

    Science.gov (United States)

    Alfred, Mary V.

    2009-01-01

    This chapter describes social capital theory as a framework for exploring women's networking and social capital resources. It presents the foundational assumptions of the theory, the benefits and risks of social capital engagement, a feminist critique of social capital, and the role of social capital in adult learning.

  18. Classification of networks of automata by dynamical mean field theory

    International Nuclear Information System (INIS)

    Burda, Z.; Jurkiewicz, J.; Flyvbjerg, H.

    1990-01-01

    Dynamical mean field theory is used to classify the 2 24 =65,536 different networks of binary automata on a square lattice with nearest neighbour interactions. Application of mean field theory gives 700 different mean field classes, which fall in seven classes of different asymptotic dynamics characterized by fixed points and two-cycles. (orig.)

  19. Wave Energy and Actor-Network Theory: The Irish Case

    OpenAIRE

    Cunningham, William

    2013-01-01

    This paper examines the role of the wave energy sector in Ireland using theories from the field of Science and Technology Studies (STS). Theoretical divisions within the field of STS are examined, particularly the Sociology of Scientific Knowledge (SSK) and Actor-Network Theory (ANT). Any conflicts which these two theories present to each other are examined through the empirical findings of the Irish wave energy sector. In particular, ANT s rejection of macro and micro distinctions when analy...

  20. Spatial analysis of bus transport networks using network theory

    Science.gov (United States)

    Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

    2018-07-01

    In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

  1. EXTERNALITIES IN EXCHANGE NETWORKS AN ADAPTATION OF EXISTING THEORIES OF EXCHANGE NETWORKS

    NARCIS (Netherlands)

    Dijkstra, Jacob

    2009-01-01

    The present paper extends the focus of network exchange research to externalities in exchange networks. Externalities of exchange are defined as direct effects on an actor's utility, of an exchange in which this actor is not involved. Existing theories in the field of network exchange do not inform

  2. Estimating network effect in geocenter motion: Theory

    Science.gov (United States)

    Zannat, Umma Jamila; Tregoning, Paul

    2017-10-01

    Geophysical models and their interpretations of several processes of interest, such as sea level rise, postseismic relaxation, and glacial isostatic adjustment, are intertwined with the need to realize the International Terrestrial Reference Frame. However, this realization needs to take into account the geocenter motion, that is, the motion of the center of figure of the Earth surface, due to, for example, deformation of the surface by earthquakes or hydrological loading effects. Usually, there is also a discrepancy, known as the network effect, between the theoretically convenient center of figure and the physically accessible center of network frames, because of unavoidable factors such as uneven station distribution, lack of stations in the oceans, disparity in the coverage between the two hemispheres, and the existence of tectonically deforming zones. Here we develop a method to estimate the magnitude of the network effect, that is, the error introduced by the incomplete sampling of the Earth surface, in measuring the geocenter motion, for a network of space geodetic stations of a fixed size N. For this purpose, we use, as our proposed estimate, the standard deviations of the changes in Helmert parameters measured by a random network of the same size N. We show that our estimate scales as 1/√N and give an explicit formula for it in terms of the vector spherical harmonics expansion of the displacement field. In a complementary paper we apply this formalism to coseismic displacements and elastic deformations due to surface water movements.

  3. Quantum Networks: General theory and applications

    International Nuclear Information System (INIS)

    Bisio, A.; D'Ariano, G. M.; Perinotti, P.; Chiribella, G.

    2011-01-01

    In this work we present a general mathematical framework to deal with Quantum Networks, i.e. networks resulting from the interconnection of elementary quantum circuits. The cornerstone of our approach is a generalization of the Choi isomorphism that allows one to efficiently represent any given Quantum Network in terms of a single positive operator. Our formalism allows one to face and solve many quantum information processing problems that would be hardly manageable otherwise, the most relevant of which are reviewed in this work: quantum process tomography, quantum cloning and learning of transformations, inversion of a unitary gate, information-disturbance tradeoff in estimating a unitary transformation, cloning and learning of a measurement device (Authors)

  4. Optimal transportation networks models and theory

    CERN Document Server

    Bernot, Marc; Morel, Jean-Michel

    2009-01-01

    The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.

  5. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida

    2014-09-01

    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  6. Building next-generation converged networks theory and practice

    CERN Document Server

    Pathan, Al-Sakib Khan

    2013-01-01

    Supplying a comprehensive introduction to next-generation networks, Building Next-Generation Converged Networks: Theory and Practice strikes a balance between how and why things work and how to make them work. It compiles recent advancements along with basic issues from the wide range of fields related to next generation networks. Containing the contributions of 56 industry experts and researchers from 16 different countries, the book presents relevant theoretical frameworks and the latest research. It investigates new technologies such as IPv6 over Low Power Wireless Personal Area Network (6L

  7. Pathways, Networks, and Systems: Theory and Experiments

    Energy Technology Data Exchange (ETDEWEB)

    Joseph H. Nadeau; John D. Lambris

    2004-10-30

    The international conference provided a unique opportunity for theoreticians and experimenters to exchange ideas, strategies, problems, challenges, language and opportunities in both formal and informal settings. This dialog is an important step towards developing a deep and effective integration of theory and experiments in studies of systems biology in humans and model organisms.

  8. Biological impacts and context of network theory

    Energy Technology Data Exchange (ETDEWEB)

    Almaas, E

    2007-01-05

    Many complex systems can be represented and analyzed as networks, and examples that have benefited from this approach span the natural sciences. For instance, we now know that systems as disparate as the World-Wide Web, the Internet, scientific collaborations, food webs, protein interactions and metabolism all have common features in their organization, the most salient of which are their scale-free connectivity distributions and their small-world behavior. The recent availability of large scale datasets that span the proteome or metabolome of an organism have made it possible to elucidate some of the organizational principles and rules that govern their function, robustness and evolution. We expect that combining the currently separate layers of information from gene regulatory-, signal transduction-, protein interaction- and metabolic networks will dramatically enhance our understanding of cellular function and dynamics.

  9. Integrated Adversarial Network Theory (iANT)

    Science.gov (United States)

    2011-07-01

    elite networks and governance changes in the 1980s. American Journal of Sociology, 103(1): 1-37. DiMaggio, P. 1986. Structural analysis of...Interorganization contagion in corporate philanthropy . Administrative Science Quarterly, 36(1): 88-105. Gargiulo, M., & Benassi, M. 1999. The dark...1): 7 1-84. Useem, M. 1979. The social organization ofthe American business elite and participation of corporation directors in the governance of

  10. Simulating activation propagation in social networks using the graph theory

    Directory of Open Access Journals (Sweden)

    František Dařena

    2010-01-01

    Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

  11. Parallel Distributed Processing Theory in the Age of Deep Networks.

    Science.gov (United States)

    Bowers, Jeffrey S

    2017-12-01

    Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.

  12. Information theory and the ethylene genetic network.

    Science.gov (United States)

    González-García, José S; Díaz, José

    2011-10-01

    The original aim of the Information Theory (IT) was to solve a purely technical problem: to increase the performance of communication systems, which are constantly affected by interferences that diminish the quality of the transmitted information. That is, the theory deals only with the problem of transmitting with the maximal precision the symbols constituting a message. In Shannon's theory messages are characterized only by their probabilities, regardless of their value or meaning. As for its present day status, it is generally acknowledged that Information Theory has solid mathematical foundations and has fruitful strong links with Physics in both theoretical and experimental areas. However, many applications of Information Theory to Biology are limited to using it as a technical tool to analyze biopolymers, such as DNA, RNA or protein sequences. The main point of discussion about the applicability of IT to explain the information flow in biological systems is that in a classic communication channel, the symbols that conform the coded message are transmitted one by one in an independent form through a noisy communication channel, and noise can alter each of the symbols, distorting the message; in contrast, in a genetic communication channel the coded messages are not transmitted in the form of symbols but signaling cascades transmit them. Consequently, the information flow from the emitter to the effector is due to a series of coupled physicochemical processes that must ensure the accurate transmission of the message. In this review we discussed a novel proposal to overcome this difficulty, which consists of the modeling of gene expression with a stochastic approach that allows Shannon entropy (H) to be directly used to measure the amount of uncertainty that the genetic machinery has in relation to the correct decoding of a message transmitted into the nucleus by a signaling pathway. From the value of H we can define a function I that measures the amount of

  13. Games as Actors - Interaction, Play, Design, and Actor Network Theory

    DEFF Research Database (Denmark)

    Jessen, Jari Due; Jessen, Carsten

    2014-01-01

    When interacting with computer games, users are forced to follow the rules of the game in return for the excitement, joy, fun, or other pursued experiences. In this paper, we investigate how games a chieve these experiences in the perspective of Actor Network Theory (ANT). Based on a qualitative......, and by doing so they create in humans what in modern play theory is known as a “state of play”...

  14. Workshop on Thermal Field Theory to Neural Networks

    CERN Document Server

    Veneziano, Gabriele; Aurenche, Patrick

    1996-01-01

    Tanguy Altherr was a Fellow in the Theory Division at CERN, on leave from LAPP (CNRS) Annecy. At the time of his accidental death in July 1994, he was only 31.A meeting was organized at CERN, covering the various aspects of his scientific interests: thermal field theory and its applications to hot or dense media, neural networks and its applications to high energy data analysis. Speakers were among his closest collaborators and friends.

  15. A network analysis of leadership theory : the infancy of integration.

    OpenAIRE

    Meuser, J. D.; Gardner, W. L.; Dinh, J. E.; Hu, J.; Liden, R. C.; Lord, R. G.

    2016-01-01

    We investigated the status of leadership theory integration by reviewing 14 years of published research (2000 through 2013) in 10 top journals (864 articles). The authors of these articles examined 49 leadership approaches/theories, and in 293 articles, 3 or more of these leadership approaches were included in their investigations. Focusing on these articles that reflected relatively extensive integration, we applied an inductive approach and used graphic network analysis as a guide for drawi...

  16. Social Network Theory in Engineering Education

    Science.gov (United States)

    Simon, Peter A.

    Collaborative groups are important both in the learning environment of engineering education and, in the real world, the business of engineering design. Selecting appropriate individuals to form an effective group and monitoring a group's progress are important aspects of successful task performance. This exploratory study looked at using the concepts of cognitive social structures, structural balance, and centrality from social network analysis as well as the measures of emotional intelligence. The concepts were used to analyze potential team members to examine if an individual's ability to perceive emotion in others and the self and to use, understand, and manage those emotions are a factor in a group's performance. The students from a capstone design course in computer engineering were used as volunteer subjects. They were formed into groups and assigned a design exercise to determine whether and which of the above-mentioned tools would be effective in both selecting teams and predicting the quality of the resultant design. The results were inconclusive with the exception of an individual's ability to accurately perceive emotions. The instruments that were successful were the Self-Monitoring scale and the accuracy scores derived from cognitive social structures and Level IV of network levels of analysis.

  17. Bridging disparate symptoms of schizophrenia: a triple network dysfunction theory

    Czech Academy of Sciences Publication Activity Database

    Nekovářová, Tereza; Fajnerová, Iveta; Horáček, J.; Španiel, F.

    2014-01-01

    Roč. 8, May 30 (2014), s. 171 ISSN 1662-5153 R&D Projects: GA MZd(CZ) NT13386; GA ČR(CZ) GAP303/12/1464; GA ČR(CZ) GBP304/12/G069; GA ČR(CZ) GA14-03627S Grant - others:GA MZd(CZ) NT14291; GA MZd(CZ) NT13843 Institutional support: RVO:67985823 Keywords : schizophrenia * self * theory of mind * forward model * default mode network * salience network * central executive network Subject RIV: FH - Neurology Impact factor: 3.270, year: 2014

  18. The structure of complex networks theory and applications

    CERN Document Server

    Estrada, Ernesto

    2012-01-01

    This book deals with the analysis of the structure of complex networks by combining results from graph theory, physics, and pattern recognition. The book is divided into two parts. 11 chapters are dedicated to the development of theoretical tools for the structural analysis of networks, and 7 chapters are illustrating, in a critical way, applications of these tools to real-world scenarios. The first chapters provide detailed coverage of adjacency and metric and topologicalproperties of networks, followed by chapters devoted to the analysis of individual fragments and fragment-based global inva

  19. Quantized detector networks the theory of observation

    CERN Document Server

    Jaroszkiewicz, George

    2017-01-01

    Scientists have been debating the meaning of quantum mechanics for over a century. This book for graduate students and researchers gets to the root of the problem; the contextual nature of empirical truth, the laws of observation and how these impact on our understanding of quantum physics. Bridging the gap between non-relativistic quantum mechanics and quantum field theory, this novel approach to quantum mechanics extends the standard formalism to cover the observer and their apparatus. The author demystifies some of the aspects of quantum mechanics that have traditionally been regarded as extraordinary, such as wave-particle duality and quantum superposition, by emphasizing the scientific principles rather than the mathematical modelling involved. Including key experiments and worked examples throughout to encourage the reader to focus on empirically sound concepts, this book avoids metaphysical speculation and also alerts the reader to the use of computer algebra to explore quantum experiments of virtually...

  20. Actor-Network Theory and Tourism : Ordering, materiality and multiplicity

    NARCIS (Netherlands)

    Duim, van der V.R.; Ren, C.; Jóhannesson, G.T.

    2012-01-01

    The recent surfacing of actor-network theory (ANT) in tourism studies correlates to a rising interest in understanding tourism as emergent thorough relational practice connecting cultures, natures and technologies in multifarious ways. Despite the widespread application of ANT across the social

  1. Effects of Actor-Network Theory in Accounting Research

    DEFF Research Database (Denmark)

    Justesen, Lise Nederland; Mouritsen, Jan

    2011-01-01

    Purpose – This paper aims to discuss how Bruno Latour's version of actor-network theory has influenced accounting research. It also seeks to show that Latour's writings contain unexplored potential that may inspire future accounting research. Design/methodology/approach – The paper takes the form...

  2. Actor/Actant-Network Theory as Emerging Methodology for ...

    African Journals Online (AJOL)

    This paper deliberates on actor/actant-network theory (AANT) as methodology for policy research in environmental education (EE). Insights are drawn from work that applied AANT to research environmental policy processes surrounding the formulation and implementation of South Africa's Plastic Bags Regulations of 2003.

  3. Network theory and its applications in economic systems

    Science.gov (United States)

    Huang, Xuqing

    This dissertation covers the two major parts of my Ph.D. research: i) developing theoretical framework of complex networks; and ii) applying complex networks models to quantitatively analyze economics systems. In part I, we focus on developing theories of interdependent networks, which includes two chapters: 1) We develop a mathematical framework to study the percolation of interdependent networks under targeted-attack and find that when the highly connected nodes are protected and have lower probability to fail, in contrast to single scale-free (SF) networks where the percolation threshold pc = 0, coupled SF networks are significantly more vulnerable with pc significantly larger than zero. 2) We analytically demonstrates that clustering, which quantifies the propensity for two neighbors of the same vertex to also be neighbors of each other, significantly increases the vulnerability of the system. In part II, we apply the complex networks models to study economics systems, which also includes two chapters: 1) We study the US corporate governance network, in which nodes representing directors and links between two directors representing their service on common company boards, and propose a quantitative measure of information and influence transformation in the network. Thus we are able to identify the most influential directors in the network. 2) We propose a bipartite networks model to simulate the risk propagation process among commercial banks during financial crisis. With empirical bank's balance sheet data in 2007 as input to the model, we find that our model efficiently identifies a significant portion of the actual failed banks reported by Federal Deposit Insurance Corporation during the financial crisis between 2008 and 2011. The results suggest that complex networks model could be useful for systemic risk stress testing for financial systems. The model also identifies that commercial rather than residential real estate assets are major culprits for the

  4. The Network Theory of Well-Being: An Introduction

    Directory of Open Access Journals (Sweden)

    Michael Bishop

    2012-11-01

    Full Text Available In this paper, I propose a novel approach to investigating the nature of well-being and a new theory about well-being. The approach is integrative and naturalistic. It holds that a theory of well-being should account for two different classes of evidence – our commonsense judgments about well-being and the science of well-being (i.e., positive psychology. The network theory holds that a person is in the state of well-being if she instantiates a homeostatically clustered network of feelings, emotions, attitudes, behaviors, traits, and interactions with the world that tends to have a relatively high number of states that feel good, that lead to states that feel good, or that are valued by the agent or her culture.

  5. Towards a predictive theory for genetic regulatory networks

    Science.gov (United States)

    Tkacik, Gasper

    When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

  6. Analyzing complex networks evolution through Information Theory quantifiers

    International Nuclear Information System (INIS)

    Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martin Gomez

    2011-01-01

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  7. Analyzing complex networks evolution through Information Theory quantifiers

    Energy Technology Data Exchange (ETDEWEB)

    Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)

    2011-01-24

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  8. Water supply network district metering theory and case study

    CERN Document Server

    Di Nardo, Armando; Di Mauro, Anna

    2013-01-01

    The management of a water supply network can be substantially improved defining permanent sectors or districts that enhances simpler water loss detection and pressure management. However, the water network partitioning may compromise water system performance, since some pipes are usually closed to delimit districts in order not to have too many metering stations, to decrease costs and simplify water balance. This may reduce the reliability of the whole system and not guarantee the delivery of water at the different network nodes. In practical applications, the design of districts or sectors is generally based on empirical approaches or on limited field experiences. The book proposes a design support methodology, based on graph theory principles and tested on real case study. The described methodology can help water utilities, professionals and researchers to define the optimal districts or sectors of a water supply network.

  9. Dynamical graph theory networks techniques for the analysis of sparse connectivity networks in dementia

    Science.gov (United States)

    Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke

    2017-05-01

    Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.

  10. Theorising big IT programmes in healthcare: strong structuration theory meets actor-network theory.

    Science.gov (United States)

    Greenhalgh, Trisha; Stones, Rob

    2010-05-01

    The UK National Health Service is grappling with various large and controversial IT programmes. We sought to develop a sharper theoretical perspective on the question "What happens - at macro-, meso- and micro-level - when government tries to modernise a health service with the help of big IT?" Using examples from data fragments at the micro-level of clinical work, we considered how structuration theory and actor-network theory (ANT) might be combined to inform empirical investigation. Giddens (1984) argued that social structures and human agency are recursively linked and co-evolve. ANT studies the relationships that link people and technologies in dynamic networks. It considers how discourses become inscribed in data structures and decision models of software, making certain network relations irreversible. Stones' (2005) strong structuration theory (SST) is a refinement of Giddens' work, systematically concerned with empirical research. It views human agents as linked in dynamic networks of position-practices. A quadripartite approcach considers [a] external social structures (conditions for action); [b] internal social structures (agents' capabilities and what they 'know' about the social world); [c] active agency and actions and [d] outcomes as they feed back on the position-practice network. In contrast to early structuration theory and ANT, SST insists on disciplined conceptual methodology and linking this with empirical evidence. In this paper, we adapt SST for the study of technology programmes, integrating elements from material interactionism and ANT. We argue, for example, that the position-practice network can be a socio-technical one in which technologies in conjunction with humans can be studied as 'actants'. Human agents, with their complex socio-cultural frames, are required to instantiate technology in social practices. Structurally relevant properties inscribed and embedded in technological artefacts constrain and enable human agency. The fortunes

  11. Ordering, materiality, and multiplicity: Enacting Actor–Network Theory in tourism

    NARCIS (Netherlands)

    Duim, van der R.; Ren, C.; Johannesson, G.T.

    2013-01-01

    In this article, we demonstrate how Actor–Network Theory has been translated into tourism research. The article presents and discusses three concepts integral to the Actor–Network Theory approach: ordering, materiality, and multiplicity. We first briefly introduce Actor–Network Theory and draw

  12. Review of network research in scientific journal ‘Entrepreneurship Theory and Practice’

    OpenAIRE

    Agnieszka Brzozowska; Michał Zdziarski

    2016-01-01

    This article aims at presenting a systematic review of publications that verified the network theory and the theory of networks empirically, published in the entrepreneurship journal with the highest Impact Factor: “Entrepreneurship Theory and Practice”. We present how publication frequency evolved over time, and classify papers into major streams of entrepreneurship research. Our findings suggest the theory of networks is an under-researched area promising for further advancing the theory of...

  13. Animal Social Network Theory Can Help Wildlife Conservation.

    Science.gov (United States)

    Snijders, Lysanne; Blumstein, Daniel T; Stanley, Christina R; Franks, Daniel W

    2017-08-01

    Many animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting, and potentially manipulating population dynamics. Various network statistics can correlate with individual fitness components and key population-level processes, yet the logical role and formal application of animal social network theory for conservation and management have not been well articulated. We outline how understanding of direct and indirect relationships between animals can be profitably applied by wildlife managers and conservationists. By doing so, we aim to stimulate the development and implementation of practical tools for wildlife conservation and management and to inspire novel behavioral research in this field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Transient response of nonlinear polymer networks: A kinetic theory

    Science.gov (United States)

    Vernerey, Franck J.

    2018-06-01

    Dynamic networks are found in a majority of natural materials, but also in engineering materials, such as entangled polymers and physically cross-linked gels. Owing to their transient bond dynamics, these networks display a rich class of behaviors, from elasticity, rheology, self-healing, or growth. Although classical theories in rheology and mechanics have enabled us to characterize these materials, there is still a gap in our understanding on how individuals (i.e., the mechanics of each building blocks and its connection with others) affect the emerging response of the network. In this work, we introduce an alternative way to think about these networks from a statistical point of view. More specifically, a network is seen as a collection of individual polymer chains connected by weak bonds that can associate and dissociate over time. From the knowledge of these individual chains (elasticity, transient attachment, and detachment events), we construct a statistical description of the population and derive an evolution equation of their distribution based on applied deformation and their local interactions. We specifically concentrate on nonlinear elastic response that follows from the strain stiffening response of individual chains of finite size. Upon appropriate averaging operations and using a mean field approximation, we show that the distribution can be replaced by a so-called chain distribution tensor that is used to determine important macroscopic measures such as stress, energy storage and dissipation in the network. Prediction of the kinetic theory are then explored against known experimental measurement of polymer responses under uniaxial loading. It is found that even under the simplest assumptions of force-independent chain kinetics, the model is able to reproduce complex time-dependent behaviors of rubber and self-healing supramolecular polymers.

  15. Game Theory for Wireless Sensor Networks: A Survey

    Science.gov (United States)

    Shi, Hai-Yan; Wang, Wan-Liang; Kwok, Ngai-Ming; Chen, Sheng-Yong

    2012-01-01

    Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field. PMID:23012533

  16. Game Theory for Wireless Sensor Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Ngai-Ming Kwok

    2012-07-01

    Full Text Available Game theory (GT is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs. This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field.

  17. Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

    Directory of Open Access Journals (Sweden)

    Rui Ding

    Full Text Available Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

  18. Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

    Science.gov (United States)

    Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

    2015-01-01

    Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

  19. Network Theory and Effects of Transcranial Brain Stimulation Methods on the Brain Networks

    Directory of Open Access Journals (Sweden)

    Sema Demirci

    2014-12-01

    Full Text Available In recent years, there has been a shift from classic localizational approaches to new approaches where the brain is considered as a complex system. Therefore, there has been an increase in the number of studies involving collaborations with other areas of neurology in order to develop methods to understand the complex systems. One of the new approaches is graphic theory that has principles based on mathematics and physics. According to this theory, the functional-anatomical connections of the brain are defined as a network. Moreover, transcranial brain stimulation techniques are amongst the recent research and treatment methods that have been commonly used in recent years. Changes that occur as a result of applying brain stimulation techniques on physiological and pathological networks help better understand the normal and abnormal functions of the brain, especially when combined with techniques such as neuroimaging and electroencephalography. This review aims to provide an overview of the applications of graphic theory and related parameters, studies conducted on brain functions in neurology and neuroscience, and applications of brain stimulation systems in the changing treatment of brain network models and treatment of pathological networks defined on the basis of this theory.

  20. Theory and design of broadband matching networks applied electricity and electronics

    CERN Document Server

    Chen, Wai-Kai

    1976-01-01

    Theory and Design of Broadband Matching Networks centers on the network theory and its applications to the design of broadband matching networks and amplifiers. Organized into five chapters, this book begins with a description of the foundation of network theory. Chapter 2 gives a fairly complete exposition of the scattering matrix associated with an n-port network. Chapter 3 considers the approximation problem along with a discussion of the approximating functions. Chapter 4 explains the Youla's theory of broadband matching by illustrating every phase of the theory with fully worked out examp

  1. Theory of liquid crystal elastomers and polymer networks : Connection between neoclassical theory and differential geometry.

    Science.gov (United States)

    Nguyen, Thanh-Son; Selinger, Jonathan V

    2017-09-01

    In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.

  2. European Conference on Game Theory & Networking Games and Management

    CERN Document Server

    Mazalov, Vladimir

    2016-01-01

    This contributed volume contains fourteen papers based on selected presentations from the European Conference on Game Theory SING11-GTM 2015, held at Saint Petersburg State University in July 2015, and the Networking Games and Management workshop, held at the Karelian Research Centre of the Russian Academy of Sciences in Petrozvavodsk, Russia, also in July 2015. These papers cover a wide range of topics in game theory, including recent advances in areas with high potential for future work, as well as new developments on classical results. Some of these include A new approach to journal ranking using methods from social choice theory; A differential game of a duopoly in which two firms are competing for market share in an industry with network externalities; The impact of information propagation in the model of tax audits; A voting model in which the results of previous votes can affect the process of coalition formation in a decision-making body; The Selten-Szidarovsky technique for the analysis of Nash equil...

  3. Matching Theory for Channel Allocation in Cognitive Radio Networks

    Directory of Open Access Journals (Sweden)

    L. Cao

    2016-12-01

    Full Text Available For a cognitive radio network (CRN in which a set of secondary users (SUs competes for a limited number of channels (spectrum resources belonging to primary users (PUs, the channel allocation is a challenge and dominates the throughput and congestion of the network. In this paper, the channel allocation problem is first formulated as the 0-1 integer programming optimization, with considering the overall utility both of primary system and secondary system. Inspired by matching theory, a many-to-one matching game is used to remodel the channel allocation problem, and the corresponding PU proposing deferred acceptance (PPDA algorithm is also proposed to yield a stable matching. We compare the performance and computation complexity between these two solutions. Numerical results demonstrate the efficiency and obtain the communication overhead of the proposed scheme.

  4. Bridging disparate symptoms of schizophrenia: a Triple network dysfunction theory

    Directory of Open Access Journals (Sweden)

    Tereza eNekovarova

    2014-05-01

    Full Text Available Schizophrenia is a complex neuropsychiatric disorder with variable symptomatology, traditionally divided into positive and negative symptoms, and cognitive deficits. Yet, the etiology of this disorder has yet to be fully understood.Recent findings suggest that alteration of the basic sense of self-awareness may be an essential distortion of schizophrenia spectrum disorders. In addition, extensive research of social and mentalizing abilities has stressed the role of distortion of social skills in schizophrenia.This article aims to propose and support a concept of triple brain network model of the dysfunctional switching between default mode and central executive network related to the aberrant activity of salience network. This model could represent a unitary mechanism of a wide array of symptom domains present in schizophrenia including the deficit of SELF (self-awareness and self-representation and theory of mind (ToM dysfunctions along with the traditional positive, negative and cognitive domains. We review previous studies which document the dysfunctions of SELF and ToM in schizophrenia together with neuroimaging data elucidating the triple brain network model as a common neuronal substrate of this dysfunction.

  5. Pearson's correlation coefficient in the theory of networks: A comment

    OpenAIRE

    Ahmed, Zafar; Kumar, Sachin

    2018-01-01

    In statistics, the Pearson correlation coefficient $r_{x,y}$ determines the degree of linear correlation between two variables and it is known that $-1 \\le r_{x,y} \\le 1$. In the theory of networks, a curious expression proposed in [PRL {\\bf 89} 208701 (2002)] for degree-degree correlation coefficient $r_{j_i,k_i}, i\\in [1,M]$ has been in use. We realize that the suggested form is the conventional Pearson's coefficient for $\\{(j_i,k_i), (k_i,j_i)\\}$ for $2M$ data points and hence it is rightl...

  6. Disaggregated regulation in network sections: The normative and positive theory; Disaggregierte Regulierung in Netzsektoren: Normative und positive Theorie

    Energy Technology Data Exchange (ETDEWEB)

    Knieps, G. [Inst. fuer Verkehrswissenschaft und Regionalpolitik, Albert-Ludwigs-Univ. Freiburg i.B. (Germany)

    2007-09-15

    The article deals with the interaction of normative and positive theorie of regulation. Those parts of the network which need regulation could be localised and regulated with the help of the normative theory of the monopolistic bottlenecks. Using the positive theory, the basic elements of a mandate for regulation in the sense of the disaggregated economy of regulation are derived.

  7. Searching for realism, structure and agency in Actor Network Theory.

    Science.gov (United States)

    Elder-Vass, Dave

    2008-09-01

    Superficially, Actor Network Theory (ANT) and critical realism (CR) are radically opposed research traditions. Written from a realist perspective, this paper asks whether there might be a basis for finding common ground between these two traditions. It looks in turn at the questions of realism, structure, and agency, analysing the differences between the two perspectives and seeking to identify what each might learn from the other. Overall, the paper argues that there is a great deal that realists can learn from actor network theory; yet ANT remains stunted by its lack of a depth ontology. It fails to recognize the significance of mechanisms, and of their dependence on emergence, and thus lacks both dimensions of the depth that is characteristic of critical realism's ontology. This prevents ANT from recognizing the role and powers of social structure; but on the other hand, realists would do well to heed ANT's call for us to trace the connections through which structures are constantly made and remade. A lack of ontological depth also underpins ANT's practice of treating human and non-human actors symmetrically, yet this remains a valuable provocation to sociologists who neglect non-human entities entirely.

  8. Using actor-network theory to study an educational situation: an ...

    African Journals Online (AJOL)

    Actor-network theory allows a researcher to analyse a complex social setting involving both human and non-human actors. An actor network can be used to model a dynamic and complex set of relationships between these actors. This article describes actor-network theory and shows how it was applied to study and model ...

  9. Multispectral Image classification using the theories of neural networks

    International Nuclear Information System (INIS)

    Ardisasmita, M.S.; Subki, M.I.R.

    1997-01-01

    Image classification is the one of the important part of digital image analysis. the objective of image classification is to identify and regroup the features occurring in an image into one or several classes in terms of the object. basic to the understanding of multispectral classification is the concept of the spectral response of an object as a function of the electromagnetic radiation and the wavelength of the spectrum. new approaches to classification has been developed to improve the result of analysis, these state-of-the-art classifiers are based upon the theories of neural networks. Neural network classifiers are algorithmes which mimic the computational abilities of the human brain. Artificial neurons are simple emulation's of biological neurons; they take in information from sensors or other artificial neurons, perform very simple operations on this data, and pass the result to other recognize the spectral signature of each image pixel. Neural network image classification has been divided into supervised and unsupervised training procedures. In the supervised approach, examples of each cover type can be located and the computer can compute spectral signatures to categorize all pixels in a digital image into several land cover classes. In supervised classification, spectral signatures are generated by mathematically grouping and it does not require analyst-specified training data. Thus, in the supervised approach we define useful information categories and then examine their spectral reparability; in the unsupervised approach the computer determines spectrally sapable classes and then we define thei information value

  10. Toward a Theory of Industrial Supply Networks: A Multi-Level Perspective via Network Analysis

    Directory of Open Access Journals (Sweden)

    Yi Zuo

    2017-07-01

    Full Text Available In most supply chains (SCs, transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS, and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs.

  11. Actor-network Theory and cartography of controversies in Information Science

    OpenAIRE

    LOURENÇO, Ramon Fernandes; TOMAÉL, Maria Inês

    2018-01-01

    Abstract The present study aims to discuss the interactions between the Actor-network Theory and the Cartography of Controversies method in Information Science research. A literature review was conducted on books, scholarly articles, and any other sources addressing the Theory-Actor Network and Cartography of Controversies. The understanding of the theoretical assumptions that guide the Network-Actor Theory allows examining important aspects to Information Science research, seeking to identif...

  12. Bridging the Gap in Port Security; Network Centric Theory Applied to Public/Private Collaboration

    National Research Council Canada - National Science Library

    Wright, Candice L

    2007-01-01

    ...." Admiral Thad Allen, 2007 The application of Network Centric Warfare theory enables all port stakeholders to better prepare for a disaster through increased information sharing and collaboration...

  13. Differential theory of learning for efficient neural network pattern recognition

    Science.gov (United States)

    Hampshire, John B., II; Vijaya Kumar, Bhagavatula

    1993-09-01

    We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

  14. Application of Game Theory Approaches in Routing Protocols for Wireless Networks

    Science.gov (United States)

    Javidi, Mohammad M.; Aliahmadipour, Laya

    2011-09-01

    An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.

  15. From static to temporal network theory: Applications to functional brain connectivity

    Directory of Open Access Journals (Sweden)

    William Hedley Thompson

    2017-06-01

    Full Text Available Network neuroscience has become an established paradigm to tackle questions related to the functional and structural connectome of the brain. Recently, interest has been growing in examining the temporal dynamics of the brain’s network activity. Although different approaches to capturing fluctuations in brain connectivity have been proposed, there have been few attempts to quantify these fluctuations using temporal network theory. This theory is an extension of network theory that has been successfully applied to the modeling of dynamic processes in economics, social sciences, and engineering article but it has not been adopted to a great extent within network neuroscience. The objective of this article is twofold: (i to present a detailed description of the central tenets of temporal network theory and describe its measures, and; (ii to apply these measures to a resting-state fMRI dataset to illustrate their utility. Furthermore, we discuss the interpretation of temporal network theory in the context of the dynamic functional brain connectome. All the temporal network measures and plotting functions described in this article are freely available as the Python package Teneto. Temporal network theory is a subfield of network theory that has had limited application to date within network neuroscience. The aims of this work are to introduce temporal network theory, define the metrics relevant to the context of network neuroscience, and illustrate their potential by analyzing a resting-state fMRI dataset. We found both between-subjects and between-task differences that illustrate the potential for these tools to be applied in a wider context. Our tools for analyzing temporal networks have been released in a Python package called Teneto.

  16. Review of network research in scientific journal ‘Entrepreneurship Theory and Practice’

    Directory of Open Access Journals (Sweden)

    Agnieszka Brzozowska

    2016-10-01

    Full Text Available This article aims at presenting a systematic review of publications that verified the network theory and the theory of networks empirically, published in the entrepreneurship journal with the highest Impact Factor: “Entrepreneurship Theory and Practice”. We present how publication frequency evolved over time, and classify papers into major streams of entrepreneurship research. Our findings suggest the theory of networks is an under-researched area promising for further advancing the theory of entrepreneurship. We also find increasing publication frequency of network related research over time. Results oriented research were most often present in reviewed articles, while relationship among network variables and innovation was only tested in two articles so far which suggests that more research is needed in this direction in the future. We belief that verification of theories of networks in entrepreneurship and verification of relationship between network variables and innovation within the network theory are most promising. The originality of this work lies in identification of research opportunities and dynamics of empirical verification of network studies in the field of entrepreneurship.

  17. Finding influential nodes for integration in brain networks using optimal percolation theory.

    Science.gov (United States)

    Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

    2018-06-11

    Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

  18. Social Support Theory: A New Framework for Exploring Gender Differences in Business Owner Networks

    DEFF Research Database (Denmark)

    Neergaard, Helle

    The paper argues that to advance knowledge about small firm networks and consider the impact of gender, research should also consider the network experiences of women business owners. To engage in such research, this paper proposes a conceptual model of business owner networking which is informed...... by social support theory....

  19. Non-parametric Bayesian networks: Improving theory and reviewing applications

    International Nuclear Information System (INIS)

    Hanea, Anca; Morales Napoles, Oswaldo; Ababei, Dan

    2015-01-01

    Applications in various domains often lead to high dimensional dependence modelling. A Bayesian network (BN) is a probabilistic graphical model that provides an elegant way of expressing the joint distribution of a large number of interrelated variables. BNs have been successfully used to represent uncertain knowledge in a variety of fields. The majority of applications use discrete BNs, i.e. BNs whose nodes represent discrete variables. Integrating continuous variables in BNs is an area fraught with difficulty. Several methods that handle discrete-continuous BNs have been proposed in the literature. This paper concentrates only on one method called non-parametric BNs (NPBNs). NPBNs were introduced in 2004 and they have been or are currently being used in at least twelve professional applications. This paper provides a short introduction to NPBNs, a couple of theoretical advances, and an overview of applications. The aim of the paper is twofold: one is to present the latest improvements of the theory underlying NPBNs, and the other is to complement the existing overviews of BNs applications with the NPNBs applications. The latter opens the opportunity to discuss some difficulties that applications pose to the theoretical framework and in this way offers some NPBN modelling guidance to practitioners. - Highlights: • The paper gives an overview of the current NPBNs methodology. • We extend the NPBN methodology by relaxing the conditions of one of its fundamental theorems. • We propose improvements of the data mining algorithm for the NPBNs. • We review the professional applications of the NPBNs.

  20. Sigmund Freud-early network theories of the brain.

    Science.gov (United States)

    Surbeck, Werner; Killeen, Tim; Vetter, Johannes; Hildebrandt, Gerhard

    2018-06-01

    Since the early days of modern neuroscience, psychological models of brain function have been a key component in the development of new knowledge. These models aim to provide a framework that allows the integration of discoveries derived from the fundamental disciplines of neuroscience, including anatomy and physiology, as well as clinical neurology and psychiatry. During the initial stages of his career, Sigmund Freud (1856-1939), became actively involved in these nascent fields with a burgeoning interest in functional neuroanatomy. In contrast to his contemporaries, Freud was convinced that cognition could not be localised to separate modules and that the brain processes cognition not in a merely serial manner but in a parallel and dynamic fashion-anticipating fundamental aspects of current network theories of brain function. This article aims to shed light on Freud's seminal, yet oft-overlooked, early work on functional neuroanatomy and his reasons for finally abandoning the conventional neuroscientific "brain-based" reference frame in order to conceptualise the mind from a purely psychological perspective.

  1. Policy learning and policy networks in theory and practice: The role of policy brokers in the Indonesian biodiesel policy network

    NARCIS (Netherlands)

    M. Howlett (Michael); Mukherjee, I. (Ishani); J.F.M. Koppenjan (Joop)

    2017-01-01

    textabstractThis paper examines how learning has been treated, generally, in policy network theories and what questions have been posed, and answered, about this phenomenon to date. We examine to what extent network characteristics and especially the presence of various types of brokers impede or

  2. A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

    OpenAIRE

    Zhao Hong-hao; Meng Fan-bo; Zhao Si-wen; Zhao Si-hang; Lu Yi

    2016-01-01

    Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distrib...

  3. A theory of intelligence: networked problem solving in animal societies

    OpenAIRE

    Shour, Robert

    2009-01-01

    A society's single emergent, increasing intelligence arises partly from the thermodynamic advantages of networking the innate intelligence of different individuals, and partly from the accumulation of solved problems. Economic growth is proportional to the square of the network entropy of a society's population times the network entropy of the number of the society's solved problems.

  4. Actor Network Theory Approach and its Application in Investigating Agricultural Climate Information System

    Directory of Open Access Journals (Sweden)

    Maryam Sharifzadeh

    2013-03-01

    Full Text Available Actor network theory as a qualitative approach to study complex social factors and process of socio-technical interaction provides new concepts and ideas to understand socio-technical nature of information systems. From the actor network theory viewpoint, agricultural climate information system is a network consisting of actors, actions and information related processes (production, transformation, storage, retrieval, integration, diffusion and utilization, control and management, and system mechanisms (interfaces and networks. Analysis of such systemsembody the identification of basic components and structure of the system (nodes –thedifferent sources of information production, extension, and users, and the understanding of how successfully the system works (interaction and links – in order to promote climate knowledge content and improve system performance to reach agricultural development. The present research attempted to introduce actor network theory as research framework based on network view of agricultural climate information system.

  5. On the Control of Consensus Networks: Theory and Applications

    Science.gov (United States)

    Hudoba de Badyn, Mathias

    Signed networks allow the study of positive and negative interactions between agents. In this thesis, three papers are presented that address controllability of networked dynamics. First, controllability of signed consensus networks is approached from a symmetry perspective, for both linear and nonlinear consensus protocols. It is shown that the graph-theoretic property of signed networks known as structural balance renders the consensus protocol uncontrollable when coupled with a certain type of symmetry. Stabilizability and output controllability of signed linear consensus is also examined, as well as a data-driven approach to finding bipartite consensus stemming from structural balance for signed nonlinear consensus. Second, an algorithm is constructed that allows one to grow a network while preserving controllability, and some generalizations of this algorithm are presented. Submodular optimization is used to analyze a second algorithm that adds nodes to a network to maximize the network connectivity.

  6. GCPSO in cooperation with graph theory to distribution network reconfiguration for energy saving

    International Nuclear Information System (INIS)

    Assadian, Mehdi; Farsangi, Malihe M.; Nezamabadi-pour, Hossein

    2010-01-01

    Network reconfiguration for loss reduction in distribution system is an important way to save energy. This paper investigates the ability of guaranteed convergence particle swarm optimization (GCPSO) and particle swarm optimization (PSO) in cooperation with graph theory for network reconfiguration to reduce the power loss and enhancement of voltage profile of distribution systems. Numerical results of three distribution systems are presented which illustrate the feasibility of the proposed method by GCPSO and PSO using the graph theory. To validate the obtained results, genetic algorithm (GA) using graph theory is also applied and is compared with the proposed GCPSO and PSO using graph theory.

  7. Self-similarity and scaling theory of complex networks

    Science.gov (United States)

    Song, Chaoming

    Scale-free networks have been studied extensively due to their relevance to many real systems as diverse as the World Wide Web (WWW), the Internet, biological and social networks. We present a novel approach to the analysis of scale-free networks, revealing that their structure is self-similar. This result is achieved by the application of a renormalization procedure which coarse-grains the system into boxes containing nodes within a given "size". Concurrently, we identify a power-law relation between the number of boxes needed to cover the network and the size of the box defining a self-similar exponent, which classifies fractal and non-fractal networks. By using the concept of renormalization as a mechanism for the growth of fractal and non-fractal modular networks, we show that the key principle that gives rise to the fractal architecture of networks is a strong effective "repulsion" between the most connected nodes (hubs) on all length scales, rendering them very dispersed. We show that a robust network comprised of functional modules, such as a cellular network, necessitates a fractal topology, suggestive of a evolutionary drive for their existence. These fundamental properties help to understand the emergence of the scale-free property in complex networks.

  8. Parallel Distributed Processing theory in the age of deep networks

    OpenAIRE

    Bowers, Jeffrey

    2017-01-01

    Parallel Distributed Processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely, that all knowledge is coded in a distributed format, and cognition is mediated by non-symbolic computations. These claims have long been debated within cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks le...

  9. Linking experiment and theory for three-dimensional networked binary metal nanoparticle–triblock terpolymer superstructures

    KAUST Repository

    Li, Zihui; Hur, Kahyun; Sai, Hiroaki; Higuchi, Takeshi; Takahara, Atsushi; Jinnai, Hiroshi; Gruner, Sol M.; Wiesner, Ulrich

    2014-01-01

    the intimate coupling of synthesis, in-depth electron tomographic characterization and theory enables exquisite control of superstructure in highly ordered porous three-dimensional continuous networks from single and binary mixtures of metal nanoparticles

  10. Mitigating Free Riding in Peer-To-Peer Networks: Game Theory ...

    African Journals Online (AJOL)

    Mitigating Free Riding in Peer-To-Peer Networks: Game Theory Approach. ... In this paper, we model the interactions between peers as a modified gift giving game and proposed an utility exchange incentive ... AJOL African Journals Online.

  11. Design of analog networks in the control theory formulation. Part 2: Numerical results

    OpenAIRE

    Zemliak, A. M.

    2005-01-01

    The paper presents numerical results of design of nonlinear electronic networks based on the problem formulation in terms of the control theory. Several examples illustrate the prospects of the approach suggested in the first part of the work.

  12. A social network model for the development of a 'Theory of Mind'

    Science.gov (United States)

    Harré, Michael S.

    2013-02-01

    A "Theory of Mind" is one of the most important skills we as humans have developed; It enables us to infer the mental states and intentions of others, build stable networks of relationships and it plays a central role in our psychological make-up and development. Findings published earlier this year have also shown that we as a species as well as each of us individually benefit from the enlargement of the underlying neuro-anatomical regions that support our social networks, mediated by our Theory of Mind that stabilises these networks. On the basis of such progress and that of earlier work, this paper draws together several different strands from psychology, behavioural economics and network theory in order to generate a novel theoretical representation of the development of our social-cognition and how subsequent larger social networks enables much of our cultural development but at the increased risk of mental disorders.

  13. The network perspective: an integration of attachment and family systems theories.

    Science.gov (United States)

    Kozlowska, Kasia; Hanney, Lesley

    2002-01-01

    In this article we discuss the network paradigm as a useful base from which to integrate attachment and family systems theories. The network perspective refers to the application of general systems theory to living systems, and provides a framework that conceptualizes the dyadic and family systems as simultaneously distinct and interconnected. Network thinking requires that the clinician holds multiple perspectives in mind, considers each system level as both a part and a whole, and shifts the focus of attention between levels as required. Key epistemological issues that have hindered the integration of the theories are discussed. These include inconsistencies within attachment theory itself and confusion surrounding the theoretical conceptualizations of the relationship between attachment and family systems theories. Detailed information about attachment categories is provided using the Dynamic Maturational model. Case vignettes illustrating work with young children and their families explore the clinical implications of integrating attachment data into family therapy practice.

  14. Networking Theories on Giftedness--What We Can Learn from Synthesizing Renzulli's Domain General and Krutetskii's Mathematics-Specific Theory

    Science.gov (United States)

    Schindler, Maike; Rott, Benjamin

    2017-01-01

    Giftedness is an increasingly important research topic in educational sciences and mathematics education in particular. In this paper, we contribute to further theorizing mathematical giftedness through illustrating how networking processes can be conducted and illustrating their potential benefits. The paper focuses on two theories: Renzulli's…

  15. Inventory theory, mode choice and network structure in freight transport

    NARCIS (Netherlands)

    Combes, F.; Tavasszy, L.A.

    2016-01-01

    In passenger transport, hub-and-spoke networks allow the transportation of small passenger flows with competitive frequencies, in a way that direct line networks cannot. Equivalently, in freight transport, it can be expected that small shipper-receiver flows of high added value commodities transit

  16. A Brief Historical Introduction to Euler's Formula for Polyhedra, Topology, Graph Theory and Networks

    Science.gov (United States)

    Debnath, Lokenath

    2010-01-01

    This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Konigsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real…

  17. A social network perspective on teacher collaboration in schools: Theory, methodology, and applications

    NARCIS (Netherlands)

    Moolenaar, Nienke

    2012-01-01

    An emerging trend in educational research is the use of social network theory and methodology to understand how teacher collaboration can support or constrain teaching, learning, and educational change. This article provides a critical synthesis of educational literature on school social networks

  18. Group field theory and tensor networks: towards a Ryu–Takayanagi formula in full quantum gravity

    Science.gov (United States)

    Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi

    2018-06-01

    We establish a dictionary between group field theory (thus, spin networks and random tensors) states and generalized random tensor networks. Then, we use this dictionary to compute the Rényi entropy of such states and recover the Ryu–Takayanagi formula, in two different cases corresponding to two different truncations/approximations, suggested by the established correspondence.

  19. Extending the theory of normative practices : an application to two cases of networked military operations

    NARCIS (Netherlands)

    Burken, van C.G.; Vries, de M.J.

    2012-01-01

    The theory of normative practices has proven to be helpful in eliciting the normative dimension of social practices. In this article we apply the theory to military practice. Since current military missions are Network Enabled Operations, which mandate a strong focus on cooperation with other

  20. Toward a generalized theory of epidemic awareness in social networks

    Science.gov (United States)

    Wu, Qingchu; Zhu, Wenfang

    We discuss the dynamics of a susceptible-infected-susceptible (SIS) model with local awareness in networks. Individual awareness to the infectious disease is characterized by a general function of epidemic information in its neighborhood. We build a high-accuracy approximate equation governing the spreading dynamics and derive an approximate epidemic threshold above which the epidemic spreads over the whole network. Our results extend the previous work and show that the epidemic threshold is dependent on the awareness function in terms of one infectious neighbor. Interestingly, when a pow-law awareness function is chosen, the epidemic threshold can emerge in infinite networks.

  1. Theory of fractional order elements based impedance matching networks

    KAUST Repository

    Radwan, Ahmed G.

    2011-03-01

    Fractional order circuit elements (inductors and capacitors) based impedance matching networks are introduced for the first time. In comparison to the conventional integer based L-type matching networks, fractional matching networks are much simpler and versatile. Any complex load can be matched utilizing a single series fractional element, which generally requires two elements for matching in the conventional approach. It is shown that all the Smith chart circles (resistance and reactance) are actually pairs of completely identical circles. They appear to be single for the conventional integer order case, where the identical circles completely overlap each other. The concept is supported by design equations and impedance matching examples. © 2010 IEEE.

  2. Animal Social Network Theory Can Help Wildlife Conservation

    NARCIS (Netherlands)

    Snijders, Lysanne; Blumstein, Daniel T.; Stanley, Christina R.; Franks, Daniel W.

    2017-01-01

    Many animals preferentially associate with certain other individuals. This social structuring can influence how populations respond to changes to their environment, thus making network analysis a promising technique for understanding, predicting, and potentially manipulating population dynamics.

  3. Design of Network Architectures: Role of Game Theory and Economics

    OpenAIRE

    Shetty, Nikhil

    2010-01-01

    The economics of the market that a network architecture enables has a important bearing on its success and eventual adoption. Some of these economic issues are tightly coupled with the design of the network architecture. A poor design could end up making certain markets very difficult to enable, even if they are in the better interest of society. Theanalysis of these cross-disciplinary problems requires understanding both the technology and the economic aspects. This thesis introduces three m...

  4. Leveraging percolation theory to single out influential spreaders in networks

    Science.gov (United States)

    Radicchi, Filippo; Castellano, Claudio

    2016-06-01

    Among the consequences of the disordered interaction topology underlying many social, technological, and biological systems, a particularly important one is that some nodes, just because of their position in the network, may have a disproportionate effect on dynamical processes mediated by the complex interaction pattern. For example, the early adoption of a commercial product by an opinion leader in a social network may change its fate or just a few superspreaders may determine the virality of a meme in social media. Despite many recent efforts, the formulation of an accurate method to optimally identify influential nodes in complex network topologies remains an unsolved challenge. Here, we present the exact solution of the problem for the specific, but highly relevant, case of the susceptible-infected-removed (SIR) model for epidemic spreading at criticality. By exploiting the mapping between bond percolation and the static properties of the SIR model, we prove that the recently introduced nonbacktracking centrality is the optimal criterion for the identification of influential spreaders in locally tree-like networks at criticality. By means of simulations on synthetic networks and on a very extensive set of real-world networks, we show that the nonbacktracking centrality is a highly reliable metric to identify top influential spreaders also in generic graphs not embedded in space and for noncritical spreading.

  5. Non-equilibrium mean-field theories on scale-free networks

    International Nuclear Information System (INIS)

    Caccioli, Fabio; Dall'Asta, Luca

    2009-01-01

    Many non-equilibrium processes on scale-free networks present anomalous critical behavior that is not explained by standard mean-field theories. We propose a systematic method to derive stochastic equations for mean-field order parameters that implicitly account for the degree heterogeneity. The method is used to correctly predict the dynamical critical behavior of some binary spin models and reaction–diffusion processes. The validity of our non-equilibrium theory is further supported by showing its relation with the generalized Landau theory of equilibrium critical phenomena on networks

  6. [Attachment theory and baby slings/carriers: technological network formation].

    Science.gov (United States)

    Lu, Zxy-Yann Jane; Lin, Wan-Shiuan

    2011-12-01

    Healthcare providers recognize the important role played by attachment theory in explaining the close relationship between mental health and social behavior in mothers and their children. This paper uses attachment theory in a socio-cultural context to ascertain the mechanism by which baby slings/carriers, a new technology, produced and reproduced the scientific motherhood. It further applies a social history of technology perspective to understand how baby carriers and attachment theory are socially constructed and historically contingent on three major transformations. These transformations include the use of attachment theory-based baby carriers to further scientific motherhood; the use of baby slings/carriers to further the medicalization of breastfeeding and enhance mother-infant attachment; and the use of baby slings/carriers to transform woman's identities by integrating scientific motherhood, independence and fashion. Implications for nursing clinical policy are suggested.

  7. Satisfaction with social networks: an examination of socioemotional selectivity theory across cohorts.

    Science.gov (United States)

    Lansford, J E; Sherman, A M; Antonucci, T C

    1998-12-01

    This study examines L. L. Carstensen's (1993, 1995) socioemotional selectivity theory within and across three cohorts spanning 4 decades. Socioemotional selectivity theory predicts that as individuals age, they narrow their social networks to devote more emotional resources to fewer relationships with close friends and family. Data from 3 cohorts of nationally representative samples were analyzed to determine whether respondents' satisfaction with the size of their social networks differed by age, cohort, or both. Results support socioemotional selectivity theory: More older adults than younger adults were satisfied with the current size of their social networks rather than wanting larger networks. These findings are consistent across all cohorts. Results are discussed with respect to social relationships across the life course.

  8. Novel Congestion-Free Alternate Routing Path Scheme using Stackelberg Game Theory Model in Wireless Networks

    Directory of Open Access Journals (Sweden)

    P. Chitra

    2017-04-01

    Full Text Available Recently, wireless network technologies were designed for most of the applications. Congestion raised in the wireless network degrades the performance and reduces the throughput. Congestion-free network is quit essen- tial in the transport layer to prevent performance degradation in a wireless network. Game theory is a branch of applied mathematics and applied sciences that used in wireless network, political science, biology, computer science, philosophy and economics. e great challenges of wireless network are their congestion by various factors. E ective congestion-free alternate path routing is pretty essential to increase network performance. Stackelberg game theory model is currently employed as an e ective tool to design and formulate conges- tion issues in wireless networks. is work uses a Stackelberg game to design alternate path model to avoid congestion. In this game, leaders and followers are selected to select an alternate routing path. e correlated equilibrium is used in Stackelberg game for making better decision between non-cooperation and cooperation. Congestion was continuously monitored to increase the throughput in the network. Simulation results show that the proposed scheme could extensively improve the network performance by reducing congestion with the help of Stackelberg game and thereby enhance throughput.

  9. Automatic theory generation from analyst text files using coherence networks

    Science.gov (United States)

    Shaffer, Steven C.

    2014-05-01

    This paper describes a three-phase process of extracting knowledge from analyst textual reports. Phase 1 involves performing natural language processing on the source text to extract subject-predicate-object triples. In phase 2, these triples are then fed into a coherence network analysis process, using a genetic algorithm optimization. Finally, the highest-value sub networks are processed into a semantic network graph for display. Initial work on a well- known data set (a Wikipedia article on Abraham Lincoln) has shown excellent results without any specific tuning. Next, we ran the process on the SYNthetic Counter-INsurgency (SYNCOIN) data set, developed at Penn State, yielding interesting and potentially useful results.

  10. An Appraisal of Social Network Theory and Analysis as Applied to Public Health: Challenges and Opportunities.

    Science.gov (United States)

    Valente, Thomas W; Pitts, Stephanie R

    2017-03-20

    The use of social network theory and analysis methods as applied to public health has expanded greatly in the past decade, yielding a significant academic literature that spans almost every conceivable health issue. This review identifies several important theoretical challenges that confront the field but also provides opportunities for new research. These challenges include (a) measuring network influences, (b) identifying appropriate influence mechanisms, (c) the impact of social media and computerized communications, (d) the role of networks in evaluating public health interventions, and (e) ethics. Next steps for the field are outlined and the need for funding is emphasized. Recently developed network analysis techniques, technological innovations in communication, and changes in theoretical perspectives to include a focus on social and environmental behavioral influences have created opportunities for new theory and ever broader application of social networks to public health topics.

  11. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.

    Science.gov (United States)

    Salim, Shelly; Moh, Sangman

    2016-06-30

    A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

  12. An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

    Directory of Open Access Journals (Sweden)

    Shelly Salim

    2016-06-01

    Full Text Available A cognitive radio sensor network (CRSN is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.

  13. A game theory-based trust measurement model for social networks.

    Science.gov (United States)

    Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong

    2016-01-01

    In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.

  14. Decorated tensor network renormalization for lattice gauge theories and spin foam models

    International Nuclear Information System (INIS)

    Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian

    2016-01-01

    Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions. (paper)

  15. Decorated tensor network renormalization for lattice gauge theories and spin foam models

    Science.gov (United States)

    Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian

    2016-05-01

    Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.

  16. A Bayes Theory-Based Modeling Algorithm to End-to-end Network Traffic

    Directory of Open Access Journals (Sweden)

    Zhao Hong-hao

    2016-01-01

    Full Text Available Recently, network traffic has exponentially increasing due to all kind of applications, such as mobile Internet, smart cities, smart transportations, Internet of things, and so on. the end-to-end network traffic becomes more important for traffic engineering. Usually end-to-end traffic estimation is highly difficult. This paper proposes a Bayes theory-based method to model the end-to-end network traffic. Firstly, the end-to-end network traffic is described as a independent identically distributed normal process. Then the Bases theory is used to characterize the end-to-end network traffic. By calculating the parameters, the model is determined correctly. Simulation results show that our approach is feasible and effective.

  17. Intra- Versus Intersex Aggression: Testing Theories of Sex Differences Using Aggression Networks.

    Science.gov (United States)

    Wölfer, Ralf; Hewstone, Miles

    2015-08-01

    Two theories offer competing explanations of sex differences in aggressive behavior: sexual-selection theory and social-role theory. While each theory has specific strengths and limitations depending on the victim's sex, research hardly differentiates between intrasex and intersex aggression. In the present study, 11,307 students (mean age = 14.96 years; 50% girls, 50% boys) from 597 school classes provided social-network data (aggression and friendship networks) as well as physical (body mass index) and psychosocial (gender and masculinity norms) information. Aggression networks were used to disentangle intra- and intersex aggression, whereas their class-aggregated sex differences were analyzed using contextual predictors derived from sexual-selection and social-role theories. As expected, results revealed that sexual-selection theory predicted male-biased sex differences in intrasex aggression, whereas social-role theory predicted male-biased sex differences in intersex aggression. Findings suggest the value of explaining sex differences separately for intra- and intersex aggression with a dual-theory framework covering both evolutionary and normative components. © The Author(s) 2015.

  18. Idea Management: Perspectives from Leadership, Learning, and Network Theory

    NARCIS (Netherlands)

    D. Deichmann (Dirk)

    2012-01-01

    textabstractIn this dissertation, we focus on how leadership styles, individual learning behaviors, and social network structures drive or inhibit organizational members to repeatedly generate and develop innovative ideas. Taking the idea management programs of three multinational companies as the

  19. Discretized kinetic theory on scale-free networks

    Science.gov (United States)

    Bertotti, Maria Letizia; Modanese, Giovanni

    2016-10-01

    The network of interpersonal connections is one of the possible heterogeneous factors which affect the income distribution emerging from micro-to-macro economic models. In this paper we equip our model discussed in [1, 2] with a network structure. The model is based on a system of n differential equations of the kinetic discretized-Boltzmann kind. The network structure is incorporated in a probabilistic way, through the introduction of a link density P(α) and of correlation coefficients P(β|α), which give the conditioned probability that an individual with α links is connected to one with β links. We study the properties of the equations and give analytical results concerning the existence, normalization and positivity of the solutions. For a fixed network with P(α) = c/α q , we investigate numerically the dependence of the detailed and marginal equilibrium distributions on the initial conditions and on the exponent q. Our results are compatible with those obtained from the Bouchaud-Mezard model and from agent-based simulations, and provide additional information about the dependence of the individual income on the level of connectivity.

  20. Macroscopic Fundamental Diagram for pedestrian networks : Theory and applications

    NARCIS (Netherlands)

    Hoogendoorn, S.P.; Daamen, W.; Knoop, V.L.; Steenbakkers, Jeroen; Sarvi, Majid

    2017-01-01

    The Macroscopic Fundamental diagram (MFD) has proven to be a powerful concept in understanding and managing vehicular network dynamics, both from a theoretical angle and from a more application-oriented perspective. In this contribution, we explore the existence and the characteristics of the

  1. Integrated service resource reservation using queueing networks theory

    DEFF Research Database (Denmark)

    Brewka, Lukasz Jerzy; Iversen, Villy Bæk; Kardaras, Georgios

    2014-01-01

    This study analyses multi-server multi-service queueing networks with service protection. To guarantee each service a certain quality-of-service and at the same time ensure high utilisation of servers, a minimum capacity is reserved each service. In addition, all services share the remaining non...

  2. Social contagion theory: examining dynamic social networks and human behavior

    OpenAIRE

    Christakis, Nicholas A.; Fowler, James H.

    2012-01-01

    Here, we review the research we have done on social contagion. We describe the methods we have employed (and the assumptions they have entailed) in order to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ...

  3. Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

    Science.gov (United States)

    Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

    2017-01-01

    Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

  4. Social contagion theory: examining dynamic social networks and human behavior.

    Science.gov (United States)

    Christakis, Nicholas A; Fowler, James H

    2013-02-20

    Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a 'three degrees of influence' property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. Copyright © 2012 John Wiley & Sons, Ltd.

  5. An analogue of Morse theory for planar linear networks and the generalized Steiner problem

    International Nuclear Information System (INIS)

    Karpunin, G A

    2000-01-01

    A study is made of the generalized Steiner problem: the problem of finding all the locally minimal networks spanning a given boundary set (terminal set). It is proposed to solve this problem by using an analogue of Morse theory developed here for planar linear networks. The space K of all planar linear networks spanning a given boundary set is constructed. The concept of a critical point and its index is defined for the length function l of a planar linear network. It is shown that locally minimal networks are local minima of l on K and are critical points of index 1. The theorem is proved that the sum of the indices of all the critical points is equal to χ(K)=1. This theorem is used to find estimates for the number of locally minimal networks spanning a given boundary set

  6. 网络经济的博弈论分析%Analysis of the Game Theory in Network Economy

    Institute of Scientific and Technical Information of China (English)

    王玉

    2001-01-01

    Based on the non-asymmetrical information game theory, this paper analyzes the trust-agency mechanism in network economy, the change of the rules of the game and the strategies of the game in the network environment.

  7. Identification of global oil trade patterns: An empirical research based on complex network theory

    International Nuclear Information System (INIS)

    Ji, Qiang; Zhang, Hai-Ying; Fan, Ying

    2014-01-01

    Highlights: • A global oil trade core network is analyzed using complex network theory. • The global oil export core network displays a scale-free behaviour. • The current global oil trade network can be divided into three trading blocs. • The global oil trade network presents a ‘robust and yet fragile’ characteristic. - Abstract: The Global oil trade pattern becomes increasingly complex, which has become one of the most important factors affecting every country’s energy strategy and economic development. In this paper, a global oil trade core network is constructed to analyze the overall features, regional characteristics and stability of the oil trade using complex network theory. The results indicate that the global oil export core network displays a scale-free behaviour, in which the trade position of nodes presents obvious heterogeneity and the ‘hub nodes’ play a ‘bridge’ role in the formation process of the trade network. The current global oil trade network can be divided into three trading blocs, including the ‘South America-West Africa-North America’ trading bloc, the ‘Middle East–Asian–Pacific region’ trading bloc, and ‘the former Soviet Union–North Africa–Europe’ trading bloc. Geopolitics and diplomatic relations are the two main reasons for this regional oil trade structure. Moreover, the global oil trade network presents a ‘robust but yet fragile’ characteristic, and the impacts of trade interruption always tend to spread throughout the whole network even if the occurrence of export disruptions is localised

  8. The use of network theory to model disparate ship design information

    Directory of Open Access Journals (Sweden)

    Douglas Rigterink

    2014-06-01

    Full Text Available This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

  9. The use of network theory to model disparate ship design information

    Science.gov (United States)

    Rigterink, Douglas; Piks, Rebecca; Singer, David J.

    2014-06-01

    This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

  10. The use of network theory to model disparate ship design information

    Directory of Open Access Journals (Sweden)

    Rigterink Douglas

    2014-06-01

    Full Text Available This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship’s distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

  11. Methodology for Simulation and Analysis of Complex Adaptive Supply Network Structure and Dynamics Using Information Theory

    Directory of Open Access Journals (Sweden)

    Joshua Rodewald

    2016-10-01

    Full Text Available Supply networks existing today in many industries can behave as complex adaptive systems making them more difficult to analyze and assess. Being able to fully understand both the complex static and dynamic structures of a complex adaptive supply network (CASN are key to being able to make more informed management decisions and prioritize resources and production throughout the network. Previous efforts to model and analyze CASN have been impeded by the complex, dynamic nature of the systems. However, drawing from other complex adaptive systems sciences, information theory provides a model-free methodology removing many of those barriers, especially concerning complex network structure and dynamics. With minimal information about the network nodes, transfer entropy can be used to reverse engineer the network structure while local transfer entropy can be used to analyze the network structure’s dynamics. Both simulated and real-world networks were analyzed using this methodology. Applying the methodology to CASNs allows the practitioner to capitalize on observations from the highly multidisciplinary field of information theory which provides insights into CASN’s self-organization, emergence, stability/instability, and distributed computation. This not only provides managers with a more thorough understanding of a system’s structure and dynamics for management purposes, but also opens up research opportunities into eventual strategies to monitor and manage emergence and adaption within the environment.

  12. Analysis of the enzyme network involved in cattle milk production using graph theory.

    Science.gov (United States)

    Ghorbani, Sholeh; Tahmoorespur, Mojtaba; Masoudi Nejad, Ali; Nasiri, Mohammad; Asgari, Yazdan

    2015-06-01

    Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.

  13. Fundamentals of wireless sensor networks theory and practice

    CERN Document Server

    Dargie, Waltenegus

    2010-01-01

    In this book, the authors describe the fundamental concepts and practical aspects of wireless sensor networks. The book provides a comprehensive view to this rapidly evolving field, including its many novel applications, ranging from protecting civil infrastructure to pervasive health monitoring. Using detailed examples and illustrations, this book provides an inside track on the current state of the technology. The book is divided into three parts. In Part I, several node architectures, applications and operating systems are discussed. In Part II, the basic architectural frameworks, including

  14. A Cross-Layer Cooperation Mechanism of Wireless Networks Based on Game Theory

    OpenAIRE

    Chunsheng, Cui; Yongjian, Yang; Liping, Huang

    2014-01-01

    To meet the wireless network congestion control problem, we give a definition of congestion degree classification and propose a mechanism of directed cooperative path net, guided by the wireless network’s cross-layer design methods and node cooperation principles. Considering the virtual collision and “starved” phenomenon in congested networks, the QRD mechanism and channel competition mechanism QPCG are proposed, with introducing the game theory into the cross-layer design. Simulation result...

  15. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  16. Exploring the Combination of Dempster-Shafer Theory and Neural Network for Predicting Trust and Distrust

    Directory of Open Access Journals (Sweden)

    Xin Wang

    2016-01-01

    Full Text Available In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this paper, we study trust and distrust prediction based on the combination of Dempster-Shafer theory and neural network. We firstly analyze the inducing factors about trust and distrust, namely, homophily, status theory, and emotion tendency. Then, we quantify inducing factors of trust and distrust, take these features as evidences, and construct evidence prototype as input nodes of multilayer neural network. Finally, we propose a framework of predicting trust and distrust which uses multilayer neural network to model the implementing process of Dempster-Shafer theory in different hidden layers, aiming to overcome the disadvantage of Dempster-Shafer theory without optimization method. Experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework.

  17. Parameter Networks: Towards a Theory of Low-level Vision,

    Science.gov (United States)

    1981-04-01

    edge in image space arid increment those points in an array. Figure 5 shows the relevant geometry . Figure 5: Geometry for the I Iough Transform. In...8217Iels suc(h ,-s thiose shown in 1ligure 7 to reorganize origami wo.d- figures. Figoure?7. 1’o show an example In detail, Kender’s techn!Ciue for...Compuiter Science Dept, Carnegie-.Mcllon U., October 1979. Kanade, Tl., "A theory of Origami world," CMU-CS-78-144, Computer Science Dept, Carnegie

  18. Mode 3 knowledge production: Systems and systems theory, clusters and networks

    OpenAIRE

    Carayannis, Elias G.; Campbell, David F. J.; Rehman, Scheherazade S.

    2016-01-01

    With the comprehensive term of "Mode 3," we want to draw a conceptual link between systems and systems theory and want to demonstrate further how this can be applied to knowledge in the next steps. Systems can be understood as being composed of "elements", which are tied together by a "self-rationale". For innovation, often innovation clusters and innovation networks are being regarded as important. By leveraging systems theory for innovation concepts, one can implement references between the...

  19. Analysis of radionuclide transport through fracture networks by percolation theory

    International Nuclear Information System (INIS)

    Ahn, Joonhong; Furuhama, Yutaka; Li, Yadong; Suzuki, Atsuyuki

    1991-01-01

    Presented are results of numerical simulations for radionuclide diffusion through fracture networks in geologic layers. Actual fracture networks are expressed as two-dimensional honeycomb percolation lattices. Random-walk simulations of diffusion on percolation lattices are made by the exact-enumeration method, and compared with those from Fickian diffusion with constant and decreasing diffusion coefficients. Mean-square displacement of a random-walker on percolation lattices increases more slowly with time than that for Fickian diffusion with the constant diffusion coefficient. Though the same relation of mean-square displacement vs. time as for the percolation lattices can be obtained for a continuum with decreasing diffusion coefficients, spatial distribution of probability densities of finding the random-walker on the percolation lattice differs from that on a continuum with the decreasing diffusion coefficient. The percolation model results in slow spreading near the origin and fast spreading in the outer region, whereas the decreasing-diffusion coefficient model shows the reverse because of smaller diffusion coefficient in the outer region. We could derive a general formula that can include both Fickian and anomalous diffusion in terms of fractal and fracton dimensionalities and the anomalous diffusion exponent. (author)

  20. Applying Game Theory in 802.11 Wireless Networks

    Directory of Open Access Journals (Sweden)

    Tomas Cuzanauskas

    2015-07-01

    Full Text Available IEEE 802.11 is one of the most popular wireless technologies in recent days. Due to easiness of adaption and relatively low cost the demand for IEEE 802.11 devices is increasing exponentially. IEEE works in two bands 2.4 GHz and 5 GHz, these bands are known as ISM band. The unlicensed bands are managed by authority which set simple rules to follow when using unlicensed bands, the rules includes requirements as maximum power, out-of-band emissions control as well as interference mitigation. However these rules became outdated as IEEE 802.11 technology is emerging and evolving in hours the rules aren’t well suited for current capabilities of IEEE 802.11 devices. In this article we present game theory based algorithm for IEEE 802.11 wireless devices, we will show that by using game theory it’s possible to achieve better usage of unlicensed spectrum as well as partially decline CSMA/CA. Finally by using this approach we might relax the currently applied maximum power rules for ISM bands, which enable IEEE 802.11 to work on longer distance and have better propagation characteristics.

  1. Incorporating Contagion in Portfolio Credit Risk Models Using Network Theory

    Directory of Open Access Journals (Sweden)

    Ioannis Anagnostou

    2018-01-01

    Full Text Available Portfolio credit risk models estimate the range of potential losses due to defaults or deteriorations in credit quality. Most of these models perceive default correlation as fully captured by the dependence on a set of common underlying risk factors. In light of empirical evidence, the ability of such a conditional independence framework to accommodate for the occasional default clustering has been questioned repeatedly. Thus, financial institutions have relied on stressed correlations or alternative copulas with more extreme tail dependence. In this paper, we propose a different remedy—augmenting systematic risk factors with a contagious default mechanism which affects the entire universe of credits. We construct credit stress propagation networks and calibrate contagion parameters for infectious defaults. The resulting framework is implemented on synthetic test portfolios wherein the contagion effect is shown to have a significant impact on the tails of the loss distributions.

  2. The Role of Adolescent Development in Social Networking Site Use: Theory and Evidence

    Directory of Open Access Journals (Sweden)

    Drew P. Cingel

    2014-03-01

    Full Text Available Using survey data collected from 260 children, adolescents, and young adults between the ages of 9 and 26, this paper offers evidence for a relationship between social networking site use and Imaginary Audience, a developmental variable in which adolescents believe others are thinking about them at all times. Specifically, after controlling for a number of variables, results indicate a significant, positive relationship between social networking site use and Imaginary Audience ideation. Additionally, results indicate a positive relationship between Imaginary Audience ideation and Facebook customization practices. Together, these findings provide evidence, based on Vygotskian developmental theory, for a general consideration of the role that currently available tools, in this case social networking sites, can have on development. Thus, findings implicate both the role of development on social networking site use, as well as the role of social networking site use on development. Overall, these findings have important implications for the study of media and human development, which are discussed in detail.

  3. Modelling the rebound effect with network theory: An insight into the European freight transport sector

    International Nuclear Information System (INIS)

    Ruzzenenti, Franco; Basosi, Riccardo

    2017-01-01

    This paper presents a two pronged approach to the study of the rebound effect, with the aim of assessing the magnitude of the effect in the European freight transport sector and proposing a new modelling framework based on network theory. The (direct) rebound effect is assessed with: 1) an econometric regression; 2) a model based on network theory and statistical mechanics. According to the econometric model the European road freight transport sector undergone a negative rebound between of −74% between 1998 and 2007 and −146% between 1998 and 2011. The network analysis delivers an estimation of network rebound ranging between −29.37% and −7.25. Overall, these results indicate that energy efficiency in Europe, between 1998 and 2011, succeed in reducing the energy consumptions amid an increasing demand for transports. Results on rebound estimation depend on the decision of using GDP as an exogenous variable, an assumption that leaves questions open about the causality chain between growth and transports. Furthermore, the network analysis highlights a structural change –a migration of production factors offshore, that might partially explain this negative effect. In this view, rebound effect analysis on a local or regional scale is becoming more and more uncertain in a globally interconnected economic context. - Highlights: • An evaluation of direct rebound effect in the freight transports with an econometric model is performed. • A new concept of rebound effect based on network theory is presented and implemented. • A comparative analysis of the two different approaches is developed. • Both models indicate that the there was a negative rebound effect in European freight transports. • Network theory proved to be a promising approach to energy systems and rebound effect modelling.

  4. Human behavior understanding in networked sensing theory and applications of networks of sensors

    CERN Document Server

    Spagnolo, Paolo; Distante, Cosimo

    2014-01-01

    This unique text/reference provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing. Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including such topics as systems design tools and techniques, in-network signals, and information processing. Additionally, the book examines a varied range of application scenarios, covering surveillance, indexing and retrieval, patient care, industrial safety, social and ambient

  5. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  6. Functional brain networks contributing to the Parieto-Frontal Integration Theory of Intelligence.

    Science.gov (United States)

    Vakhtin, Andrei A; Ryman, Sephira G; Flores, Ranee A; Jung, Rex E

    2014-12-01

    The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence. Published by Elsevier Inc.

  7. Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey.

    Science.gov (United States)

    Abdalzaher, Mohamed S; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel

    2016-06-29

    We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs.

  8. Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey

    Directory of Open Access Journals (Sweden)

    Mohamed S. Abdalzaher

    2016-06-01

    Full Text Available We present a study of using game theory for protecting wireless sensor networks (WSNs from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs.

  9. Actor-network-theory perspective on a forestry decision support system design

    NARCIS (Netherlands)

    Boerboom, L.G.J.; Ferritti, V.

    2014-01-01

    Use of decision support systems (DSS) has thus far been framed as a social process of adoption or technical process of usability. We analyze the development of a DSS as a process of institutionalization of new as well as drift of existing practices. We write an Actor-Network-Theory (ANT) account,

  10. Time dependent mechanical modeling for polymers based on network theory

    Energy Technology Data Exchange (ETDEWEB)

    Billon, Noëlle [MINES ParisTech, PSL-Research University, CEMEF – Centre de mise en forme des matériaux, CNRS UMR 7635, CS 10207 rue Claude Daunesse 06904 Sophia Antipolis Cedex (France)

    2016-05-18

    Despite of a lot of attempts during recent years, complex mechanical behaviour of polymers remains incompletely modelled, making industrial design of structures under complex, cyclic and hard loadings not totally reliable. The non linear and dissipative viscoelastic, viscoplastic behaviour of those materials impose to take into account non linear and combined effects of mechanical and thermal phenomena. In this view, a visco-hyperelastic, viscoplastic model, based on network description of the material has recently been developed and designed in a complete thermodynamic frame in order to take into account those main thermo-mechanical couplings. Also, a way to account for coupled effects of strain-rate and temperature was suggested. First experimental validations conducted in the 1D limit on amorphous rubbery like PMMA in isothermal conditions led to pretty goods results. In this paper a more complete formalism is presented and validated in the case of a semi crystalline polymer, a PA66 and a PET (either amorphous or semi crystalline) are used. Protocol for identification of constitutive parameters is described. It is concluded that this new approach should be the route to accurately model thermo-mechanical behaviour of polymers using a reduced number of parameters of some physical meaning.

  11. Efficient computation in networks of spiking neurons: simulations and theory

    International Nuclear Information System (INIS)

    Natschlaeger, T.

    1999-01-01

    One of the most prominent features of biological neural systems is that individual neurons communicate via short electrical pulses, the so called action potentials or spikes. In this thesis we investigate possible mechanisms which can in principle explain how complex computations in spiking neural networks (SNN) can be performed very fast, i.e. within a few 10 milliseconds. Some of these models are based on the assumption that relevant information is encoded by the timing of individual spikes (temporal coding). We will also discuss a model which is based on a population code and still is able to perform fast complex computations. In their natural environment biological neural systems have to process signals with a rich temporal structure. Hence it is an interesting question how neural systems process time series. In this context we explore possible links between biophysical characteristics of single neurons (refractory behavior, connectivity, time course of postsynaptic potentials) and synapses (unreliability, dynamics) on the one hand and possible computations on times series on the other hand. Furthermore we describe a general model of computation that exploits dynamic synapses. This model provides a general framework for understanding how neural systems process time-varying signals. (author)

  12. A game theory approach to target tracking in sensor networks.

    Science.gov (United States)

    Gu, Dongbing

    2011-02-01

    In this paper, we investigate a moving-target tracking problem with sensor networks. Each sensor node has a sensor to observe the target and a processor to estimate the target position. It also has wireless communication capability but with limited range and can only communicate with neighbors. The moving target is assumed to be an intelligent agent, which is "smart" enough to escape from the detection by maximizing the estimation error. This adversary behavior makes the target tracking problem more difficult. We formulate this target estimation problem as a zero-sum game in this paper and use a minimax filter to estimate the target position. The minimax filter is a robust filter that minimizes the estimation error by considering the worst case noise. Furthermore, we develop a distributed version of the minimax filter for multiple sensor nodes. The distributed computation is implemented via modeling the information received from neighbors as measurements in the minimax filter. The simulation results show that the target tracking algorithm proposed in this paper provides a satisfactory result.

  13. Actor networks in strategic niche management : insights from social network theory

    NARCIS (Netherlands)

    Caniëls, M.C.J.; Romijn, H.A.

    2008-01-01

    This paper contributes to Strategic Niche Management (SNM), an analytical technique designed to facilitate the introduction and diffusion of radically new sustainable technologies through societal experiments. According to SNM, intensive networking among social actors is a crucial process for the

  14. Network Theory: A Primer and Questions for Air Transportation Systems Applications

    Science.gov (United States)

    Holmes, Bruce J.

    2004-01-01

    A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.

  15. Modeling and dynamical topology properties of VANET based on complex networks theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hong; Li, Jie, E-mail: prof.li@foxmail.com [School of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan, 430074 (China)

    2015-01-15

    Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a

  16. Combining evolutionary game theory and network theory to analyze human cooperation patterns

    International Nuclear Information System (INIS)

    Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro; Catania, Emanuele; Guardo, Ermanno; Pagano, Salvatore

    2016-01-01

    Highlights: • We investigate the evolutionary dynamics of human cooperation in a social network. • We introduce the concepts of “Critical Mass”, centrality measure and homophily. • The emergence of cooperation is affected by the spatial choice of the “Critical Mass”. • Our findings show that homophily speeds up the convergence towards cooperation. • Centrality and “Critical Mass” spatial choice partially offset the impact of homophily. - Abstract: As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially

  17. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  18. Putting Gino's lesson to work: Actor-network theory, enacted humanity, and rehabilitation.

    Science.gov (United States)

    Abrams, Thomas; Gibson, Barbara E

    2016-02-01

    This article argues that rehabilitation enacts a particular understanding of "the human" throughout therapeutic assessment and treatment. Following Michel Callon and Vololona Rabeharisoa's "Gino's Lesson on Humanity," we suggest that this is not simply a top-down process, but is cultivated in the application and response to biomedical frameworks of human ability, competence, and responsibility. The emergence of the human is at once a materially contingent, moral, and interpersonal process. We begin the article by outlining the basics of the actor-network theory that underpins "Gino's Lesson on Humanity." Next, we elucidate its central thesis regarding how disabled personhood emerges through actor-network interactions. Section "Learning Gino's lesson" draws on two autobiographical examples, examining the emergence of humanity through rehabilitation, particularly assessment measures and the responses to them. We conclude by thinking about how rehabilitation and actor-network theory might take this lesson on humanity seriously. © The Author(s) 2016.

  19. The gender of science: reflections on the actor-network theory and the feminist perspective

    Directory of Open Access Journals (Sweden)

    Gabriel Pugliese Cardoso

    2015-06-01

    Full Text Available This article discusses some of the principles that guide the descriptive forms of the actor-network theory (ANT of Bruno Latour and feminist standpoint theory formulated by Sandra Harding and Evelyn Fox Keller, through my research on the "Marie Curie Case". As a singular case between gender and science, the goal of thispaper is to play with ANT certainties against feminist perspective uncertainties. In the other hand, the certainties of feminist perspective are put against the uncertainties of ANT. With this counterpoint we intend to promote a reaction - in the chemical sense of the word – to the descriptive forms of the actor-network theory and feminist perspective taking away the obviousness of some of their assumptions. Doing that, we explore the moves of those reactions and their effects to the description which we do about science.

  20. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    NARCIS (Netherlands)

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of

  1. Network theory-based analysis of risk interactions in large engineering projects

    International Nuclear Information System (INIS)

    Fang, Chao; Marle, Franck; Zio, Enrico; Bocquet, Jean-Claude

    2012-01-01

    This paper presents an approach based on network theory to deal with risk interactions in large engineering projects. Indeed, such projects are exposed to numerous and interdependent risks of various nature, which makes their management more difficult. In this paper, a topological analysis based on network theory is presented, which aims at identifying key elements in the structure of interrelated risks potentially affecting a large engineering project. This analysis serves as a powerful complement to classical project risk analysis. Its originality lies in the application of some network theory indicators to the project risk management field. The construction of the risk network requires the involvement of the project manager and other team members assigned to the risk management process. Its interpretation improves their understanding of risks and their potential interactions. The outcomes of the analysis provide a support for decision-making regarding project risk management. An example of application to a real large engineering project is presented. The conclusion is that some new insights can be found about risks, about their interactions and about the global potential behavior of the project. - Highlights: ► The method addresses the modeling of complexity in project risk analysis. ► Network theory indicators enable other risks than classical criticality analysis to be highlighted. ► This topological analysis improves project manager's understanding of risks and risk interactions. ► This helps project manager to make decisions considering the position in the risk network. ► An application to a real tramway implementation project in a city is provided.

  2. Endogenous Molecular-Cellular Network Cancer Theory: A Systems Biology Approach.

    Science.gov (United States)

    Wang, Gaowei; Yuan, Ruoshi; Zhu, Xiaomei; Ao, Ping

    2018-01-01

    In light of ever apparent limitation of the current dominant cancer mutation theory, a quantitative hypothesis for cancer genesis and progression, endogenous molecular-cellular network hypothesis has been proposed from the systems biology perspective, now for more than 10 years. It was intended to include both the genetic and epigenetic causes to understand cancer. Its development enters the stage of meaningful interaction with experimental and clinical data and the limitation of the traditional cancer mutation theory becomes more evident. Under this endogenous network hypothesis, we established a core working network of hepatocellular carcinoma (HCC) according to the hypothesis and quantified the working network by a nonlinear dynamical system. We showed that the two stable states of the working network reproduce the main known features of normal liver and HCC at both the modular and molecular levels. Using endogenous network hypothesis and validated working network, we explored genetic mutation pattern in cancer and potential strategies to cure or relieve HCC from a totally new perspective. Patterns of genetic mutations have been traditionally analyzed by posteriori statistical association approaches in light of traditional cancer mutation theory. One may wonder the possibility of a priori determination of any mutation regularity. Here, we found that based on the endogenous network theory the features of genetic mutations in cancers may be predicted without any prior knowledge of mutation propensities. Normal hepatocyte and cancerous hepatocyte stable states, specified by distinct patterns of expressions or activities of proteins in the network, provide means to directly identify a set of most probable genetic mutations and their effects in HCC. As the key proteins and main interactions in the network are conserved through cell types in an organism, similar mutational features may also be found in other cancers. This analysis yielded straightforward and testable

  3. An application of the graph theory which examines the metro networks

    Directory of Open Access Journals (Sweden)

    Svetla STOILOVA

    2015-06-01

    Full Text Available The graph theory gives a mathematical representation of transport networks and allows us to study their characteristics effectively. A research of the structure of metro system has been conducted in the study by using the graph theory. The study includes subway systems of 22 European capitals. New indicators have been defined in the research such as a degree of routing, a connectivity of the route, average length per link (which takes into account the number of routes, intensity of the route, density of the route. The new and the existing indicators have been used to analyze and classify the metro networks. The statistical method cluster analysis has been applied to classify the networks. Ten indicators have been used to carry out an analysis. The metro systems in European capitals have been classified in three clusters. The first cluster includes large metro systems, the second one includes small metro networks whereas the third cluster includes metro networks with only one line. The combination of both two methods has been used for the first time in this research. The methodology could be used to evaluate other existing metro networks as well as for preliminary analysis in the design of subway systems.

  4. Game theory and extremal optimization for community detection in complex dynamic networks.

    Science.gov (United States)

    Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca

    2014-01-01

    The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.

  5. Using Social Network Theory to Influence the Development of State and Local Primary Prevention Capacity-Building Teams

    Science.gov (United States)

    Cook-Craig, Patricia G.

    2010-01-01

    This article examines the role that social network theory and social network analysis has played in assessing and developing effective primary prevention networks across a southeastern state. In 2004 the state began an effort to develop a strategic plan for the primary prevention of violence working with local communities across the state. The…

  6. Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

    Science.gov (United States)

    Kölzsch, A.; Blasius, B.

    2011-12-01

    The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global shipping. This is the first stage of the invasion process where it is still possible to intervene with regulating measures. We compile a selection of widely used and newly developed network properties and apply these to analyse the structure and spread characteristics of the directed and weighted global cargo ship network (GCSN). Our results reveal that the GCSN is highly efficient, shows small world characteristics and is positive assortative, indicating that quick spread of invasive organisms between ports is likely. The GCSN shows strong community structure and contains two large communities, the Atlantic and Pacific trading groups. Ports that appear as connector hubs and are of high centralities are the Suez and Panama Canal, Singapore and Shanghai. Furthermore, from robustness analyses and the network's percolation behaviour, we evaluate differences of onboard and in-port ballast water treatment, set them into context with previous studies and advise bioinvasion management strategies.

  7. Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network

    NARCIS (Netherlands)

    Kölzsch, A.; Blasius, B.

    2011-01-01

    The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global

  8. Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

    Science.gov (United States)

    Calvin, Olivia L; McDowell, J J

    2016-06-01

    The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this experiment, neural networks were developed from the theory to extend the unified theory of reinforcement to operant behavior on single-alternative variable-interval schedules. This area of operant research was selected because previously developed neural networks could be applied to it without significant alteration. Previous research with humans and animals indicates that the pattern of their steady-state behavior is hyperbolic when plotted against the obtained rate of reinforcement (Herrnstein, 1970). A genetic algorithm was used in the first part of the experiment to determine parameter values for the neural networks, because values that were used in previous research did not result in a hyperbolic pattern of behavior. After finding these parameters, hyperbolic and other similar functions were fitted to the behavior produced by the neural networks. The form of the neural network's behavior was best described by an exponentiated hyperbola (McDowell, 1986; McLean and White, 1983; Wearden, 1981), which was derived from the generalized matching law (Baum, 1974). In post-hoc analyses the addition of a baseline rate of behavior significantly improved the fit of the exponentiated hyperbola and removed systematic residuals. The form of this function was consistent with human and animal behavior, but the estimated parameter values were not. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Optimization of flow modeling in fractured media with discrete fracture network via percolation theory

    Science.gov (United States)

    Donado-Garzon, L. D.; Pardo, Y.

    2013-12-01

    Fractured media are very heterogeneous systems where occur complex physical and chemical processes to model. One of the possible approaches to conceptualize this type of massifs is the Discrete Fracture Network (DFN). Donado et al., modeled flow and transport in a granitic batholith based on this approach and found good fitting with hydraulic and tracer tests, but the computational cost was excessive due to a gigantic amount of elements to model. We present in this work a methodology based on percolation theory for reducing the number of elements and in consequence, to reduce the bandwidth of the conductance matrix and the execution time of each network. DFN poses as an excellent representation of all the set of fractures of the media, but not all the fractures of the media are part of the conductive network. Percolation theory is used to identify which nodes or fractures are not conductive, based on the occupation probability or percolation threshold. In a fractured system, connectivity determines the flow pattern in the fractured rock mass. This volume of fluid is driven through connection paths formed by the fractures, when the permeability of the rock is negligible compared to the fractures. In a population of distributed fractures, each of this that has no intersection with any connected fracture do not contribute to generate a flow field. This algorithm also permits us to erase these elements however they are water conducting and hence, refine even more the backbone of the network. We used 100 different generations of DFN that were optimized in this study using percolation theory. In each of the networks calibrate hydrodynamic parameters as hydraulic conductivity and specific storage coefficient, for each of the five families of fractures, yielding a total of 10 parameters to estimate, at each generation. Since the effects of the distribution of fault orientation changes the value of the percolation threshold, but not the universal laws of classical

  10. GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.

    Science.gov (United States)

    Lin, Chi; Wu, Guowei; Pirozmand, Poria

    2015-06-04

    The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.

  11. Functional network-based statistics in depression: Theory of mind subnetwork and importance of parietal region.

    Science.gov (United States)

    Lai, Chien-Han; Wu, Yu-Te; Hou, Yuh-Ming

    2017-08-01

    The functional network analysis of whole brain is an emerging field for research in depression. We initiated this study to investigate which subnetwork is significantly altered within the functional connectome in major depressive disorder (MDD). The study enrolled 52 first-episode medication-naïve patients with MDD and 40 controls for functional network analysis. All participants received the resting-state functional imaging using a 3-Tesla magnetic resonance scanner. After preprocessing, we calculated the connectivity matrix of functional connectivity in whole brain for each subject. The network-based statistics of connectome was used to perform group comparisons between patients and controls. The correlations between functional connectivity and clinical parameters were also performed. MDD patients had significant alterations in the network involving "theory of mind" regions, such as the left precentral gyrus, left angular gyrus, bilateral rolandic operculums and left inferior frontal gyrus. The center node of significant network was the left angular gyrus. No significant correlations of functional connectivity within the subnetwork and clinical parameters were noted. Functional connectivity of "theory of mind" subnetwork may be the core issue for pathophysiology in MDD. In addition, the center role of parietal region should be emphasized in future study. Copyright © 2017. Published by Elsevier B.V.

  12. The Construction of Higher Education Entrepreneur Services Network System a Research Based on Ecological Systems Theory

    Science.gov (United States)

    Xue, Jingxin

    The article aims to completely, systematically and objectively analyze the current situation of Entrepreneurship Education in China with Ecological Systems Theory. From this perspective, the author discusses the structure, function and its basic features of higher education entrepreneur services network system, and puts forward the opinion that every entrepreneurship organization in higher education institution does not limited to only one platform. Different functional supporting platforms should be combined closed through composite functional organization to form an integrated network system, in which each unit would impels others' development.

  13. Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

    Science.gov (United States)

    Ho, Ching S.; Liou, Juin J.; Georgiopoulos, Michael; Christodoulou, Christos G.

    1994-03-01

    This paper presents an analog circuit design and implementation for an adaptive resonance theory neural network architecture called the augmented ART1 neural network (AART1-NN). Practical monolithic operational amplifiers (Op-Amps) LM741 and LM318 are selected to implement the circuit, and a simple compensation scheme is developed to adjust the Op-Amp electrical characteristics to meet the design requirement. A 7-node prototype circuit has been designed and verified using the Pspice circuit simulator run on a Sun workstation. Results simulated from the AART1-NN circuit using the LM741, LM318, and ideal Op-Amps are presented and compared.

  14. A study on the critical factors which influence habitual entrepreneurs' success in networking from the perspective of social captial theory

    OpenAIRE

    Li, SiQi

    2012-01-01

    The aim of the research is to provide an insight on the critical factors which influence habitual entrepreneurs’ success in networking through which effective networking strategies may lead to increased business performance. The perspective of explaining the factors adopts social capital theory and social dimensions of entrepreneurs’ network. The key findings suggest that social capital is in a form of non-linear pattern that the interactions are complex. Network configuration influences effe...

  15. Analysis of Online Social Networks to Understand Information Sharing Behaviors Through Social Cognitive Theory.

    Science.gov (United States)

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-05-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples' behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of "leaders" on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of "followers", people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

  16. American Long-Distance Locomobility and the Spaces of Actor-Network Theory

    Directory of Open Access Journals (Sweden)

    Michael Minn

    2016-03-01

    Full Text Available Much of the discourse surrounding national intercity passenger rail service in the United States revolves around why it has lagged so far behind European and Asian counterparts. However, a more interesting question might be why it has survived despite competition from faster, more nimble transport modes, discriminatory public policy, and the ascension of neoliberal discourse hostile to public endeavor. This paper uses the concept of durability in actor-network theory to offer some insights into how the system has achieved a remarkable but problematic stability, and how that durability relates to an imagined role for national intercity passenger rail in a future of increasingly constrained material resources. This paper also demonstrates the application of actor-network theory (ANT in a way that can serve as a useful introduction to and template for the use of that methodology.

  17. Langevin-elasticity-theory-based description of the tensile properties of double network rubbers

    Czech Academy of Sciences Publication Activity Database

    Meissner, Bohumil; Matějka, Libor

    2003-01-01

    Roč. 44, č. 16 (2003), s. 4611-4617 ISSN 0032-3861 R&D Projects: GA ČR GA104/00/1311; GA AV ČR IAA4050008 Institutional research plan: CEZ:AV0Z4050913 Keywords : theory of rubber elasticity * double network rubbers * experimental testing Subject RIV: CD - Macromolecular Chemistry Impact factor: 2.340, year: 2003

  18. Analysing collaboration among HIV agencies through combining network theory and relational coordination.

    Science.gov (United States)

    Khosla, Nidhi; Marsteller, Jill Ann; Hsu, Yea Jen; Elliott, David L

    2016-02-01

    Agencies with different foci (e.g. nutrition, social, medical, housing) serve people living with HIV (PLHIV). Serving needs of PLHIV comprehensively requires a high degree of coordination among agencies which often benefits from more frequent communication. We combined Social Network theory and Relational Coordination theory to study coordination among HIV agencies in Baltimore. Social Network theory implies that actors (e.g., HIV agencies) establish linkages amongst themselves in order to access resources (e.g., information). Relational Coordination theory suggests that high quality coordination among agencies or teams relies on the seven dimensions of frequency, timeliness and accuracy of communication, problem-solving communication, knowledge of agencies' work, mutual respect and shared goals. We collected data on frequency of contact from 57 agencies using a roster method. Response options were ordinal ranging from 'not at all' to 'daily'. We analyzed data using social network measures. Next, we selected agencies with which at least one-third of the sample reported monthly or more frequent interaction. This yielded 11 agencies whom we surveyed on seven relational coordination dimensions with questions scored on a Likert scale of 1-5. Network density, defined as the proportion of existing connections to all possible connections, was 20% when considering monthly or higher interaction. Relational coordination scores from individual agencies to others ranged between 1.17 and 5.00 (maximum possible score 5). The average scores for different dimensions across all agencies ranged between 3.30 and 4.00. Shared goals (4.00) and mutual respect (3.91) scores were highest, while scores such as knowledge of each other's work and problem-solving communication were relatively lower. Combining theoretically driven analyses in this manner offers an innovative way to provide a comprehensive picture of inter-agency coordination and the quality of exchange that underlies

  19. Altered Brain Network in Amyotrophic Lateral Sclerosis: A Resting Graph Theory-Based Network Study at Voxel-Wise Level.

    Science.gov (United States)

    Zhou, Chaoyang; Hu, Xiaofei; Hu, Jun; Liang, Minglong; Yin, Xuntao; Chen, Lin; Zhang, Jiuquan; Wang, Jian

    2016-01-01

    Amyotrophic lateral sclerosis (ALS) is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex-matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC), a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe, and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC's z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

  20. Altered brain network in Amyotrophic Lateral Sclerosis: a resting graph theory-based network study at voxel-wise level

    Directory of Open Access Journals (Sweden)

    Chaoyang eZhou

    2016-05-01

    Full Text Available Amyotrophic lateral sclerosis (ALS is a rare degenerative disorder characterized by loss of upper and lower motor neurons. Neuroimaging has provided noticeable evidence that ALS is a complex disease, and shown that anatomical and functional lesions extend beyond precentral cortices and corticospinal tracts, to include the corpus callosum; frontal, sensory, and premotor cortices; thalamus; and midbrain. The aim of this study is to investigate graph theory-based functional network abnormalities at voxel-wise level in ALS patients on a whole brain scale. Forty-three ALS patients and 44 age- and sex- matched healthy volunteers were enrolled. The voxel-wise network degree centrality (DC, a commonly employed graph-based measure of network organization, was used to characterize the alteration of whole brain functional network. Compared with the controls, the ALS patients showed significant increase of DC in the left cerebellum posterior lobes, bilateral cerebellum crus, bilateral occipital poles, right orbital frontal lobe and bilateral prefrontal lobes; significant decrease of DC in the bilateral primary motor cortex, bilateral sensory motor region, right prefrontal lobe, left bilateral precuneus, bilateral lateral temporal lobes, left cingulate cortex, and bilateral visual processing cortex. The DC’s z-scores of right inferior occipital gyrus were significant negative correlated with the ALSFRS-r scores. Our findings confirm that the regions with abnormal network DC in ALS patients were located in multiple brain regions including primary motor, somatosensory and extra-motor areas, supporting the concept that ALS is a multisystem disorder. Specifically, our study found that DC in the visual areas was altered and ALS patients with higher DC in right inferior occipital gyrus have more severity of disease. The result demonstrated that the altered DC value in this region can probably be used to assess severity of ALS.

  1. Driving the brain towards creativity and intelligence: A network control theory analysis.

    Science.gov (United States)

    Kenett, Yoed N; Medaglia, John D; Beaty, Roger E; Chen, Qunlin; Betzel, Richard F; Thompson-Schill, Sharon L; Qiu, Jiang

    2018-01-04

    High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. [Reliability theory based on quality risk network analysis for Chinese medicine injection].

    Science.gov (United States)

    Li, Zheng; Kang, Li-Yuan; Fan, Xiao-Hui

    2014-08-01

    A new risk analysis method based upon reliability theory was introduced in this paper for the quality risk management of Chinese medicine injection manufacturing plants. The risk events including both cause and effect ones were derived in the framework as nodes with a Bayesian network analysis approach. It thus transforms the risk analysis results from failure mode and effect analysis (FMEA) into a Bayesian network platform. With its structure and parameters determined, the network can be used to evaluate the system reliability quantitatively with probabilistic analytical appraoches. Using network analysis tools such as GeNie and AgenaRisk, we are able to find the nodes that are most critical to influence the system reliability. The importance of each node to the system can be quantitatively evaluated by calculating the effect of the node on the overall risk, and minimization plan can be determined accordingly to reduce their influences and improve the system reliability. Using the Shengmai injection manufacturing plant of SZYY Ltd as a user case, we analyzed the quality risk with both static FMEA analysis and dynamic Bayesian Network analysis. The potential risk factors for the quality of Shengmai injection manufacturing were identified with the network analysis platform. Quality assurance actions were further defined to reduce the risk and improve the product quality.

  3. A Game Theory Based Congestion Control Protocol for Wireless Personal Area Networks

    Directory of Open Access Journals (Sweden)

    Chuang Ma

    2016-01-01

    Full Text Available In wireless sensor networks (WSNs, the presence of congestion increases the ratio of packet loss and energy consumption and reduces the network throughput. Particularly, this situation will be more complex in Internet of Things (IoT environment, which is composed of thousands of heterogeneous nodes. RPL is an IPv6 routing protocol in low power and lossy networks standardized by IETF. However, the RPL can induce problems under network congestion, such as frequently parent changing and throughput degradation. In this paper, we address the congestion problem between parent nodes and child nodes in RPL-enabled networks, which typically consist of low power and resource constraint devices. To mitigate the effect of network congestion, we design a parent-change procedure by game theory strategy, by which the child nodes can change next hop neighbors toward the sink. Comparing to the ContikiRPL implementation, the simulation results show that our protocol can achieve more than two times improvement in throughput and reduce packet loss rate with less increasing of average hop count.

  4. Mean-field Theory for Some Bus Transport Networks with Random Overlapping Clique Structure

    International Nuclear Information System (INIS)

    Yang Xuhua; Sun Bao; Wang Bo; Sun Youxian

    2010-01-01

    Transport networks, such as railway networks and airport networks, are a kind of random network with complex topology. Recently, more and more scholars paid attention to various kinds of transport networks and try to explore their inherent characteristics. Here we study the exponential properties of a recently introduced Bus Transport Networks (BTNs) evolution model with random overlapping clique structure, which gives a possible explanation for the observed exponential distribution of the connectivities of some BTNs of three major cities in China. Applying mean-field theory, we analyze the BTNs model and prove that this model has the character of exponential distribution of the connectivities, and develop a method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the exponents. By comparing mean-field based theoretic results with the statistical data of real BTNs, we observe that, as a whole, both of their data show similar character of exponential distribution of the connectivities, and their exponents have same order of magnitude, which show the availability of the analytical result of this paper. (general)

  5. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

    Science.gov (United States)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  6. Understanding and Using the Controller Area Network Communication Protocol Theory and Practice

    CERN Document Server

    Di Natale, Marco; Giusto, Paolo; Ghosal, Arkadeb

    2012-01-01

    This is the first book to offer a hands-on guide to designing, analyzing and debugging a communication infrastructure based on the Controller Area Network (CAN) bus.  Although the CAN bus standard is well established and currently used in most automotive systems, as well as avionics, medical systems and other devices, its features are not fully understood by most developers, who tend to misuse the network. This results in lost opportunities for better efficiency and performance.   This book offers a comprehensive range of architectural solutions and domains of analysis. It also provides formal models and analytical results, with thorough discussion of their applicability, so that it serves as an invaluable reference for researchers and students, as well as practicing engineers.    Offers the first comprehensive guide to bridging the gap between theory and implementation of the widely accepted Controller Area Network (CAN) bus; Provides examples and best practices for design of communication systems, as w...

  7. Locally excitatory, globally inhibitory oscillator networks: theory and application to scene segmentation

    Science.gov (United States)

    Wang, DeLiang; Terman, David

    1995-01-01

    A novel class of locally excitatory, globally inhibitory oscillator networks (LEGION) is proposed and investigated analytically and by computer simulation. The model of each oscillator corresponds to a standard relaxation oscillator with two time scales. The network exhibits a mechanism of selective gating, whereby an oscillator jumping up to its active phase rapidly recruits the oscillators stimulated by the same pattern, while preventing other oscillators from jumping up. We show analytically that with the selective gating mechanism the network rapidly achieves both synchronization within blocks of oscillators that are stimulated by connected regions and desynchronization between different blocks. Computer simulations demonstrate LEGION's promising ability for segmenting multiple input patterns in real time. This model lays a physical foundation for the oscillatory correlation theory of feature binding, and may provide an effective computational framework for scene segmentation and figure/ground segregation.

  8. A Network Neuroscience of Human Learning: Potential to Inform Quantitative Theories of Brain and Behavior.

    Science.gov (United States)

    Bassett, Danielle S; Mattar, Marcelo G

    2017-04-01

    Humans adapt their behavior to their external environment in a process often facilitated by learning. Efforts to describe learning empirically can be complemented by quantitative theories that map changes in neurophysiology to changes in behavior. In this review we highlight recent advances in network science that offer a sets of tools and a general perspective that may be particularly useful in understanding types of learning that are supported by distributed neural circuits. We describe recent applications of these tools to neuroimaging data that provide unique insights into adaptive neural processes, the attainment of knowledge, and the acquisition of new skills, forming a network neuroscience of human learning. While promising, the tools have yet to be linked to the well-formulated models of behavior that are commonly utilized in cognitive psychology. We argue that continued progress will require the explicit marriage of network approaches to neuroimaging data and quantitative models of behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Linking experiment and theory for three-dimensional networked binary metal nanoparticle–triblock terpolymer superstructures

    KAUST Repository

    Li, Zihui

    2014-02-21

    © 2014 Macmillan Publishers Limited. Controlling superstructure of binary nanoparticle mixtures in three dimensions from self-assembly opens enormous opportunities for the design of materials with unique properties. Here we report on how the intimate coupling of synthesis, in-depth electron tomographic characterization and theory enables exquisite control of superstructure in highly ordered porous three-dimensional continuous networks from single and binary mixtures of metal nanoparticles with a triblock terpolymer. Poly(isoprene-block-styrene-block-(N,N-dimethylamino)ethyl methacrylate) is synthesized and used as structure-directing agent for ligand-stabilized platinum and gold nanoparticles. Quantitative analysis provides insights into short-and long-range nanoparticle-nanoparticle correlations, and local and global contributions to structural chirality in the networks. Results provide synthesis criteria for next-generation mesoporous network superstructures from binary nanoparticle mixtures for potential applications in areas including catalysis.

  10. An Interview with Tony David Sampson: Author of Virality: Contagion Theory in the Age of Networks

    Directory of Open Access Journals (Sweden)

    Tara Robbins Fee

    2016-12-01

    Full Text Available Tony D. Sampson is Reader in Digital Culture and Communication in the School of Arts and Digital Industries (ADI at the University of East London, where he directs the EmotionUX lab, supervising research on the cognitive, emotional, and affective aspects of user experience. In 2013, he co-founded Club Critical Theory, an organization dedicated to the application of critical theory in everyday life in Southend-on-Sea, Essex. Tony is the author of Virality: Contagion Theory in the Age of Networks and The Assemblage Brain: Sense Making in Neuroculture, both from the University of Minnesota Press. He blogs at viralcontagion.wordpress.com. The editors of this special NANO issue are delighted to have the opportunity to talk with Tony about how his work touches on issues of imitation and contagion—a loaded term unpacked within his 2012 book.

  11. Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

    Directory of Open Access Journals (Sweden)

    van der Flier Wiesje M

    2009-08-01

    Full Text Available Abstract Background Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD and frontotemporal lobar degeneration (FTLD by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL, a measure of functional connectivity, was calculated for each sensor pair in 0.5–4 Hz, 4–8 Hz, 8–10 Hz, 10–13 Hz, 13–30 Hz and 30–45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity, characteristic path length (global connectivity and degree correlation (network 'assortativity'. All results were normalized for network size and compared with random control networks. Results In AD, the clustering coefficient decreased in the lower alpha and beta bands (p Conclusion With decreasing local and global connectivity parameters, the large-scale functional brain network organization in AD deviates from the optimal 'small-world' network structure towards a more 'random' type. This is associated with less efficient information exchange between brain areas, supporting the disconnection hypothesis of AD. Surprisingly, FTLD patients show changes in the opposite direction, towards a (perhaps excessively more 'ordered' network structure, possibly reflecting a different underlying pathophysiological process.

  12. Visibility graph analysis on quarterly macroeconomic series of China based on complex network theory

    Science.gov (United States)

    Wang, Na; Li, Dong; Wang, Qiwen

    2012-12-01

    The visibility graph approach and complex network theory provide a new insight into time series analysis. The inheritance of the visibility graph from the original time series was further explored in the paper. We found that degree distributions of visibility graphs extracted from Pseudo Brownian Motion series obtained by the Frequency Domain algorithm exhibit exponential behaviors, in which the exponential exponent is a binomial function of the Hurst index inherited in the time series. Our simulations presented that the quantitative relations between the Hurst indexes and the exponents of degree distribution function are different for different series and the visibility graph inherits some important features of the original time series. Further, we convert some quarterly macroeconomic series including the growth rates of value-added of three industry series and the growth rates of Gross Domestic Product series of China to graphs by the visibility algorithm and explore the topological properties of graphs associated from the four macroeconomic series, namely, the degree distribution and correlations, the clustering coefficient, the average path length, and community structure. Based on complex network analysis we find degree distributions of associated networks from the growth rates of value-added of three industry series are almost exponential and the degree distributions of associated networks from the growth rates of GDP series are scale free. We also discussed the assortativity and disassortativity of the four associated networks as they are related to the evolutionary process of the original macroeconomic series. All the constructed networks have “small-world” features. The community structures of associated networks suggest dynamic changes of the original macroeconomic series. We also detected the relationship among government policy changes, community structures of associated networks and macroeconomic dynamics. We find great influences of government

  13. Applying network theory to animal movements to identify properties of landscape space use.

    Science.gov (United States)

    Bastille-Rousseau, Guillaume; Douglas-Hamilton, Iain; Blake, Stephen; Northrup, Joseph M; Wittemyer, George

    2018-04-01

    Network (graph) theory is a popular analytical framework to characterize the structure and dynamics among discrete objects and is particularly effective at identifying critical hubs and patterns of connectivity. The identification of such attributes is a fundamental objective of animal movement research, yet network theory has rarely been applied directly to animal relocation data. We develop an approach that allows the analysis of movement data using network theory by defining occupied pixels as nodes and connection among these pixels as edges. We first quantify node-level (local) metrics and graph-level (system) metrics on simulated movement trajectories to assess the ability of these metrics to pull out known properties in movement paths. We then apply our framework to empirical data from African elephants (Loxodonta africana), giant Galapagos tortoises (Chelonoidis spp.), and mule deer (Odocoileous hemionus). Our results indicate that certain node-level metrics, namely degree, weight, and betweenness, perform well in capturing local patterns of space use, such as the definition of core areas and paths used for inter-patch movement. These metrics were generally applicable across data sets, indicating their robustness to assumptions structuring analysis or strategies of movement. Other metrics capture local patterns effectively, but were sensitive to specified graph properties, indicating case specific applications. Our analysis indicates that graph-level metrics are unlikely to outperform other approaches for the categorization of general movement strategies (central place foraging, migration, nomadism). By identifying critical nodes, our approach provides a robust quantitative framework to identify local properties of space use that can be used to evaluate the effect of the loss of specific nodes on range wide connectivity. Our network approach is intuitive, and can be implemented across imperfectly sampled or large-scale data sets efficiently, providing a

  14. Network Theory Integrated Life Cycle Assessment for an Electric Power System

    Directory of Open Access Journals (Sweden)

    Heetae Kim

    2015-08-01

    Full Text Available In this study, we allocate Greenhouse gas (GHG emissions of electricity transmission to the consumers. As an allocation basis, we introduce energy distance. Energy distance takes the transmission load on the electricity energy system into account in addition to the amount of electricity consumption. As a case study, we estimate regional GHG emissions of electricity transmission loss in Chile. Life cycle assessment (LCA is used to estimate the total GHG emissions of the Chilean electric power system. The regional GHG emission of transmission loss is calculated from the total GHG emissions. We construct the network model of Chilean electric power grid as an undirected network with 466 nodes and 543 edges holding the topology of the power grid based on the statistical record. We analyze the total annual GHG emissions of the Chilean electricity energy system as 23.07 Mt CO2-eq. and 1.61 Mt CO2-eq. for the transmission loss, respectively. The total energy distance for the electricity transmission accounts for 12,842.10 TWh km based on network analysis. We argue that when the GHG emission of electricity transmission loss is estimated, the electricity transmission load should be separately considered. We propose network theory as a useful complement to LCA analysis for the complex allocation. Energy distance is especially useful on a very large-scale electric power grid such as an intercontinental transmission network.

  15. Comparing brain networks of different size and connectivity density using graph theory.

    Directory of Open Access Journals (Sweden)

    Bernadette C M van Wijk

    Full Text Available Graph theory is a valuable framework to study the organization of functional and anatomical connections in the brain. Its use for comparing network topologies, however, is not without difficulties. Graph measures may be influenced by the number of nodes (N and the average degree (k of the network. The explicit form of that influence depends on the type of network topology, which is usually unknown for experimental data. Direct comparisons of graph measures between empirical networks with different N and/or k can therefore yield spurious results. We list benefits and pitfalls of various approaches that intend to overcome these difficulties. We discuss the initial graph definition of unweighted graphs via fixed thresholds, average degrees or edge densities, and the use of weighted graphs. For instance, choosing a threshold to fix N and k does eliminate size and density effects but may lead to modifications of the network by enforcing (ignoring non-significant (significant connections. Opposed to fixing N and k, graph measures are often normalized via random surrogates but, in fact, this may even increase the sensitivity to differences in N and k for the commonly used clustering coefficient and small-world index. To avoid such a bias we tried to estimate the N,k-dependence for empirical networks, which can serve to correct for size effects, if successful. We also add a number of methods used in social sciences that build on statistics of local network structures including exponential random graph models and motif counting. We show that none of the here-investigated methods allows for a reliable and fully unbiased comparison, but some perform better than others.

  16. An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

    International Nuclear Information System (INIS)

    Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

    2011-01-01

    This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

  17. Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

    Science.gov (United States)

    Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

    2016-04-01

    Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of

  18. Practice of Connectivism As Learning Theory: Enhancing Learning Process Through Social Networking Site (Facebook

    Directory of Open Access Journals (Sweden)

    Fahriye Altınay Aksal

    2013-12-01

    Full Text Available The impact of the digital age within learning and social interaction has been growing rapidly. The realm of digital age and computer mediated communication requires reconsidering instruction based on collaborative interactive learning process and socio-contextual experience for learning. Social networking sites such as facebook can help create group space for digital dialogue to inform, question and challenge within a frame of connectivism as learning theory within the digital age. The aim of this study is to elaborate the practice of connectivism as learning theory in terms of internship course. Facebook group space provided social learning platform for dialogue and negotiation beside the classroom learning and teaching process in this study. The 35 internship students provided self-reports within a frame of this qualitative research. This showed how principles of theory practiced and how this theory and facebook group space contribute learning, selfleadership, decision making and reflection skills. As the research reflects a practice of new theory based on action research, learning is not individualistic attempt in the digital age as regards the debate on learning in digital age within a frame of connectivism

  19. Learning network theory : its contribution to our understanding of work-based learning projects and learning climate

    OpenAIRE

    Poell, R.F.; Moorsel, M.A.A.H. van

    1996-01-01

    This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of learning groups in organisations. Four theoretical types of learning projects are distinguished. Four different approaches to the learning climate of work groups are compared to the approach offered by t...

  20. Differential recruitment of theory of mind brain network across three tasks: An independent component analysis.

    Science.gov (United States)

    Thye, Melissa D; Ammons, Carla J; Murdaugh, Donna L; Kana, Rajesh K

    2018-07-16

    Social neuroscience research has focused on an identified network of brain regions primarily associated with processing Theory of Mind (ToM). However, ToM is a broad cognitive process, which encompasses several sub-processes, such as mental state detection and intentional attribution, and the connectivity of brain regions underlying the broader ToM network in response to paradigms assessing these sub-processes requires further characterization. Standard fMRI analyses which focus only on brain activity cannot capture information about ToM processing at a network level. An alternative method, independent component analysis (ICA), is a data-driven technique used to isolate intrinsic connectivity networks, and this approach provides insight into network-level regional recruitment. In this fMRI study, three complementary, but distinct ToM tasks assessing mental state detection (e.g. RMIE: Reading the Mind in the Eyes; RMIV: Reading the Mind in the Voice) and intentional attribution (Causality task) were each analyzed using ICA in order to separately characterize the recruitment and functional connectivity of core nodes in the ToM network in response to the sub-processes of ToM. Based on visual comparison of the derived networks for each task, the spatiotemporal network patterns were similar between the RMIE and RMIV tasks, which elicited mentalizing about the mental states of others, and these networks differed from the network derived for the Causality task, which elicited mentalizing about goal-directed actions. The medial prefrontal cortex, precuneus, and right inferior frontal gyrus were seen in the components with the highest correlation with the task condition for each of the tasks highlighting the role of these regions in general ToM processing. Using a data-driven approach, the current study captured the differences in task-related brain response to ToM in three distinct ToM paradigms. The findings of this study further elucidate the neural mechanisms associated

  1. [A non-classical approach to medical practices: Michel Foucault and Actor-Network Theory].

    Science.gov (United States)

    Bińczyk, E

    2001-01-01

    The text presents an analysis of medical practices stemming from two sources: Michel Foucault's conception and the research of Annemarie Mol and John Law, representatives of a trend known as Actor-Network Theory. Both approaches reveal significant theoretical kinship: they can be successfully consigned to the framework of non-classical sociology of science. I initially refer to the cited conceptions as a version of non-classical sociology of medicine. The identity of non-classical sociology of medicine hinges on the fact that it undermines the possibility of objective definitions of disease, health and body. These are rather approached as variable social and historical phenomena, co-constituted by medical practices. To both Foucault and Mol the main object of interest was not medicine as such, but rather the network of medical practices. Mol and Law sketch a new theoretical perspective for the analysis of medical practices. They attempt to go beyond the dichotomous scheme of thinking about the human body as an object of medical research and the subject of private experience. Research on patients suffering blood-sugar deficiency provide the empirical background for the thesis of Actor-Network Theory representatives. Michel Foucault's conceptions are extremely critical of medical practices. The French researcher describes the processes of 'medicalising' Western society as the emergence of a new type of power. He attempts to sensitise the reader to the ethical dimension of the processes of medicalising society.

  2. Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions

    Directory of Open Access Journals (Sweden)

    Dalhatu Muhammed

    2018-02-01

    Full Text Available Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal, long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted.

  3. Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.

    Science.gov (United States)

    Muhammed, Dalhatu; Anisi, Mohammad Hossein; Zareei, Mahdi; Vargas-Rosales, Cesar; Khan, Anwar

    2018-02-01

    Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted.

  4. An examination of network position and childhood relational aggression: integrating resource control and social exchange theories.

    Science.gov (United States)

    Neal, Jennifer Watling; Cappella, Elise

    2012-01-01

    Applying resource control theory and social exchange theory, we examined the social network conditions under which elementary age children were likely to engage in relational aggression. Data on classroom peer networks and peer-nominated behaviors were collected on 671 second- through fourth-grade children in 34 urban, low-income classrooms. Nested regression models with robust cluster standard errors demonstrated that the association between children's number of relationships and their levels of relational aggression was moderated by the number of relationships that their affiliates had. Children with more peer relationships (i.e., higher network centrality) exhibited higher levels of relational aggression, but only when these relationships were with peers who had fewer connections themselves (i.e., poorly connected peers). This finding remained significant even when controlling for common predictors of relational aggression including gender, overt aggression, prosocial behavior, victimization, social preference, and perceived popularity. Results are discussed in terms of their implications for advancing the literature on childhood relational aggression and their practical applications for identifying children at risk for these behaviors. © 2012 Wiley Periodicals, Inc.

  5. Further evidence of alerted default network connectivity and association with theory of mind ability in schizophrenia.

    Science.gov (United States)

    Mothersill, Omar; Tangney, Noreen; Morris, Derek W; McCarthy, Hazel; Frodl, Thomas; Gill, Michael; Corvin, Aiden; Donohoe, Gary

    2017-06-01

    Resting-state functional magnetic resonance imaging (rs-fMRI) has repeatedly shown evidence of altered functional connectivity of large-scale networks in schizophrenia. The relationship between these connectivity changes and behaviour (e.g. symptoms, neuropsychological performance) remains unclear. Functional connectivity in 27 patients with schizophrenia or schizoaffective disorder, and 25 age and gender matched healthy controls was examined using rs-fMRI. Based on seed regions from previous studies, we examined functional connectivity of the default, cognitive control, affective and attention networks. Effects of symptom severity and theory of mind performance on functional connectivity were also examined. Patients showed increased connectivity between key nodes of the default network including the precuneus and medial prefrontal cortex compared to controls (pmind performance were both associated with altered connectivity of default regions within the patient group (pmind performance. Extending these findings by examining the effects of emerging social cognition treatments on both default connectivity and theory of mind performance is now an important goal for research. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Adaptive capacity of geographical clusters: Complexity science and network theory approach

    Science.gov (United States)

    Albino, Vito; Carbonara, Nunzia; Giannoccaro, Ilaria

    This paper deals with the adaptive capacity of geographical clusters (GCs), that is a relevant topic in the literature. To address this topic, GC is considered as a complex adaptive system (CAS). Three theoretical propositions concerning the GC adaptive capacity are formulated by using complexity theory. First, we identify three main properties of CAS s that affect the adaptive capacity, namely the interconnectivity, the heterogeneity, and the level of control, and define how the value of these properties influence the adaptive capacity. Then, we associate these properties with specific GC characteristics so obtaining the key conditions of GCs that give them the adaptive capacity so assuring their competitive advantage. To test these theoretical propositions, a case study on two real GCs is carried out. The considered GCs are modeled as networks where firms are nodes and inter-firms relationships are links. Heterogeneity, interconnectivity, and level of control are considered as network properties and thus measured by using the methods of the network theory.

  7. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Science.gov (United States)

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  8. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Directory of Open Access Journals (Sweden)

    Xiaolei Ma

    Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  9. Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions

    Science.gov (United States)

    Muhammed, Dalhatu; Anisi, Mohammad Hossein; Vargas-Rosales, Cesar; Khan, Anwar

    2018-01-01

    Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node’s cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted. PMID:29389874

  10. Criminal groups and transnational illegal markets : A more detailed examination on the basis of Social Network Theory

    NARCIS (Netherlands)

    Bruinsma, Gerben; Bernasco, Wim

    In the study of organised crime, the traditional view of criminal groups as centrally controlled organisations has been replaced by the notion of criminal networks. However, little use has been made of concepts and theories of social networks that have developed in other social sciences. This paper

  11. Causal relationship between the global foreign exchange market based on complex networks and entropy theory

    International Nuclear Information System (INIS)

    Cao, Guangxi; Zhang, Qi; Li, Qingchen

    2017-01-01

    Highlights: • Mutual information is used as the edge weights of nodes instead of PCC, which overcomes the shortcomings of linear correlation functions. • SGD turns into a new cluster center and gradually becomes a point connecting the Asian and European clusters during and after the US sub-prime crisis. • Liang's entropy theory, which has not been adopted before in the global foreign exchange market, is considered. - Abstract: The foreign exchange (FX) market is a typical complex dynamic system under the background of exchange rate marketization reform and is an important part of the financial market. This study aims to generate an international FX network based on complex network theory. This study employs the mutual information method to judge the nonlinear characteristics of 54 major currencies in international FX markets. Through this method, we find that the FX network possesses a small average path length and a large clustering coefficient under different thresholds and that it exhibits small-world characteristics as a whole. Results show that the relationship between FX rates is close. Volatility can quickly transfer in the whole market, and the FX volatility of influential individual states transfers at a fast pace and a large scale. The period from July 21, 2005 to March 31, 2015 is subdivided into three sub-periods (i.e., before, during, and after the US sub-prime crisis) to analyze the topology evolution of FX markets using the maximum spanning tree approach. Results show that the USD gradually lost its core position, EUR remained a stable center, and the center of the Asian cluster became unstable. Liang's entropy theory is used to analyze the causal relationship between the four large clusters of the world.

  12. OUTDOOR RECREATION THROUGH THE PRISM OF ACTOR-NETWORK THEORY: CHALLENGES AND PROSPECTS

    Directory of Open Access Journals (Sweden)

    Yohann Rech

    2009-12-01

    Full Text Available Actor-network theory (ANT shows how scientific and technical innovations may take the form of a socio-technical network, by the aggregation of humans and non-humans (Callon, 1986; Latour, 1989. This article reflects on the contributions and limits of ANT to examine a particular object of research presenting regular innovations: the outdoor recreation. Firstly, the integration of non-humans to the analysis (Latour, 2006 is relevant in the study of nature sports because physical entities transform the action and involve specific associations. Then it is a particular epistemological positioning that shakes the dichotomies up and givesimportance to the reflexive activity of actors. Finally, understanding the development of collectives is useful for the study of nature sports. The construction of a social coexistence between different activities (sports activities and other activities strongly questions the political transformation of contemporary democracy, including the establishment of a participatory management.

  13. An object recognition method based on fuzzy theory and BP networks

    Science.gov (United States)

    Wu, Chuan; Zhu, Ming; Yang, Dong

    2006-01-01

    It is difficult to choose eigenvectors when neural network recognizes object. It is possible that the different object eigenvectors is similar or the same object eigenvectors is different under scaling, shifting, rotation if eigenvectors can not be chosen appropriately. In order to solve this problem, the image is edged, the membership function is reconstructed and a new threshold segmentation method based on fuzzy theory is proposed to get the binary image. Moment invariant of binary image is extracted and normalized. Some time moment invariant is too small to calculate effectively so logarithm of moment invariant is taken as input eigenvectors of BP network. The experimental results demonstrate that the proposed approach could recognize the object effectively, correctly and quickly.

  14. Beyond effectuation: Analysing the transformation of business ideas into ventures using actor-network theory"

    DEFF Research Database (Denmark)

    Murdock, Karen; Varnes, Claus Juul

    2018-01-01

    definition of the entrepreneurial endeavour. Originality/value This paper examines how ideas are transformed into business ventures by using the ANT to expand understanding from effectuation theory. This shows that means, for instance, are not given but are co-created by the process of translation....../methodology/approach This study uses a longitudinal case study design. The case provides an overview of a new business’s emergence based on three identified translations, each representing critical junctures in the business’s development. An ethnographic approach is selected, which combines observations with qualitative...... as new humans or non-humans become part of it. Including a resource in the network means simultaneously changing the network. This interactionism shows that what sparks interest or attracts resources to a business idea is not simply an influx of additional resources but is simultaneously a dynamic...

  15. Characterization and detection of thermoacoustic combustion oscillations based on statistical complexity and complex-network theory

    Science.gov (United States)

    Murayama, Shogo; Kinugawa, Hikaru; Tokuda, Isao T.; Gotoda, Hiroshi

    2018-02-01

    We present an experimental study on the characterization of dynamic behavior of flow velocity field during thermoacoustic combustion oscillations in a turbulent confined combustor from the viewpoints of statistical complexity and complex-network theory, involving detection of a precursor of thermoacoustic combustion oscillations. The multiscale complexity-entropy causality plane clearly shows the possible presence of two dynamics, noisy periodic oscillations and noisy chaos, in the shear layer regions (1) between the outer recirculation region in the dump plate and a recirculation flow in the wake of the centerbody and (2) between the outer recirculation region in the dump plate and a vortex breakdown bubble away from the centerbody. The vertex strength in the turbulence network and the community structure of the vorticity field can identify the vortical interactions during thermoacoustic combustion oscillations. Sequential horizontal visibility graph motifs are useful for capturing a precursor of themoacoustic combustion oscillations.

  16. Securing mobile ad hoc networks using danger theory-based artificial immune algorithm.

    Science.gov (United States)

    Abdelhaq, Maha; Alsaqour, Raed; Abdelhaq, Shawkat

    2015-01-01

    A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs.

  17. A User Cooperation Stimulating Strategy Based on Cooperative Game Theory in Cooperative Relay Networks

    Directory of Open Access Journals (Sweden)

    Ping Zhang

    2009-01-01

    Full Text Available This paper proposes a user cooperation stimulating strategy among rational users. The strategy is based on cooperative game theory and enacted in the context of cooperative relay networks. Using the pricing-based mechanism, the system is modeled initially with two nodes and a Base Station (BS. Within this framework, each node is treated as a rational decision maker. To this end, each node can decide whether to cooperate and how to cooperate. Cooperative game theory assists in providing an optimal system utility and provides fairness among users. Under different cooperative forwarding modes, certain questions are carefully investigated, including “what is each node's best reaction to maximize its utility?” and “what is the optimal reimbursement to encourage cooperation?” Simulation results show that the nodes benefit from the proposed cooperation stimulating strategy in terms of utility and thus justify the fairness between each user.

  18. A User Cooperation Stimulating Strategy Based on Cooperative Game Theory in Cooperative Relay Networks

    Directory of Open Access Journals (Sweden)

    Jiang Fan

    2009-01-01

    Full Text Available This paper proposes a user cooperation stimulating strategy among rational users. The strategy is based on cooperative game theory and enacted in the context of cooperative relay networks. Using the pricing-based mechanism, the system is modeled initially with two nodes and a Base Station (BS. Within this framework, each node is treated as a rational decision maker. To this end, each node can decide whether to cooperate and how to cooperate. Cooperative game theory assists in providing an optimal system utility and provides fairness among users. Under different cooperative forwarding modes, certain questions are carefully investigated, including "what is each node's best reaction to maximize its utility?" and "what is the optimal reimbursement to encourage cooperation?" Simulation results show that the nodes benefit from the proposed cooperation stimulating strategy in terms of utility and thus justify the fairness between each user.

  19. Cryptographic Puzzles and Game Theory against DoS and DDoS attacks in Networks

    DEFF Research Database (Denmark)

    Mikalas, Antonis; Komninos, Nikos; Prasad, Neeli R.

    2008-01-01

    In this chapter, we present techniques to defeat Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. In the _rst part, we describe client puzzle techniques that are based on the idea of computationally exhausting a malicious user when he attempts to launch an attack. In the ......In this chapter, we present techniques to defeat Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. In the _rst part, we describe client puzzle techniques that are based on the idea of computationally exhausting a malicious user when he attempts to launch an attack....... In the second part we are introducing some basic principles of game theory and we discuss how game theoretical frameworks can protect computer networks. Finally, we show techniques that combine client puzzles with game theory in order to provide DoS and DDoS resilience....

  20. Optimal design of hydrometric monitoring networks with dynamic components based on Information Theory

    Science.gov (United States)

    Alfonso, Leonardo; Chacon, Juan; Solomatine, Dimitri

    2016-04-01

    The EC-FP7 WeSenseIt project proposes the development of a Citizen Observatory of Water, aiming at enhancing environmental monitoring and forecasting with the help of citizens equipped with low-cost sensors and personal devices such as smartphones and smart umbrellas. In this regard, Citizen Observatories may complement the limited data availability in terms of spatial and temporal density, which is of interest, among other areas, to improve hydraulic and hydrological models. At this point, the following question arises: how can citizens, who are part of a citizen observatory, be optimally guided so that the data they collect and send is useful to improve modelling and water management? This research proposes a new methodology to identify the optimal location and timing of potential observations coming from moving sensors of hydrological variables. The methodology is based on Information Theory, which has been widely used in hydrometric monitoring design [1-4]. In particular, the concepts of Joint Entropy, as a measure of the amount of information that is contained in a set of random variables, which, in our case, correspond to the time series of hydrological variables captured at given locations in a catchment. The methodology presented is a step forward in the state of the art because it solves the multiobjective optimisation problem of getting simultaneously the minimum number of informative and non-redundant sensors needed for a given time, so that the best configuration of monitoring sites is found at every particular moment in time. To this end, the existing algorithms have been improved to make them efficient. The method is applied to cases in The Netherlands, UK and Italy and proves to have a great potential to complement the existing in-situ monitoring networks. [1] Alfonso, L., A. Lobbrecht, and R. Price (2010a), Information theory-based approach for location of monitoring water level gauges in polders, Water Resour. Res., 46(3), W03528 [2] Alfonso, L., A

  1. Unifying Pore Network Modeling, Continuous Time Random Walk Theory and Experiment - Accomplishments and Future Directions

    Science.gov (United States)

    Bijeljic, B.

    2008-05-01

    This talk will describe and highlight the advantages offered by a methodology that unifies pore network modeling, CTRW theory and experiment in description of solute dispersion in porous media. Solute transport in a porous medium is characterized by the interplay of advection and diffusion (described by Peclet number, Pe) that cause spreading of solute particles. This spreading is traditionally described by dispersion coefficients, D, defined by σ 2 = 2Dt, where σ 2 is the variance of the solute position and t is the time. Using a pore-scale network model based on particle tracking, the rich Peclet- number dependence of dispersion coefficient is predicted from first principles and is shown to compare well with experimental data for restricted diffusion, transition, power-law and mechanical dispersion regimes in the asymptotic limit. In the asymptotic limit D is constant and can be used in an averaged advection-dispersion equation. However, it is highly important to recognize that, until the velocity field is fully sampled, the particle transport is non-Gaussian and D possesses temporal or spatial variation. Furthermore, temporal probability density functions (PDF) of tracer particles are studied in pore networks and an excellent agreement for the spectrum of transition times for particles from pore to pore is obtained between network model results and CTRW theory. Based on the truncated power-law interpretation of PDF-s, the physical origin of the power-law scaling of dispersion coefficient vs. Peclet number has been explained for unconsolidated porous media, sands and a number of sandstones, arriving at the same conclusion from numerical network modelling, analytic CTRW theory and experiment. Future directions for further applications of the methodology presented are discussed in relation to the scale- dependent solute dispersion and reactive transport. Significance of pre-asymptotic dispersion in porous media is addressed from pore-scale upwards and the impact

  2. Real-Time Dynamics in U(1 Lattice Gauge Theories with Tensor Networks

    Directory of Open Access Journals (Sweden)

    T. Pichler

    2016-03-01

    Full Text Available Tensor network algorithms provide a suitable route for tackling real-time-dependent problems in lattice gauge theories, enabling the investigation of out-of-equilibrium dynamics. We analyze a U(1 lattice gauge theory in (1+1 dimensions in the presence of dynamical matter for different mass and electric-field couplings, a theory akin to quantum electrodynamics in one dimension, which displays string breaking: The confining string between charges can spontaneously break during quench experiments, giving rise to charge-anticharge pairs according to the Schwinger mechanism. We study the real-time spreading of excitations in the system by means of electric-field and particle fluctuations. We determine a dynamical state diagram for string breaking and quantitatively evaluate the time scales for mass production. We also show that the time evolution of the quantum correlations can be detected via bipartite von Neumann entropies, thus demonstrating that the Schwinger mechanism is tightly linked to entanglement spreading. To present a variety of possible applications of this simulation platform, we show how one could follow the real-time scattering processes between mesons and the creation of entanglement during scattering processes. Finally, we test the quality of quantum simulations of these dynamics, quantifying the role of possible imperfections in cold atoms, trapped ions, and superconducting circuit systems. Our results demonstrate how entanglement properties can be used to deepen our understanding of basic phenomena in the real-time dynamics of gauge theories such as string breaking and collisions.

  3. Fractal Point Process and Queueing Theory and Application to Communication Networks

    National Research Council Canada - National Science Library

    Wornel, Gregory

    1999-01-01

    .... A unifying theme in the approaches to these problems has been an integration of interrelated perspectives from communication theory, information theory, signal processing theory, and control theory...

  4. Extraction of business relationships in supply networks using statistical learning theory.

    Science.gov (United States)

    Zuo, Yi; Kajikawa, Yuya; Mori, Junichiro

    2016-06-01

    Supply chain management represents one of the most important scientific streams of operations research. The supply of energy, materials, products, and services involves millions of transactions conducted among national and local business enterprises. To deliver efficient and effective support for supply chain design and management, structural analyses and predictive models of customer-supplier relationships are expected to clarify current enterprise business conditions and to help enterprises identify innovative business partners for future success. This article presents the outcomes of a recent structural investigation concerning a supply network in the central area of Japan. We investigated the effectiveness of statistical learning theory to express the individual differences of a supply chain of enterprises within a certain business community using social network analysis. In the experiments, we employ support vector machine to train a customer-supplier relationship model on one of the main communities extracted from a supply network in the central area of Japan. The prediction results reveal an F-value of approximately 70% when the model is built by using network-based features, and an F-value of approximately 77% when the model is built by using attribute-based features. When we build the model based on both, F-values are improved to approximately 82%. The results of this research can help to dispel the implicit design space concerning customer-supplier relationships, which can be explored and refined from detailed topological information provided by network structures rather than from traditional and attribute-related enterprise profiles. We also investigate and discuss differences in the predictive accuracy of the model for different sizes of enterprises and types of business communities.

  5. Extraction of business relationships in supply networks using statistical learning theory

    Directory of Open Access Journals (Sweden)

    Yi Zuo

    2016-06-01

    Full Text Available Supply chain management represents one of the most important scientific streams of operations research. The supply of energy, materials, products, and services involves millions of transactions conducted among national and local business enterprises. To deliver efficient and effective support for supply chain design and management, structural analyses and predictive models of customer–supplier relationships are expected to clarify current enterprise business conditions and to help enterprises identify innovative business partners for future success. This article presents the outcomes of a recent structural investigation concerning a supply network in the central area of Japan. We investigated the effectiveness of statistical learning theory to express the individual differences of a supply chain of enterprises within a certain business community using social network analysis. In the experiments, we employ support vector machine to train a customer–supplier relationship model on one of the main communities extracted from a supply network in the central area of Japan. The prediction results reveal an F-value of approximately 70% when the model is built by using network-based features, and an F-value of approximately 77% when the model is built by using attribute-based features. When we build the model based on both, F-values are improved to approximately 82%. The results of this research can help to dispel the implicit design space concerning customer–supplier relationships, which can be explored and refined from detailed topological information provided by network structures rather than from traditional and attribute-related enterprise profiles. We also investigate and discuss differences in the predictive accuracy of the model for different sizes of enterprises and types of business communities.

  6. Exploring agency beyond humans: the compatibility of Actor-Network Theory (ANT and resilience thinking

    Directory of Open Access Journals (Sweden)

    Angga Dwiartama

    2014-09-01

    Full Text Available At first glance, the compatibility of social theory and resilience thinking is not entirely evident, in part because the ontology of the former is rooted in social interactions among human beings rather than ecological process. Despite this difference, resilience thinking engages with particular aspects of social organization that have generated intense debates within social science, namely the role of humans as integral elements of social-ecological systems and the processes through which given social structures (including material relations are either maintained or transformed. Among social theoretical approaches, Actor-Network Theory (ANT is noted for its distinctive approach to these aspects. ANT proposes that human and nonhuman components (both referred to as actants have the same capacity to influence the development of social-ecological systems (represented as actor-networks by enacting relations and enrolling other actors. We explore the notion of agency that is employed in resilience thinking and ANT in order to extend our understandings of human-environment relationships through complementary insights from each approach. The discussion is illustrated by reference to ongoing assessment of resilience as it is experienced and expressed in two distinctive agricultural production systems: Indonesian rice and New Zealand kiwifruit. We conclude by establishing the potential for ANT to provide more profound theoretical conceptualizations of agency, both human and nonhuman, in analyses of social ecological systems.

  7. Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 1. Flow without reactions

    Science.gov (United States)

    Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.

    2017-12-01

    We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.

  8. Real-time flood forecasts & risk assessment using a possibility-theory based fuzzy neural network

    Science.gov (United States)

    Khan, U. T.

    2016-12-01

    Globally floods are one of the most devastating natural disasters and improved flood forecasting methods are essential for better flood protection in urban areas. Given the availability of high resolution real-time datasets for flood variables (e.g. streamflow and precipitation) in many urban areas, data-driven models have been effectively used to predict peak flow rates in river; however, the selection of input parameters for these types of models is often subjective. Additionally, the inherit uncertainty associated with data models along with errors in extreme event observations means that uncertainty quantification is essential. Addressing these concerns will enable improved flood forecasting methods and provide more accurate flood risk assessments. In this research, a new type of data-driven model, a quasi-real-time updating fuzzy neural network is developed to predict peak flow rates in urban riverine watersheds. A possibility-to-probability transformation is first used to convert observed data into fuzzy numbers. A possibility theory based training regime is them used to construct the fuzzy parameters and the outputs. A new entropy-based optimisation criterion is used to train the network. Two existing methods to select the optimum input parameters are modified to account for fuzzy number inputs, and compared. These methods are: Entropy-Wavelet-based Artificial Neural Network (EWANN) and Combined Neural Pathway Strength Analysis (CNPSA). Finally, an automated algorithm design to select the optimum structure of the neural network is implemented. The overall impact of each component of training this network is to replace the traditional ad hoc network configuration methods, with one based on objective criteria. Ten years of data from the Bow River in Calgary, Canada (including two major floods in 2005 and 2013) are used to calibrate and test the network. The EWANN method selected lagged peak flow as a candidate input, whereas the CNPSA method selected lagged

  9. Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.

    Science.gov (United States)

    Pantazis, Yannis; Katsoulakis, Markos A; Vlachos, Dionisios G

    2013-10-22

    Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve networks of coupled jump stochastic processes with a large number of parameters that need to be suitably calibrated against experimental data. In this direction, the parameter sensitivity analysis of reaction networks is an essential mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, existing sensitivity analysis approaches such as variants of the finite difference method can have an overwhelming computational cost in models with a high-dimensional parameter space. We develop a sensitivity analysis methodology suitable for complex stochastic reaction networks with a large number of parameters. The proposed approach is based on Information Theory methods and relies on the quantification of information loss due to parameter perturbations between time-series distributions. For this reason, we need to work on path-space, i.e., the set consisting of all stochastic trajectories, hence the proposed approach is referred to as "pathwise". The pathwise sensitivity analysis method is realized by employing the rigorously-derived Relative Entropy Rate, which is directly computable from the propensity functions. A key aspect of the method is that an associated pathwise Fisher Information Matrix (FIM) is defined, which in turn constitutes a gradient-free approach to quantifying parameter sensitivities. The structure of the FIM turns out to be block-diagonal, revealing hidden parameter dependencies and sensitivities in reaction networks. As a gradient-free method, the proposed sensitivity analysis provides a significant advantage when dealing with complex stochastic systems with a large number of parameters. In addition, the knowledge of the structure of the FIM can allow to efficiently address

  10. Optimization of hydrometric monitoring network in urban drainage systems using information theory.

    Science.gov (United States)

    Yazdi, J

    2017-10-01

    Regular and continuous monitoring of urban runoff in both quality and quantity aspects is of great importance for controlling and managing surface runoff. Due to the considerable costs of establishing new gauges, optimization of the monitoring network is essential. This research proposes an approach for site selection of new discharge stations in urban areas, based on entropy theory in conjunction with multi-objective optimization tools and numerical models. The modeling framework provides an optimal trade-off between the maximum possible information content and the minimum shared information among stations. This approach was applied to the main surface-water collection system in Tehran to determine new optimal monitoring points under the cost considerations. Experimental results on this drainage network show that the obtained cost-effective designs noticeably outperform the consulting engineers' proposal in terms of both information contents and shared information. The research also determined the highly frequent sites at the Pareto front which might be important for decision makers to give a priority for gauge installation on those locations of the network.

  11. Aberrant functioning of the theory-of-mind network in children and adolescents with autism.

    Science.gov (United States)

    Kana, Rajesh K; Maximo, Jose O; Williams, Diane L; Keller, Timothy A; Schipul, Sarah E; Cherkassky, Vladimir L; Minshew, Nancy J; Just, Marcel Adam

    2015-01-01

    Theory-of-mind (ToM), the ability to infer people's thoughts and feelings, is a pivotal skill in effective social interactions. Individuals with autism spectrum disorders (ASD) have been found to have altered ToM skills, which significantly impacts the quality of their social interactions. Neuroimaging studies have reported altered activation of the ToM cortical network, especially in adults with autism, yet little is known about the brain responses underlying ToM in younger individuals with ASD. This functional magnetic resonance imaging (fMRI) study investigated the neural mechanisms underlying ToM in high-functioning children and adolescents with ASD and matched typically developing (TD) peers. fMRI data were acquired from 13 participants with ASD and 13 TD control participants while they watched animations involving two "interacting" geometrical shapes. Participants with ASD showed significantly reduced activation, relative to TD controls, in regions considered part of the ToM network, the mirror network, and the cerebellum. Functional connectivity analyses revealed underconnectivity between frontal and posterior regions during task performance in the ASD participants. Overall, the findings of this study reveal disruptions in the brain circuitry underlying ToM in ASD at multiple levels, including decreased activation and decreased functional connectivity.

  12. Information theory and signal transduction systems: from molecular information processing to network inference.

    Science.gov (United States)

    Mc Mahon, Siobhan S; Sim, Aaron; Filippi, Sarah; Johnson, Robert; Liepe, Juliane; Smith, Dominic; Stumpf, Michael P H

    2014-11-01

    Sensing and responding to the environment are two essential functions that all biological organisms need to master for survival and successful reproduction. Developmental processes are marshalled by a diverse set of signalling and control systems, ranging from systems with simple chemical inputs and outputs to complex molecular and cellular networks with non-linear dynamics. Information theory provides a powerful and convenient framework in which such systems can be studied; but it also provides the means to reconstruct the structure and dynamics of molecular interaction networks underlying physiological and developmental processes. Here we supply a brief description of its basic concepts and introduce some useful tools for systems and developmental biologists. Along with a brief but thorough theoretical primer, we demonstrate the wide applicability and biological application-specific nuances by way of different illustrative vignettes. In particular, we focus on the characterisation of biological information processing efficiency, examining cell-fate decision making processes, gene regulatory network reconstruction, and efficient signal transduction experimental design. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Asymptotic Analysis of Large Cooperative Relay Networks Using Random Matrix Theory

    Directory of Open Access Journals (Sweden)

    H. Poor

    2008-04-01

    Full Text Available Cooperative transmission is an emerging communication technology that takes advantage of the broadcast nature of wireless channels. In cooperative transmission, the use of relays can create a virtual antenna array so that multiple-input/multiple-output (MIMO techniques can be employed. Most existing work in this area has focused on the situation in which there are a small number of sources and relays and a destination. In this paper, cooperative relay networks with large numbers of nodes are analyzed, and in particular the asymptotic performance improvement of cooperative transmission over direction transmission and relay transmission is analyzed using random matrix theory. The key idea is to investigate the eigenvalue distributions related to channel capacity and to analyze the moments of this distribution in large wireless networks. A performance upper bound is derived, the performance in the low signal-to-noise-ratio regime is analyzed, and two approximations are obtained for high and low relay-to-destination link qualities, respectively. Finally, simulations are provided to validate the accuracy of the analytical results. The analysis in this paper provides important tools for the understanding and the design of large cooperative wireless networks.

  14. Design of a universal two-layered neural network derived from the PLI theory

    Science.gov (United States)

    Hu, Chia-Lun J.

    2004-05-01

    The if-and-only-if (IFF) condition that a set of M analog-to-digital vector-mapping relations can be learned by a one-layered-feed-forward neural network (OLNN) is that all the input analog vectors dichotomized by the i-th output bit must be positively, linearly independent, or PLI. If they are not PLI, then the OLNN just cannot learn no matter what learning rules is employed because the solution of the connection matrix does not exist mathematically. However, in this case, one can still design a parallel-cascaded, two-layered, perceptron (PCTLP) to acheive this general mapping goal. The design principle of this "universal" neural network is derived from the major mathematical properties of the PLI theory - changing the output bits of the dependent relations existing among the dichotomized input vectors to make the PLD relations PLI. Then with a vector concatenation technique, the required mapping can still be learned by this PCTLP system with very high efficiency. This paper will report in detail the mathematical derivation of the general design principle and the design procedures of the PCTLP neural network system. It then will be verified in general by a practical numerical example.

  15. ‘Living' theory: a pedagogical framework for process support in networked learning

    Directory of Open Access Journals (Sweden)

    Philipa Levy

    2006-12-01

    Full Text Available This paper focuses on the broad outcome of an action research project in which practical theory was developed in the field of networked learning through case-study analysis of learners' experiences and critical evaluation of educational practice. It begins by briefly discussing the pedagogical approach adopted for the case-study course and the action research methodology. It then identifies key dimensions of four interconnected developmental processes–orientation, communication, socialisation and organisation–that were associated with ‘learning to learn' in the course's networked environment, and offers a flavour of participants' experiences in relation to these processes. A number of key evaluation issues that arose are highlighted. Finally, the paper presents the broad conceptual framework for the design and facilitation of process support in networked learning that was derived from this research. The framework proposes a strong, explicit focus on support for process as well as domain learning, and progression from tighter to looser design and facilitation structures for process-focused (as well as domain-focused learning tasks.

  16. A Game Theory-Based Obstacle Avoidance Routing Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Shujun Bi

    2011-09-01

    Full Text Available The obstacle avoidance problem in geographic forwarding is an important issue for location-based routing in wireless sensor networks. The presence of an obstacle leads to several geographic routing problems such as excessive energy consumption and data congestion. Obstacles are hard to avoid in realistic environments. To bypass obstacles, most routing protocols tend to forward packets along the obstacle boundaries. This leads to a situation where the nodes at the boundaries exhaust their energy rapidly and the obstacle area is diffused. In this paper, we introduce a novel routing algorithm to solve the obstacle problem in wireless sensor networks based on a game-theory model. Our algorithm forms a concave region that cannot forward packets to achieve the aim of improving the transmission success rate and decreasing packet transmission delays. We consider the residual energy, out-degree and forwarding angle to determine the forwarding probability and payoff function of forwarding candidates. This achieves the aim of load balance and reduces network energy consumption. Simulation results show that based on the average delivery delay, energy consumption and packet delivery ratio performances our protocol is superior to other traditional schemes.

  17. Application of Percolation Theory to Complex Interconnected Networks in Advanced Functional Composites

    Science.gov (United States)

    Hing, P.

    2011-11-01

    Percolation theory deals with the behaviour of connected clusters in a system. Originally developed for studying the flow of liquid in a porous body, the percolation theory has been extended to quantum computation and communication, entanglement percolation in quantum networks, cosmology, chaotic situations, properties of disordered solids, pandemics, petroleum industry, finance, control of traffic and so on. In this paper, the application of various models of the percolation theory to predict and explain the properties of a specially developed family of dense sintered and highly refractory Al2O3-W composites for potential application in high intensity discharge light sources such as high pressure sodium lamps and ceramic metal halide lamps are presented and discussed. The low cost, core-shell concept can be extended to develop functional composite materials with unusual dielectric, electrical, magnetic, superconducting, and piezoelectric properties starting from a classical insulator. The core shell concept can also be applied to develop catalysts with high specific surface areas with minimal amount of expensive platinium, palladium or rare earth nano structured materials for light harvesting, replicating natural photosynthesis, in synthetic zeolite composites for the cracking and separation of crude oil. There is also possibility of developing micron and nanosize Faraday cages for quantum devices, nano electronics and spintronics. The possibilities are limitless.

  18. Quantitative design of emergency monitoring network for river chemical spills based on discrete entropy theory.

    Science.gov (United States)

    Shi, Bin; Jiang, Jiping; Sivakumar, Bellie; Zheng, Yi; Wang, Peng

    2018-05-01

    Field monitoring strategy is critical for disaster preparedness and watershed emergency environmental management. However, development of such is also highly challenging. Despite the efforts and progress thus far, no definitive guidelines or solutions are available worldwide for quantitatively designing a monitoring network in response to river chemical spill incidents, except general rules based on administrative divisions or arbitrary interpolation on routine monitoring sections. To address this gap, a novel framework for spatial-temporal network design was proposed in this study. The framework combines contaminant transport modelling with discrete entropy theory and spectral analysis. The water quality model was applied to forecast the spatio-temporal distribution of contaminant after spills and then corresponding information transfer indexes (ITIs) and Fourier approximation periodic functions were estimated as critical measures for setting sampling locations and times. The results indicate that the framework can produce scientific preparedness plans of emergency monitoring based on scenario analysis of spill risks as well as rapid design as soon as the incident happened but not prepared. The framework was applied to a hypothetical spill case based on tracer experiment and a real nitrobenzene spill incident case to demonstrate its suitability and effectiveness. The newly-designed temporal-spatial monitoring network captured major pollution information at relatively low costs. It showed obvious benefits for follow-up early-warning and treatment as well as for aftermath recovery and assessment. The underlying drivers of ITIs as well as the limitations and uncertainty of the approach were analyzed based on the case studies. Comparison with existing monitoring network design approaches, management implications, and generalized applicability were also discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

  19. Actor-Network Theory and methodology: Just what does it mean to say that nonhumans have agency?

    Science.gov (United States)

    Sayes, Edwin

    2014-02-01

    Actor-Network Theory is a controversial social theory. In no respect is this more so than the role it 'gives' to nonhumans: nonhumans have agency, as Latour provocatively puts it. This article aims to interrogate the multiple layers of this declaration to understand what it means to assert with Actor-Network Theory that nonhumans exercise agency. The article surveys a wide corpus of statements by the position's leading figures and emphasizes the wider methodological framework in which these statements are embedded. With this work done, readers will then be better placed to reject or accept the Actor-Network position - understanding more precisely what exactly it is at stake in this decision.

  20. Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes

    Science.gov (United States)

    2014-09-01

    networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis

  1. STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

    Science.gov (United States)

    Cooke, C. H.

    1975-01-01

    STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

  2. Investigation on law and economics of listed companies' financing preference based on complex network theory.

    Directory of Open Access Journals (Sweden)

    Jian Yang

    Full Text Available In this paper, complex network theory is used to make time-series analysis of key indicators of governance structure and financing data. We analyze scientific listed companies' governance data from 2010 to 2014 and divide them into groups in accordance with the similarity they share. Then we select sample companies to analyze their financing data and explore the influence of governance structure on financing decision and the financing preference they display. This paper reviews relevant laws and regulations of financing from the perspective of law and economics, then proposes reasonable suggestions to consummate the law for the purpose of regulating listed companies' financing. The research provides a reference for making qualitative analysis on companies' financing.

  3. Improving the accuracy of Møller-Plesset perturbation theory with neural networks

    Science.gov (United States)

    McGibbon, Robert T.; Taube, Andrew G.; Donchev, Alexander G.; Siva, Karthik; Hernández, Felipe; Hargus, Cory; Law, Ka-Hei; Klepeis, John L.; Shaw, David E.

    2017-10-01

    Noncovalent interactions are of fundamental importance across the disciplines of chemistry, materials science, and biology. Quantum chemical calculations on noncovalently bound complexes, which allow for the quantification of properties such as binding energies and geometries, play an essential role in advancing our understanding of, and building models for, a vast array of complex processes involving molecular association or self-assembly. Because of its relatively modest computational cost, second-order Møller-Plesset perturbation (MP2) theory is one of the most widely used methods in quantum chemistry for studying noncovalent interactions. MP2 is, however, plagued by serious errors due to its incomplete treatment of electron correlation, especially when modeling van der Waals interactions and π-stacked complexes. Here we present spin-network-scaled MP2 (SNS-MP2), a new semi-empirical MP2-based method for dimer interaction-energy calculations. To correct for errors in MP2, SNS-MP2 uses quantum chemical features of the complex under study in conjunction with a neural network to reweight terms appearing in the total MP2 interaction energy. The method has been trained on a new data set consisting of over 200 000 complete basis set (CBS)-extrapolated coupled-cluster interaction energies, which are considered the gold standard for chemical accuracy. SNS-MP2 predicts gold-standard binding energies of unseen test compounds with a mean absolute error of 0.04 kcal mol-1 (root-mean-square error 0.09 kcal mol-1), a 6- to 7-fold improvement over MP2. To the best of our knowledge, its accuracy exceeds that of all extant density functional theory- and wavefunction-based methods of similar computational cost, and is very close to the intrinsic accuracy of our benchmark coupled-cluster methodology itself. Furthermore, SNS-MP2 provides reliable per-conformation confidence intervals on the predicted interaction energies, a feature not available from any alternative method.

  4. How network-based incubation helps start-up performance : a systematic review against the background of management theories

    OpenAIRE

    Eveleens, Chris P.; van Rijnsoever, Frank J.; Niesten, Eva M M I

    2017-01-01

    The literature on how network-based incubation influences the performance of technology-based start-ups has recently grown considerably and provided valuable insights. However, at the same time this literature has become quite fragmented, inconsistently conceptualised, and theoretically underdeveloped. Therefore, this article uses three management theories to structure the literature, improve the theoretical underpinning and develop an agenda for further research. The management theories are ...

  5. Load reduction test method of similarity theory and BP neural networks of large cranes

    Science.gov (United States)

    Yang, Ruigang; Duan, Zhibin; Lu, Yi; Wang, Lei; Xu, Gening

    2016-01-01

    Static load tests are an important means of supervising and detecting a crane's lift capacity. Due to space restrictions, however, there are difficulties and potential danger when testing large bridge cranes. To solve the loading problems of large-tonnage cranes during testing, an equivalency test is proposed based on the similarity theory and BP neural networks. The maximum stress and displacement of a large bridge crane is tested in small loads, combined with the training neural network of a similar structure crane through stress and displacement data which is collected by a physics simulation progressively loaded to a static load test load within the material scope of work. The maximum stress and displacement of a crane under a static load test load can be predicted through the relationship of stress, displacement, and load. By measuring the stress and displacement of small tonnage weights, the stress and displacement of large loads can be predicted, such as the maximum load capacity, which is 1.25 times the rated capacity. Experimental study shows that the load reduction test method can reflect the lift capacity of large bridge cranes. The load shedding predictive analysis for Sanxia 1200 t bridge crane test data indicates that when the load is 1.25 times the rated lifting capacity, the predicted displacement and actual displacement error is zero. The method solves the problem that lifting capacities are difficult to obtain and testing accidents are easily possible when 1.25 times related weight loads are tested for large tonnage cranes.

  6. Combining a dispersal model with network theory to assess habitat connectivity.

    Science.gov (United States)

    Lookingbill, Todd R; Gardner, Robert H; Ferrari, Joseph R; Keller, Cherry E

    2010-03-01

    Assessing the potential for threatened species to persist and spread within fragmented landscapes requires the identification of core areas that can sustain resident populations and dispersal corridors that can link these core areas with isolated patches of remnant habitat. We developed a set of GIS tools, simulation methods, and network analysis procedures to assess potential landscape connectivity for the Delmarva fox squirrel (DFS; Sciurus niger cinereus), an endangered species inhabiting forested areas on the Delmarva Peninsula, USA. Information on the DFS's life history and dispersal characteristics, together with data on the composition and configuration of land cover on the peninsula, were used as input data for an individual-based model to simulate dispersal patterns of millions of squirrels. Simulation results were then assessed using methods from graph theory, which quantifies habitat attributes associated with local and global connectivity. Several bottlenecks to dispersal were identified that were not apparent from simple distance-based metrics, highlighting specific locations for landscape conservation, restoration, and/or squirrel translocations. Our approach links simulation models, network analysis, and available field data in an efficient and general manner, making these methods useful and appropriate for assessing the movement dynamics of threatened species within landscapes being altered by human and natural disturbances.

  7. Dynamical assessment for evolutions of Atomic-Multinology (AM) in technology innovation using social network theory

    International Nuclear Information System (INIS)

    Woo, Taeho

    2012-01-01

    Highlights: ► The popularity of AM is analyzed by the social network theory. ► The graphical and colorful configurations are used for the meaning of the incident. ► The new industrial field is quantified by dynamical investigations. ► AM can be successfully used in nuclear industry for technology innovation. ► The method could be used for other industries. - Abstract: The technology evolution is investigated. The proposed Atomic Multinology (AM) is quantified by the dynamical method incorporated with Monte-Carlo method. There are three kinds of the technologies as the info-technology (IT), nano-technology (NT), and bio-technology (BT), which are applied to the nuclear technology. AM is initiated and modeled for the dynamic quantifications. The social network algorithm is used in the dynamical simulation for the management of the projects. The result shows that the successfulness of the AM increases, where the 60 years are the investigated period. The values of the dynamical simulation increase in later stage, which means that the technology is matured as time goes on.

  8. Game Theory Based Security in Wireless Body Area Network with Stackelberg Security Equilibrium.

    Science.gov (United States)

    Somasundaram, M; Sivakumar, R

    2015-01-01

    Wireless Body Area Network (WBAN) is effectively used in healthcare to increase the value of the patient's life and also the value of healthcare services. The biosensor based approach in medical care system makes it difficult to respond to the patients with minimal response time. The medical care unit does not deploy the accessing of ubiquitous broadband connections full time and hence the level of security will not be high always. The security issue also arises in monitoring the user body function records. Most of the systems on the Wireless Body Area Network are not effective in facing the security deployment issues. To access the patient's information with higher security on WBAN, Game Theory with Stackelberg Security Equilibrium (GTSSE) is proposed in this paper. GTSSE mechanism takes all the players into account. The patients are monitored by placing the power position authority initially. The position authority in GTSSE is the organizer and all the other players react to the organizer decision. Based on our proposed approach, experiment has been conducted on factors such as security ratio based on patient's health information, system flexibility level, energy consumption rate, and information loss rate. Stackelberg Security considerably improves the strength of solution with higher security.

  9. Implementation of Solid Waste Policies in Pernambuco: a study from the institutional theory and interorganizational networks

    Directory of Open Access Journals (Sweden)

    Maria Luciana de Almeida

    2015-09-01

    Full Text Available Solid waste is a problem in the Brazilian context, not only because it is growing in larger proportions than the population and leading to soil and water contamination, but also because it is a vector for diseases and causes economic losses, since much of what is discarded can be reused. After several years of intense debate, the Brazilian law applying to national solid waste policy was sanctioned; this law contains goals to be achieved and challenges to be overcome. Since this is a major issue, the purpose of this paper is to discuss the implementation of public policies on solid waste, emphasizing the initiatives carried out in the state of Pernambuco, from the perspectives of institutional theory and inter-organizational networks. By analysing the provisions of the law, we can observe a coercive tendency to bring the states and municipalities to establish networks in order to meet demands related to solid waste, since the pertinent legislation induces the involved entities to develop this kind of partnership in order to obtain resources

  10. Game Theory Based Security in Wireless Body Area Network with Stackelberg Security Equilibrium

    Science.gov (United States)

    Somasundaram, M.; Sivakumar, R.

    2015-01-01

    Wireless Body Area Network (WBAN) is effectively used in healthcare to increase the value of the patient's life and also the value of healthcare services. The biosensor based approach in medical care system makes it difficult to respond to the patients with minimal response time. The medical care unit does not deploy the accessing of ubiquitous broadband connections full time and hence the level of security will not be high always. The security issue also arises in monitoring the user body function records. Most of the systems on the Wireless Body Area Network are not effective in facing the security deployment issues. To access the patient's information with higher security on WBAN, Game Theory with Stackelberg Security Equilibrium (GTSSE) is proposed in this paper. GTSSE mechanism takes all the players into account. The patients are monitored by placing the power position authority initially. The position authority in GTSSE is the organizer and all the other players react to the organizer decision. Based on our proposed approach, experiment has been conducted on factors such as security ratio based on patient's health information, system flexibility level, energy consumption rate, and information loss rate. Stackelberg Security considerably improves the strength of solution with higher security. PMID:26759829

  11. Practical application of game theory based production flow planning method in virtual manufacturing networks

    Science.gov (United States)

    Olender, M.; Krenczyk, D.

    2016-08-01

    Modern enterprises have to react quickly to dynamic changes in the market, due to changing customer requirements and expectations. One of the key area of production management, that must continuously evolve by searching for new methods and tools for increasing the efficiency of manufacturing systems is the area of production flow planning and control. These aspects are closely connected with the ability to implement the concept of Virtual Enterprises (VE) and Virtual Manufacturing Network (VMN) in which integrated infrastructure of flexible resources are created. In the proposed approach, the players role perform the objects associated with the objective functions, allowing to solve the multiobjective production flow planning problems based on the game theory, which is based on the theory of the strategic situation. For defined production system and production order models ways of solving the problem of production route planning in VMN on computational examples for different variants of production flow is presented. Possible decision strategy to use together with an analysis of calculation results is shown.

  12. Energy Dependent Divisible Load Theory for Wireless Sensor Network Workload Allocation

    Directory of Open Access Journals (Sweden)

    Haiyan Shi

    2012-01-01

    Full Text Available The wireless sensor network (WSN, consisting of a large number of microsensors with wireless communication abilities, has become an indispensable tool for use in monitoring and surveillance applications. Despite its advantages in deployment flexibility and fault tolerance, the WSN is vulnerable to failures due to the depletion of limited onboard battery energy. A major portion of energy consumption is caused by the transmission of sensed results to the master processor. The amount of energy used, in fact, is related to both the duration of sensing and data transmission. Hence, in order to extend the operation lifespan of the WSN, a proper allocation of sensing workload among the sensors is necessary. An assignment scheme is here formulated on the basis of the divisible load theory, namely, the energy dependent divisible load theory (EDDLT for sensing workload allocations. In particular, the amount of residual energies onboard sensors are considered while deciding the workload assigned to each sensor. Sensors with smaller amount of residual energy are assigned lighter workloads, thus, allowing for a reduced energy consumption and the sensor lifespan is extended. Simulation studies are conducted and results have illustrated the effectiveness of the proposed workload allocation method.

  13. Subthalamic nucleus stimulation affects theory of mind network: a PET study in Parkinson's disease.

    Science.gov (United States)

    Péron, Julie; Le Jeune, Florence; Haegelen, Claire; Dondaine, Thibaut; Drapier, Dominique; Sauleau, Paul; Reymann, Jean-Michel; Drapier, Sophie; Rouaud, Tiphaine; Millet, Bruno; Vérin, Marc

    2010-03-29

    There appears to be an overlap between the limbic system, which is modulated by subthalamic nucleus (STN) deep brain stimulation (DBS) in Parkinson's disease (PD), and the brain network that mediates theory of mind (ToM). Accordingly, the aim of the present study was to investigate the effects of STN DBS on ToM of PD patients and to correlate ToM modifications with changes in glucose metabolism. To this end, we conducted (18)FDG-PET scans in 13 PD patients in pre- and post-STN DBS conditions and correlated changes in their glucose metabolism with modified performances on the Eyes test, a visual ToM task requiring them to describe thoughts or feelings conveyed by photographs of the eye region. Postoperative PD performances on this emotion recognition task were significantly worse than either preoperative PD performances or those of healthy controls (HC), whereas there was no significant difference between preoperative PD and HC. Conversely, PD patients in the postoperative condition performed within the normal range on the gender attribution task included in the Eyes test. As far as the metabolic results are concerned, there were correlations between decreased cerebral glucose metabolism and impaired ToM in several cortical areas: the bilateral cingulate gyrus (BA 31), right middle frontal gyrus (BA 8, 9 and 10), left middle frontal gyrus (BA 6), temporal lobe (fusiform gyrus, BA 20), bilateral parietal lobe (right BA 3 and right and left BA 7) and bilateral occipital lobe (BA 19). There were also correlations between increased cerebral glucose metabolism and impaired ToM in the left superior temporal gyrus (BA 22), left inferior frontal gyrus (BA 13 and BA 47) and right inferior frontal gyrus (BA 47). All these structures overlap with the brain network that mediates ToM. These results seem to confirm that STN DBS hinders the ability to infer the mental states of others and modulates a distributed network known to subtend ToM.

  14. A new wind power prediction method based on chaotic theory and Bernstein Neural Network

    International Nuclear Information System (INIS)

    Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

    2016-01-01

    The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

  15. Thinking Management and Leadership within Colleges and Schools Somewhat Differently: A Practice-Based, Actor-Network Theory Perspective

    Science.gov (United States)

    Mulcahy, Dianne; Perillo, Suzanne

    2011-01-01

    This article examines the significance of materiality for management and leadership in education using resources provided by actor-network theory (ANT). Espousing the idea that human interactions are mediated by material objects and that these objects participate in the production of practices, ANT affords thinking management and leadership in a…

  16. Pragmatics in action: indirect requests engage theory of mind areas and the cortical motor network.

    Science.gov (United States)

    van Ackeren, Markus J; Casasanto, Daniel; Bekkering, Harold; Hagoort, Peter; Rueschemeyer, Shirley-Ann

    2012-11-01

    motor areas reliably more than comprehension of sentences devoid of any implicit motor information. This is true despite the fact that IR sentences contain no lexical reference to action. (2) Comprehension of IR sentences also reliably activates substantial portions of the theory of mind network, known to be involved in making inferences about mental states of others. The implications of these findings for embodied theories of language are discussed.

  17. Exploring the use of grounded theory as a methodological approach to examine the 'black box' of network leadership in the national quality forum.

    Science.gov (United States)

    Hoflund, A Bryce

    2013-01-01

    This paper describes how grounded theory was used to investigate the "black box" of network leadership in the creation of the National Quality Forum. Scholars are beginning to recognize the importance of network organizations and are in the embryonic stages of collecting and analyzing data about network leadership processes. Grounded theory, with its focus on deriving theory from empirical data, offers researchers a distinctive way of studying little-known phenomena and is therefore well suited to exploring network leadership processes. Specifically, this paper provides an overview of grounded theory, a discussion of the appropriateness of grounded theory to investigating network phenomena, a description of how the research was conducted, and a discussion of the limitations and lessons learned from using this approach.

  18. Metacommunity theory as a multispecies, multiscale framework for studying the influence of river network structure on riverine communities and ecosystems

    Science.gov (United States)

    Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.

    2011-01-01

    Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.

  19. Subthalamic nucleus stimulation affects theory of mind network: a PET study in Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Julie Péron

    Full Text Available BACKGROUND: There appears to be an overlap between the limbic system, which is modulated by subthalamic nucleus (STN deep brain stimulation (DBS in Parkinson's disease (PD, and the brain network that mediates theory of mind (ToM. Accordingly, the aim of the present study was to investigate the effects of STN DBS on ToM of PD patients and to correlate ToM modifications with changes in glucose metabolism. METHODOLOGY/PRINCIPAL FINDINGS: To this end, we conducted (18FDG-PET scans in 13 PD patients in pre- and post-STN DBS conditions and correlated changes in their glucose metabolism with modified performances on the Eyes test, a visual ToM task requiring them to describe thoughts or feelings conveyed by photographs of the eye region. Postoperative PD performances on this emotion recognition task were significantly worse than either preoperative PD performances or those of healthy controls (HC, whereas there was no significant difference between preoperative PD and HC. Conversely, PD patients in the postoperative condition performed within the normal range on the gender attribution task included in the Eyes test. As far as the metabolic results are concerned, there were correlations between decreased cerebral glucose metabolism and impaired ToM in several cortical areas: the bilateral cingulate gyrus (BA 31, right middle frontal gyrus (BA 8, 9 and 10, left middle frontal gyrus (BA 6, temporal lobe (fusiform gyrus, BA 20, bilateral parietal lobe (right BA 3 and right and left BA 7 and bilateral occipital lobe (BA 19. There were also correlations between increased cerebral glucose metabolism and impaired ToM in the left superior temporal gyrus (BA 22, left inferior frontal gyrus (BA 13 and BA 47 and right inferior frontal gyrus (BA 47. All these structures overlap with the brain network that mediates ToM. CONCLUSION/SIGNIFICANCE: These results seem to confirm that STN DBS hinders the ability to infer the mental states of others and modulates a

  20. Spectral Graph Theory Analysis of Software-Defined Networks to Improve Performance and Security

    Science.gov (United States)

    2015-09-01

    too costly to continue operating and administrating them in the same basic manner as standardized by Advanced Research Projects Agency Network...to better monitor the network as compared to network perimeter defenses, such as firewalls and web server demilitarized zones (DMZs). The Open Network

  1. Opening the black box of quality improvement collaboratives: an Actor-Network theory approach

    Directory of Open Access Journals (Sweden)

    Broer Tineke

    2010-09-01

    Full Text Available Abstract Background Quality improvement collaboratives are often labeled as black boxes because effect studies usually do not describe exactly how the results were obtained. In this article we propose a way of opening such a black box, by taking up a dynamic perspective based on Actor-Network Theory. We thereby analyze how the problematisation process and the measurement practices are constructed. Findings from this analysis may have consequences for future evaluation studies of collaboratives. Methods In an ethnographic design we probed two projects within a larger quality improvement collaborative on long term mental health care and care for the intellectually disabled. Ethnographic observations were made at nine national conferences. Furthermore we conducted six case studies involving participating teams. Additionally, we interviewed the two program leaders of the overall projects. Results In one project the problematisation seemed to undergo a shift of focus away from the one suggested by the project leaders. In the other we observed multiple roles of the measurement instrument used. The instrument did not only measure effects of the improvement actions but also changed these actions and affected the actors involved. Conclusions Effectiveness statistics ideally should be complemented with an analysis of the construction of the collaborative and the improvement practices. Effect studies of collaboratives could benefit from a mixed methods research design that combines quantitative and qualitative methods.

  2. Interactions between Depression and Facilitation within Neural Networks: Updating the Dual-Process Theory of Plasticity

    Science.gov (United States)

    Prescott, Steven A.

    1998-01-01

    Repetitive stimulation often results in habituation of the elicited response. However, if the stimulus is sufficiently strong, habituation may be preceded by transient sensitization or even replaced by enduring sensitization. In 1970, Groves and Thompson formulated the dual-process theory of plasticity to explain these characteristic behavioral changes on the basis of competition between decremental plasticity (depression) and incremental plasticity (facilitation) occurring within the neural network. Data from both vertebrate and invertebrate systems are reviewed and indicate that the effects of depression and facilitation are not exclusively additive but, rather, that those processes interact in a complex manner. Serial ordering of induction of learning, in which a depressing locus precedes the modulatory system responsible for inducing facilitation, causes the facilitation to wane. The parallel and/or serial expression of depression and waning facilitation within the stimulus–response pathway culminates in the behavioral changes that characterize dual-process learning. A mathematical model is presented to formally express and extend understanding of the interactions between depression and facilitation. PMID:10489261

  3. Game-Theory-Based Approach for Energy Routing in a Smart Grid Network

    Directory of Open Access Journals (Sweden)

    June S. Hong

    2016-01-01

    Full Text Available Small power plants and buildings with renewable power generation capability have recently been added to traditional central power plants. Through these facilities, prosumers appear to have a concurrent role in both energy production and consumption. Based on bidirectional power transfers by large numbers of prosumers, a smart microgrid has become an important factor in efficiently controlling the microgrids used in power markets and in conducting effective power trades among grids. In this paper, we present an approach utilizing the game theory for effective and efficient energy routing, which is a novel and challenging procedure for a smart microgrid network. First, we propose strategies for choosing the desired transaction price for both electricity surpluses and shortages to maximize profits through energy transactions. An optimization scheme is utilized to search for an energy route with minimum cost using the solving method used in a traditional transportation problem by treating the sale and purchase quantities as transportation supply and demand, respectively. To evaluate the effect of the proposed decision strategies, we simulated our mechanism, and the results proved that our mechanism yields results pursued by each strategy. Our proposed strategies will contribute to spreading a smart microgrid for enhancing the utilization of microgrids.

  4. A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network.

    Science.gov (United States)

    Chen, Yuzhong; Weng, Shining; Guo, Wenzhong; Xiong, Naixue

    2016-02-19

    Vehicular ad hoc networks (VANETs) have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency.

  5. Theory of mind network activity is altered in subjects with familial liability for schizophrenia

    Science.gov (United States)

    Mohnke, Sebastian; Erk, Susanne; Schnell, Knut; Romanczuk-Seiferth, Nina; Schmierer, Phöbe; Romund, Lydia; Garbusow, Maria; Wackerhagen, Carolin; Ripke, Stephan; Grimm, Oliver; Haller, Leila; Witt, Stephanie H.; Degenhardt, Franziska; Tost, Heike; Heinz, Andreas; Meyer-Lindenberg, Andreas; Walter, Henrik

    2016-01-01

    As evidenced by a multitude of studies, abnormalities in Theory of Mind (ToM) and its neural processing might constitute an intermediate phenotype of schizophrenia. If so, neural alterations during ToM should be observable in unaffected relatives of patients as well, since they share a considerable amount of genetic risk. While behaviorally, impaired ToM function is confirmed meta-analytically in relatives, evidence on aberrant function of the neural ToM network is sparse and inconclusive. The present study therefore aimed to further explore the neural correlates of ToM in relatives of schizophrenia. About 297 controls and 63 unaffected first-degree relatives of patients with schizophrenia performed a ToM task during functional magnetic resonance imaging. Consistent with the literature relatives exhibited decreased activity of the medial prefrontal cortex. Additionally, increased recruitment of the right middle temporal gyrus and posterior cingulate cortex was found, which was related to subclinical paranoid symptoms in relatives. These results further support decreased medial prefrontal activation during ToM as an intermediate phenotype of genetic risk for schizophrenia. Enhanced recruitment of posterior ToM areas in relatives might indicate inefficiency mechanisms in the presence of genetic risk. PMID:26341902

  6. Generalizing a nonlinear geophysical flood theory to medium-sized river networks

    Science.gov (United States)

    Gupta, Vijay K.; Mantilla, Ricardo; Troutman, Brent M.; Dawdy, David; Krajewski, Witold F.

    2010-01-01

    The central hypothesis of a nonlinear geophysical flood theory postulates that, given space-time rainfall intensity for a rainfall-runoff event, solutions of coupled mass and momentum conservation differential equations governing runoff generation and transport in a self-similar river network produce spatial scaling, or a power law, relation between peak discharge and drainage area in the limit of large area. The excellent fit of a power law for the destructive flood event of June 2008 in the 32,400-km2 Iowa River basin over four orders of magnitude variation in drainage areas supports the central hypothesis. The challenge of predicting observed scaling exponent and intercept from physical processes is explained. We show scaling in mean annual peak discharges, and briefly discuss that it is physically connected with scaling in multiple rainfall-runoff events. Scaling in peak discharges would hold in a non-stationary climate due to global warming but its slope and intercept would change.

  7. Effective connectivity gateways to the Theory of Mind network in processing communicative intention.

    Science.gov (United States)

    Tettamanti, Marco; Vaghi, Matilde M; Bara, Bruno G; Cappa, Stefano F; Enrici, Ivan; Adenzato, Mauro

    2017-07-15

    An Intention Processing Network (IPN), involving the medial prefrontal cortex, precuneus, bilateral posterior superior temporal sulcus, and temporoparietal junctions, plays a fundamental role in comprehending intentions underlying action goals. In a previous fMRI study, we showed that, depending on the linguistic or extralinguistic (gestural) modality used to convey the intention, the IPN is complemented by activation of additional brain areas, reflecting distinct modality-specific input gateways to the IPN. These areas involve, for the linguistic modality, the left inferior frontal gyrus (LIFG), and for the extralinguistic modality, the right inferior frontal gyrus (RIFG). Here, we tested the modality-specific gateway hypothesis, by using DCM to measure inter-regional functional integration dynamics between the IPN and LIFG/RIFG gateways. We found strong evidence of a well-defined effective connectivity architecture mediating the functional integration between the IPN and the inferior frontal cortices. The connectivity dynamics indicate a modality-specific propagation of stimulus information from LIFG to IPN for the linguistic modality, and from RIFG to IPN for the extralinguistic modality. Thus, we suggest a functional model in which the modality-specific gateways mediate the structural and semantic decoding of the stimuli, and allow for the modality-specific communicative information to be integrated in Theory of Mind inferences elaborated through the IPN. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. Social anxiety disorder exhibit impaired networks involved in self and theory of mind processing.

    Science.gov (United States)

    Cui, Qian; Vanman, Eric J; Long, Zhiliang; Pang, Yajing; Chen, Yuyan; Wang, Yifeng; Duan, Xujun; Chen, Heng; Gong, Qiyong; Zhang, Wei; Chen, Huafu

    2017-08-01

    Most previous studies regarding social anxiety disorder (SAD) have focused on the role of emotional dysfunction, while impairments in self- and theory of mind (ToM)-processing have relatively been neglected. This study utilised functional connectivity density (FCD), resting-state functional connectivity (RSFC) and discriminant analyses to investigate impairments in self- and ToM-related networks in patients with SAD. Patients with SAD exhibited decreased long-range FCD in the right rostral anterior cingulate cortex (rACC) and decreased short-range FCD in the right superior temporal gyrus (STG)-key nodes involved in self- and ToM-processing, respectively. Decreased RSFC of the right rACC and STG with widespread frontal, temporal, posteromedial, sensorimotor, and somatosensory, regions was also observed in patients with SAD. Altered RSFC between the right rACC and bilateral superior frontal gyrus, between the right rACC and right middle frontal gyrus, and within the right STG itself provided the greatest contribution to individual diagnoses of SAD, with an accuracy of 84.5%. These results suggest that a lack of cognitive inhibition on emotional self-referential processing as well as impairments in social information integration may play critical roles in the pathomechanism of SAD and highlight the importance of recognising such features in the diagnosis and treatment of SAD. © The Author (2017). Published by Oxford University Press.

  9. Exploring the social without a separate domain for religion: on actor-network theory and religion

    Directory of Open Access Journals (Sweden)

    Peik Ingman

    2012-01-01

    Full Text Available In post-secular societies—after secularisation—it may increasingly be the case that the connecting and structuring of religious matter is done outsidedesignated religious sites and without appointed religious experts. The centres of calculation have changed and so the connections between these are different. The former ways of translation and ordering are transforming into new ones. By exiting the designated sites religious matter has found new freedom with the new associations and inventions in the processes of translation. Less control leads to more heterogeneous agencies and facilitates the mobility of religious materials. This less controlled mobility of religious actants can also produce an apparent increase of religious matter, but this does not necessarily mean the return of religion. In any case, this increased plurality combined with increased mobility calls for perspectives which can recognise novelty, andnot just in comparison with previous states of affairs. Actor-network theory (ANT is about tracing the webs of associations between myriad actants whose collective actions produce what we call ‘society’. Dismissing the notion of ‘the social’ as a kind of ‘stuff ’, ANT insists that sociology should focus on the interactional processes—the circulation of ‘the social’ among human and non-human actants—collectively assembling emerging states of affairs.

  10. A Game Theory Algorithm for Intra-Cluster Data Aggregation in a Vehicular Ad Hoc Network

    Directory of Open Access Journals (Sweden)

    Yuzhong Chen

    2016-02-01

    Full Text Available Vehicular ad hoc networks (VANETs have an important role in urban management and planning. The effective integration of vehicle information in VANETs is critical to traffic analysis, large-scale vehicle route planning and intelligent transportation scheduling. However, given the limitations in the precision of the output information of a single sensor and the difficulty of information sharing among various sensors in a highly dynamic VANET, effectively performing data aggregation in VANETs remains a challenge. Moreover, current studies have mainly focused on data aggregation in large-scale environments but have rarely discussed the issue of intra-cluster data aggregation in VANETs. In this study, we propose a multi-player game theory algorithm for intra-cluster data aggregation in VANETs by analyzing the competitive and cooperative relationships among sensor nodes. Several sensor-centric metrics are proposed to measure the data redundancy and stability of a cluster. We then study the utility function to achieve efficient intra-cluster data aggregation by considering both data redundancy and cluster stability. In particular, we prove the existence of a unique Nash equilibrium in the game model, and conduct extensive experiments to validate the proposed algorithm. Results demonstrate that the proposed algorithm has advantages over typical data aggregation algorithms in both accuracy and efficiency.

  11. Bayesian networks and information theory for audio-visual perception modeling.

    Science.gov (United States)

    Besson, Patricia; Richiardi, Jonas; Bourdin, Christophe; Bringoux, Lionel; Mestre, Daniel R; Vercher, Jean-Louis

    2010-09-01

    Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions through a rigorous and systematic data-driven process. This requires considering the general relationships between the physical events or factors involved in the process, not only in quantitative terms, but also in term of the influence of one factor on another. We use tools from information theory and probabilistic reasoning to derive relationships between the random variables of interest, where the central notion is that of conditional independence. Using mutual information analysis to guide the model elicitation process, a probabilistic causal model encoded as a Bayesian network is obtained. We exemplify the method by using data collected in an audio-visual localization task for human subjects, and we show that it yields a well-motivated model with good predictive ability. The model elicitation process offers new prospects for the investigation of the cognitive mechanisms of multisensory perception.

  12. Rethinking agency and medical adherence technology: applying Actor Network Theory to the case study of Digital Pills.

    Science.gov (United States)

    Hurtado-de-Mendoza, Alejandra; Cabling, Mark L; Sheppard, Vanessa B

    2015-12-01

    Much literature surrounding medical technology and adherence posits that technology is a mechanism for social control. This assumes that the medical establishment can take away patients' agency. Although power relationships and social control can play a key role, medical technology can also serve as an agentive tool to be utilized. We (1) offer the alternative framework of Actor Network Theory to view medical technology, (2) discuss the literature on medication adherence and technology, (3) delve into the ramifications of looking at adherence as a network and (4) use Digital Pills as a case study of dispersed agency. © 2015 John Wiley & Sons Ltd.

  13. Mathematical models of electrical network systems theory and applications : an introduction

    CERN Document Server

    Kłos, Andrzej

    2017-01-01

    This book is for all those who are looking for a non-conventional mathematical model of electrical network systems. It presents a modern approach using linear algebra and derives various commonly unknown quantities and interrelations of network analysis. It also explores some applications of algebraic network model of and solves some examples of previously unsolved network problems in planning and operation of network systems. Complex mathematical aspects are illustrated and described in a way that is understandable for non-mathematicians. Discussing interesting concepts and practically useful methods of network analysis, it is a valuable resource for lecturers, students, engineers and research workers. .

  14. Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

    Science.gov (United States)

    Kotegawa, Tatsuya

    Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high

  15. Permanent Set of Cross-Linking Networks: Comparison of Theory with Molecular Dynamics Simulations

    DEFF Research Database (Denmark)

    Rottach, Dana R.; Curro, John G.; Budzien, Joanne

    2006-01-01

    The permanent set of cross-linking networks is studied by molecular dynamics. The uniaxial stress for a bead-spring polymer network is investigated as a function of strain and cross-link density history, where cross-links are introduced in unstrained and strained networks. The permanent set...

  16. MODELING AND STRUCTURING OF ENTERPRISE MANAGEMENT SYSTEM RESORT SPHERE BASED ON ELEMENTS OF NEURAL NETWORK THEORY: THE METHODOLOGICAL BASIS

    Directory of Open Access Journals (Sweden)

    Rena R. Timirualeeva

    2015-01-01

    Full Text Available The article describes the methodology of modeling andstructuring of business networks theory. Accounting ofenvironmental factors mega-, macro- and mesolevels, theinternal state of the managed system and the error management command execution by control system implemented inthis. The proposed methodology can improve the quality of enterprise management of resort complex through a moreflexible response to changes in the parameters of the internaland external environments.

  17. Moving from theory to practice: A participatory social network mapping approach to address unmet need for family planning in Benin.

    Science.gov (United States)

    Igras, Susan; Diakité, Mariam; Lundgren, Rebecka

    2017-07-01

    In West Africa, social factors influence whether couples with unmet need for family planning act on birth-spacing desires. Tékponon Jikuagou is testing a social network-based intervention to reduce social barriers by diffusing new ideas. Individuals and groups judged socially influential by their communities provide entrée to networks. A participatory social network mapping methodology was designed to identify these diffusion actors. Analysis of monitoring data, in-depth interviews, and evaluation reports assessed the methodology's acceptability to communities and staff and whether it produced valid, reliable data to identify influential individuals and groups who diffuse new ideas through their networks. Results indicated the methodology's acceptability. Communities were actively and equitably engaged. Staff appreciated its ability to yield timely, actionable information. The mapping methodology also provided valid and reliable information by enabling communities to identify highly connected and influential network actors. Consistent with social network theory, this methodology resulted in the selection of informal groups and individuals in both informal and formal positions. In-depth interview data suggest these actors were diffusing new ideas, further confirming their influence/connectivity. The participatory methodology generated insider knowledge of who has social influence, challenging commonly held assumptions. Collecting and displaying information fostered staff and community learning, laying groundwork for social change.

  18. Impact of Sink Node Placement onto Wireless Sensor Networks Performance Regarding Clustering Routing and Compressive Sensing Theory

    Directory of Open Access Journals (Sweden)

    Shima Pakdaman Tirani

    2016-01-01

    Full Text Available Wireless Sensor Networks (WSNs consist of several sensor nodes with sensing, computation, and wireless communication capabilities. The energy constraint is one of the most important issues in these networks. Thus, the data-gathering process should be carefully designed to conserve the energy. In this situation, a load balancing strategy can enhance the resources utilization, and consequently, increase the network lifetime. Furthermore, recently, the sparse nature of data in WSNs has been motivated the use of the compressive sensing as an efficient data gathering technique. Using the compressive sensing theory significantly leads to decreasing the volume of the transmitted data. Taking the above challenges into account, the main goal of this paper is to jointly consider the compressive sensing method and the load-balancing in WSNs. In this regards, using the conventional network model, we analyze the network performance in several different states. These states challenge the sink location in term of the number of transmissions. Numerical results demonstrate the efficiency of the load-balancing in the network performance.

  19. Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

    Science.gov (United States)

    Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

    2017-12-01

    Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.

  20. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Y W [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Zhang, L F [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China); Huang, J P [Surface Physics Laboratory and Department of Physics, Fudan University, Shanghai 200433 (China)

    2007-07-20

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property.

  1. The Watts-Strogatz network model developed by including degree distribution: theory and computer simulation

    International Nuclear Information System (INIS)

    Chen, Y W; Zhang, L F; Huang, J P

    2007-01-01

    By using theoretical analysis and computer simulations, we develop the Watts-Strogatz network model by including degree distribution, in an attempt to improve the comparison between characteristic path lengths and clustering coefficients predicted by the original Watts-Strogatz network model and those of the real networks with the small-world property. Good agreement between the predictions of the theoretical analysis and those of the computer simulations has been shown. It is found that the developed Watts-Strogatz network model can fit the real small-world networks more satisfactorily. Some other interesting results are also reported by adjusting the parameters in a model degree-distribution function. The developed Watts-Strogatz network model is expected to help in the future analysis of various social problems as well as financial markets with the small-world property

  2. A Net of Friends: Investigating Friendship by Integrating Attachment Theory and Social Network Analysis.

    Science.gov (United States)

    Gillath, Omri; Karantzas, Gery C; Selcuk, Emre

    2017-11-01

    The current article focuses on attachment style-an individual difference widely studied in the field of close relationships-and its application to the study of social networks. Specifically, we investigated whether attachment style predicts perception and management of social networks. In Study 1, we examined the associations of attachment style with perceptions of network tie strength and multiplexity. In Studies 2a and 2b, we investigated the association between attachment style and network management skills (initiating, maintaining, and dissolving ties) and whether network management skills mediated the associations of attachment style with network tie strength and multiplexity. In Study 3, experimentally enhancing attachment security made people more likely to initiate and less likely to dissolve social ties (for the latter, especially among those high on avoidance or anxiety). As for maintenance, security priming also increased maintenance; however, mainly among people high on attachment anxiety or low on attachment avoidance.

  3. Cell Deployment Optimization for Cloud Radio Access Networks using Teletraffic Theory

    DEFF Research Database (Denmark)

    Popovska Avramova, Andrijana; Christiansen, Henrik Lehrmann; Iversen, Villy Bæk

    2015-01-01

    Cloud Radio Access Network (C-RAN) is a new mobile radio access network design based on centralized and pooled processing. It offers potential cost savings by utilizing the so-called tidal effect due to user mobility in cellular networks. This paper provides a quantitative analysis...... to dynamically re-assign cells to a pool of baseband units. The re-assignment is based on the cell load and traffic characteristics such that effective utilization of the baseband resources is assured....

  4. An equal force theory for network models of soft materials with arbitrary molecular weight distribution

    Science.gov (United States)

    Verron, E.; Gros, A.

    2017-09-01

    Most network models for soft materials, e.g. elastomers and gels, are dedicated to idealized materials: all chains admit the same number of Kuhn segments. Nevertheless, such standard models are not appropriate for materials involving multiple networks, and some specific constitutive equations devoted to these materials have been derived in the last few years. In nearly all cases, idealized networks of different chain lengths are assembled following an equal strain assumption; only few papers adopt an equal stress assumption, although some authors argue that such hypothesis would reflect the equilibrium of the different networks in contact. In this work, a full-network model with an arbitrary chain length distribution is derived by considering that chains of different lengths satisfy the equal force assumption in each direction of the unit sphere. The derivation is restricted to non-Gaussian freely jointed chains and to affine deformation of the sphere. Firstly, after a proper definition of the undeformed configuration of the network, we demonstrate that the equal force assumption leads to the equality of a normalized stretch in chains of different lengths. Secondly, we establish that the network with chain length distribution behaves as an idealized full-network of which both chain length and density of are provided by the chain length distribution. This approach is finally illustrated with two examples: the derivation of a new expression for the Young modulus of bimodal interpenetrated polymer networks, and the prediction of the change in fluorescence during deformation of mechanochemically responsive elastomers.

  5. A Perron–Frobenius theory for block matrices associated to a multiplex network

    International Nuclear Information System (INIS)

    Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

    2015-01-01

    The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers

  6. A Perron-Frobenius theory for block matrices associated to a multiplex network

    Science.gov (United States)

    Romance, Miguel; Solá, Luis; Flores, Julio; García, Esther; García del Amo, Alejandro; Criado, Regino

    2015-03-01

    The uniqueness of the Perron vector of a nonnegative block matrix associated to a multiplex network is discussed. The conclusions come from the relationships between the irreducibility of some nonnegative block matrix associated to a multiplex network and the irreducibility of the corresponding matrices to each layer as well as the irreducibility of the adjacency matrix of the projection network. In addition the computation of that Perron vector in terms of the Perron vectors of the blocks is also addressed. Finally we present the precise relations that allow to express the Perron eigenvector of the multiplex network in terms of the Perron eigenvectors of its layers.

  7. Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory

    Directory of Open Access Journals (Sweden)

    Qian Hong

    2008-05-01

    Full Text Available Abstract Background: Several approaches, including metabolic control analysis (MCA, flux balance analysis (FBA, correlation metric construction (CMC, and biochemical circuit theory (BCT, have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis. Results: In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SRT where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of RT BS and ST BS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix eAt plays a central role in CMC. Conclusion: One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA.

  8. Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

    Science.gov (United States)

    Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

    2018-01-01

    Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

  9. Abnormal brain white matter network in young smokers: a graph theory analysis study.

    Science.gov (United States)

    Zhang, Yajuan; Li, Min; Wang, Ruonan; Bi, Yanzhi; Li, Yangding; Yi, Zhang; Liu, Jixin; Yu, Dahua; Yuan, Kai

    2018-04-01

    Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups. The results demonstrated that both young smokers and nonsmokers had small-world topology in WM network. Further analysis revealed that the young smokers exhibited the abnormal topological organization, i.e., increased network strength, global efficiency, and decreased shortest path length. In addition, the increased nodal efficiency predominately was located in frontal cortex, striatum and anterior cingulate gyrus (ACG) in smokers. Moreover, based on network-based statistic (NBS) approach, the significant increased FA-weighted WM connections were mainly found in the PFC, ACG and supplementary motor area (SMA) regions. Meanwhile, the network parameters were correlated with the nicotine dependence severity (FTND) scores, and the nodal efficiency of orbitofrontal cortex was positive correlation with the cigarette per day (CPD) in young smokers. We revealed the abnormal topological organization of WM network in young smokers, which may improve our understanding of the neural mechanism of young smokers form WM topological organization level.

  10. A Trust Evaluation Algorithm for Wireless Sensor Networks Based on Node Behaviors and D-S Evidence Theory

    Directory of Open Access Journals (Sweden)

    Jiangwen Wan

    2011-01-01

    Full Text Available For wireless sensor networks (WSNs, many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that ‘hard to acquire and easy to lose’. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation.

  11. A trust evaluation algorithm for wireless sensor networks based on node behaviors and D-S evidence theory.

    Science.gov (United States)

    Feng, Renjian; Xu, Xiaofeng; Zhou, Xiang; Wan, Jiangwen

    2011-01-01

    For wireless sensor networks (WSNs), many factors, such as mutual interference of wireless links, battlefield applications and nodes exposed to the environment without good physical protection, result in the sensor nodes being more vulnerable to be attacked and compromised. In order to address this network security problem, a novel trust evaluation algorithm defined as NBBTE (Node Behavioral Strategies Banding Belief Theory of the Trust Evaluation Algorithm) is proposed, which integrates the approach of nodes behavioral strategies and modified evidence theory. According to the behaviors of sensor nodes, a variety of trust factors and coefficients related to the network application are established to obtain direct and indirect trust values through calculating weighted average of trust factors. Meanwhile, the fuzzy set method is applied to form the basic input vector of evidence. On this basis, the evidence difference is calculated between the indirect and direct trust values, which link the revised D-S evidence combination rule to finally synthesize integrated trust value of nodes. The simulation results show that NBBTE can effectively identify malicious nodes and reflects the characteristic of trust value that 'hard to acquire and easy to lose'. Furthermore, it is obvious that the proposed scheme has an outstanding advantage in terms of illustrating the real contribution of different nodes to trust evaluation.

  12. THE DEVELOPMENT OF THE THEORY OF INSTANTANEOUS POWER OF THREE-PHASE NETWORK IN TERMS OF NETWORK CENTRISM

    Directory of Open Access Journals (Sweden)

    Ye. I. Sokol

    2017-08-01

    Full Text Available Purpose. Information technologies allow multidimensional analysis of information about the state of the power system in a single information space in terms of providing network-centric approach to control and use of unmanned aerial vehicles as tools for condition monitoring of three-phase network. Methodology. The idea of energy processes in three independent (rather than four dependent curves vector-functions with values in the arithmetic three-dimensional space adequately for both 4-wire and 3–wire circuits. The presence of zero sequence current structural (and mathematically features a 4-wire scheme of energy from a 3-wire circuit. The zero sequence voltage caused by the displacement of the zero voltage phases. Offset zero in the calculations can be taken into account by appropriate selection of the reference voltages. Both of these energetic phenomena with common methodical positions are described in the framework of the general mathematical model, in which a significant role is played by the ort zero sequence. Results. Vector approach with a unified voice allows us to obtain and analyze new energy characteristics for 4–wire and 3–wire circuits in sinusoidal and non-sinusoidal mode, both in temporal and frequency domain. Originality. Symmetric sinusoidal mode is balanced, even with non-zero reactive power. The converse is not true. The mode can be balanced and unbalanced load. The mode can be balanced and unbalanced voltage. Practical value. Assessing balance in network mode and the impact of instantaneous power on the magnitude of the losses, will allow to avoid the appearance of zero sequence and, thus, to improve the quality of electricity.

  13. Distributed source coding of video

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Van Luong, Huynh

    2015-01-01

    A foundation for distributed source coding was established in the classic papers of Slepian-Wolf (SW) [1] and Wyner-Ziv (WZ) [2]. This has provided a starting point for work on Distributed Video Coding (DVC), which exploits the source statistics at the decoder side offering shifting processing...... steps, conventionally performed at the video encoder side, to the decoder side. Emerging applications such as wireless visual sensor networks and wireless video surveillance all require lightweight video encoding with high coding efficiency and error-resilience. The video data of DVC schemes differ from...... the assumptions of SW and WZ distributed coding, e.g. by being correlated in time and nonstationary. Improving the efficiency of DVC coding is challenging. This paper presents some selected techniques to address the DVC challenges. Focus is put on pin-pointing how the decoder steps are modified to provide...

  14. Applying policy network theory to policy-making in China: the case of urban health insurance reform.

    Science.gov (United States)

    Zheng, Haitao; de Jong, Martin; Koppenjan, Joop

    2010-01-01

    In this article, we explore whether policy network theory can be applied in the People's Republic of China (PRC). We carried out a literature review of how this approach has already been dealt with in the Chinese policy sciences thus far. We then present the key concepts and research approach in policy networks theory in the Western literature and try these on a Chinese case to see the fit. We follow this with a description and analysis of the policy-making process regarding the health insurance reform in China from 1998 until the present. Based on this case study, we argue that this body of theory is useful to describe and explain policy-making processes in the Chinese context. However, limitations in the generic model appear in capturing the fundamentally different political and administrative systems, crucially different cultural values in the applicability of some research methods common in Western countries. Finally, we address which political and cultural aspects turn out to be different in the PRC and how they affect methodological and practical problems that PRC researchers will encounter when studying decision-making processes.

  15. Complexity theory and financial regulation: economic policy needs interdisciplinary network analysis and behavioral modeling

    NARCIS (Netherlands)

    Battiston, S.; Farmer, J.D.; Flache, A.; Garlaschelli, D.; Haldane, A.G.; Heesterbeek, H.; Hommes, C.; Jaeger, C.; May, R.; Scheffer, M.

    2016-01-01

    Traditional economic theory could not explain, much less predict, the near collapse of the financial system and its long-lasting effects on the global economy. Since the 2008 crisis, there has been increasing interest in using ideas from complexity theory to make sense of economic and financial

  16. Applying the Uses and Gratifications Theory to Compare Higher Education Students' Motivation for Using Social Networking Sites: Experiences from Iran, Malaysia, United Kingdom, and South Africa

    Science.gov (United States)

    Karimi, Leila; Khodabandelou, Rouhollah; Ehsani, Maryam; Ahmad, Muhammad

    2014-01-01

    Drawing from the Uses and Gratifications Theory, this study examined the Gratification Sought and the Gratification Obtained from using Social Networking Sites among Iranian, Malaysian, British, and South African higher education students. This comparison allowed to drawing conclusions about how social networking sites fulfill users' needs with…

  17. A dynamic approach merging network theory and credit risk techniques to assess systemic risk in financial networks.

    Science.gov (United States)

    Petrone, Daniele; Latora, Vito

    2018-04-03

    The interconnectedness of financial institutions affects instability and credit crises. To quantify systemic risk we introduce here the PD model, a dynamic model that combines credit risk techniques with a contagion mechanism on the network of exposures among banks. A potential loss distribution is obtained through a multi-period Monte Carlo simulation that considers the probability of default (PD) of the banks and their tendency of defaulting in the same time interval. A contagion process increases the PD of banks exposed toward distressed counterparties. The systemic risk is measured by statistics of the loss distribution, while the contribution of each node is quantified by the new measures PDRank and PDImpact. We illustrate how the model works on the network of the European Global Systemically Important Banks. For a certain range of the banks' capital and of their assets volatility, our results reveal the emergence of a strong contagion regime where lower default correlation between banks corresponds to higher losses. This is the opposite of the diversification benefits postulated by standard credit risk models used by banks and regulators who could therefore underestimate the capital needed to overcome a period of crisis, thereby contributing to the financial system instability.

  18. Mean field theory of epidemic spreading with effective contacts on networks

    International Nuclear Information System (INIS)

    Wu, Qingchu; Chen, Shufang

    2015-01-01

    We present a general approach to the analysis of the susceptible-infected-susceptible model with effective contacts on networks, where each susceptible node will be infected with a certain probability only for effective contacts. In the network, each node has a given effective contact number. By using the one-vertex heterogenous mean-field (HMF) approximation and the pair HMF approximation, we obtain conditions for epidemic outbreak on degree-uncorrelated networks. Our results suggest that the epidemic threshold is closely related to the effective contact and its distribution. However, when the effective contact is only dependent of node degree, the epidemic threshold can be established by the degree distribution of networks.

  19. A Lagrangian Formulation of Neural Networks I: Theory and Analog Dynamics

    Science.gov (United States)

    Mjolsness, Eric; Miranker, Willard L.

    1997-01-01

    We expand the mathematicla apparatus for relaxation networks, which conventionally consists of an objective function E and a dynamics given by a system of differenctial equations along whose trajectories E is diminished.

  20. An Interview with Tony David Sampson: Author of Virality: Contagion Theory in the Age of Networks

    OpenAIRE

    Tara Robbins Fee; Samuel B. Fee; Tony D. Sampson

    2016-01-01

    Tony D. Sampson is Reader in Digital Culture and Communication in the School of Arts and Digital Industries (ADI) at the University of East London, where he directs the EmotionUX lab, supervising research on the cognitive, emotional, and affective aspects of user experience. In 2013, he co-founded Club Critical Theory, an organization dedicated to the application of critical theory in everyday life in Southend-on-Sea, Essex. Tony is the author of Virality: Contagion Theory in the Age of Netwo...

  1. The Role of Adolescent Development in Social Networking Site Use: Theory and Evidence

    OpenAIRE

    Drew P. Cingel; Ellen Wartella; Marina Krcmar

    2014-01-01

    Using survey data collected from 260 children, adolescents, and young adults between the ages of 9 and 26, this paper offers evidence for a relationship between social networking site use and Imaginary Audience, a developmental variable in which adolescents believe others are thinking about them at all times. Specifically, after controlling for a number of variables, results indicate a significant, positive relationship between social networking site use and Imaginary Audience ideation. Addit...

  2. Using Cultural Historical Activity Theory (CHAT) to Frame `SuperclubsPLUS', an Online Social Network for Children

    Science.gov (United States)

    Masters, Jennifer

    This paper uses a Cultural Historical Activity Theory framework to describe a social-networking online community project, “SuperclubsPLUS”, for children aged 6-12. The use of the CHAT frame enables a detailed description of connections within the project as participants work together to achieve individual and common goals. Application of this structure to the SuperclubsPLUS environment supports the concept that the community is continually changing, shaped by the interactions of the participants. It is anticipated that this snapshot of the project will provide a tangible base in order to further develop and map ongoing patterns of interaction for research.

  3. Actor-Network Theory as a sociotechnical lens to explore the relationship of nurses and technology in practice: methodological considerations for nursing research.

    Science.gov (United States)

    Booth, Richard G; Andrusyszyn, Mary-Anne; Iwasiw, Carroll; Donelle, Lorie; Compeau, Deborah

    2016-06-01

    Actor-Network Theory is a research lens that has gained popularity in the nursing and health sciences domains. The perspective allows a researcher to describe the interaction of actors (both human and non-human) within networked sociomaterial contexts, including complex practice environments where nurses and health technology operate. This study will describe Actor-Network Theory and provide methodological considerations for researchers who are interested in using this sociotechnical lens within nursing and informatics-related research. Considerations related to technology conceptualization, levels of analysis, and sampling procedures in Actor-Network Theory based research are addressed. Finally, implications for future nursing research within complex environments are highlighted. © 2015 John Wiley & Sons Ltd.

  4. Reseña del blog: Networks & Matters: a blog on Actor-Network Theory and philosophical empirism

    Directory of Open Access Journals (Sweden)

    Jorge Leandro Castillo Sepúlveda

    2010-03-01

    Full Text Available La Teoría del Actor-Red, inscrita en los estudios sociales de la ciencia y la tecnología, constituye una aproximación que ha trascendido el ámbito de las investigaciones sociotécnicas, alcanzando el análisis de las rupturas, formaciones y estabilizaciones de las formas más generales de orden social. Networks & Matters, blog creado por cuatro académicos e investigadores reconocidos en el área, constituye un espacio adecuado para actualizarse en discusiones teóricas en torno a esta teoría y a sus asuntos relacionados. Las posibilidades que brinda el formato para comentar y generar discusiones en torno a las temáticas propuestas y la de establecer vínculos hacia otros sitios  y medios relacionados, se conjugan con la exposición de eventos y de publicaciones, tanto nuevas como clásicas. El estilo prolijo de las notas resulta apropiado para quienes se interesen en el campo de la interacción entre ciencia, tecnología y sociedad, y para quienes se adentren en este.

  5. Network theory may explain the vulnerability of medieval human settlements to the Black Death pandemic.

    Science.gov (United States)

    Gómez, José M; Verdú, Miguel

    2017-03-06

    Epidemics can spread across large regions becoming pandemics by flowing along transportation and social networks. Two network attributes, transitivity (when a node is connected to two other nodes that are also directly connected between them) and centrality (the number and intensity of connections with the other nodes in the network), are widely associated with the dynamics of transmission of pathogens. Here we investigate how network centrality and transitivity influence vulnerability to diseases of human populations by examining one of the most devastating pandemic in human history, the fourteenth century plague pandemic called Black Death. We found that, after controlling for the city spatial location and the disease arrival time, cities with higher values of both centrality and transitivity were more severely affected by the plague. A simulation study indicates that this association was due to central cities with high transitivity undergo more exogenous re-infections. Our study provides an easy method to identify hotspots in epidemic networks. Focusing our effort in those vulnerable nodes may save time and resources by improving our ability of controlling deadly epidemics.

  6. Breaking news dissemination in the media via propagation behavior based on complex network theory

    Science.gov (United States)

    Liu, Nairong; An, Haizhong; Gao, Xiangyun; Li, Huajiao; Hao, Xiaoqing

    2016-07-01

    The diffusion of breaking news largely relies on propagation behaviors in the media. The tremendous and intricate propagation relationships in the media form a complex network. An improved understanding of breaking news diffusion characteristics can be obtained through the complex network research. Drawing on the news data of Bohai Gulf oil spill event from June 2011 to May 2014, we constructed a weighted and directed complex network in which media are set as nodes, the propagation relationships as edges and the propagation times as the weight of the edges. The primary results show (1) the propagation network presents small world feature, which means relations among media are close and breaking news originating from any node can spread rapidly; (2) traditional media and official websites are the typical sources for news propagation, while business portals are news collectors and spreaders; (3) the propagation network is assortative and the group of core media facilities the spread of breaking news faster; (4) for online media, news originality factor become less important to propagation behaviors. This study offers a new insight to explore information dissemination from the perspective of statistical physics and is beneficial for utilizing the public opinion in a positive way.

  7. Stationary patterns in star networks of bistable units: Theory and application to chemical reactions.

    Science.gov (United States)

    Kouvaris, Nikos E; Sebek, Michael; Iribarne, Albert; Díaz-Guilera, Albert; Kiss, István Z

    2017-04-01

    We present theoretical and experimental studies on pattern formation with bistable dynamical units coupled in a star network configuration. By applying a localized perturbation to the central or the peripheral elements, we demonstrate the subsequent spreading, pinning, or retraction of the activations; such analysis enables the characterization of the formation of stationary patterns of localized activity. The results are interpreted with a theoretical analysis of a simplified bistable reaction-diffusion model. Weak coupling results in trivial pinned states where the activation cannot propagate. At strong coupling, a uniform state is expected with active or inactive elements at small or large degree networks, respectively. A nontrivial stationary spatial pattern, corresponding to an activation pinning, is predicted to occur at an intermediate number of peripheral elements and at intermediate coupling strengths, where the central activation of the network is pinned, but the peripheral activation propagates toward the center. The results are confirmed in experiments with star networks of bistable electrochemical reactions. The experiments confirm the existence of the stationary spatial patterns and the dependence of coupling strength on the number of peripheral elements for transitions between pinned and retreating or spreading fronts in forced network configurations (where the central or periphery elements are forced to maintain their states).

  8. Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

    Science.gov (United States)

    Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

    2017-05-01

    The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

  9. Trust and Its Impact on Cooperation in Alliance Networks:Theory and Practice

    Directory of Open Access Journals (Sweden)

    Wlodzimierz SROKA

    2011-11-01

    Full Text Available At present we can observe the increasing role of cooperation among companies all around the world. Cooperation includes many forms, such as alliances, joint ventures, networks, clusters, outsourcing and others. Trust is one of the most important factors of success of any cooperation activity, because it can lower transaction costs, increase productivity and innovativeness, facilitate inter-organizational relationships and resolve conflicts. Therefore the paper discusses the basic problems of trust in alliance networks. The text consists of theoretical deliberations devoted to alliance networks and trust. The practical case of the company from machine industry that formed a portfolio of alliances based on trust is also an important part of the text. The conclusion of the paper is that portfolio of alliances based on trust is worth pursuing.

  10. Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Sang Ki; Chang, Soon Heung

    1994-01-01

    A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods. ((orig.))

  11. A new paradigm for particle tracking velocimetry, based on graph-theory and pulsed neural network

    International Nuclear Information System (INIS)

    Derou, D.; Herault, L.

    1994-01-01

    The Particle Tracking Velocimetry (PTV) technique works by recording, at different instances in time, positions of small tracers particles following a flow and illuminated by a sheet, or pseudo sheet, of light. It aims to recognize each particle trajectory, constituted of n different spots and determine thus each particle velocity vector. In this paper, we devise a new method, taking into account a global consistency of the trajectories to be extracted, in terms of visual perception and physical properties. It is based on a graph-theoretic formulation of the particle tracking problem and the use of an original neural network, called pulsed neural network. (authors). 4 figs

  12. A Game Theory Based Approach for Power Efficient Vehicular Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Kun Hua

    2017-01-01

    Full Text Available Green communications are playing critical roles in vehicular ad hoc networks (VANETs, while the deployment of a power efficient VANET is quite challenging in practice. To add more greens into such kind of complicated and time-varying mobile network, we specifically investigate the throughput and transmission delay performances for real-time and delay sensitive services through a repeated game theoretic solution. This paper has employed Nash Equilibrium in the noncooperative game model and analyzes its efficiency. Simulation results have shown an obvious improvement on power efficiency through such efforts.

  13. Consumer adoption of social networking sites: implications for theory and practice

    NARCIS (Netherlands)

    Lorenzo Romero, Carlota; Constantinides, Efthymios; Alarcon-del-Amo, Maria-del-Carmen

    2011-01-01

    Purpose – The purpose of this paper is to study factors affecting the acceptance of social networking sites (SNS), analyze users' practices and behavior in these environments and assess the degree of acceptance of SNS in The Netherlands. Design/methodology/approach – An extended technology

  14. Application of Financial Risk-reward Theory to Link and Network Optimization

    Science.gov (United States)

    2011-10-01

    use game-theoretic ap- proach to predict the performance of multi-user communication and various capital asset pricing models ( CAPM ) to assess the...Adaptive Power Control Schemes in Interference Channels Ad-hoc networking has been of critical interest to the military for many years. In commercial

  15. Extreme value theory, Poisson-Dirichlet distributions, and first passage percolation on random networks

    NARCIS (Netherlands)

    Bhamidi, S.; Van der Hofstad, R.; Hooghiemstra, G.

    2010-01-01

    We study first passage percolation (FPP) on the configuration model (CM) having power-law degrees with exponent ? ? [1, 2) and exponential edge weights. We derive the distributional limit of the minimal weight of a path between typical vertices in the network and the number of edges on the

  16. Use of formative research and social network theory to develop a group walking intervention: Sumter County on the Move!

    Science.gov (United States)

    Forthofer, Melinda; Burroughs-Girardi, Ericka; Stoisor-Olsson, Liliana; Wilcox, Sara; Sharpe, Patricia A; Pekuri, Linda M

    2016-10-01

    Although social support is a frequently cited enabler of physical activity, few studies have examined how to harness social support in interventions. This paper describes community-based formative research to design a walking program for mobilizing naturally occurring social networks to support increases in walking behavior. Focus group methods were used to engage community members in discussions about desired walking program features. The research was conducted with underserved communities in Sumter County, South Carolina. The majority of focus group participants were women (76%) and African American (92%). Several important themes emerged from the focus group results regarding attitudes toward walking, facilitators of and barriers to walking, ideal walking program characteristics, and strategies for encouraging community members to walk. Most noteably, the role of existing social networks as a supportive influence on physical activity was a recurring theme in our formative research and a gap in the existing evidence base. The resulting walking program focused on strategies for mobilizing, supporting and reinforcing existing social networks as mechanisms for increasing walking. Our approach to linking theory, empirical evidence and community-based formative research for the development of a walking intervention offers an example for practitioners developing intervention strategies for a wide range of behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. On the Biological Plausibility of Grandmother Cells: Implications for Neural Network Theories in Psychology and Neuroscience

    Science.gov (United States)

    Bowers, Jeffrey S.

    2009-01-01

    A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated…

  18. Fitting Multidimensional Amotivation into the Self-Determination Theory Nomological Network: Application in School Physical Education

    Science.gov (United States)

    Vlachopoulos, Symeon P.; Katartzi, Ermioni S.; Kontou, Maria G.

    2013-01-01

    The present study investigated the nomological validity of the Amotivation Inventory-Physical Education (Shen, Wingert, Li, Sun, & Rukavina, 2010b) scores by examining the associations of ability, effort, value, and task characteristics amotivation beliefs with self-determination theory variables. Data were collected from 401 fifth- and…

  19. System identification and adaptive control theory and applications of the neurofuzzy and fuzzy cognitive network models

    CERN Document Server

    Boutalis, Yiannis; Kottas, Theodore; Christodoulou, Manolis A

    2014-01-01

    Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented.  Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model  stems  from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering s...

  20. A Comprehensive Theory of Algorithms for Wireless Networks and Mobile Systems

    Science.gov (United States)

    2016-06-08

    pages 109-118, July 2015. [3] Magnus Halldorsson, Stephan Holzer and Nancy Lynch. A Local Broadcast Layer for the SINR Network Model. ACM Symposium on...publication, 2014. [9] Magnus Halldorsson, Stephan Holzer, Pradipta Mitra and Roger Wattenhofer. The Power of Oblivious Wireless Power. Submitted for...David Peleg. Nonuniform SINR+Voronoi Diagrams are Effectively Uniform. In Yoram Moses, editor, Distributed Computing: 29th International Symposium

  1. Analysis of Social Network Dynamics with Models from the Theory of Complex Adaptive Systems

    OpenAIRE

    Lymperopoulos , Ilias; Lekakos , George

    2013-01-01

    Part 4: Protocols, Regulation and Social Networking; International audience; The understanding and modeling of social dynamics in a complex and unpredictable world, emerges as a research target of particular importance. Success in this direction can yield valuable knowledge as to how social phenomena form and evolve in varying socioeconomic contexts comprising economic crises, societal disasters, cultural differences and security threats among others. The study of social dynamics occurring in...

  2. Development of flow network analysis code for block type VHTR core by linear theory method

    International Nuclear Information System (INIS)

    Lee, J. H.; Yoon, S. J.; Park, J. W.; Park, G. C.

    2012-01-01

    VHTR (Very High Temperature Reactor) is high-efficiency nuclear reactor which is capable of generating hydrogen with high temperature of coolant. PMR (Prismatic Modular Reactor) type reactor consists of hexagonal prismatic fuel blocks and reflector blocks. The flow paths in the prismatic VHTR core consist of coolant holes, bypass gaps and cross gaps. Complicated flow paths are formed in the core since the coolant holes and bypass gap are connected by the cross gap. Distributed coolant was mixed in the core through the cross gap so that the flow characteristics could not be modeled as a simple parallel pipe system. It requires lot of effort and takes very long time to analyze the core flow with CFD analysis. Hence, it is important to develop the code for VHTR core flow which can predict the core flow distribution fast and accurate. In this study, steady state flow network analysis code is developed using flow network algorithm. Developed flow network analysis code was named as FLASH code and it was validated with the experimental data and CFD simulation results. (authors)

  3. Theory-based metrological traceability in education: A reading measurement network.

    Science.gov (United States)

    Fisher, William P; Stenner, A Jackson

    2016-10-01

    Huge resources are invested in metrology and standards in the natural sciences, engineering, and across a wide range of commercial technologies. Significant positive returns of human, social, environmental, and economic value on these investments have been sustained for decades. Proven methods for calibrating test and survey instruments in linear units are readily available, as are data- and theory-based methods for equating those instruments to a shared unit. Using these methods, metrological traceability is obtained in a variety of commercially available elementary and secondary English and Spanish language reading education programs in the U.S., Canada, Mexico, and Australia. Given established historical patterns, widespread routine reproduction of predicted text-based and instructional effects expressed in a common language and shared frame of reference may lead to significant developments in theory and practice. Opportunities for systematic implementations of teacher-driven lean thinking and continuous quality improvement methods may be of particular interest and value.

  4. Can Burt's Theory of Structural Holes be Applied to Study Social Support Among Mid-Age Female Sex Workers? A Multi-Site Egocentric Network Study in China.

    Science.gov (United States)

    Liu, Hongjie

    2017-12-01

    The epidemic of HIV/AIDS continues to spread among older adults and mid-age female sex workers (FSWs) over 35 years old. We used egocentric network data collected from three study sites in China to examine the applicability of Burt's Theory of Social Holes to study social support among mid-age FSWs. Using respondent-driven sampling, 1245 eligible mid-age FSWs were interviewed. Network structural holes were measured by network constraint and effective size. Three types of social networks were identified: family networks, workplace networks, and non-FSW networks. A larger effective size was significantly associated with a higher level of social support [regression coefficient (β) 5.43-10.59] across the three study samples. In contrast, a greater constraint was significantly associated with a lower level of social support (β -9.33 to -66.76). This study documents the applicability of the Theory of Structural Holes in studying network support among marginalized populations, such as FSWs.

  5. Quantification of motor network dynamics in Parkinson's disease by means of landscape and flux theory.

    Directory of Open Access Journals (Sweden)

    Han Yan

    Full Text Available The basal ganglia neural circuit plays an important role in motor control. Despite the significant efforts, the understanding of the principles and underlying mechanisms of this modulatory circuit and the emergence of abnormal synchronized oscillations in movement disorders is still challenging. Dopamine loss has been proved to be responsible for Parkinson's disease. We quantitatively described the dynamics of the basal ganglia-thalamo-cortical circuit in Parkinson's disease in terms of the emergence of both abnormal firing rates and firing patterns in the circuit. We developed a potential landscape and flux framework for exploring the modulatory circuit. The driving force of the circuit can be decomposed into a gradient of the potential, which is associated with the steady-state probability distributions, and the curl probability flux term. We uncovered the underlying potential landscape as a Mexican hat-shape closed ring valley where abnormal oscillations emerge due to dopamine depletion. We quantified the global stability of the network through the topography of the landscape in terms of the barrier height, which is defined as the potential difference between the maximum potential inside the ring and the minimum potential along the ring. Both a higher barrier and a larger flux originated from detailed balance breaking result in more stable oscillations. Meanwhile, more energy is consumed to support the increasing flux. Global sensitivity analysis on the landscape topography and flux indicates how changes in underlying neural network regulatory wirings and external inputs influence the dynamics of the system. We validated two of the main hypotheses(direct inhibition hypothesis and output activation hypothesis on the therapeutic mechanism of deep brain stimulation (DBS. We found GPe appears to be another effective stimulated target for DBS besides GPi and STN. Our approach provides a general way to quantitatively explore neural networks and may

  6. Top-Down Influences on Local Networks: Basic Theory with Experimental Implications

    Directory of Open Access Journals (Sweden)

    Ramesh eSrinivasan

    2013-04-01

    Full Text Available The response of a population of sensory neurons to an external stimulus depends not only on the receptive field properties of the neurons, but also the level of arousal and attention or goal-oriented cognitive biases that guide information processing. These top-down effects on the sensory neurons bias the output of the neurons and affect behavioral outcomes such as stimulus detection, discrimination, and response time. In any physiological study, neural dynamics are observed in a specific brain state; the background state partly determines neuronal excitability. Experimental studies in humans and animal models have also demonstrated that slow oscillations (typically in the alpha or theta bands modulate the fast oscillations (gamma band associated with local networks of neurons. Cross-frequency interaction is of interest as a mechanism for top-down or bottom-up interactions between systems at different spatial scales. We develop a generic model of top-down influences on local networks appropriate for comparison with EEG. EEG provides excellent temporal resolution to investigate neuronal oscillations but is space-averaged on the cm scale. Thus, appropriate EEG models are developed in terms of population synaptic activity. We used the Wilson-Cowan population model to investigate fast (gamma band oscillations generated by a local network of excitatory and inhibitory neurons. We modified the Wilson-Cowan equations to make them more physiologically realistic by explicitly incorporating background state variables into the model. We found that the population response is strongly influenced by the background state. We apply the model to reproduce the modulation of gamma rhythms by theta rhythms as has been observed in animal models and human ECoG and EEG studies. The concept of a dynamic background state presented here using the Wilson-Cowan model can be readily applied to incorporate top-down modulation in more detailed models of specific sensory

  7. A Cloud Theory-Based Trust Computing Model in Social Networks

    Directory of Open Access Journals (Sweden)

    Fengming Liu

    2016-12-01

    Full Text Available How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node’s comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved.

  8. Game Theory Based Security in Wireless Body Area Network with Stackelberg Security Equilibrium

    OpenAIRE

    Somasundaram, M.; Sivakumar, R.

    2015-01-01

    Wireless Body Area Network (WBAN) is effectively used in healthcare to increase the value of the patient’s life and also the value of healthcare services. The biosensor based approach in medical care system makes it difficult to respond to the patients with minimal response time. The medical care unit does not deploy the accessing of ubiquitous broadband connections full time and hence the level of security will not be high always. The security issue also arises in monitoring the user body fu...

  9. Application of Fuzzy theory with neutral network and cognitive map on decision making

    International Nuclear Information System (INIS)

    Hla Aung; Tin Maung

    2001-01-01

    The format reasoning involves establishment of causal relationships among concepts. These are commonly represented by cognitive maps. However, the concepts and their relationships could be fuzzy. In this paper we review some properties of fuzzy cognitive maps. This paper shows that one of the solutions is to introduce the idea of disconcepts along with concepts to arrive at reasonings that are intuitively satisfying. A neutral network architecture based on associative memory and a framework for fuzzy cognitive maps based knowledge processing tool has also been proposed. The proposed method is tested on a cognitive map of a publishing company. (author)

  10. Applying the Uses and Gratifications Theory to Compare Higher Education Students’ Motivation for Using Social Networking Sites: Experiences from Iran, Malaysia, United Kingdom, and South Africa

    OpenAIRE

    Karimi, Leila; Khodabandelou, Rouhollah; Ehsani, Maryam; Ahmad, Muhammad

    2014-01-01

    Drawing from the Uses and Gratifications Theory, this study examined the Gratification Sought and the Gratification Obtained from using Social Networking Sites among Iranian, Malaysian, British, and South African higher education students. This comparison allowed to drawing conclusions about how social networking sites fulfill users’ needs with different cultures. Data were collected through a quantitative study applying online and paper- based questionnaire carried out in 2013, using a repre...

  11. Memory and Actor-Network Theory: Mediation in Websites of Estadão and Folha de S. Paulo

    Directory of Open Access Journals (Sweden)

    Allysson Viana Martins

    2013-09-01

    Full Text Available This paper discusses how the ideas that guide the Actor-Network Theory (ANT can be the basis for studies from journalism produced for the internet. We seek to apply the principles of ANT to understand the resource mnemonics uses in web journalism and understand which modalities of mediation characterize these uses. The websites of the Estadão and Folha de S. Paulo formed the corpusto be among the main Brazilian (web newspapers, regarding the trials of the specificities of web journalism. The study was conducted in a typical weekin which there has been no event or event featured so as not to corrupt or emphasize some associations. We realize how much can be misleading to consider the mere presence of memory as an indication of quality or depth content.

  12. Reassembling the Information Technology Innovation Process: An Actor Network Theory Method for Managing the Initiation, Production, and Diffusion of Innovations

    Science.gov (United States)

    Zendejas, Gerardo; Chiasson, Mike

    This paper will propose and explore a method to enhance focal actors' abilities to enroll and control the many social and technical components interacting during the initiation, production, and diffusion of innovations. The reassembling and stabilizing of such components is the challenging goal of the focal actors involved in these processes. To address this possibility, a healthcare project involving the initiation, production, and diffusion of an IT-based innovation will be influenced by the researcher, using concepts from actor network theory (ANT), within an action research methodology (ARM). The experiences using this method, and the nature of enrolment and translation during its use, will highlight if and how ANT can provide a problem-solving method to help assemble the social and technical actants involved in the diffusion of an innovation. Finally, the paper will discuss the challenges and benefits of implementing such methods to attain widespread diffusion.

  13. Digital Citizen Participation within Schools in the United Kingdom and Indonesia: An Actor–Network Theory (ANT Perspective

    Directory of Open Access Journals (Sweden)

    Muhammad Yusuf

    2016-11-01

    Full Text Available Citizen engagement and participation are a key focus for government and government agencies, and with the advent of Internet technologies questions arise about the role and impact of technology on citizen participation. This paper aims to explore the role of technology in citizen participation within schools. This research used in-depth comparative case studies using examples from two different schools and school systems, one in the United Kingdom and one in Indonesia. The wider school systems are complex and dynamic environments with multiple stakeholders, media, and supporting systems, and the schools operate under geopolitical and social influences. This paper provides a framework, based on Actor-Network Theory (ANT, for capturing e-participation in schools, particularly identifying the influence of technology as a conduit for enabling, engaging, and empowering stakeholders.

  14. Social Networking Sites and Self-Promotional Culture. Notes for a Theory of the Mosaic Identity

    Directory of Open Access Journals (Sweden)

    Lucía Caro Castaño

    2017-05-01

    Full Text Available This exploratory work theorizes about how social networking sites favor, as identity technologies, a way of conceiving and presenting individual identity in self-promotional terms. As a result of the normalization of this logic –which is coherent with the late capitalism’ promotional culture–, it is growing the incorporation of self-branding practices in the users's daily communication. Besides, it is increasing the perception of the social profiles as micro-media and the interpretation of the own network as a personal audience. In brief, four main trends in the presentation of identity which are promoted by these web services are identified: a distributed and fragmented conception of the self, where the tiles from mass media become key content to express subjectivity; a tendency to quantify relationships and affections; the perception of being in an unavoidable competition with others; and standardization of the audiovisual presentation of self as a communicative material capable of attracting attention and communicate authenticity.

  15. A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2016-04-01

    Full Text Available With the increasing demands for better transmission speed and robust quality of service (QoS, the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users. A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives.

  16. Development of classification and prediction methods of critical heat flux using fuzzy theory and artificial neural networks

    International Nuclear Information System (INIS)

    Moon, Sang Ki

    1995-02-01

    This thesis applies new information techniques, artificial neural networks, (ANNs) and fuzzy theory, to the investigation of the critical heat flux (CHF) phenomenon for water flow in vertical round tubes. The work performed are (a) classification and prediction of CHF based on fuzzy clustering and ANN, (b) prediction and parametric trends analysis of CHF using ANN with the introduction of dimensionless parameters, and (c) detection of CHF occurrence using fuzzy rule and spatiotemporal neural network (STN). Fuzzy clustering and ANN are used for classification and prediction of the CHF using primary system parameters. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulted clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanisms. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods. Parametric trends of the CHF are analyzed by applying artificial neural networks to a CHF data base for water flow in uniformly heated vertical round tubes. The analyses are performed from three viewpoints, i.e., for fixed inlet conditions, for fixed exit conditions, and based on local conditions hypothesis. In order to remove the necessity of data classification, Katto and Groeneveld et al.'s dimensionless parameters are introduced in training the ANNs with the experimental CHF data. The trained ANNs predict the CHF better than any other conventional correlations, showing RMS error of 8.9%, 13.1%, and 19.3% for fixed inlet conditions, for fixed exit conditions, and for local

  17. Path synthesis of four-bar mechanisms using synergy of polynomial neural network and Stackelberg game theory

    Science.gov (United States)

    Ahmadi, Bahman; Nariman-zadeh, Nader; Jamali, Ali

    2017-06-01

    In this article, a novel approach based on game theory is presented for multi-objective optimal synthesis of four-bar mechanisms. The multi-objective optimization problem is modelled as a Stackelberg game. The more important objective function, tracking error, is considered as the leader, and the other objective function, deviation of the transmission angle from 90° (TA), is considered as the follower. In a new approach, a group method of data handling (GMDH)-type neural network is also utilized to construct an approximate model for the rational reaction set (RRS) of the follower. Using the proposed game-theoretic approach, the multi-objective optimal synthesis of a four-bar mechanism is then cast into a single-objective optimal synthesis using the leader variables and the obtained RRS of the follower. The superiority of using the synergy game-theoretic method of Stackelberg with a GMDH-type neural network is demonstrated for two case studies on the synthesis of four-bar mechanisms.

  18. Illuminating the Dark Side of the Internet with Actor-Network Theory: An Integrative Review of Current Cybercrime Research

    Directory of Open Access Journals (Sweden)

    Rocci Luppicini

    2014-06-01

    Full Text Available Cybercrime is a relatively new area of research within criminology and media studies. The purpose of this paper is to pull together current research scholarship at the intersection of Actor-Network Theory (ANT and cybercrime by addressing the following question: How does ANT apply to cybercrime research? A selective integrative review of cybercrime research utilizing ANT was conducted to examine recent developments and identify trends. The review draws on core research papers that span 2002 to 2013. Findings provided a strong indication of ANT’s role in key areas of current cybercrime, namely, cyber bullying, cyber theft, and cyber terrorism and cyber espionage. More specifically, ANT was applied within cyber criminology research to address complex problems involving human-technological interactions, advance alternative models and theoretical perspectives, compare ANT with existing models and theoretical perspectives, and leverage understanding of network influences on actors. Recommendations are provided to help optimize the application of ANT to cybercrime research and practice. This paper helps advance knowledge at the intersection of ANT and the study of cyber criminology.

  19. From translation to enactment: contributions of the Actor-Network Theory to the processual approach to organizations

    Directory of Open Access Journals (Sweden)

    Patricia Kinast De Camillis

    Full Text Available Abstract In the area of Administration, especially in the Organizational Studies (OS, the Actor-Network Theory (ANT has been regarded as part of a movement that aims to leave the functional emphasis of organization and pursue the study of process and practices of organizing - the processual approach to organizations. However, criticism to the ANT has led some authors to seek to overcome them through analytical twists concerning certain concepts. One of these "twists" involved the concept of translation and the inclusion of the concept of enactment . This article discusses both notions with the aid of two studies developed having these concepts as a basis, in order to indicate that the choice of enactment brings along a processual view different from that observed in translation. The concept of translation addresses the predominant and it emphasizes understanding how networks of relationships and objects become "stable"; in turn, enact works with multiplicity and fluidity, where the process takes precedence over things. Although the proposed term enactment does not seek to directly face all criticism, it contributes so that ANT does not take a neutral or mechanical view in its analyses and descriptions. Enactment has the view of organization as a result and product of continuous process and it allows understanding that this is not just working or not (success or failure, but it concerns the "production" of multiple realities when we conduct research in Administration having the processual approach to organizations as a basis.

  20. Real-Time Multifault Rush Repairing Strategy Based on Utility Theory and Multiagent System in Distribution Networks

    Directory of Open Access Journals (Sweden)

    Zhao Hao

    2016-01-01

    Full Text Available The problem of multifault rush repair in distribution networks (DNs is a multiobjective dynamic combinatorial problem with topology constraints. The problem consists of archiving an optimal faults’ allocation strategy to squads and an admissible multifault rush repairing strategy with coordinating switch operations. In this article, the utility theory is introduced to solve the first problem and a new discrete bacterial colony chemotaxis (DBCC algorithm is proposed for the second problem to determine the optimal sequence for each squad to repair faults and the corresponding switch operations. The above solution is called the two-stage approach. Additionally, a double mathematical optimization model based on the fault level is proposed in the second stage to minimize the outage loss and total repairing time. The real-time adjustment multiagent system (RA-MAS is proposed to provide facility to achieve online multifault rush repairing strategy in DNs when there are emergencies after natural disasters. The two-stage approach is illustrated with an example from a real urban distribution network and the simulation results show the effectiveness of the two-stage approach.

  1. Structural Variability within Frontoparietal Networks and Individual Differences in Attentional Functions: An Approach Using the Theory of Visual Attention.

    Science.gov (United States)

    Chechlacz, Magdalena; Gillebert, Celine R; Vangkilde, Signe A; Petersen, Anders; Humphreys, Glyn W

    2015-07-29

    Visuospatial attention allows us to select and act upon a subset of behaviorally relevant visual stimuli while ignoring distraction. Bundesen's theory of visual attention (TVA) (Bundesen, 1990) offers a quantitative analysis of the different facets of attention within a unitary model and provides a powerful analytic framework for understanding individual differences in attentional functions. Visuospatial attention is contingent upon large networks, distributed across both hemispheres, consisting of several cortical areas interconnected by long-association frontoparietal pathways, including three branches of the superior longitudinal fasciculus (SLF I-III) and the inferior fronto-occipital fasciculus (IFOF). Here we examine whether structural variability within human frontoparietal networks mediates differences in attention abilities as assessed by the TVA. Structural measures were based on spherical deconvolution and tractography-derived indices of tract volume and hindrance-modulated orientational anisotropy (HMOA). Individual differences in visual short-term memory (VSTM) were linked to variability in the microstructure (HMOA) of SLF II, SLF III, and IFOF within the right hemisphere. Moreover, VSTM and speed of information processing were linked to hemispheric lateralization within the IFOF. Differences in spatial bias were mediated by both variability in microstructure and volume of the right SLF II. Our data indicate that the microstructural and macrostrucutral organization of white matter pathways differentially contributes to both the anatomical lateralization of frontoparietal attentional networks and to individual differences in attentional functions. We conclude that individual differences in VSTM capacity, processing speed, and spatial bias, as assessed by TVA, link to variability in structural organization within frontoparietal pathways. Copyright © 2015 Chechlacz et al.

  2. Multiobjective Optimization of Water Distribution Networks Using Fuzzy Theory and Harmony Search

    Directory of Open Access Journals (Sweden)

    Zong Woo Geem

    2015-07-01

    Full Text Available Thus far, various phenomenon-mimicking algorithms, such as genetic algorithm, simulated annealing, tabu search, shuffled frog-leaping, ant colony optimization, harmony search, cross entropy, scatter search, and honey-bee mating, have been proposed to optimally design the water distribution networks with respect to design cost. However, flow velocity constraint, which is critical for structural robustness against water hammer or flow circulation against substance sedimentation, was seldom considered in the optimization formulation because of computational complexity. Thus, this study proposes a novel fuzzy-based velocity reliability index, which is to be maximized while the design cost is simultaneously minimized. The velocity reliability index is included in the existing cost optimization formulation and this extended multiobjective formulation is applied to two bench-mark problems. Results show that the model successfully found a Pareto set of multiobjective design solutions in terms of cost minimization and reliability maximization.

  3. Opening up the solar box: Cultural resource management and actor network theory in solar energy projects in the Mojave Desert

    Science.gov (United States)

    Gorrie, Bryan F.

    This project considers the ways that Actor-Network Theory (ANT) can be brought to bear upon Cultural Resource Management (CRM) practices on renewable energy projects. ANT is a way of making inquiry into scientific knowledge practices and as CRM is intended to preserve environmental, historic, and prehistoric resources, it necessarily involves certain kinds of knowledge generation about regions in which projects are being developed. Because the practice of CRM is complex, involving a range of actors from developers to biologists, native peoples to academics, private landholders to environmental and cultural activists, it is imperative to account for the interests of all stakeholders and to resist devolving into the polemical relations of winners and losers, good and bad participants, or simple situations of right and wrong. This project intends to account for the "matters of concern" of various actors, both primary and secondary, by examining the case study of a single solar installation project in the Mojave Desert. A theoretical description of ANT is provided at the beginning and the concerns of this theory are brought to bear upon the case study project through describing the project, discussing the laws governing CRM on federal lands and in the state of California, and providing the points of view of various interviewees who worked directly or indirectly on various aspects of CRM for the solar project. The creators of ANT claim that it is not a methodology but it does speak to ethnomethodologies in that it insists that there is always something more to learn from inquiring into and describing any given situation. These descriptions avoid generalizations, providing instead various points of entry, from diverse perspectives to the project. There is an invitation to avoid assuming that one knows all there is to know about a given situation and to choose instead to continue investigating and thus give voice to the more obscure, often marginalized, voices in the

  4. Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

    Science.gov (United States)

    Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

    2016-06-01

    Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.

  5. Understanding the motivations and activities of transnational advocacy networks against child sex trafficking in the Mekong Subregion: The value of cosmopolitan globalisation theory

    Directory of Open Access Journals (Sweden)

    Deanna Davy

    2013-03-01

    Full Text Available Child sex trafficking has become one of the most highly publicised social issues of our time and, due to its global nature, transnational anti-trafficking advocacy networks are well placed and central to lead campaigns against it. Whilst there is an abundance of literature on the subjects of child sex trafficking and transnational advocacy networks we lack an understanding of the motivations of these networks that act as buffers against trafficking. Cosmopolitan globalisation theory remains a compelling framework for examining the motivations of transnational anti-child sex trafficking networks in the Greater Mekong Subregion. Applying a cosmopolitan globalisation lens, this article discusses the social justice goals of transnational advocacy networks, their centrality in combating child sex trafficking, and their ability to perform cosmopolitan ‘globalisation from below’ to counter global social problems.

  6. A source-initiated on-demand routing algorithm based on the Thorup-Zwick theory for mobile wireless sensor networks.

    Science.gov (United States)

    Mao, Yuxin; Zhu, Ping

    2013-01-01

    The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks.

  7. Editorial of the Special Issue on Human-Technology Interaction and Technology Adoption: Exploring Frameworks other than Actor-Network Theory

    DEFF Research Database (Denmark)

    Tanev, Stoyan

    2014-01-01

    Actor-network theory (ANT) has established itself as a valuable resource for the analysis of technology innovation and adoption. One of the main reasons for the success of the Innovation Translation Model (a specific instantiation of ANT) is the fact that it fits very well the emerging dominance...... challenges. This is why in this special issue we have focused on exploring, in parallel to ANT, other approaches that have also proven valuable in studying technology adoption and human-technology interaction. Some of these approaches share significant common ground with ANT. They also diverge in some......, Design in-use, Practice theory, Innovation diffusion, Consumer innovativeness and Activity theory....

  8. Graph Theory-Based Technique for Isolating Corrupted Boundary Conditions in Continental-Scale River Network Hydrodynamic Simulation

    Science.gov (United States)

    Yu, C. W.; Hodges, B. R.; Liu, F.

    2017-12-01

    Development of continental-scale river network models creates challenges where the massive amount of boundary condition data encounters the sensitivity of a dynamic nu- merical model. The topographic data sets used to define the river channel characteristics may include either corrupt data or complex configurations that cause instabilities in a numerical solution of the Saint-Venant equations. For local-scale river models (e.g. HEC- RAS), modelers typically rely on past experience to make ad hoc boundary condition adjustments that ensure a stable solution - the proof of the adjustment is merely the sta- bility of the solution. To date, there do not exist any formal methodologies or automated procedures for a priori detecting/fixing boundary conditions that cause instabilities in a dynamic model. Formal methodologies for data screening and adjustment are a critical need for simulations with a large number of river reaches that draw their boundary con- dition data from a wide variety of sources. At the continental scale, we simply cannot assume that we will have access to river-channel cross-section data that has been ade- quately analyzed and processed. Herein, we argue that problematic boundary condition data for unsteady dynamic modeling can be identified through numerical modeling with the steady-state Saint-Venant equations. The fragility of numerical stability increases with the complexity of branching in river network system and instabilities (even in an unsteady solution) are typically triggered by the nonlinear advection term in Saint-Venant equations. It follows that the behavior of the simpler steady-state equations (which retain the nonlin- ear term) can be used to screen the boundary condition data for problematic regions. In this research, we propose a graph-theory based method to isolate the location of corrupted boundary condition data in a continental-scale river network and demonstrate its utility with a network of O(10^4) elements. Acknowledgement

  9. Exploring the Relational Efforts Making up a Curriculum Concept--An Actor-Network Theory Analysis of the Curriculum Concept of "Children's Interests"

    Science.gov (United States)

    Moberg, Emilie

    2018-01-01

    This paper undertakes an investigation of the "life" of the curriculum concept of "children's interests" in a preschool practice. The concept of "children's interests" plays a vital role in the Swedish preschool curriculum text and in the preschool field. Strongly inspired by Actor-network theory readings, the paper…

  10. Foodsheds in Virtual Water Flow Networks: A Spectral Graph Theory Approach

    Directory of Open Access Journals (Sweden)

    Nina Kshetry

    2017-06-01

    Full Text Available A foodshed is a geographic area from which a population derives its food supply, but a method to determine boundaries of foodsheds has not been formalized. Drawing on the food–water–energy nexus, we propose a formal network science definition of foodsheds by using data from virtual water flows, i.e., water that is virtually embedded in food. In particular, we use spectral graph partitioning for directed graphs. If foodsheds turn out to be geographically compact, it suggests the food system is local and therefore reduces energy and externality costs of food transport. Using our proposed method we compute foodshed boundaries at the global-scale, and at the national-scale in the case of two of the largest agricultural countries: India and the United States. Based on our determination of foodshed boundaries, we are able to better understand commodity flows and whether foodsheds are contiguous and compact, and other factors that impact environmental sustainability. The formal method we propose may be used more broadly to study commodity flows and their impact on environmental sustainability.

  11. Examining Self-Disclosure on Social Networking Sites: A Flow Theory and Privacy Perspective

    Directory of Open Access Journals (Sweden)

    George Oppong Appiagyei Ampong

    2018-06-01

    Full Text Available Social media and other web 2.0 tools have provided users with the platform to interact with and also disclose personal information to not only their friends and acquaintances but also relative strangers with unprecedented ease. This has enhanced the ability of people to share more about themselves, their families, and their friends through a variety of media including text, photo, and video, thus developing and sustaining social and business relationships. The purpose of the paper is to identify the factors that predict self-disclosure on social networking sites from the perspective of privacy and flow. Data was collected from 452 students in three leading universities in Ghana and analyzed with Partial Least Square-Structural Equation Modeling. Results from the study revealed that privacy risk was the most significant predictor. We also found privacy awareness, privacy concerns, and privacy invasion experience to be significant predictors of self-disclosure. Interaction and perceived control were found to have significant effect on self-disclosure. In all, the model accounted for 54.6 percent of the variance in self-disclosure. The implications and limitations of the current study are discussed, and directions for future research proposed.

  12. Examining Self-Disclosure on Social Networking Sites: A Flow Theory and Privacy Perspective.

    Science.gov (United States)

    Ampong, George Oppong Appiagyei; Mensah, Aseda; Adu, Adolph Sedem Yaw; Addae, John Agyekum; Omoregie, Osaretin Kayode; Ofori, Kwame Simpe

    2018-06-06

    Social media and other web 2.0 tools have provided users with the platform to interact with and also disclose personal information to not only their friends and acquaintances but also relative strangers with unprecedented ease. This has enhanced the ability of people to share more about themselves, their families, and their friends through a variety of media including text, photo, and video, thus developing and sustaining social and business relationships. The purpose of the paper is to identify the factors that predict self-disclosure on social networking sites from the perspective of privacy and flow. Data was collected from 452 students in three leading universities in Ghana and analyzed with Partial Least Square-Structural Equation Modeling. Results from the study revealed that privacy risk was the most significant predictor. We also found privacy awareness, privacy concerns, and privacy invasion experience to be significant predictors of self-disclosure. Interaction and perceived control were found to have significant effect on self-disclosure. In all, the model accounted for 54.6 percent of the variance in self-disclosure. The implications and limitations of the current study are discussed, and directions for future research proposed.

  13. Case Library Construction Technology of Energy Loss in Distribution Networks Considering Regional Differentiation Theory

    Directory of Open Access Journals (Sweden)

    Ze Yuan

    2017-11-01

    Full Text Available The grid structures, load levels, and running states of distribution networks in different supply regions are known as the influencing factors of energy loss. In this paper, the case library of energy loss is constructed to differentiate the crucial factors of energy loss in the different supply regions. First of all, the characteristic state values are selected as the representation of the cases based on the analysis of energy loss under various voltage classes and in different types of regions. Then, the methods of Grey Relational Analysis and the K-Nearest Neighbor are utilized to implement the critical technologies of case library construction, including case representation, processing, analysis, and retrieval. Moreover, the analysis software of the case library is designed based on the case library construction technology. Some case studies show that there are many differences and similarities concerning the factors that influence the energy loss in different types of regions. In addition, the most relevant sample case can be retrieved from the case library. Compared with the traditional techniques, constructing a case library provides a new way to find out the characteristics of energy loss in different supply regions and constitutes differentiated loss-reducing programs.

  14. Direct gaze elicits atypical activation of the theory-of-mind network in autism spectrum conditions.

    Science.gov (United States)

    von dem Hagen, Elisabeth A H; Stoyanova, Raliza S; Rowe, James B; Baron-Cohen, Simon; Calder, Andrew J

    2014-06-01

    Eye contact plays a key role in social interaction and is frequently reported to be atypical in individuals with autism spectrum conditions (ASCs). Despite the importance of direct gaze, previous functional magnetic resonance imaging in ASC has generally focused on paradigms using averted gaze. The current study sought to determine the neural processing of faces displaying direct and averted gaze in 18 males with ASC and 23 matched controls. Controls showed an increased response to direct gaze in brain areas implicated in theory-of-mind and gaze perception, including medial prefrontal cortex, temporoparietal junction, posterior superior temporal sulcus region, and amygdala. In contrast, the same regions showed an increased response to averted gaze in individuals with an ASC. This difference was confirmed by a significant gaze direction × group interaction. Relative to controls, participants with ASC also showed reduced functional connectivity between these regions. We suggest that, in the typical brain, perceiving another person gazing directly at you triggers spontaneous attributions of mental states (e.g. he is "interested" in me), and that such mental state attributions to direct gaze may be reduced or absent in the autistic brain.

  15. Functional brain networks and white matter underlying theory-of-mind in autism.

    Science.gov (United States)

    Kana, Rajesh K; Libero, Lauren E; Hu, Christi P; Deshpande, Hrishikesh D; Colburn, Jeffrey S

    2014-01-01

    Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism.

  16. TCP Performance in Multi-Polling Game Theory-Based IEEE 802.11 Networks

    Directory of Open Access Journals (Sweden)

    Cuzanauskas Tomas

    2016-12-01

    Full Text Available Easy usage and integration with various applications made IEEE 802.11 one of the most used technologies these days, both at home and business premises. Over the years, there have been many additional improvements to the 802.11 standards. Nevertheless, the algorithms and Media Access Control (MAC layer methods are almost the same as in previous Wi-Fi versions. In this paper, a set of methods to improve the total system capacity is proposed – such as efficient transmit power management based on Game Theory with a custom wireless medium protocol. The transmit power management and wireless medium protocol is verified by both simulation and real application scenarios. The results conclude that the capacity of the proposed wireless medium protocol is overall 20 percent higher than the standard 802.11 wireless medium access protocols. Additional TCP Acknowledgment filtering, which was tested together with the proposed wireless medium access protocol, can provide up to 10-percent-higher TCP throughput in high-density scenarios, especially for asymmetrical traffic cases. The conducted research suggests that efficient power management could result in lighter transmit power allocation rules that are currently set by the local regulators for current Wi-Fi devices. Thus, better propagation characteristics and wireless medium management would lead to an overall higher wireless system capacity.

  17. PRODIAG: Combined expert system/neural network for process fault diagnosis. Volume 1, Theory

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.

    1995-09-01

    The function of the PRODIAG code is to diagnose on-line the root cause of a thermal-hydraulic (T-H) system transient with trace back to the identification of the malfunctioning component using the T-H instrumentation signals exclusively. The code methodology is based on the Al techniques of automated reasoning/expert systems (ES) and artificial neural networks (ANN). The research and development objective is to develop a generic code methodology which would be plant- and T-H-system-independent. For the ES part the only plant or T-H system specific code requirements would be implemented through input only and at that only through a Piping and Instrumentation Diagram (PID) database. For the ANN part the only plant or T-H system specific code requirements would be through the ANN training data for normal component characteristics and the same PID database information. PRODIAG would, therefore, be generic and portable from T-H system to T-H system and from plant to plant without requiring any code-related modifications except for the PID database and the ANN training with the normal component characteristics. This would give PRODIAG the generic feature which numerical simulation plant codes such as TRAC or RELAP5 have. As the code is applied to different plants and different T-H systems, only the connectivity information, the operating conditions and the normal component characteristics are changed, and the changes are made entirely through input. Verification and validation of PRODIAG would, be T-H system independent and would be performed only ``once``.

  18. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  19. Effects of Social Support About Physical Activity on Social Networking Sites: Applying the Theory of Planned Behavior.

    Science.gov (United States)

    Zhang, Ni; Campo, Shelly; Yang, Jingzhen; Janz, Kathleen F; Snetselaar, Linda G; Eckler, Petya

    2015-01-01

    Despite the physical and mental health benefits of leisure-time physical activity (LTPA), only about half of college students participate in the recommended amount of LTPA. While college students are avid users of social network sites (SNSs), whether SNSs would be an effective channel for promoting LTPA through peer social support is unclear. The aim of this study was to explore the effects of social support from students' contacts on SNSs on their intention to participate in LTPA, applying the Theory of Planned Behavior. Participants were recruited through a mass e-mail sent to undergraduate students at a large Midwestern university in fall 2011. In total, 439 surveys were analyzed. Descriptive analyses and analysis for mediating effects were conducted. Social support about LTPA from contacts on SNSs has indirect effect on intention through affective attitude, instrumental attitude, and perceived behavioral control (PBC). The results indicate that social support about LTPA from contacts on SNSs might not be effective to change students' intention unless attitudes and PBC are changed. Future interventions aiming to promote students' intention to participate in LTPA by increasing support from contacts on SNSs should increase affective attitude, instrumental attitude, and PBC at the same time.

  20. Distributed k-Means Algorithm and Fuzzy c-Means Algorithm for Sensor Networks Based on Multiagent Consensus Theory.

    Science.gov (United States)

    Qin, Jiahu; Fu, Weiming; Gao, Huijun; Zheng, Wei Xing

    2016-03-03

    This paper is concerned with developing a distributed k-means algorithm and a distributed fuzzy c-means algorithm for wireless sensor networks (WSNs) where each node is equipped with sensors. The underlying topology of the WSN is supposed to be strongly connected. The consensus algorithm in multiagent consensus theory is utilized to exchange the measurement information of the sensors in WSN. To obtain a faster convergence speed as well as a higher possibility of having the global optimum, a distributed k-means++ algorithm is first proposed to find the initial centroids before executing the distributed k-means algorithm and the distributed fuzzy c-means algorithm. The proposed distributed k-means algorithm is capable of partitioning the data observed by the nodes into measure-dependent groups which have small in-group and large out-group distances, while the proposed distributed fuzzy c-means algorithm is capable of partitioning the data observed by the nodes into different measure-dependent groups with degrees of membership values ranging from 0 to 1. Simulation results show that the proposed distributed algorithms can achieve almost the same results as that given by the centralized clustering algorithms.

  1. Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

    Science.gov (United States)

    He, Yongqun

    2016-06-01

    Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

  2. Strategic business networks in theory and practice. Success factors for network-based management of market partnerships in the energy sector; Strategische Unternehmensnetzwerke in Theorie und Praxis. Erfolgsfaktoren eines netzwerkbasierten Managements von Marktpartnerschaften in der Energiewirtschaft

    Energy Technology Data Exchange (ETDEWEB)

    Hennigs, Joerg

    2011-07-01

    Inspired by the steadily growing discussion around the phenomenon of human networks in science and professional practice the present study undertakes to investigate to what extent the research strategy of business networks can be adapted to the management of market partnerships in the energy sector and is suitable for facilitating the tasks and goals of an efficient network management. Especially in industrial branches with low customer contact intensity, there is great economic value in knowing about potential network partners who could serve as links to customers and the possibilities of customer development and of encouraging customers to participate in desired network activities.

  3. Discutindo a aprendizagem sob a perspectiva da teoria ator-rede Discussing learning under actor-network theory perspective

    Directory of Open Access Journals (Sweden)

    Maria de Fátima Aranha de Queiroz e Melo

    2011-04-01

    Full Text Available Neste trabalho, discutimos as aprendizagens como um fenômeno dinâmico e multifacetado, produto de uma série de condições que emergem numa causalidade em redes, tomando o corpo enquanto uma instância mediadora que se afeta como um todo nas interações com o mundo. Apoiamo-nos no conceito de tradução defendido pela Teoria Ator-Rede, buscando seus desdobramentos no campo da Psicologia para entender a construção das identidades como apostas sempre provisórias das mesclas de materialidade e socialidade que vão se processando ao longo das biografias dos humanos. Valemo-nos dos princípios Stengers-Despret, atualizados por Latour, apontando para uma epistemologia política alternativa ao fazer uma reflexão sobre o ensinar, o aprender e construir conhecimento: enquanto um processo necessariamente vinculado e sintonizado com outros; enquanto uma empreitada de riscos que leva em conta, como estratégia de sobrevivência, as recalcitrâncias em humanos e não humanos; que oferece ocasiões para diferir num movimento em que todos os envolvidos se modificam pelos efeitos que causam reciprocamente uns nos outros; enquanto uma prática plural e inclusiva, tendo, finalmente, um mundo comum como o objetivo maior destas construções.In this paper, we pose learning as a dynamic and multifaceted phenomenon, which is the product of a series of conditions emerging from a networking causality, taking body as a mediating instance between subject and the world, affecting reciprocally each other. Based on concept of translation, defended by Actor-Network Theory, we searched their unfolding in Psychology field in order to understand the construction of identities as bets, always temporaries, of materiality and sociality processed mixtures, during human biography lifetime. We used Stengers-Despret principles, brought up to date for Latour, pointing to an alternative political epistemology reflecting on teaching, learning and knowledge construction: while a

  4. An Exploration of Social Networking Sites (SNS) Adoption in Malaysia Using Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) And Intrinsic Motivation

    OpenAIRE

    Goh Say Leng; Suddin Lada; Mohd Zulkifli Muhammad; Ag Asri Hj Ag Ibrahim; Tamrin Amboala

    2011-01-01

    The objective of the paper is to explore the factors that encourage students to adopt social network sites (SNS) in Malaysia and to use the study’s findings to develop guidelines for SNS providers on how to maximize the rate of adoption. A conceptual model of Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB) and intrinsic motivation is proposed and empirically tested in the context of SNS usage. Structural Equation modelling was used on the survey data from 283 university s...

  5. Learning about a fish from an ANT: actor network theory and science education in the postgenomic era

    Science.gov (United States)

    Pierce, Clayton

    2015-03-01

    This article uses actor network theory (ANT) to develop a more appropriate model of scientific literacy for students, teachers, and citizens in a society increasingly populated with biotechnological and bioscientific nonhumans. In so doing, I take the recent debate surrounding the first genetically engineered animal food product under review by the FDA, AquaBounty Technologies' AquAdvantage® salmon, as a vehicle for exploring the ways in which the biosciences have fundamentally altered the boundary between nature and culture and thus the way the public understands both. In response to the new challenges of a postgenomic society, I outline three frameworks for using ANT literacies in classroom settings. Each frame, I argue, is foundational to the development of a scientific literacy that can trace and map actors involved in controversies such as the AquAdvantage® salmon. In examining these frames I follow the actor of a salmon through an environmental history lens, the technoscientific literacy operating in AquaBounty's FDA application and the National Academies new science education framework, and finally to a model of democracy rooted in an ethic of the common. The ultimate claim of this article is that until science education (and education in general) can begin to include nonhumans such as the AquAdvantage® salmon as part of a common political framework, students, educators, and community members will continue to be at the mercy of experts and corporate stakeholders for defining the terms in which people heal, feed, and educate themselves now and in the future.

  6. Development of Taiwanese government’s climate policy after the Kyoto protocol: Applying policy network theory as an analytical framework

    International Nuclear Information System (INIS)

    Shyu, Chian-Woei

    2014-01-01

    Given its limited involvement in and recognition by international organizations, Taiwan is not presently a signatory to the United Nations Framework Convention on Climate Change (UNFCCC) or the Kyoto Protocol. The objective of this study is to analyze how and the extent to which changes in an exogenous factor, namely the Kyoto Protocol and Post-Kyoto climate negotiations, affect and ultimately lead to the formulation of and changes in the Taiwanese government's climate policy. This study applies policy network theory to examine the development of and changes in the Taiwanese government's climate policy. The results demonstrate that international climate agreements and negotiations play a key role in the development of, changes to, and transformation of Taiwan's climate policy. Scarce evidence was found in this study to demonstrate that domestic or internal factors affect climate change policy. Despite its lack of participation in the UNFCCC and the Kyoto Protocol, Taiwan has adopted national climate change strategies, action plans, and programs to reduce greenhouse gas emissions. However, these climate policies and measures are fairly passive and aim to only conform to the minimal requirements for developing countries under international climate agreements and negotiations. This process results in inconsistent and variable climate policies, targets, and regulations. - Highlights: • Taiwan is not a signatory to the UNFCCC or its Kyoto Protocol. • International climate agreements strongly affected Taiwan's climate policy. • Little evidence was found that domestic factors affect Taiwan's climate policy. • New climate policies, regulations, and laws are formulated and implemented. • Climate policies, targets, and regulations change frequently and are inconsistent

  7. Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space

    Directory of Open Access Journals (Sweden)

    A. A. De Bona

    2016-01-01

    Full Text Available The city of Curitiba, located at Southern Brazil, is recognized by its urban planning structured on three pillars: land use, collective transportation, and traffic. With 3.8 million people in its metropolitan area, the public transport system deals with approximately 2.5 million passengers daily. The structure and properties of such a transportation system have substantial implications for the urban planning and public politics for sustainable development of Curitiba. Therefore, this paper analyzes the structure of the public transportation system of Curitiba through the theory of complex networks in a static approach of network topology and presents a comparative analysis of the results from Curitiba, three cities from China (Shanghai, Beijing, and Guangzhou, and three cities from Poland (GOP, Warszawa, and Łódź. The transportation network was modeled as a complex network with exact geographical coordinates of its bus stops. In all bus lines, the method used was the P-Space. The results show that this bus network has characteristics of both small-world and scale-free networks.

  8. Innovations in workplace accessibility and accommodation for persons with hearing loss: using social networking and community of practice theory to promote knowledge exchange and change.

    Science.gov (United States)

    Shaw, Lynn; Jennings, Mary Beth; Poost-Foroosh, Laya; Hodgins, Heather; Kuchar, Ashley

    2013-01-01

    Despite widespread availability of assistive technology and the role of occupational therapists and audiologists in workplace health, little is known about how these groups influence the health of workers with hearing loss. Based on a previously conducted study, this paper explores the need for networking and community of practice theory to promote knowledge sharing and use between occupational therapists, audiologists, educators, regulators, workers, and employers. Five occupational therapists and five audiologists participated in in-depth interviews. Grounded theory was used to investigate the processes that hinder or support these professionals in addressing the accommodation needs of and workplace accessibility for workers with hearing loss. Constraints to addressing the needs of workers with hearing loss included: lack of knowledge about professional practice processes, lack of networking, lack of knowledge on current research, and lack of knowledge on the realm of expertise of audiologists by occupational therapists and of occupational therapists by audiologists. Innovations in workplace practice in hearing loss require engagement of occupational therapists, audiologists, and employers in knowledge transfer, networking, and learning. This column introduces two theories that may guide the use and development of evidence, knowledge, and expertise toward innovations in hearing work practice.

  9. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  10. How well do mean field theories of spiking quadratic-integrate-and-fire networks work in realistic parameter regimes?

    Science.gov (United States)

    Grabska-Barwińska, Agnieszka; Latham, Peter E

    2014-06-01

    We use mean field techniques to compute the distribution of excitatory and inhibitory firing rates in large networks of randomly connected spiking quadratic integrate and fire neurons. These techniques are based on the assumption that activity is asynchronous and Poisson. For most parameter settings these assumptions are strongly violated; nevertheless, so long as the networks are not too synchronous, we find good agreement between mean field prediction and network simulations. Thus, much of the intuition developed for randomly connected networks in the asynchronous regime applies to mildly synchronous networks.

  11. Bullying Victimization, Social Network Usage, and Delinquent Coping in a Sample of Urban Youth: Examining the Predictions of General Strain Theory.

    Science.gov (United States)

    Baker, Thomas; Pelfrey, William V

    2016-12-01

    Guided by the propositions of general strain theory, this study examines the impact of experienced and anticipated strains on the delinquent coping of adolescents while accounting for the usage of social networking sites. Specifically, this study uses self-report survey data collected from 3,195 middle and high school students in a single Midwest city in the United States to explore the effect of experiencing the strains of traditional bullying victimization and cyberbullying victimization on adolescents self-reported soft drug use, hard drug use, and weapon carrying behavior. These relationships are explored among both frequent and infrequent users of social networking sites. Results indicate that cyberbullying victimization and the anticipated strain of feeling unsafe at or on the way to or from school are significantly and positively associated with all three mechanisms of delinquent coping among both frequent and infrequent social network users.

  12. Recovery and Resource Allocation Strategies to Maximize Mobile Network Survivability by Using Game Theories and Optimization Techniques

    Directory of Open Access Journals (Sweden)

    Pei-Yu Chen

    2013-01-01

    Full Text Available With more and more mobile device users, an increasingly important and critical issue is how to efficiently evaluate mobile network survivability. In this paper, a novel metric called Average Degree of Disconnectivity (Average DOD is proposed, in which the concept of probability is calculated by the contest success function. The DOD metric is used to evaluate the damage degree of the network, where the larger the value of the Average DOD, the more the damage degree of the network. A multiround network attack-defense scenario as a mathematical model is used to support network operators to predict all the strategies both cyber attacker and network defender would likely take. In addition, the Average DOD would be used to evaluate the damage degree of the network. In each round, the attacker could use the attack resources to launch attacks on the nodes of the target network. Meanwhile, the network defender could reallocate its existing resources to recover compromised nodes and allocate defense resources to protect the survival nodes of the network. In the approach to solving this problem, the “gradient method” and “game theory” are adopted to find the optimal resource allocation strategies for both the cyber attacker and mobile network defender.

  13. Complexities’ day-to-day dynamic evolution analysis and prediction for a Didi taxi trip network based on complex network theory

    Science.gov (United States)

    Zhang, Lin; Lu, Jian; Zhou, Jialin; Zhu, Jinqing; Li, Yunxuan; Wan, Qian

    2018-03-01

    Didi Dache is the most popular taxi order mobile app in China, which provides online taxi-hailing service. The obtained big database from this app could be used to analyze the complexities’ day-to-day dynamic evolution of Didi taxi trip network (DTTN) from the level of complex network dynamics. First, this paper proposes the data cleaning and modeling methods for expressing Nanjing’s DTTN as a complex network. Second, the three consecutive weeks’ data are cleaned to establish 21 DTTNs based on the proposed big data processing technology. Then, multiple topology measures that characterize the complexities’ day-to-day dynamic evolution of these networks are provided. Third, these measures of 21 DTTNs are calculated and subsequently explained with actual implications. They are used as a training set for modeling the BP neural network which is designed for predicting DTTN complexities evolution. Finally, the reliability of the designed BP neural network is verified by comparing with the actual data and the results obtained from ARIMA method simultaneously. Because network complexities are the basis for modeling cascading failures and conducting link prediction in complex system, this proposed research framework not only provides a novel perspective for analyzing DTTN from the level of system aggregated behavior, but can also be used to improve the DTTN management level.

  14. Optimising social information by game theory and ant colony method to enhance routing protocol in opportunistic networks

    Directory of Open Access Journals (Sweden)

    Chander Prabha

    2016-09-01

    Full Text Available The data loss and disconnection of nodes are frequent in the opportunistic networks. The social information plays an important role in reducing the data loss because it depends on the connectivity of nodes. The appropriate selection of next hop based on social information is critical for improving the performance of routing in opportunistic networks. The frequent disconnection problem is overcome by optimising the social information with Ant Colony Optimization method which depends on the topology of opportunistic network. The proposed protocol is examined thoroughly via analysis and simulation in order to assess their performance in comparison with other social based routing protocols in opportunistic network under various parameters settings.

  15. Evaluation of hydrogen bond networks in cellulose Iβ and II crystals using density functional theory and Car-Parrinello molecular dynamics.

    Science.gov (United States)

    Hayakawa, Daichi; Nishiyama, Yoshiharu; Mazeau, Karim; Ueda, Kazuyoshi

    2017-09-08

    Crystal models of cellulose Iβ and II, which contain various hydrogen bonding (HB) networks, were analyzed using density functional theory and Car-Parrinello molecular dynamics (CPMD) simulations. From the CPMD trajectories, the power spectra of the velocity correlation functions of hydroxyl groups involved in hydrogen bonds were calculated. For the Iβ allomorph, HB network A, which is dominant according to the neutron diffraction data, was stable, and the power spectrum represented the essential features of the experimental IR spectra. In contrast, network B, which is a minor structure, was unstable because its hydroxymethyl groups reoriented during the CPMD simulation, yielding a different crystal structure to that determined by experiments. For the II allomorph, a HB network A is proposed based on diffraction data, whereas molecular modeling identifies an alternative network B. Our simulations showed that the interaction energies of the cellulose II (B) model are slightly more favorable than model II(A). However, the evaluation of the free energy should be waited for the accurate determination from the energy point of view. For the IR calculation, cellulose II (B) model reproduces the spectra better than model II (A). Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Strategic Ecological Network Competition in Emerging Markets: Theory and Case Analysis of A GPS Vehicle Navigation Firm

    Institute of Scientific and Technical Information of China (English)

    XIAO Lei; LI Shi-ming; ZHANG Jia-tong

    2006-01-01

    Using the case study methodology, firm's competition behavior in strategic network and strategic ecosystems are analyzed. With the ecology view, there is consistency between strategic network and strategic ecosystem. Enterprise should pursue for suitable ecological niche to hold a strategic competitive power.

  17. Non-Gaussian theory of rubberlike elasticity based on rotational isomeric state simulations of network chain configurations. II. Bimodal poly(dimethylsiloxane) networks

    International Nuclear Information System (INIS)

    Curro, J.G.; Mark, J.E.

    1984-01-01

    Bimodal, poly(dimethylsiloxane) (PDMS) networks containing a large mole fraction of very short chains have been shown to be unusually tough elastomers. The purpose of this investigation is to understand the rubber elasticity behavior of these bimodal networks. As a first approach, we have assumed that the average chain deformation is affine. This deformation, however, is partitioned nonaffinely between the long and short chains so that the free energy is minimized. Gaussian statistics are used for the long chains. The distribution function for the short chains is found from Monte Carlo calculations. This model predicts an upturn in the stress-strain curve, the steepness depending on the network composition, as is observed experimentally

  18. From ‘Post-Industrial’ to ‘Network Society’ and Beyond: The Political Conjunctures and Current Crisis of Information Society Theory

    Directory of Open Access Journals (Sweden)

    Marko Ampuja

    2014-07-01

    Full Text Available This article critically discusses the intellectual and conceptual shifts that have occurred in information society theories (and also policies in the previous four decades. We will examine the topic by focusing on the work of Daniel Bell and Manuel Castells, arguably two of the most important information society theorists. A key element in the academic shift from “post-industrial” (Bell thinking to the discourse on “network society” (Castells is that it has brought forward a different way of understanding the role of the state vis-a-vis the development of new information and communication technologies, as well as a new assessment of the role of the state in the economy and society at large. Against the Keynesian undertones of Bell’s ideas, Castells’ network society theory represents a neoliberally restructured version of “information society” that is associated with the rise of flexibility, individuality and a new culture of innovation. We argue that these changing discourses on the information society have served a definite hegemonic function for political elites, offering useful ideals and conceptions for forming politics and political compromises in different historical conjunctures. We conclude the article by looking at how the on-going global economic crisis and neoliberalism’s weakening hegemonic potential and turn to austerity and authoritarian solutions challenges existing information society theories.

  19. Theorizing "Lay Theories of Media": A Case Study of the Dissent! Network at the 2005 Gleneagles G8 Summit

    NARCIS (Netherlands)

    P. McCurdy (Patrick)

    2011-01-01

    textabstractDrawing on "active audience studies" and recent theories of mediation, the concept of "lay theories of media" is proposed as a means to understand how social movement actors think about and interact with news media as part of the "practice" of activism. The argument is made via a case

  20. Innovation, Product Development, and New Business Models in Networks: How to come from case studies to a valid and operational theory

    DEFF Research Database (Denmark)

    Rasmussen, Erik Stavnsager; Jørgensen, Jacob Høj; Goduscheit, René Chester

    2007-01-01

    We have in the research project NEWGIBM (New Global ICT based Business Models) during 2005 and 2006 closely cooperated with a group of firms. The focus in the project has been development of new business models (and innovation) in close cooperation with multiple partners. These partners have been...... customers, suppliers, R&D partners, and others. The methodological problem is thus, how to come from e.g. one in-depth case study to a more formalized theory or model on how firms can develop new projects and be innovative in a network. The paper is structured so that it starts with a short presentation...... of the two key concepts in our research setting and theoretical models: Innovation and networks. It is not our intention in this paper to present a lengthy discussion of the two concepts, but a short presentation is necessary to understand the validity and interpretation discussion later in the paper. Next...

  1. Structure and stability of acrolein and allyl alcohol networks on Ag(111) from density functional theory based calculations with dispersion corrections

    Science.gov (United States)

    Ferullo, Ricardo M.; Branda, Maria Marta; Illas, Francesc

    2013-11-01

    The interaction of acrolein and allyl alcohol with the Ag(111) surface has been studied by means of periodic density functional theory based calculations including explicitly dispersion terms. Different coverage values have been explored going from isolated adsorbed molecules to isolated dimers, interacting dimers or ordered overlayers. The inclusion of the dispersion terms largely affects the calculated values of the adsorption energy and also the distance between adsorbed molecule and the metallic surface but much less the adsorbate-adsorbate interactions. Owing to the large dipole moment of acrolein, the present calculations predict that at high coverage this molecule forms a stable extensive two-dimensional network on the surface, caused by the alignment of the adsorbate dipoles. For the case of allyl alcohol, dimers and complex networks exhibit similar stability.

  2. A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

    Science.gov (United States)

    Russo, Lucia; Russo, Paola; Siettos, Constantinos I

    2016-01-01

    Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.

  3. A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

    Directory of Open Access Journals (Sweden)

    Lucia Russo

    Full Text Available Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a an artificial forest of randomly distributed density of vegetation, and (b a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.

  4. Research on investment decisions model of trans-regional transmission network based on the theory of NPV

    Science.gov (United States)

    Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

    2018-02-01

    The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

  5. Unifying Pore Network Modeling, Continuous Time Random Walk (CTRW) Theory and Experiment to Describe Impact of Spatial Heterogeneities on Solute Dispersion at Multiple Length-scales

    Science.gov (United States)

    Bijeljic, B.; Blunt, M. J.; Rhodes, M. E.

    2009-04-01

    This talk will describe and highlight the advantages offered by a novel methodology that unifies pore network modeling, CTRW theory and experiment in description of solute dispersion in porous media. Solute transport in a porous medium is characterized by the interplay of advection and diffusion (described by Peclet number, Pe) that cause dispersion of solute particles. Dispersion is traditionally described by dispersion coefficients, D, that are commonly calculated from the spatial moments of the plume. Using a pore-scale network model based on particle tracking, the rich Peclet-number dependence of dispersion coefficient is predicted from first principles and is shown to compare well with experimental data for restricted diffusion, transition, power-law and mechanical dispersion regimes in the asymptotic limit. In the asymptotic limit D is constant and can be used in an averaged advection-dispersion equation. However, it is highly important to recognize that, until the velocity field is fully sampled, the particle transport is non-Gaussian and D possesses temporal or spatial variation. Furthermore, temporal probability density functions (PDF) of tracer particles are studied in pore networks and an excellent agreement for the spectrum of transition times for particles from pore to pore is obtained between network model results and CTRW theory. Based on the truncated power-law interpretation of PDF-s, the physical origin of the power-law scaling of dispersion coefficient vs. Peclet number has been explained for unconsolidated porous media, sands and a number of sandstones, arriving at the same conclusion from numerical network modelling, analytic CTRW theory and experiment. The length traveled by solute plumes before Gaussian behaviour is reached increases with an increase in heterogeneity and/or Pe. This opens up the question on the nature of dispersion in natural systems where the heterogeneities at the larger scales will significantly increase the range of

  6. Graph theory

    CERN Document Server

    Gould, Ronald

    2012-01-01

    This introduction to graph theory focuses on well-established topics, covering primary techniques and including both algorithmic and theoretical problems. The algorithms are presented with a minimum of advanced data structures and programming details. This thoroughly corrected 1988 edition provides insights to computer scientists as well as advanced undergraduates and graduate students of topology, algebra, and matrix theory. Fundamental concepts and notation and elementary properties and operations are the first subjects, followed by examinations of paths and searching, trees, and networks. S

  7. Studying Dynamics in Business Networks

    DEFF Research Database (Denmark)

    Andersen, Poul Houman; Anderson, Helen; Havila, Virpi

    1998-01-01

    This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...

  8. The Economics of Networking

    DEFF Research Database (Denmark)

    Sørensen, Olav Jull

    The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory.......The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory....

  9. Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data-fusion technique

    International Nuclear Information System (INIS)

    Hou Zhijian; Lian Zhiwei; Yao Ye; Yuan Xinjian

    2006-01-01

    A novel method integrating rough sets (RS) theory and an artificial neural network (ANN) based on data-fusion technique is presented to forecast an air-conditioning load. Data-fusion technique is the process of combining multiple sensors data or related information to estimate or predict entity states. In this paper, RS theory is applied to find relevant factors to the load, which are used as inputs of an artificial neural-network to predict the cooling load. To improve the accuracy and enhance the robustness of load forecasting results, a general load-prediction model, by synthesizing multi-RSAN (MRAN), is presented so as to make full use of redundant information. The optimum principle is employed to deduce the weights of each RSAN model. Actual prediction results from a real air-conditioning system show that, the MRAN forecasting model is better than the individual RSAN and moving average (AMIMA) ones, whose relative error is within 4%. In addition, individual RSAN forecasting results are better than that of ARIMA

  10. Actor-network theory (ANT: uma tradução para compreender o relacional e o estrutural nas redes interorganizacionais?

    Directory of Open Access Journals (Sweden)

    Jackeline Amantino-de-Andrade

    Full Text Available Este ensaio propõe abordar a actor-network theory na análise relacional de redes interorganizacionais, considerando que outras abordagens apresentam limitações, por sustentarem uma divisão entre estrutura e agência. Para consubstanciar essa proposição, primeiramente, é apresentada uma revisão das abordagens de rede nas ciências sociais e, especificamente, nos estudos organizacionais, procurando demonstrar suas distinções, suas inter-relações e sua comum limitação ao se apoiar no estrutural em detrimento do relacional. Em seguida, é apresentada a actor-network theory, com destaque para sua capacidade de integrar o relacional e o estrutural na compreensão dos fenômenos de ordenação; procurando também se evidenciar as aplicações verificadas no campo dos estudos organizacionais. Finalmente, são consideradas as críticas a essa abordagem, ressaltando a diferença de pressupostos, bem como a sua capacidade de trazer contribuições para questões ainda não completamente respondidas, principalmente, quando considerados os fenômenos interorganizacionais.

  11. Uncertainty theory

    CERN Document Server

    Liu, Baoding

    2015-01-01

    When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...

  12. Matching theory

    CERN Document Server

    Plummer, MD

    1986-01-01

    This study of matching theory deals with bipartite matching, network flows, and presents fundamental results for the non-bipartite case. It goes on to study elementary bipartite graphs and elementary graphs in general. Further discussed are 2-matchings, general matching problems as linear programs, the Edmonds Matching Algorithm (and other algorithmic approaches), f-factors and vertex packing.

  13. PPP-RTK by means of S-system theory: revisiting the undifferenced, uncombined network model and a case study

    Science.gov (United States)

    Zhang, Baocheng; Yuan, Yunbin

    2017-04-01

    A synthesis of two prevailing Global Navigation Satellite System (GNSS) positioning technologies, namely the precise point positioning (PPP) and the network-based real-time kinematic (NRTK), results in the emergence of the PPP-RTK. This new concept preferably integrates the typical advantage of PPP (e.g. flexibility) and that of NRTK (e.g. efficiency), such that it enables single-receiver users to achieve high positioning accuracy with reasonable timeliness through integer ambiguity resolution (IAR). The realization of PPP-RTK needs to accomplish two sequential tasks. The first task is to determine a class of corrections including, necessarily, the satellite orbits, the satellite clocks and the satellite phase (and code, in case of more than two frequencies) biases at the network level. With these corrections, the second task, then, is capable of solving for the ambiguity-fixed, absolute position(s) at the user level. In this contribution, we revisit three variants (geometry-free, geometry-fixed, and geometry- and satellite-clock-fixed) of undifferenced, uncombined PPP-RTK network model and discuss their implications for practical use. We carry out a case study using multi-day, dual-frequency GPS data from the Crustal Movement Observation Network of China (CMONOC), aiming to assess the (static and kinematic) positioning performance (in terms of time-to-first-fix and accuracy) that is achievable by PPP-RTK users across China.

  14. A Process Perspective on Regulation: A Grounded Theory Study into Regulatory Practice in Newly Liberalized Network-Based Markets

    NARCIS (Netherlands)

    Ubacht, J.

    The transition from a former monopolistic towards a more competitive market in
    newly liberalized network-based markets raises regulatory issues. National Regulatory Authorities (NRA) face the challenge to deal with these issues in order to guide the transition process. Although this transition

  15. A Fast Reactive Power Optimization in Distribution Network Based on Large Random Matrix Theory and Data Analysis

    Directory of Open Access Journals (Sweden)

    Wanxing Sheng

    2016-05-01

    Full Text Available In this paper, a reactive power optimization method based on historical data is investigated to solve the dynamic reactive power optimization problem in distribution network. In order to reflect the variation of loads, network loads are represented in a form of random matrix. Load similarity (LS is defined to measure the degree of similarity between the loads in different days and the calculation method of the load similarity of load random matrix (LRM is presented. By calculating the load similarity between the forecasting random matrix and the random matrix of historical load, the historical reactive power optimization dispatching scheme that most matches the forecasting load can be found for reactive power control usage. The differences of daily load curves between working days and weekends in different seasons are considered in the proposed method. The proposed method is tested on a standard 14 nodes distribution network with three different types of load. The computational result demonstrates that the proposed method for reactive power optimization is fast, feasible and effective in distribution network.

  16. How network-based incubation helps start-up performance : a systematic review against the background of management theories

    NARCIS (Netherlands)

    Eveleens, Chris P.|info:eu-repo/dai/nl/369284704; van Rijnsoever, Frank J.|info:eu-repo/dai/nl/314100334; Niesten, Eva M M I

    2017-01-01

    The literature on how network-based incubation influences the performance of technology-based start-ups has recently grown considerably and provided valuable insights. However, at the same time this literature has become quite fragmented, inconsistently conceptualised, and theoretically

  17. Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

    Science.gov (United States)

    Lee, Ki Jung

    2013-01-01

    Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

  18. MySpace and Facebook: applying the uses and gratifications theory to exploring friend-networking sites.

    Science.gov (United States)

    Raacke, John; Bonds-Raacke, Jennifer

    2008-04-01

    The increased use of the Internet as a new tool in communication has changed the way people interact. This fact is even more evident in the recent development and use of friend-networking sites. However, no research has evaluated these sites and their impact on college students. Therefore, the present study was conducted to evaluate: (a) why people use these friend-networking sites, (b) what the characteristics are of the typical college user, and (c) what uses and gratifications are met by using these sites. Results indicated that the vast majority of college students are using these friend-networking sites for a significant portion of their day for reasons such as making new friends and locating old friends. Additionally, both men and women of traditional college age are equally engaging in this form of online communication with this result holding true for nearly all ethnic groups. Finally, results showed that many uses and gratifications are met by users (e.g., "keeping in touch with friends"). Results are discussed in light of the impact that friend-networking sites have on communication and social needs of college students.

  19. Insights into Intrinsic Brain Networks based on Graph Theory and PET in right- compared to left-sided Temporal Lobe Epilepsy.

    Science.gov (United States)

    Vanicek, Thomas; Hahn, Andreas; Traub-Weidinger, Tatjana; Hilger, Eva; Spies, Marie; Wadsak, Wolfgang; Lanzenberger, Rupert; Pataraia, Ekaterina; Asenbaum-Nan, Susanne

    2016-06-28

    The human brain exhibits marked hemispheric differences, though it is not fully understood to what extent lateralization of the epileptic focus is relevant. Preoperative [(18)F]FDG-PET depicts lateralization of seizure focus in patients with temporal lobe epilepsy and reveals dysfunctional metabolic brain connectivity. The aim of the present study was to compare metabolic connectivity, inferred from inter-regional [(18)F]FDG PET uptake correlations, in right-sided (RTLE; n = 30) and left-sided TLE (LTLE; n = 32) with healthy controls (HC; n = 31) using graph theory based network analysis. Comparing LTLE and RTLE and patient groups separately to HC, we observed higher lobar connectivity weights in RTLE compared to LTLE for connections of the temporal and the parietal lobe of the contralateral hemisphere (CH). Moreover, especially in RTLE compared to LTLE higher local efficiency were found in the temporal cortices and other brain regions of the CH. The results of this investigation implicate altered metabolic networks in patients with TLE specific to the lateralization of seizure focus, and describe compensatory mechanisms especially in the CH of patients with RTLE. We propose that graph theoretical analysis of metabolic connectivity using [(18)F]FDG-PET offers an important additional modality to explore brain networks.

  20. Behavioral and multimodal neuroimaging evidence for a deficit in brain timing networks in stuttering: A hypothesis and theory

    Directory of Open Access Journals (Sweden)

    Andrew C Etchell

    2014-06-01

    Full Text Available The fluent production of speech requires accurately timed movements. In this article, we propose that a deficit in brain timing networks is the core neurophysiological deficit in stuttering. We first discuss the experimental evidence supporting the involvement of the basal ganglia and supplementary motor area in stuttering and the involvement of the cerebellum as a mechanism for compensating for the neural deficits that underlie stuttering. Next, we outline the involvement of the right inferior frontal gyrus as another putative compensatory locus in stuttering and suggest a role for this structure in an expanded core timing-network. Subsequently, we review behavioral studies of timing in people who stutter and examine their behavioral performance as compared to people who do not stutter. Finally, we highlight challenges to existing research and provide avenues for future research with specific hypotheses.

  1. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks

    OpenAIRE

    Wang, Yongqiang; Nunez, Felipe; Doyle III, Francis J.

    2012-01-01

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is incr...

  2. A statistical mechanical theory of proton transport kinetics in hydrogen-bonded networks based on population correlation functions with applications to acids and bases.

    Science.gov (United States)

    Tuckerman, Mark E; Chandra, Amalendu; Marx, Dominik

    2010-09-28

    Extraction of relaxation times, lifetimes, and rates associated with the transport of topological charge defects in hydrogen-bonded networks from molecular dynamics simulations is a challenge because proton transfer reactions continually change the identity of the defect core. In this paper, we present a statistical mechanical theory that allows these quantities to be computed in an unbiased manner. The theory employs a set of suitably defined indicator or population functions for locating a defect structure and their associated correlation functions. These functions are then used to develop a chemical master equation framework from which the rates and lifetimes can be determined. Furthermore, we develop an integral equation formalism for connecting various types of population correlation functions and derive an iterative solution to the equation, which is given a graphical interpretation. The chemical master equation framework is applied to the problems of both hydronium and hydroxide transport in bulk water. For each case it is shown that the theory establishes direct links between the defect's dominant solvation structures, the kinetics of charge transfer, and the mechanism of structural diffusion. A detailed analysis is presented for aqueous hydroxide, examining both reorientational time scales and relaxation of the rotational anisotropy, which is correlated with recent experimental results for these quantities. Finally, for OH(-)(aq) it is demonstrated that the "dynamical hypercoordination mechanism" is consistent with available experimental data while other mechanistic proposals are shown to fail. As a means of going beyond the linear rate theory valid from short up to intermediate time scales, a fractional kinetic model is introduced in the Appendix in order to describe the nonexponential long-time behavior of time-correlation functions. Within the mathematical framework of fractional calculus the power law decay ∼t(-σ), where σ is a parameter of the

  3. Performative studies in the actor-network theory (“technological performativity” in works of G. Kien

    Directory of Open Access Journals (Sweden)

    E A Goryacheva

    2013-12-01

    Full Text Available The article considers some theoretical and methodological prerequisites of shaping the concept of «technological performativity» in the works of modern researcher G. Kien whose approach can be characterized as interdisciplinary. Among the numerous existing preconditions of this concept, the author focuses primarily on G. Austin`s theory of speech acts, as well as G. Butler`s gender studies.

  4. A robust cooperative spectrum sensing scheme based on Dempster-Shafer theory and trustworthiness degree calculation in cognitive radio networks

    Science.gov (United States)

    Wang, Jinlong; Feng, Shuo; Wu, Qihui; Zheng, Xueqiang; Xu, Yuhua; Ding, Guoru

    2014-12-01

    Cognitive radio (CR) is a promising technology that brings about remarkable improvement in spectrum utilization. To tackle the hidden terminal problem, cooperative spectrum sensing (CSS) which benefits from the spatial diversity has been studied extensively. Since CSS is vulnerable to the attacks initiated by malicious secondary users (SUs), several secure CSS schemes based on Dempster-Shafer theory have been proposed. However, the existing works only utilize the current difference of SUs, such as the difference in SNR or similarity degree, to evaluate the trustworthiness of each SU. As the current difference is only one-sided and sometimes inaccurate, the statistical information contained in each SU's historical behavior should not be overlooked. In this article, we propose a robust CSS scheme based on Dempster-Shafer theory and trustworthiness degree calculation. It is carried out in four successive steps, which are basic probability assignment (BPA), trustworthiness degree calculation, selection and adjustment of BPA, and combination by Dempster-Shafer rule, respectively. Our proposed scheme evaluates the trustworthiness degree of SUs from both current difference aspect and historical behavior aspect and exploits Dempster-Shafer theory's potential to establish a `soft update' approach for the reputation value maintenance. It can not only differentiate malicious SUs from honest ones based on their historical behaviors but also reserve the current difference for each SU to achieve a better real-time performance. Abundant simulation results have validated that the proposed scheme outperforms the existing ones under the impact of different attack patterns and different number of malicious SUs.

  5. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks.

    Science.gov (United States)

    Wang, Yongqiang; Núñez, Felipe; Doyle, Francis J

    2012-07-25

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is increased even under a fixed transmission power. Given that energy consumption in synchronization is determined by the product of synchronization time and transformation power, the new strategy reduces energy consumption in clock synchronization. QualNet experiments confirm the theoretical results.

  6. The Use of Comprehensive Molecular Profiling with Network and Control Theory to Better Understand GWI and Model Therapeutic Strategies

    Science.gov (United States)

    2011-07-01

    in chronic fatigue syndrome. J Chronic Fatigue syndrome, 1:23-42, 1995 102. Von Roenn JH, Armstrong D, Kotler DP, Cohn DL, Klimas NG, Tchekmedyian...of similar size and order. For any network with order, N, and normalized principle eigenvector, bX (with a maxi- mum component, xmax = max[xi]), a...prevent the degradation of GLP-1 [42], are now marketed for the treatment of type 2 diabetes mellitus (T2DM). Considering that DPPIV/CD26 has a key role

  7. Identity theory and personality theory: mutual relevance.

    Science.gov (United States)

    Stryker, Sheldon

    2007-12-01

    Some personality psychologists have found a structural symbolic interactionist frame and identity theory relevant to their work. This frame and theory, developed in sociology, are first reviewed. Emphasized in the review are a multiple identity conception of self, identities as internalized expectations derived from roles embedded in organized networks of social interaction, and a view of social structures as facilitators in bringing people into networks or constraints in keeping them out, subsequently, attention turns to a discussion of the mutual relevance of structural symbolic interactionism/identity theory and personality theory, looking to extensions of the current literature on these topics.

  8. Theory of mind mediates the prospective relationship between abnormal social brain network morphology and chronic behavior problems after pediatric traumatic brain injury.

    Science.gov (United States)

    Ryan, Nicholas P; Catroppa, Cathy; Beare, Richard; Silk, Timothy J; Crossley, Louise; Beauchamp, Miriam H; Yeates, Keith Owen; Anderson, Vicki A

    2016-04-01

    Childhood and adolescence coincide with rapid maturation and synaptic reorganization of distributed neural networks that underlie complex cognitive-affective behaviors. These regions, referred to collectively as the 'social brain network' (SBN) are commonly vulnerable to disruption from pediatric traumatic brain injury (TBI); however, the mechanisms that link morphological changes in the SBN to behavior problems in this population remain unclear. In 98 children and adolescents with mild to severe TBI, we acquired 3D T1-weighted MRIs at 2-8 weeks post-injury. For comparison, 33 typically developing controls of similar age, sex and education were scanned. All participants were assessed on measures of Theory of Mind (ToM) at 6 months post-injury and parents provided ratings of behavior problems at 24-months post-injury. Severe TBI was associated with volumetric reductions in the overall SBN package, as well as regional gray matter structural change in multiple component regions of the SBN. When compared with TD controls and children with milder injuries, the severe TBI group had significantly poorer ToM, which was associated with more frequent behavior problems and abnormal SBN morphology. Mediation analysis indicated that impaired theory of mind mediated the prospective relationship between abnormal SBN morphology and more frequent chronic behavior problems. Our findings suggest that sub-acute alterations in SBN morphology indirectly contribute to long-term behavior problems via their influence on ToM. Volumetric change in the SBN and its putative hub regions may represent useful imaging biomarkers for prediction of post-acute social cognitive impairment, which may in turn elevate risk for chronic behavior problems. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  9. The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

    Science.gov (United States)

    Li, Man; Wang, Yanhui; Jia, Limin

    2017-01-01

    Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

  10. Dynamic Traffic Congestion Simulation and Dissipation Control Based on Traffic Flow Theory Model and Neural Network Data Calibration Algorithm

    Directory of Open Access Journals (Sweden)

    Li Wang

    2017-01-01

    Full Text Available Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole.

  11. The modeling of attraction characteristics regarding passenger flow in urban rail transit network based on field theory.

    Directory of Open Access Journals (Sweden)

    Man Li

    Full Text Available Aimed at the complicated problems of attraction characteristics regarding passenger flow in urban rail transit network, the concept of the gravity field of passenger flow is proposed in this paper. We establish the computation methods of field strength and potential energy to reveal the potential attraction relationship among stations from the perspective of the collection and distribution of passenger flow and the topology of network. As for the computation methods of field strength, an optimum path concept is proposed to define betweenness centrality parameter. Regarding the computation of potential energy, Compound Simpson's Rule Formula is applied to get a solution to the function. Taking No. 10 Beijing Subway as a practical example, an analysis of simulation and verification is conducted, and the results shows in the following ways. Firstly, the bigger field strength value between two stations is, the stronger passenger flow attraction is, and the greater probability of the formation of the largest passenger flow of section is. Secondly, there is the greatest passenger flow volume and circulation capacity between two zones of high potential energy.

  12. The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures

    International Nuclear Information System (INIS)

    Eusgeld, Irene; Kroeger, Wolfgang; Sansavini, Giovanni; Schlaepfer, Markus; Zio, Enrico

    2009-01-01

    A framework for the analysis of the vulnerability of critical infrastructures has been proposed by some of the authors. The framework basically consists of two successive stages: (i) a screening analysis for identifying the parts of the critical infrastructure most relevant with respect to its vulnerability and (ii) a detailed modeling of the operational dynamics of the identified parts for gaining insights on the causes and mechanisms responsible for the vulnerability. In this paper, a critical presentation is offered of the results of a set of investigations aimed at evaluating the potentials of (i) using network analysis based on measures of topological interconnection and reliability efficiency, for the screening task; (ii) using object-oriented modeling as the simulation framework to capture the detailed dynamics of the operational scenarios involving the most vulnerable parts of the critical infrastructure as identified by the preceding network analysis. A case study based on the Swiss high-voltage transmission system is considered. The results are cross-compared and evaluated; the needs of further research are defined

  13. A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

    Science.gov (United States)

    Ji, Xuewu; He, Xiangkun; Lv, Chen; Liu, Yahui; Wu, Jian

    2018-06-01

    Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.

  14. On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of $mathcal {S}$ S -system theory

    Science.gov (United States)

    Odijk, Dennis; Zhang, Baocheng; Khodabandeh, Amir; Odolinski, Robert; Teunissen, Peter J. G.

    2016-01-01

    The concept of integer ambiguity resolution-enabled Precise Point Positioning (PPP-RTK) relies on appropriate network information for the parameters that are common between the single-receiver user that applies and the network that provides this information. Most of the current methods for PPP-RTK are based on forming the ionosphere-free combination using dual-frequency Global Navigation Satellite System (GNSS) observations. These methods are therefore restrictive in the light of the development of new multi-frequency GNSS constellations, as well as from the point of view that the PPP-RTK user requires ionospheric corrections to obtain integer ambiguity resolution results based on short observation time spans. The method for PPP-RTK that is presented in this article does not have above limitations as it is based on the undifferenced, uncombined GNSS observation equations, thereby keeping all parameters in the model. Working with the undifferenced observation equations implies that the models are rank-deficient; not all parameters are unbiasedly estimable, but only combinations of them. By application of S-system theory the model is made of full rank by constraining a minimum set of parameters, or S-basis. The choice of this S-basis determines the estimability and the interpretation of the parameters that are transmitted to the PPP-RTK users. As this choice is not unique, one has to be very careful when comparing network solutions in different S-systems; in that case the S-transformation, which is provided by the S-system method, should be used to make the comparison. Knowing the estimability and interpretation of the parameters estimated by the network is shown to be crucial for a correct interpretation of the estimable PPP-RTK user parameters, among others the essential ambiguity parameters, which have the integer property which is clearly following from the interpretation of satellite phase biases from the network. The flexibility of the S-system method is

  15. Next Day Building Load Predictions based on Limited Input Features Using an On-Line Laterally Primed Adaptive Resonance Theory Artificial Neural Network.

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Photovoltaic and Grid Integration Group; Robinson, Matt [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering; Yasaei, Yasser [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Caudell, Thomas [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Martinez-Ramon, Manel [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering; Mammoli, Andrea [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Mechanical Engineering

    2016-07-01

    Optimal integration of thermal energy storage within commercial building applications requires accurate load predictions. Several methods exist that provide an estimate of a buildings future needs. Methods include component-based models and data-driven algorithms. This work implemented a previously untested algorithm for this application that is called a Laterally Primed Adaptive Resonance Theory (LAPART) artificial neural network (ANN). The LAPART algorithm provided accurate results over a two month period where minimal historical data and a small amount of input types were available. These results are significant, because common practice has often overlooked the implementation of an ANN. ANN have often been perceived to be too complex and require large amounts of data to provide accurate results. The LAPART neural network was implemented in an on-line learning manner. On-line learning refers to the continuous updating of training data as time occurs. For this experiment, training began with a singe day and grew to two months of data. This approach provides a platform for immediate implementation that requires minimal time and effort. The results from the LAPART algorithm were compared with statistical regression and a component-based model. The comparison was based on the predictions linear relationship with the measured data, mean squared error, mean bias error, and cost savings achieved by the respective prediction techniques. The results show that the LAPART algorithm provided a reliable and cost effective means to predict the building load for the next day.

  16. Blowing against the wind-An exploratory application of actor network theory to the analysis of local controversies and participation processes in wind energy

    International Nuclear Information System (INIS)

    Jolivet, Eric; Heiskanen, Eva

    2010-01-01

    This paper analyses the deployment of wind power and the related local controversies using actor-network theory (ANT). ANT provides conceptual instruments for a fine-tuned analysis of the contingencies that condition a project's success or failure by focusing on the micro-decisions that intertwine the material aspects of the technology, the site where it is implemented, the participation process, and the social relations in which they are embedded. By considering controversies as alternative efforts of competing networks of actors to 'frame' the reality and enroll others, ANT sheds light on the complex and political nature of planning a wind farm project, insofar as it consist in aligning material and human behaviours into a predictable scenario. 'Overflows' occur when actors do not conform to expectations, adopt conflicting positions and develop their own interpretations of the project, thus obliging designers to adapt their frames and change their plans. To demonstrate this framework, we apply it to the case of a wind farm project in the South of France, near Albi. Our analysis suggests a new approach to examining wind power projects in terms of the interaction between globally circulating technologies, unique characteristics of the site, the participation process and the social dynamics that emerge when these are combined.

  17. Think about and intervene in the territory through the Actor Network Theory Pensar e intervenir el territorio a traves de la Teoria del Actor-Red

    Directory of Open Access Journals (Sweden)

    Juan E. Cabrera

    2011-03-01

    Full Text Available The purpose of this article is to think about the similarities between the ways of seeing the territory as a network, some theoretical positions about the territory concept and actor network theory.
    After focusing on proposing a way of understanding the relationships between actors when they will intervene in the territory through the public policies and territorial planning, i ll try to apply the ANT model of public policy management through the guidance of ANT El propósito de este artículo es reflexionar sobre las coincidencias entre la forma de ver el territorio como red, algunas posturas teóricas sobre su concepto y la teoría del actor-red.
    Sobre lo anterior se centra en proponer una forma de entender las relaciones entre actores cuando se va a intervenir el territorio a través de políticas públicas como la planificación utilizando un modelo de gestión territorial a través de las orientaciones de la TAR.   

  18. TV programme presentations: Bang Goes the Theory by BBC (2010) and Beyond the Atom with John Ellis by Redes and Science Networks (2010)

    CERN Document Server

    Carolyn Lee

    2011-01-01

    BBC’s Bang Goes the Theory explores various aspects of science. In this episode, presenter Dallas Campbell travels to CERN to meet physicist Tara Shears and learn more about antimatter. Other topics include breath-holding techniques such as free diving, and what exactly is horsepower and how is it measured? In addition, Redes and Science Networks have produced "Beyond the Atom with John Ellis", a TV programme presented by Eduard Punset and featuring CERN theorist John Ellis. The aim of this programme is to understand more about what matter is and what the physicists working on the LHC experiments hope to discover, including the Higgs boson, dark matter and supersymmetry. This programme is in English and Spanish with English subtitles. Bang Goes the Theory will be presented on Friday 11 March from 13:00 to 13:30 Language: English Beyond the Atom with John Ellis will be presented on Friday 11 March from 13:30 to 14:00 Language: English and Spanish with English subtitles Both will be...

  19. Classification of Incomplete Data Based on Evidence Theory and an Extreme Learning Machine in Wireless Sensor Networks.

    Science.gov (United States)

    Zhang, Yang; Liu, Yun; Chao, Han-Chieh; Zhang, Zhenjiang; Zhang, Zhiyuan

    2018-03-30

    In wireless sensor networks, the classification of incomplete data reported by sensor nodes is an open issue because it is difficult to accurately estimate the missing values. In many cases, the misclassification is unacceptable considering that it probably brings catastrophic damages to the data users. In this paper, a novel classification approach of incomplete data is proposed to reduce the misclassification errors. This method uses the regularized extreme learning machine to estimate the potential values of missing data at first, and then it converts the estimations into multiple classification results on the basis of the distance between interval numbers. Finally, an evidential reasoning rule is adopted to fuse these classification results. The final decision is made according to the combined basic belief assignment. The experimental results show that this method has better performance than other traditional classification methods of incomplete data.

  20. Real-Time Support on IEEE 802.11 Wireless Ad-Hoc Networks: Reality vs. Theory

    Science.gov (United States)

    Kang, Mikyung; Kang, Dong-In; Suh, Jinwoo

    The usable throughput of an IEEE 802.11 system for an application is much less than the raw bandwidth. Although 802.11b has a theoretical maximum of 11Mbps, more than half of the bandwidth is consumed by overhead leaving at most 5Mbps of usable bandwidth. Considering this characteristic, this paper proposes and analyzes a real-time distributed scheduling scheme based on the existing IEEE 802.11 wireless ad-hoc networks, using USC/ISI's Power Aware Sensing Tracking and Analysis (PASTA) hardware platform. We compared the distributed real-time scheduling scheme with the real-time polling scheme to meet deadline, and compared a measured real bandwidth with a theoretical result. The theoretical and experimental results show that the distributed scheduling scheme can guarantee real-time traffic and enhances the performance up to 74% compared with polling scheme.

  1. Neural network modelling and dynamical system theory: are they relevant to study the governing dynamics of association football players?

    Science.gov (United States)

    Dutt-Mazumder, Aviroop; Button, Chris; Robins, Anthony; Bartlett, Roger

    2011-12-01

    Recent studies have explored the organization of player movements in team sports using a range of statistical tools. However, the factors that best explain the performance of association football teams remain elusive. Arguably, this is due to the high-dimensional behavioural outputs that illustrate the complex, evolving configurations typical of team games. According to dynamical system analysts, movement patterns in team sports exhibit nonlinear self-organizing features. Nonlinear processing tools (i.e. Artificial Neural Networks; ANNs) are becoming increasingly popular to investigate the coordination of participants in sports competitions. ANNs are well suited to describing high-dimensional data sets with nonlinear attributes, however, limited information concerning the processes required to apply ANNs exists. This review investigates the relative value of various ANN learning approaches used in sports performance analysis of team sports focusing on potential applications for association football. Sixty-two research sources were summarized and reviewed from electronic literature search engines such as SPORTDiscus, Google Scholar, IEEE Xplore, Scirus, ScienceDirect and Elsevier. Typical ANN learning algorithms can be adapted to perform pattern recognition and pattern classification. Particularly, dimensionality reduction by a Kohonen feature map (KFM) can compress chaotic high-dimensional datasets into low-dimensional relevant information. Such information would be useful for developing effective training drills that should enhance self-organizing coordination among players. We conclude that ANN-based qualitative analysis is a promising approach to understand the dynamical attributes of association football players.

  2. Research on Risk Evaluation of Transnational Power Networking Projects Based on the Matter-Element Extension Theory and Granular Computing

    Directory of Open Access Journals (Sweden)

    Jinying Li

    2017-10-01

    Full Text Available In project management, risk assessment is crucial for stakeholders to identify the risk factors during the whole life cycle of the project. A risk evaluation index system of a transnational networking project, which provides an effective way for the grid integration of clean electricity and the sustainable development of the power industry, is constructed in this paper. Meanwhile, a combination of granular computing and order relation analysis (G1 method is applied to determine the weight of each indicator and the matter-element extension evaluation model is also employed to seek the global optimal decision during the risk assessment. Finally, a case study is given to validate the index system and evaluation model established in this paper by assessing two different investment schemes of a transnational high voltage direct current (HVDC transmission project. The result shows that the comprehensive risk level of Scheme 1 is “Low” and the level of Scheme 2 is “General”, which means Scheme 1 is better for the stakeholders from the angle of risk control. The main practical significance of this paper lies in that it can provide a reference and decision support for the government’s power sectors, investment companies and other stakeholders when carrying out related activities.

  3. Networking for big data

    CERN Document Server

    Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

    2015-01-01

    Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

  4. Further Evidence for the Impact of a Genome-Wide-Supported Psychosis Risk Variant in ZNF804A on the Theory of Mind Network

    Science.gov (United States)

    Mohnke, Sebastian; Erk, Susanne; Schnell, Knut; Schütz, Claudia; Romanczuk-Seiferth, Nina; Grimm, Oliver; Haddad, Leila; Pöhland, Lydia; Garbusow, Maria; Schmitgen, Mike M; Kirsch, Peter; Esslinger, Christine; Rietschel, Marcella; Witt, Stephanie H; Nöthen, Markus M; Cichon, Sven; Mattheisen, Manuel; Mühleisen, Thomas; Jensen, Jimmy; Schott, Björn H; Maier, Wolfgang; Heinz, Andreas; Meyer-Lindenberg, Andreas; Walter, Henrik

    2014-01-01

    The single-nucleotide polymorphism (SNP) rs1344706 in ZNF804A is one of the best-supported risk variants for psychosis. We hypothesized that this SNP contributes to the development of schizophrenia by affecting the ability to understand other people's mental states. This skill, commonly referred to as Theory of Mind (ToM), has consistently been found to be impaired in schizophrenia. Using functional magnetic resonance imaging, we previously showed that in healthy individuals rs1344706 impacted on activity and connectivity of key areas of the ToM network, including the dorsomedial prefrontal cortex, temporo-parietal junction, and the posterior cingulate cortex, which show aberrant activity in schizophrenia patients, too. We aimed to replicate these results in an independent sample of 188 healthy German volunteers. In order to assess the reliability of brain activity elicited by the ToM task, 25 participants performed the task twice with an interval of 14 days showing excellent accordance in recruitment of key ToM areas. Confirming our previous results, we observed decreasing activity of the left temporo-parietal junction, dorsomedial prefrontal cortex, and the posterior cingulate cortex with increasing number of risk alleles during ToM. Complementing our replication sample with the discovery sample, analyzed in a previous report (total N=297), further revealed negative genotype effects in the left dorsomedial prefrontal cortex as well as in the temporal and parietal regions. In addition, as shown previously, rs1344706 risk allele dose positively predicted increased frontal–temporo-parietal connectivity. These findings confirm the effects of the psychosis risk variant in ZNF804A on the dysfunction of the ToM network. PMID:24247043

  5. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

    of CoPs we shall argue that the metaphor or theory of networked learning is itself confronted with some central tensions and challenges that need to be addressed. We then explore these theoretical and analytic challenges to the network metaphor, through an analysis of a Danish social networking site. We......In this article we take up a critique of the concept of Communities of Practice (CoP) voiced by several authors, who suggest that networks may provide a better metaphor to understand social forms of organisation and learning. Through a discussion of the notion of networked learning and the critique...... argue that understanding meaning-making and ‘networked identities’ may be relevant analytic entry points in navigating the challenges....

  6. Design of Gravity Survey Network using Fractal Theory to Delineate Hydrocarbon bearing Jabera Structure, Vindhyan Basin, Central India

    Science.gov (United States)

    Dimri, V. P.; Srivastava, R. P.; Vedanti, N.

    2006-12-01

    A gravity survey network was designed using fractal dimension analysis to delineate a domal structure (Jabera dome) reported in southeastern part of the Vindhyan basin, Central India. This area is also regarded as a `high risk-high reward' frontier area for hydrocarbon exploration in previous studies, hence our aim was to delineate shape and lateral extent of the reported domal structure. Based on the synthetic grid, designed using the concept of fractal dimension, gravity data is collected in Jabera-Damoh area of Vindhyan basin. The collected data is random, but the data density is significant, hence the data points are sorted in a way so that they are close to the synthetic grid points of given grid interval. After sorting the data, again the fractal dimension analysis using box counting method has been carried out to avoid the aliasing in the data due to interpolation and also to know the optimum number of data points sufficient for desired quality of Bouguer anomaly maps. Optimization of number of stations takes care of time and cost involved in the survey and the detectibility limit ensures that the data collected is good enough to resolve the target body under study. The fractal dimension analysis gives clue to select these parameters. It showed that it is always preferable to have well distributed station locations instead of clustering the observation points at some geologically known feature because clustering of data points below required station spacing is not going to add much information where as equally distributed observation points add the information. The study area lies in a difficult terrain of Vindhayn basin, hence according to the accessibility, fractal dimension analysis of the real data sorted approximately at regular grid intervals on 2,3, and 4 km has been done and using the concept of optimum gridding interval Bouguer anomaly maps of the region are prepared. The preliminary depth values of the major interfaces in the area were obtained

  7. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  8. Green mobile networks a networking perspective

    CERN Document Server

    Ansari, Nirwan

    2016-01-01

    Combines the hot topics of energy efficiency and next generation mobile networking, examining techniques and solutions. Green communications is a very hot topic. Ever increasing mobile network bandwidth rates significantly impacts on operating costs due to aggregate network energy consumption. As such, design on 4G networks and beyond has increasingly started to focus on 'energy efficiency' or so-called 'green' networks. Many techniques and solutions have been proposed to enhance the energy efficiency of mobile networks, yet no book has provided an in-depth analysis of the energy consumption issues in mobile networks nor offers detailed theories, tools and solutions for solving the energy efficiency problems.

  9. Bayesian networks with examples in R

    CERN Document Server

    Scutari, Marco

    2014-01-01

    Introduction. The Discrete Case: Multinomial Bayesian Networks. The Continuous Case: Gaussian Bayesian Networks. More Complex Cases. Theory and Algorithms for Bayesian Networks. Real-World Applications of Bayesian Networks. Appendices. Bibliography.

  10. Improving access to health information for older migrants by using grounded theory and social network analysis to understand their information behaviour and digital technology use.

    Science.gov (United States)

    Goodall, K T; Newman, L A; Ward, P R

    2014-11-01

    Migrant well-being can be strongly influenced by the migration experience and subsequent degree of mainstream language acquisition. There is little research on how older Culturally And Linguistically Diverse (CALD) migrants who have 'aged in place' find health information, and the role which digital technology plays in this. Although the research for this paper was not focused on cancer, we draw out implications for providing cancer-related information to this group. We interviewed 54 participants (14 men and 40 women) aged 63-94 years, who were born in Italy or Greece, and who migrated to Australia mostly as young adults after World War II. Constructivist grounded theory and social network analysis were used for data analysis. Participants identified doctors, adult children, local television, spouse, local newspaper and radio as the most important information sources. They did not generally use computers, the Internet or mobile phones to access information. Literacy in their birth language, and the degree of proficiency in understanding and using English, influenced the range of information sources accessed and the means used. The ways in which older CALD migrants seek and access information has important implications for how professionals and policymakers deliver relevant information to them about cancer prevention, screening, support and treatment, particularly as information and resources are moved online as part of e-health. © 2014 John Wiley & Sons Ltd.

  11. Chain and network science: A research framework

    NARCIS (Netherlands)

    Omta, S.W.F.; Trienekens, J.H.; Beers, G.

    2001-01-01

    In this first article of the Journal on Chain and Network Science the base-line is set for a discussion on contents and scope of chain and network theory. Chain and network research is clustered into four main ‘streams’: Network theory, social capital theory, supply chain management and business

  12. Social networks

    CERN Document Server

    Etaner-Uyar, A Sima

    2014-01-01

    The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

  13. Recent advances on failure and recovery in networks of networks

    International Nuclear Information System (INIS)

    Shekhtman, Louis M.; Danziger, Michael M.; Havlin, Shlomo

    2016-01-01

    Until recently, network science has focused on the properties of single isolated networks that do not interact or depend on other networks. However it has now been recognized that many real-networks, such as power grids, transportation systems, and communication infrastructures interact and depend on other networks. Here, we will present a review of the framework developed in recent years for studying the vulnerability and recovery of networks composed of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes, like for example certain people, play a role in two networks, i.e. in a multiplex. Dependency relations may act recursively and can lead to cascades of failures concluding in sudden fragmentation of the system. We review the analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. The general theory and behavior of interdependent networks has many novel features that are not present in classical network theory. Interdependent networks embedded in space are significantly more vulnerable compared to non-embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences. Finally, when recovery of components is possible, global spontaneous recovery of the networks and hysteresis phenomena occur. The theory developed for this process points to an optimal repairing strategy for a network of networks. Understanding realistic effects present in networks of networks is required in order to move towards determining system vulnerability.

  14. Network Affordances

    DEFF Research Database (Denmark)

    Samson, Audrey; Soon, Winnie

    2015-01-01

    This paper examines the notion of network affordance within the context of network art. Building on Gibson's theory (Gibson, 1979) we understand affordance as the perceived and actual parameters of a thing. We expand on Gaver's affordance of predictability (Gaver, 1996) to include ecological...... and computational parameters of unpredictability. We illustrate the notion of unpredictability by considering four specific works that were included in a network art exhibiton, SPEED SHOW [2.0] Hong Kong. The paper discusses how the artworks are contingent upon the parameteric relations (Parisi, 2013......), of the network. We introduce network affordance as a dynamic framework that could articulate the experienced tension arising from the (visible) symbolic representation of computational processes and its hidden occurrences. We base our proposal on the experience of both organising the SPEED SHOW and participating...

  15. Managing Interorganizational Networks

    DEFF Research Database (Denmark)

    Gustafsson, Jeppe

    bold enough to predict that networks will become the dominant organisation form in future. Several authors maintain that the shift from traditional hierarchical structures to networks involves dramatic changes for managers and employees (Champy 2002, Rohlin 1994, Kanter 2002). This article seeks...... organisation theories and theories about strategic management....

  16. Animal transportation networks

    Science.gov (United States)

    Perna, Andrea; Latty, Tanya

    2014-01-01

    Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research. PMID:25165598

  17. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2017-01-01

    the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  18. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2018-01-01

    the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  19. Research into Queueing Network Theory.

    Science.gov (United States)

    1977-09-01

    and Zeigler, B. (1975) "Equilibrium properties of arbitrarily interconnected queueing netowrks ," Tech. Report 75-4, Computer and Communication...Associate. The project was extremely fortunate to secure the services of Dr. Wendel. Dr. Wendel was a project member for one month in the summer of

  20. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  1. Spectrum and network measurements

    CERN Document Server

    Witte, Robert A

    2014-01-01

    This new edition of Spectrum and Network Measurements enables readers to understand the basic theory, relate it to measured results, and apply it when creating new designs. This comprehensive treatment of frequency domain measurements successfully consolidates all the pertinent theory into one text. It covers the theory and practice of spectrum and network measurements in electronic systems. It also provides thorough coverage of Fourier analysis, transmission lines, intermodulation distortion, signal-to-noise ratio and S-parameters.

  2. Social exchange : Relations and networks

    NARCIS (Netherlands)

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network

  3. Social exchange: Relations and networks

    OpenAIRE

    Dijkstra, Jacob

    2015-01-01

    In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network research. The paper provides an accessible entry into the literature on social exchange.

  4. Nepal Networking

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    , as a Danida fellow. Today, the older sister works in Nepal and the younger in Seattle, where they still make use of their personal networks including connections to their fellow alumni of technical assistance courses. Inspired by work on social remittances in combination with network theory , I argue......Technical Assistance courses have many functions apart from disseminating knowledge and information, one such function is to engender networks. During the course period, participants meet and establish contact and some of these contacts remain connections between alumni for many years after...... the courses are finished. The alumni networks depend on the uses they are put to by the individual alumni and the support they get from alumni and host countries. The United Nations initiated technical assistance courses in the late 1940s in order to train nationals from developing countries as a means...

  5. Cascading Failures and Recovery in Networks of Networks

    Science.gov (United States)

    Havlin, Shlomo

    Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.

  6. Reactors, Weapons, X-Rays, and Solar Panels: Using SCOT, Technological Frame, Epistemic Culture, and Actor Network Theory to Investigate Technology

    Science.gov (United States)

    Sovacool, Benjamin K.

    2006-01-01

    The article explores how four different theories have been used to investigate technology. It highlights the worth and limitations of each theory and argues that an eclectic, ever-evolving approach to the study of technology is warranted. (Contains 1 table.)

  7. Temporal networks

    Science.gov (United States)

    Holme, Petter; Saramäki, Jari

    2012-10-01

    A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

  8. Network Leadership: An Emerging Practice

    Science.gov (United States)

    Tremblay, Christopher W.

    2012-01-01

    Network leadership is an emerging approach that can have an impact on change in education and in society. According to Merriam-Webster (2011), a network is "an interconnected or interrelated chain, group, or system." Intentional interconnectedness is what separates network leadership from other leadership theories. Network leadership has the…

  9. Vulnerability and controllability of networks of networks

    International Nuclear Information System (INIS)

    Liu, Xueming; Peng, Hao; Gao, Jianxi

    2015-01-01

    Network science is a highly interdisciplinary field ranging from natural science to engineering technology and it has been applied to model complex systems and used to explain their behaviors. Most previous studies have been focus on isolated networks, but many real-world networks do in fact interact with and depend on other networks via dependency connectivities, forming “networks of networks” (NON). The interdependence between networks has been found to largely increase the vulnerability of interacting systems, when a node in one network fails, it usually causes dependent nodes in other networks to fail, which, in turn, may cause further damage on the first network and result in a cascade of failures with sometimes catastrophic consequences, e.g., electrical blackouts caused by the interdependence of power grids and communication networks. The vulnerability of a NON can be analyzed by percolation theory that can be used to predict the critical threshold where a NON collapses. We review here the analytic framework for analyzing the vulnerability of NON, which yields novel percolation laws for n-interdependent networks and also shows that percolation theory of a single network studied extensively in physics and mathematics in the last 50 years is a specific limited case of the more general case of n interacting networks. Understanding the mechanism behind the cascading failure in NON enables us finding methods to decrease the vulnerability of the natural systems and design of more robust infrastructure systems. By examining the vulnerability of NON under targeted attack and studying the real interdependent systems, we find two methods to decrease the systems vulnerability: (1) protect the high-degree nodes, and (2) increase the degree correlation between networks. Furthermore, the ultimate proof of our understanding of natural and technological systems is reflected in our ability to control them. We also review the recent studies and challenges on the

  10. Social Networking Sites in Education

    OpenAIRE

    Suková, Lenka

    2010-01-01

    Diploma thesis deals with social networking sites and their use in education. Thesis is divided into two general parts. The first part deals with theory of learning; Bloom's taxonomy of educational objectives and new educational theory based on learning in networks -- Connectivism. After that thesis focuses on the definition of social networking sites, introduction of some of the best known social networking sites and examples of their use in foreign and domestic educational practice. The sec...

  11. Synchronization of oscillators in complex networks

    Indian Academy of Sciences (India)

    Theory of identical or complete synchronization of identical oscillators in arbitrary networks is introduced. In addition, several graph theory concepts and results that augment the synchronization theory and a tie in closely to random, semirandom, and regular networks are introduced. Combined theories are used to explore ...

  12. Synchronization of oscillators in complex networks

    Indian Academy of Sciences (India)

    Abstract. Theory of identical or complete synchronization of identical oscillators in arbitrary networks is introduced. In addition, several graph theory concepts and results that augment the synchronization theory and a tie in closely to random, semirandom, and regular networks are introduced. Combined theories are used to ...

  13. Electric theory

    International Nuclear Information System (INIS)

    Gong, Ha Seong

    2006-02-01

    This book explains electric theory which is divided into four chapters. The first chapter includes electricity and material, electric field, capacitance, magnetic field and electromagnetic force, inductance. The second chapter mentions electronic circuit analysis, electric resistance,heating and power, chemical activity on current and battery with electrolysis. The third chapter deals with an alternating current circuit about the basics of an AC circuit, operating of resistance, inductance and capacitance, series circuit and parallel circuit of PLC, an alternating current circuit, Three-phase Alternating current, two terminal pair network and voltage and current of non-linearity circuit. The last explains transient phenomena of RC series circuit, RL series circuit, transient phenomena of an alternating current circuit and transient phenomena of RLC series circuit.

  14. Estimation of the hydraulic conductivity of a two-dimensional fracture network using effective medium theory and power-law averaging

    Science.gov (United States)

    Zimmerman, R. W.; Leung, C. T.

    2009-12-01

    Most oil and gas reservoirs, as well as most potential sites for nuclear waste disposal, are naturally fractured. In these sites, the network of fractures will provide the main path for fluid to flow through the rock mass. In many cases, the fracture density is so high as to make it impractical to model it with a discrete fracture network (DFN) approach. For such rock masses, it would be useful to have recourse to analytical, or semi-analytical, methods to estimate the macroscopic hydraulic conductivity of the fracture network. We have investigated single-phase fluid flow through generated stochastically two-dimensional fracture networks. The centers and orientations of the fractures are uniformly distributed, whereas their lengths follow a lognormal distribution. The aperture of each fracture is correlated with its length, either through direct proportionality, or through a nonlinear relationship. The discrete fracture network flow and transport simulator NAPSAC, developed by Serco (Didcot, UK), is used to establish the “true” macroscopic hydraulic conductivity of the network. We then attempt to match this value by starting with the individual fracture conductances, and using various upscaling methods. Kirkpatrick’s effective medium approximation, which works well for pore networks on a core scale, generally underestimates the conductivity of the fracture networks. We attribute this to the fact that the conductances of individual fracture segments (between adjacent intersections with other fractures) are correlated with each other, whereas Kirkpatrick’s approximation assumes no correlation. The power-law averaging approach proposed by Desbarats for porous media is able to match the numerical value, using power-law exponents that generally lie between 0 (geometric mean) and 1 (harmonic mean). The appropriate exponent can be correlated with statistical parameters that characterize the fracture density.

  15. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  16. Networks: structure and action : steering in and steering by policy networks

    NARCIS (Netherlands)

    Dassen, A.

    2010-01-01

    This thesis explores the opportunities to build a structural policy network model that is rooted in social network theories. By making a distinction between a process of steering in networks, and a process of steering by networks, it addresses the effects of network structures on network dynamics as

  17. On skein relations in class S theories

    International Nuclear Information System (INIS)

    Tachikawa, Yuji; Watanabe, Noriaki

    2015-01-01

    Loop operators of a class S theory arise from networks on the corresponding Riemann surface, and their operator product expansions are given in terms of the skein relations, that we describe in detail in the case of class S theories of type A. As two applications, we explicitly determine networks corresponding to dyonic loops of N=4SU(3) super Yang-Mills, and compute the superconformal index of a nontrivial network operator of the T 3 theory.

  18. Statistical Inference for Cultural Consensus Theory

    Science.gov (United States)

    2014-02-24

    Social Network Conference XXXII , Redondo Beach, California, March 2012. Agrawal, K. (Presenter), and Batchelder, W. H. Cultural Consensus Theory...Aggregating Complete Signed Graphs Under a Balance Constraint -- Part 2. International Sunbelt Social Network Conference XXXII , Redondo Beach

  19. FMG, RENUM, LINEL, ELLFMG, ELLP, and DIMES: Chain of programs for calculating and analyzing fluid flow through two-dimensional fracture networks -- theory and design

    International Nuclear Information System (INIS)

    Billaux, D.; Bodea, S.; Long, J.

    1988-02-01

    This report describes some of the programs developed at Lawrence Berkeley Laboratory for network modelling. By themselves, these programs form a complete chain for the study of the equivalent permeability of two-dimensional fracture networks. FMG generates the fractures considered as line discontinuities, with any desired distribution of aperture, length, and orientation. The locations of these fractures on a plane can be either specified or generated randomly. The intersections of these fractures with each other, and with the boundaries of a specified flow region, are determined, and a finite element line network is output. RENUM is a line network optimizer. Nodes very close to each other are merged, dead-ends are removed, and the nodes are then renumbered in order to minimize the bandwidth of the corresponding linear system of equations. LINEL computes the steady state flux through a mesh of line elements previously processed by program RENUM. Equivalent directional permeabilities are output. ELLFMG determines the three components of the permeability tensor which best fits the directional permeabilities output by LINEL. A measure of the goodness fit is also computed. Two plotting programs, DIMES and ELLP, help visualize the outputs of these programs. DIMES plots the line network at various stages of the process. ELLP plots the equivalent permeability results. 14 refs., 25 figs

  20. A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa.

    Science.gov (United States)

    Roy, Sandip; McElwain, Terry F; Wan, Yan

    2011-10-01

    Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission. A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community. The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary