WorldWideScience

Sample records for networked slepian-wolf theory

  1. Cores of Cooperative Games in Information Theory

    Directory of Open Access Journals (Sweden)

    Mokshay Madiman

    2008-05-01

    Full Text Available Cores of cooperative games are ubiquitous in information theory and arise most frequently in the characterization of fundamental limits in various scenarios involving multiple users. Examples include classical settings in network information theory such as Slepian-Wolf source coding and multiple access channels, classical settings in statistics such as robust hypothesis testing, and new settings at the intersection of networking and statistics such as distributed estimation problems for sensor networks. Cooperative game theory allows one to understand aspects of all these problems from a fresh and unifying perspective that treats users as players in a game, sometimes leading to new insights. At the heart of these analyses are fundamental dualities that have been long studied in the context of cooperative games; for information theoretic purposes, these are dualities between information inequalities on the one hand and properties of rate, capacity, or other resource allocation regions on the other.

  2. Cores of Cooperative Games in Information Theory

    Directory of Open Access Journals (Sweden)

    Madiman Mokshay

    2008-01-01

    Full Text Available Cores of cooperative games are ubiquitous in information theory and arise most frequently in the characterization of fundamental limits in various scenarios involving multiple users. Examples include classical settings in network information theory such as Slepian-Wolf source coding and multiple access channels, classical settings in statistics such as robust hypothesis testing, and new settings at the intersection of networking and statistics such as distributed estimation problems for sensor networks. Cooperative game theory allows one to understand aspects of all these problems from a fresh and unifying perspective that treats users as players in a game, sometimes leading to new insights. At the heart of these analyses are fundamental dualities that have been long studied in the context of cooperative games; for information theoretic purposes, these are dualities between information inequalities on the one hand and properties of rate, capacity, or other resource allocation regions on the other.

  3. 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

  4. 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...

  5. Queueing theory and network applications

    CERN Document Server

    Takahashi, Yutaka; Yue, Wuyi; Nguyen, Viet-Ha

    2016-01-01

    The 16 papers of this proceedings have been selected from the submissions to the 10th  International Conference on Queueing Theory and Network Applications (QTNA2015) held on 17-20 August, 2015 in Ha Noi and Ha Long, Vietnam. All contributions discuss theoretical and practical issues connected with queueing theory and its applications in networks and other related fields. The book brings together researchers, scientists and practitioners from the world and offers an open forum to share the latest important research accomplishments and challenging problems in the area of queueing theory and network applications.

  6. Graph theory and interconnection networks

    CERN Document Server

    Hsu, Lih-Hsing

    2008-01-01

    The advancement of large scale integrated circuit technology has enabled the construction of complex interconnection networks. Graph theory provides a fundamental tool for designing and analyzing such networks. Graph Theory and Interconnection Networks provides a thorough understanding of these interrelated topics. After a brief introduction to graph terminology, the book presents well-known interconnection networks as examples of graphs, followed by in-depth coverage of Hamiltonian graphs. Different types of problems illustrate the wide range of available methods for solving such problems. The text also explores recent progress on the diagnosability of graphs under various models.

  7. Information Theory of Networks

    Directory of Open Access Journals (Sweden)

    Matthias Dehmer

    2011-11-01

    Full Text Available The paper puts the emphasis on surveying information-theoretic network measures for analyzing the structure of networks. In order to apply the quantities interdisciplinarily, we also discuss some of their properties such as their structural interpretation and uniqueness.

  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. 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.

  10. 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....

  11. 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.

  12. 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...

  13. 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

  14. Applying Information Theory to Neuronal Networks: From Theory to Experiments

    NARCIS (Netherlands)

    Jung, T.I.; Vogiatzian, F.; Har-Shemesh, O.; Fitzsimons, C.P.; Quax, R.

    2014-01-01

    Information-theory is being increasingly used to analyze complex, self-organizing processes on networks, predominantly in analytical and numerical studies. Perhaps one of the most paradigmatic complex systems is a network of neurons, in which cognition arises from the information storage, transfer,

  15. 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.

  16. Network Detection Theory and Performance

    OpenAIRE

    Smith, Steven T.; Senne, Kenneth D.; Philips, Scott; Kao, Edward K.; Bernstein, Garrett

    2013-01-01

    Network detection is an important capability in many areas of applied research in which data can be represented as a graph of entities and relationships. Oftentimes the object of interest is a relatively small subgraph in an enormous, potentially uninteresting background. This aspect characterizes network detection as a "big data" problem. Graph partitioning and network discovery have been major research areas over the last ten years, driven by interest in internet search, cyber security, soc...

  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. 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

  19. 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.

  20. Graphical Model Theory for Wireless Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Davis, William B.

    2002-12-08

    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.

  1. 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.

  2. Information theory perspective on network robustness

    Energy Technology Data Exchange (ETDEWEB)

    Schieber, Tiago A. [Departmento de Engenharia de Produção, Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil); Industrial and Systems Engineering, University of Florida, Gainesville, FL (United States); Carpi, Laura [Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Colom 11, Terrassa, 08222, Barcelona (Spain); Frery, Alejandro C. [Laboratório de Computação Científica e Análise Numérica (LaCCAN), Universidade Federal de Alagoas, Maceió, Alagoas (Brazil); Rosso, Osvaldo A. [Instituto de Física, Universidade Federal de Alagoas, Maceió, Alagoas (Brazil); Instituto Tecnológico de Buenos Aires (ITBA), Ciudad Autónoma de Buenos Aires (Argentina); Pardalos, Panos M. [Industrial and Systems Engineering, University of Florida, Gainesville, FL (United States); Ravetti, Martín G., E-mail: martin.ravetti@dep.ufmg.br [Departmento de Engenharia de Produção, Universidade Federal de Minas Gerais, Belo Horizonte, MG (Brazil); Departament de Física Fonamental, Universitat de Barcelona, Barcelona (Spain)

    2016-01-28

    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.

  3. 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.

  4. Theory of Semiflexible Filaments and Networks

    Directory of Open Access Journals (Sweden)

    Fanlong Meng

    2017-02-01

    Full Text Available We briefly review the recent developments in the theory of individual semiflexible filaments, and of a crosslinked network of such filaments, both permanent and transient. Starting from the free energy of an individual semiflexible chain, models on its force-extension relation and other mechanical properties such as Euler buckling are discussed. For a permanently crosslinked network of filaments, theories on how the network responds to deformation are provided, with a focus on continuum approaches. Characteristic features of filament networks, such as nonlinear stress-strain relation, negative normal stress, tensegrity, and marginal stability are discussed. In the new area of transient filament network, where the crosslinks can be dynamically broken and re-formed, we show some recent attempts for understanding the dynamics of the crosslinks, and the related rheological properties, such as stress relaxation, yield stress and plasticity.

  5. 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

  6. Research into Queueing Network Theory.

    Science.gov (United States)

    1977-09-01

    recomposition , and stretching) that have been considered in queueing networks map arrival processes that are Markov renewal processes into other...research under this contract are marked by a double asterik(**). Other references are to work cited in the body of the report and are not ideas

  7. 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).

  8. 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

  9. Exploring network theory for mass drug administration.

    Science.gov (United States)

    Chami, Goylette F; Molyneux, David H; Kontoleon, Andreas A; Dunne, David W

    2013-08-01

    Network theory is a well-established discipline that uses mathematical graphs to describe biological, physical, and social systems. The topologies across empirical networks display strikingly similar organizational properties. In particular, the characteristics of these networks allow computational analysis to contribute data unattainable from examining individual components in isolation. However, the interdisciplinary and quantitative nature of network analysis has yet to be exploited by public health initiatives to distribute preventive chemotherapies. One notable application is the 2012 World Health Organization (WHO) Roadmap for Neglected Tropical Diseases (NTDs) where there is a need to upscale distribution capacity and to target systematic noncompliers. An understanding of local networks for analysing the distributional properties of community-directed treatment may facilitate sustainable expansion of mass drug-administration (MDA) programs. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. 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.

  11. 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

  12. Neurocognitive networks: findings, models, and theory.

    Science.gov (United States)

    Meehan, Timothy P; Bressler, Steven L

    2012-11-01

    Through its early history, cognitive neuroscience largely followed a modular paradigm wherein high-level cognitive functions were mapped onto locally segregated brain regions. However, recent evidence drives a continuing shift away from modular theories of cognitive brain function, and toward theories which hold that cognition arises from the integrated activity of large-scale, distributed networks of brain regions. A growing consensus favors the fundamental concept of this new paradigm: the large-scale cognitive brain network, or neurocognitive network. This consensus was the motivation for Neurocognitive Networks 2010 (NCN 2010), a conference sponsored by the Cognitive Neuroscience Program of the National Science Foundation, organized by Drs. Steven Bressler and Craig Richter of Florida Atlantic University (FAU), and held at FAU in Boca Raton, FL on January 29-30, 2010. NCN 2010 gathered together some of today's leading investigators of neurocognitive networks. This paper serves to review their presentations as they relate to the paradigm of neurocognitive networks, as well as to compile the emergent themes, questions, and possible future research directions that arose from the conference. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Fuzzy neural networks: theory and applications

    Science.gov (United States)

    Gupta, Madan M.

    1994-10-01

    During recent years, significant advances have been made in two distinct technological areas: fuzzy logic and computational neural networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. It also provides a mathematical morphology to emulate certain perceptual and linguistic attributes associated with human cognition. On the other hand, the computational neural network paradigms have evolved in the process of understanding the incredible learning and adaptive features of neuronal mechanisms inherent in certain biological species. Computational neural networks replicate, on a small scale, some of the computational operations observed in biological learning and adaptation. The integration of these two fields, fuzzy logic and neural networks, have given birth to an emerging technological field -- fuzzy neural networks. Fuzzy neural networks, have the potential to capture the benefits of these two fascinating fields, fuzzy logic and neural networks, into a single framework. The intent of this tutorial paper is to describe the basic notions of biological and computational neuronal morphologies, and to describe the principles and architectures of fuzzy neural networks. Towards this goal, we develop a fuzzy neural architecture based upon the notion of T-norm and T-conorm connectives. An error-based learning scheme is described for this neural structure.

  14. Network Neuroscience Theory of Human Intelligence.

    Science.gov (United States)

    Barbey, Aron K

    2018-01-01

    An enduring aim of research in the psychological and brain sciences is to understand the nature of individual differences in human intelligence, examining the stunning breadth and diversity of intellectual abilities and the remarkable neurobiological mechanisms from which they arise. This Opinion article surveys recent neuroscience evidence to elucidate how general intelligence, g, emerges from individual differences in the network architecture of the human brain. The reviewed findings motivate new insights about how network topology and dynamics account for individual differences in g, represented by the Network Neuroscience Theory. According to this framework, g emerges from the small-world topology of brain networks and the dynamic reorganization of its community structure in the service of system-wide flexibility and adaptation. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

  15. Using graph theory to analyze biological networks

    Science.gov (United States)

    2011-01-01

    Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

  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. Interdisciplinary contributions to theory for collaborative networks

    CERN Document Server

    Dekkers, Rob

    2012-01-01

    Scientific progress on a field is mostly discussed within disciplines. Far less attention is paid to outside or between disciplines' work. To speed up research progresses for Collaborative Networks in Manufacturing, a base for further grounded theory establishment is propagated recalling some of the most relevant chapters of philosophy of science. The focus is put onto the roles of disciplines and their scholars involved in interdisciplinary contexts in order to further motivate as well as to hint at a number of catalysing forces and fruitful impacts of outside disciplines' work.

  18. 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

  19. 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

  20. 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

  1. 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...

  2. 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…

  3. 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.…

  4. Network anomaly detection system with optimized DS evidence theory.

    Science.gov (United States)

    Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu

    2014-01-01

    Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.

  5. The Embedded Self: A Social Networks Approach to Identity Theory

    Science.gov (United States)

    Walker, Mark H.; Lynn, Freda B.

    2013-01-01

    Despite the fact that key sociological theories of self and identity view the self as fundamentally rooted in networks of interpersonal relationships, empirical research investigating how personal network structure influences the self is conspicuously lacking. To address this gap, we examine links between network structure and role identity…

  6. 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.

  7. Robustness of complex networks : Theory and application

    NARCIS (Netherlands)

    Wang, X.

    2016-01-01

    Failures of networks, such as power outages in power systems, congestions in
    transportation networks, paralyse our daily life and introduce a tremendous cascading effect on our society. Networks should be constructed and operated in a robust way against random failures or deliberate

  8. 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.

  9. Applied Hypergame Theory for Network Defense

    Science.gov (United States)

    2013-06-01

    themselves. The investigation of the competition between species has given rise to evolutionary game theory. Even evolutionary game theory itself has evolved...to be applied to economics, sociology, and anthropology [7]. Application of game theory principles can be used wherever there is a contest over...Murad Mehmet Bayraktar. “Game Theory and Intrusion Detection Systems”, 2006. ISA 767-Secure E-Commerce. [7] Alexander, J. McKenzie. “ Evolutionary

  10. 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.

  11. 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

  12. The theory of pattern formation on directed networks.

    Science.gov (United States)

    Asllani, Malbor; Challenger, Joseph D; Pavone, Francesco Saverio; Sacconi, Leonardo; Fanelli, Duccio

    2014-07-31

    Dynamical processes on networks have generated widespread interest in recent years. The theory of pattern formation in reaction-diffusion systems defined on symmetric networks has often been investigated, due to its applications in a wide range of disciplines. Here we extend the theory to the case of directed networks, which are found in a number of different fields, such as neuroscience, computer networks and traffic systems. Owing to the structure of the network Laplacian, the dispersion relation has both real and imaginary parts, at variance with the case for a symmetric, undirected network. The homogeneous fixed point can become unstable due to the topology of the network, resulting in a new class of instabilities, which cannot be induced on undirected graphs. Results from a linear stability analysis allow the instability region to be analytically traced. Numerical simulations show travelling waves, or quasi-stationary patterns, depending on the characteristics of the underlying graph.

  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. 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

  15. 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

  16. Brain and cognitive reserve: Translation via network control theory.

    Science.gov (United States)

    Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H; Thompson-Schill, Sharon L; Bassett, Danielle S

    2017-04-01

    Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. 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

  18. Application of Random Matrix Theory to Complex Networks

    Science.gov (United States)

    Rai, Aparna; Jalan, Sarika

    The present article provides an overview of recent developments in spectral analysis of complex networks under random matrix theory framework. Adjacency matrix of unweighted networks, reviewed here, differ drastically from a random matrix, as former have only binary entries. Remarkably, short range correlations in corresponding eigenvalues of such matrices exhibit Gaussian orthogonal statistics of RMT and thus bring them into the universality class. Spectral rigidity of spectra provides measure of randomness in underlying networks. We will consider several examples of model networks vastly studied in last two decades. To the end we would provide potential of RMT framework and obtained results to understand and predict behavior of complex systems with underlying network structure.

  19. 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.

  20. Integrated Adversarial Network Theory (iANT)

    Science.gov (United States)

    2011-07-01

    in Language : A Semiotic Approach to Literature and Art. New York: Columbia University Press Kumbasar, E., Romney, K. A., & Batchelder, W. H. 1994...threat Mimetic Processes E.g., imitation, theft Osmotic Processes E.g., language acquisition, schemas Table 3: Mechanisms/processes cross-classified...level ofthe specific theories ofSWT and SH, it should be obvious that Burt’s theory is closely related to Granovetter’s. In Burt’s language , A has more

  1. Network meta-analysis, electrical networks and graph theory.

    Science.gov (United States)

    Rücker, Gerta

    2012-12-01

    Network meta-analysis is an active field of research in clinical biostatistics. It aims to combine information from all randomized comparisons among a set of treatments for a given medical condition. We show how graph-theoretical methods can be applied to network meta-analysis. A meta-analytic graph consists of vertices (treatments) and edges (randomized comparisons). We illustrate the correspondence between meta-analytic networks and electrical networks, where variance corresponds to resistance, treatment effects to voltage, and weighted treatment effects to current flows. Based thereon, we then show that graph-theoretical methods that have been routinely applied to electrical networks also work well in network meta-analysis. In more detail, the resulting consistent treatment effects induced in the edges can be estimated via the Moore-Penrose pseudoinverse of the Laplacian matrix. Moreover, the variances of the treatment effects are estimated in analogy to electrical effective resistances. It is shown that this method, being computationally simple, leads to the usual fixed effect model estimate when applied to pairwise meta-analysis and is consistent with published results when applied to network meta-analysis examples from the literature. Moreover, problems of heterogeneity and inconsistency, random effects modeling and including multi-armed trials are addressed. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

  2. 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.

  3. 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

  4. On the genesis of the idiotypic network theory.

    Science.gov (United States)

    Civello, Andrea

    2013-01-01

    The idiotypic network theory (INT) was conceived by the Danish immunologist Niels Kaj Jerne in 1973/1974. It proposes an overall view of the immune system as a network of lymphocytes and antibodies. The paper tries to offer a reconstruction of the genesis of the theory, now generally discarded and of mostly historical interest, first of all, by taking into account the context in which Jerne's theoretical proposal was advanced. It is argued the theory challenged, in a sense, the supremacy of the clonal selection theory (CST), this being regarded as the predominant paradigm in the immunological scenario. As CST found shortcomings in explaining certain phenomena, anomalies, one could view INT as a competing paradigm claiming to be able to make sense of such phenomena in its own conceptual framework. After a summary outline of the historical background and some relevant terminological elucidations, a narrative of the various phases of elaboration of the theory is proposed, up to its official public presentation.

  5. 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

  6. Realizing Wisdom Theory in Complex Learning Networks

    Science.gov (United States)

    Kok, Ayse

    2009-01-01

    The word "wisdom" is rarely seen in contemporary technology and learning discourse. This conceptual paper aims to provide some clear principles that answer the question: How can we establish wisdom in complex learning networks? By considering the nature of contemporary calls for wisdom the paper provides a metatheoretial framework to evaluate the…

  7. Neural networks, penalty logic and optimality theory

    NARCIS (Netherlands)

    Blutner, R.; Benz, A.; Blutner, R.

    2009-01-01

    Ever since the discovery of neural networks, there has been a controversy between two modes of information processing. On the one hand, symbolic systems have proven indispensable for our understanding of higher intelligence, especially when cognitive domains like language and reasoning are examined.

  8. 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.

  9. Cognitive Radio Networks From Theory to Practice

    CERN Document Server

    Khattab, Ahmed; Bayoumi, Magdy

    2013-01-01

    This book describes a communication paradigm that could shape the future of wireless communication networks, Opportunistic Spectrum Access (OSA) in Cognitive Radio Networks (CRN).  While several theoretical OSA approaches have been proposed, they are challenged by the practical limitations of cognitive radios: the key enabling technology of OSA.  This book presents an unprecedented formulation of the OSA problem in CNR that takes into account the practical limitations encountered due to existing technologies. Based on such a problem formulation, this book presents a framework and protocol details implementing the analytically-optimized solution of this problem. Unlike the state-of-the-art of CRN implementations that typically target software define radios which are not suitable for real systems, this book describes the implementation of distributed OSA, using practical radio transceiver technologies. It provides a thorough characterization of the gains available to theoretical OSA approaches if the practica...

  10. 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.

  11. 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

  12. Effects of Actor-Network Theory in Accounting Research

    DEFF Research Database (Denmark)

    Justesen, Lise Nederland; Mouritsen, Jan

    2011-01-01

    of a critical literature review and discussion. Findings – Since the early 1990s, actor-network theory, particularly the work of Bruno Latour, has inspired accounting researchers and led to a number of innovative studies of accounting phenomena. In particular, Latour's book, Science in Action, has been...... number of accounting papers that apply actor-network theory. A different sample might have given a somewhat different picture. Furthermore, it focuses on the influence of Latour's work and refrains from discussing how the writings of Michel Callon, John Law or other thinkers within the actor......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...

  13. 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.

  14. 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.

  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. 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.

  17. 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.

  18. Graph theory network function in Parkinson's disease assessed with electroencephalography.

    Science.gov (United States)

    Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G

    2016-05-01

    To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Complex network theory, streamflow, and hydrometric monitoring system design

    Science.gov (United States)

    Halverson, M. J.; Fleming, S. W.

    2015-07-01

    Network theory is applied to an array of streamflow gauges located in the Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the analysis is to assess whether insights from this branch of mathematical graph theory can be meaningfully applied to hydrometric data, and, more specifically, whether it may help guide decisions concerning stream gauge placement so that the full complexity of the regional hydrology is efficiently captured. The streamflow data, when represented as a complex network, have a global clustering coefficient and average shortest path length consistent with small-world networks, which are a class of stable and efficient networks common in nature, but the observed degree distribution did not clearly indicate a scale-free network. Stability helps ensure that the network is robust to the loss of nodes; in the context of a streamflow network, stability is interpreted as insensitivity to station removal at random. Community structure is also evident in the streamflow network. A network theoretic community detection algorithm identified separate communities, each of which appears to be defined by the combination of its median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in this region in turn mainly reflects basin elevation) and geographic proximity to other communities (reflecting shared or different daily meteorological forcing). Furthermore, betweenness analyses suggest a handful of key stations which serve as bridges between communities and might be highly valued. We propose that an idealized sampling network should sample high-betweenness stations, small-membership communities which are by definition rare or undersampled relative to other communities, and index stations having large numbers of intracommunity links, while retaining some degree of redundancy to maintain network robustness.

  20. 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

  1. 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...

  2. Network Security Risk Assessment Based on Item Response Theory

    Directory of Open Access Journals (Sweden)

    Fangwei Li

    2015-08-01

    Full Text Available Owing to the traditional risk assessment method has one-sidedness and is difficult to reflect the real network situation, a risk assessment method based on Item Response Theory (IRT is put forward in network security. First of all, the novel algorithms of calculating the threat of attack and the successful probability of attack are proposed by the combination of IRT model and Service Security Level. Secondly, the service weight of importance is calculated by the three-demarcation analytic hierarchy process. Finally, the risk situation graph of service, host and network logic layer could be generated by the improved method. The simulation results show that this method can be more comprehensive consideration of factors which are affecting network security, and a more realistic network risk situation graph in real-time will be obtained.

  3. 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

  4. Evaluating Action Learning: A Critical Realist Complex Network Theory Approach

    Science.gov (United States)

    Burgoyne, John G.

    2010-01-01

    This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…

  5. 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.

  6. 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

  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. Chemical reaction network approaches to Biochemical Systems Theory.

    Science.gov (United States)

    Arceo, Carlene Perpetua P; Jose, Editha C; Marin-Sanguino, Alberto; Mendoza, Eduardo R

    2015-11-01

    This paper provides a framework to represent a Biochemical Systems Theory (BST) model (in either GMA or S-system form) as a chemical reaction network with power law kinetics. Using this representation, some basic properties and the application of recent results of Chemical Reaction Network Theory regarding steady states of such systems are shown. In particular, Injectivity Theory, including network concordance [36] and the Jacobian Determinant Criterion [43], a "Lifting Theorem" for steady states [26] and the comprehensive results of Müller and Regensburger [31] on complex balanced equilibria are discussed. A partial extension of a recent Emulation Theorem of Cardelli for mass action systems [3] is derived for a subclass of power law kinetic systems. However, it is also shown that the GMA and S-system models of human purine metabolism [10] do not display the reactant-determined kinetics assumed by Müller and Regensburger and hence only a subset of BST models can be handled with their approach. Moreover, since the reaction networks underlying many BST models are not weakly reversible, results for non-complex balanced equilibria are also needed. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. 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

  10. 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.

  11. Randomly evolving idiotypic networks: modular mean field theory.

    Science.gov (United States)

    Schmidtchen, Holger; Behn, Ulrich

    2012-07-01

    We develop a modular mean field theory for a minimalistic model of the idiotypic network. The model comprises the random influx of new idiotypes and a deterministic selection. It describes the evolution of the idiotypic network towards complex modular architectures, the building principles of which are known. The nodes of the network can be classified into groups of nodes, the modules, which share statistical properties. Each node experiences only the mean influence of the groups to which it is linked. Given the size of the groups and linking between them the statistical properties such as mean occupation, mean lifetime, and mean number of occupied neighbors are calculated for a variety of patterns and compared with simulations. For a pattern which consists of pairs of occupied nodes correlations are taken into account.

  12. Tensor Networks for Lattice Gauge Theories with Continuous Groups

    Directory of Open Access Journals (Sweden)

    L. Tagliacozzo

    2014-11-01

    Full Text Available We discuss how to formulate lattice gauge theories in the tensor-network language. In this way, we obtain both a consistent-truncation scheme of the Kogut-Susskind lattice gauge theories and a tensor-network variational ansatz for gauge-invariant states that can be used in actual numerical computations. Our construction is also applied to the simplest realization of the quantum link models or gauge magnets and provides a clear way to understand their microscopic relation with the Kogut-Susskind lattice gauge theories. We also introduce a new set of gauge-invariant operators that modify continuously Rokhsar-Kivelson wave functions and can be used to extend the phase diagrams of known models. As an example, we characterize the transition between the deconfined phase of the Z_{2} lattice gauge theory and the Rokhsar-Kivelson point of the U(1 gauge magnet in 2D in terms of entanglement entropy. The topological entropy serves as an order parameter for the transition but not the Schmidt gap.

  13. 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

  14. 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.

  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.

  16. 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.

  17. 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

  18. 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.

  19. 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...

  20. 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.

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

    Science.gov (United States)

    Nekovarova, Tereza; Fajnerova, Iveta; Horacek, Jiri; Spaniel, Filip

    2014-01-01

    Schizophrenia is a complex neuropsychiatric disorder with variable symptomatology, traditionally divided into positive and negative symptoms, and cognitive deficits. However, 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 a triple brain network model of the dysfunctional switching between default mode and central executive network (CEN) related to the aberrant activity of the 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 that support the triple brain network model as a common neuronal substrate of this dysfunction.

  2. 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.

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

    DEFF Research Database (Denmark)

    Jessen, Jari Due; Jessen, Carsten

    2014-01-01

    data from a study of board games , computer games, and exergames, we conclude that games are actors that produce experiences by exercising power over the user’ s abilities, for example their cognitive functions. Games are designed to take advantage of the characteristics of the human players......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...

  4. 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 ...

  5. Transportation and dynamic networks: Models, theory, and applications to supply chains, electric power, and financial networks

    Science.gov (United States)

    Liu, Zugang

    Network systems, including transportation and logistic systems, electric power generation and distribution networks as well as financial networks, provide the critical infrastructure for the functioning of our societies and economies. The understanding of the dynamic behavior of such systems is also crucial to national security and prosperity. The identification of new connections between distinct network systems is the inspiration for the research in this dissertation. In particular, I answer two questions raised by Beckmann, McGuire, and Winsten (1956) and Copeland (1952) over half a century ago, which are, respectively, how are electric power flows related to transportation flows and does money flow like water or electricity? In addition, in this dissertation, I achieve the following: (1) I establish the relationships between transportation networks and three other classes of complex network systems: supply chain networks, electric power generation and transmission networks, and financial networks with intermediation. The establishment of such connections provides novel theoretical insights as well as new pricing mechanisms, and efficient computational methods. (2) I develop new modeling frameworks based on evolutionary variational inequality theory that capture the dynamics of such network systems in terms of the time-varying flows and incurred costs, prices, and, where applicable, profits. This dissertation studies the dynamics of such network systems by addressing both internal competition and/or cooperation, and external changes, such as varying costs and demands. (3) I focus, in depth, on electric power supply chains. By exploiting the relationships between transportation networks and electric power supply chains, I develop a large-scale network model that integrates electric power supply chains and fuel supply markets. The model captures both the economic transactions as well as the physical transmission constraints. The model is then applied to the New

  6. 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.

  7. Morphological brain network assessed using graph theory and network filtration in deaf adults.

    Science.gov (United States)

    Kim, Eunkyung; Kang, Hyejin; Lee, Hyekyoung; Lee, Hyo-Jeong; Suh, Myung-Whan; Song, Jae-Jin; Oh, Seung-Ha; Lee, Dong Soo

    2014-09-01

    Prolonged deprivation of auditory input can change brain networks in pre- and postlingual deaf adults by brain-wide reorganization. To investigate morphological changes in these brains voxel-based morphometry, voxel-wise correlation with the primary auditory cortex, and whole brain network analyses using morphological covariance were performed in eight prelingual deaf, eleven postlingual deaf, and eleven hearing adults. Network characteristics based on graph theory and network filtration based on persistent homology were examined. Gray matter density in the primary auditor cortex was preserved in prelingual deafness, while it tended to decrease in postlingual deafness. Unlike postlingual, prelingual deafness showed increased bilateral temporal connectivity of the primary auditory cortex compared to the hearing adults. Of the graph theory-based characteristics, clustering coefficient, betweenness centrality, and nodal efficiency all increased in prelingual deafness, while all the parameters of postlingual deafness were similar to the hearing adults. Patterns of connected components changing during network filtration were different between prelingual deafness and hearing adults according to the barcode, dendrogram, and single linkage matrix representations, while these were the same in postlingual deafness. Nodes in fronto-limbic and left temporal components were closely coupled, and nodes in the temporo-parietal component were loosely coupled, in prelingual deafness. Patterns of connected components changing in postlingual deafness were the same as hearing adults. We propose that the preserved density of auditory cortex associated with increased connectivity in prelingual deafness, and closer coupling between certain brain areas, represent distinctive reorganization of auditory and related cortices compared with hearing or postlingual deaf adults. The differential network reorganization in the prelingual deaf adults could be related to the absence of auditory speech

  8. Up the ANTe: Understanding Entrepreneurial Leadership Learning through Actor-Network Theory

    Science.gov (United States)

    Smith, Sue; Kempster, Steve; Barnes, Stewart

    2017-01-01

    This article explores the role of educators in supporting the development of entrepreneurial leadership learning by creating peer learning networks of owner-managers of small businesses. Using actor-network theory, the authors think through the process of constructing and maintaining a peer learning network (conceived of as an actor-network) and…

  9. Methods of information theory and algorithmic complexity for network biology.

    Science.gov (United States)

    Zenil, Hector; Kiani, Narsis A; Tegnér, Jesper

    2016-03-01

    We survey and introduce concepts and tools located at the intersection of information theory and network biology. We show that Shannon's information entropy, compressibility and algorithmic complexity quantify different local and global aspects of synthetic and biological data. We show examples such as the emergence of giant components in Erdös-Rényi random graphs, and the recovery of topological properties from numerical kinetic properties simulating gene expression data. We provide exact theoretical calculations, numerical approximations and error estimations of entropy, algorithmic probability and Kolmogorov complexity for different types of graphs, characterizing their variant and invariant properties. We introduce formal definitions of complexity for both labeled and unlabeled graphs and prove that the Kolmogorov complexity of a labeled graph is a good approximation of its unlabeled Kolmogorov complexity and thus a robust definition of graph complexity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Nuclear charge radii: density functional theory meets Bayesian neural networks

    Science.gov (United States)

    Utama, R.; Chen, Wei-Chia; Piekarewicz, J.

    2016-11-01

    The distribution of electric charge in atomic nuclei is fundamental to our understanding of the complex nuclear dynamics and a quintessential observable to validate nuclear structure models. The aim of this study is to explore a novel approach that combines sophisticated models of nuclear structure with Bayesian neural networks (BNN) to generate predictions for the charge radii of thousands of nuclei throughout the nuclear chart. A class of relativistic energy density functionals is used to provide robust predictions for nuclear charge radii. In turn, these predictions are refined through Bayesian learning for a neural network that is trained using residuals between theoretical predictions and the experimental data. Although predictions obtained with density functional theory provide a fairly good description of experiment, our results show significant improvement (better than 40%) after BNN refinement. Moreover, these improved results for nuclear charge radii are supplemented with theoretical error bars. We have successfully demonstrated the ability of the BNN approach to significantly increase the accuracy of nuclear models in the predictions of nuclear charge radii. However, as many before us, we failed to uncover the underlying physics behind the intriguing behavior of charge radii along the calcium isotopic chain.

  11. A Theory of Decomposition of Complex Chemical Networks using the Hill Functions

    CERN Document Server

    Chikayama, Eisuke

    2014-01-01

    The design and synthesis of complex and large mimicked biochemical networks de novo is an unsolved problem in synthetic biology. To address this limitation without resorting to ad hoc computations and experiments, a predictive mathematical theory is required to reduce these complex chemical networks into natural physico-chemical expressions. Here we provide a mathematical theory that offers a physico-chemical expression for a large chemical network that is almost arbitrarily both nonlinear and complex. Unexpectedly, the theory demonstrates that such networks can be decomposed into reactions based solely on the Hill equation, a simple chemical logic gate. This theory, analogous to implemented electrical logic gates or functional algorithms in a computer, is proposed for implementing regulated sequences of functional chemical reactions, such as mimicked genes, transcriptional regulation, signal transduction, protein interaction, and metabolic networks, into an artificial designed chemical network.

  12. Network theory: key issues for the analysis of the "brain drain"

    Directory of Open Access Journals (Sweden)

    Diana Carolina Henao

    2012-12-01

    Full Text Available This paper offers an analysis of the brain drain from the perspective of the network theory. Some definitions and key concepts of the network theory have been discussed in relation to criteria and reasons that are taken into account by people with broad educational capital from developing countries who are involved in the research in different areas of knowledge and who seek to adapt to other scientific collaboration networks in the developed countries.

  13. 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...... is found from the strain of the network after it returns to the state-of-ease where the stress is zero. The permanent set simulations are compared with theory using the independent network hypothesis, together with the various theoretical rubber elasticity theories: affine, phantom, constrained junction...

  14. 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....

  15. An Introduction to Network Psychometrics: Relating Ising Network Models to Item Response Theory Models.

    Science.gov (United States)

    Marsman, M; Borsboom, D; Kruis, J; Epskamp, S; van Bork, R; Waldorp, L J; Maas, H L J van der; Maris, G

    2017-11-07

    In recent years, network models have been proposed as an alternative representation of psychometric constructs such as depression. In such models, the covariance between observables (e.g., symptoms like depressed mood, feelings of worthlessness, and guilt) is explained in terms of a pattern of causal interactions between these observables, which contrasts with classical interpretations in which the observables are conceptualized as the effects of a reflective latent variable. However, few investigations have been directed at the question how these different models relate to each other. To shed light on this issue, the current paper explores the relation between one of the most important network models-the Ising model from physics-and one of the most important latent variable models-the Item Response Theory (IRT) model from psychometrics. The Ising model describes the interaction between states of particles that are connected in a network, whereas the IRT model describes the probability distribution associated with item responses in a psychometric test as a function of a latent variable. Despite the divergent backgrounds of the models, we show a broad equivalence between them and also illustrate several opportunities that arise from this connection.

  16. A Simulation Study for Emergency/Disaster Management by Applying Complex Networks Theory

    Directory of Open Access Journals (Sweden)

    Li Jin

    2014-04-01

    Full Text Available Earthquakes, hurricanes, flooding and terrorist attacks pose a severe threat to our society. What’s more, when such a disaster happens, it can spread in a wide range with ubiquitous presence of a large-scale networked system. Therefore, the emergency/disaster management faces new challenges that the decision-makers have extra difficulties in perceiving the disaster dynamic spreading processes under this networked environment. This study tries to use the complex networks theory to tackle this complexity and the result shows the theory is a promising approach to support disaster/emergency management by focusing on simulation experiments of small world networks and scale free networks. The theory can be used to capture and describe the evolution mechanism, evolution discipline and overall behavior of a networked system. In particular, the complex networks theory is very strong at analyzing the complexity and dynamical changes of a networked system, which can improve the situation awareness after a disaster has occurred and help perceive its dynamic process, which is very important for high-quality decision making. In addition, this study also shows the use of the complex networks theory can build a visualized process to track the dynamic spreading of a disaster in a networked system.

  17. 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.

  18. Adaptive Selection of Cryptographic Protocols in Wireless Sensor Networks using Evolutionary Game Theory

    National Research Council Canada - National Science Library

    Arora, Srishti; Singh, Prabhjot; Gupta, Ashok Ji

    2016-01-01

    ... with contrary motives contend with each other. Various solutions basedon Game theory have been recently proposed which dealt with security aspects of wireless sensor networks(WSNs). However, th...

  19. 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…

  20. 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.

  1. Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

    Science.gov (United States)

    Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-03-01

    "A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. A Practical Theory of Micro-Solar Power Sensor Networks

    Science.gov (United States)

    2009-04-20

    Pavan Sikka, Tim Wark, and Les Overs. Long-duration solar-powered wireless sensor networks. The Fourth IEEE workshop on Embedded Networked Sensors (EmNets...node. International Symposium on Low Power Electronics and Design (ISLPED ‘06), October 2006. [SCV+06] Pavan Sikka, Peter Corke, Philip Valencia

  3. 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

  4. 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 surrounding the Plastic Bags Regulations ... 2002); 'waste wars' in Ireland (Davies, 2003) and recycling in Norway (Eik & Brekke, 2003). ... as actors and actor-networks put the Plastic Bags Regulations into circulation as focal actant (token).

  5. Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

    Directory of Open Access Journals (Sweden)

    Kaat Alaerts

    Full Text Available The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON. Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD have deficits in the social domain and exhibit alterations in this neural network.Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC.Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength. Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD.While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

  6. Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.

    Science.gov (United States)

    Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole

    2015-01-01

    The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.

  7. 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…

  8. A Social Network Perspective on Teacher Collaboration in Schools: Theory, Methodology, and Applications

    Science.gov (United States)

    Moolenaar, Nienke M.

    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 among educators to advance our understanding of the…

  9. 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

  10. Untangling Word Webs: Graph Theory and the Notion of Density in Second Language Word Association Networks.

    Science.gov (United States)

    Wilks, Clarissa; Meara, Paul

    2002-01-01

    Examines the implications of the metaphor of the vocabulary network. Takes a formal approach to the exploration of this metaphor by applying the principles of graph theory to word association data to compare the relative densities of the first language and second language lexical networks. (Author/VWL)

  11. In search of a network theory of innovations: relations, positions, and perspectives

    NARCIS (Netherlands)

    Leydesdorff, L.; Ahrweiler, P.

    2014-01-01

    As a complement to Nelson and Winter's (1977) article titled "In Search of a Useful Theory of Innovation," a sociological perspective on innovation networks can be elaborated using Luhmann's social systems theory, on the one hand, and Latour's "sociology of translations," on the other. Because of a

  12. 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.

  13. 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.

  14. 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.

  15. [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.

  16. 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.

  17. 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.

  18. Graph Theory-Based Pinning Synchronization of Stochastic Complex Dynamical Networks.

    Science.gov (United States)

    Li, Xiao-Jian; Yang, Guang-Hong

    2017-02-01

    This paper is concerned with the adaptive pinning synchronization problem of stochastic complex dynamical networks (CDNs). Based on algebraic graph theory and Lyapunov theory, pinning controller design conditions are derived, and the rigorous convergence analysis of synchronization errors in the probability sense is also conducted. Compared with the existing results, the topology structures of stochastic CDN are allowed to be unknown due to the use of graph theory. In particular, it is shown that the selection of nodes for pinning depends on the unknown lower bounds of coupling strengths. Finally, an example on a Chua's circuit network is given to validate the effectiveness of the theoretical results.

  19. Asymptotic theory for the dynamic of networks with heterogenous social capital allocation

    CERN Document Server

    Ubaldi, Enrico; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

    2015-01-01

    The structure and dynamic of social network are largely determined by the heterogeneous interaction activity and social capital allocation of individuals. These features interplay in a non-trivial way in the formation of network and challenge a rigorous dynamical system theory of network evolution. Here we study seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the node's activity and social capital allocation can be described by two general functional forms that can be used to define a simple stochastic model for social network dynamic. This model allows the explicit asymptotic solution of the Master Equation describing the system dynamic, and provides the scaling laws characterizing the time evolution of the social network degree distribution and individual node's ego network. The analytical predictions reproduce with accuracy the empirical observations validating the theoretical approach....

  20. 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.

  1. 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.

  2. Accuracy of mean-field theory for dynamics on real-world networks.

    Science.gov (United States)

    Gleeson, James P; Melnik, Sergey; Ward, Jonathan A; Porter, Mason A; Mucha, Peter J

    2012-02-01

    Mean-field analysis is an important tool for understanding dynamics on complex networks. However, surprisingly little attention has been paid to the question of whether mean-field predictions are accurate, and this is particularly true for real-world networks with clustering and modular structure. In this paper, we compare mean-field predictions to numerical simulation results for dynamical processes running on 21 real-world networks and demonstrate that the accuracy of such theory depends not only on the mean degree of the networks but also on the mean first-neighbor degree. We show that mean-field theory can give (unexpectedly) accurate results for certain dynamics on disassortative real-world networks even when the mean degree is as low as 4.

  3. 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.

  4. Statistical theory of designed quantum transport across disordered networks

    Science.gov (United States)

    Walschaers, Mattia; Mulet, Roberto; Wellens, Thomas; Buchleitner, Andreas

    2015-04-01

    We explain how centrosymmetry, together with a dominant doublet of energy eigenstates in the local density of states, can guarantee interference-assisted, strongly enhanced, strictly coherent quantum excitation transport between two predefined sites of a random network of two-level systems. Starting from a generalization of the chaos-assisted tunnelling mechanism, we formulate a random matrix theoretical framework for the analytical prediction of the transfer time distribution, of lower bounds of the transfer efficiency, and of the scaling behavior of characteristic statistical properties with the size of the network. We show that these analytical predictions compare well to numerical simulations, using Hamiltonians sampled from the Gaussian orthogonal ensemble.

  5. 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.

  6. Tuning RED parameters in satellite networks using control theory

    Science.gov (United States)

    Sridharan, Mukundan; Durresi, Arjan; Chellappan, Sriram; Ozbay, Hitay; Jain, Raj

    2003-08-01

    Congestion in the Internet results in wasted bandwidth and also stands in the way of guaranteeing QoS. The effect of congestion is multiplied many fold in Satellite networks, where the resources are very expensive. Thus congestion control has a special significance in the performance of Satellite networks. In today's Internet, congestion control is implemented mostly using some form of the de facto standard, RED. But tuning of parameters in RED has been a major problem throughout. Achieving high throughput with corresponding low delays is the main goal in parameter setting. It is also desired to keep the oscillations in the queue low to reduce jitter, so that the QoS guarantees can be improved. In this paper, we use a previously linearized fluid flow model of TCP-RED to study the performance and stability of the Queue in the router. We use classical control tools like Tracking Error minimization and Delay Margin to study the performance, stability of the system. We use the above-mentioned tools to provide guidelines for setting the parameters in RED, such that the throughput, delay and jitter of the system are optimized. Thus we provide guidelines for optimizing satellite IP networks. We apply our results exclusively for optimizing the performance of satellite networks, where the effects of congestion are much pronounced and need for optimization is much important. We use ns simulator to validate our results to support our analysis.

  7. Workshop: Theory an Applications of Coupled Cell Networks

    Science.gov (United States)

    2006-03-22

    Economia and Centro de Matematica , Universidade do Porto) Application of coupled cell systems have been made to a wide range of problems in the physical and...Departamento de Matematica Pura da Faculdade de Ciencias do Porto) As pointed by [1], in the class of coupled cell networks that permits self-coupling

  8. On Optimal Policies for Network Coded Cooperation: Theory and Implementation

    DEFF Research Database (Denmark)

    Khamfroush, Hana; Lucani Rötter, Daniel Enrique; Pahlevani, Peyman

    2014-01-01

    's Raspberry Pi testbed and compared with random linear network coding (RLNC) broadcast in terms of completion time, total number of required transmissions, and percentage of delivered generations. Our measurements show that enabling cooperation only among pairs of devices can decrease the completion time...

  9. 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...

  10. 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

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

    African Journals Online (AJOL)

    The paper reveals that the application of AANT methodology made it possible to trace relationships, actors, actants and actor/actant-networks surrounding the Plastic Bags Regulations as quasi-object (token). The methodology also enabled a focus on understanding and investigating tensions, debates and responses ...

  12. Increased segregation of brain networks in focal epilepsy: An fMRI graph theory finding.

    Science.gov (United States)

    Pedersen, Mangor; Omidvarnia, Amir H; Walz, Jennifer M; Jackson, Graeme D

    2015-01-01

    Focal epilepsy is conceived of as activating local areas of the brain as well as engaging regional brain networks. Graph theory represents a powerful quantitative framework for investigation of brain networks. Here we investigate whether functional network changes are present in extratemporal focal epilepsy. Task-free functional magnetic resonance imaging data from 15 subjects with extratemporal epilepsy and 26 age and gender matched healthy controls were used for analysis. Local network properties were calculated using local efficiency, clustering coefficient and modularity metrics. Global network properties were assessed with global efficiency and betweenness centrality metrics. Cost-efficiency of the networks at both local and global levels was evaluated by estimating the physical distance between functionally connected nodes, in addition to the overall numbers of connections in the network. Clustering coefficient, local efficiency and modularity were significantly higher in individuals with focal epilepsy than healthy control subjects, while global efficiency and betweenness centrality were not significantly different between the two groups. Local network properties were also highly efficient, at low cost, in focal epilepsy subjects compared to healthy controls. Our results show that functional networks in focal epilepsy are altered in a way that the nodes of the network are more isolated. We postulate that network regularity, or segregation of the nodes of the networks, may be an adaptation that inhibits the conversion of the interictal state to seizures. It remains possible that this may be part of the epileptogenic process or an effect of medications.

  13. Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

    Science.gov (United States)

    Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

    2017-01-01

    Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary

  14. Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

    Directory of Open Access Journals (Sweden)

    Anke Meyer-Bäse

    2017-10-01

    Full Text Available Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and

  15. A Balanced Theory of Sourcing, Collaboration and Networks

    NARCIS (Netherlands)

    B. Nooteboom (Bart)

    2002-01-01

    textabstractIn a synthesis of recent advances, this article gives a fresh, balanced theory of inter-organizational relations. It integrates competence and governance perspectives. It considers the choice between mergers/acquisitions and alliances. It offers a toolbox of instruments to govern

  16. Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

    Science.gov (United States)

    Calvin, Nicholas T; J McDowell, J

    2015-11-01

    For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. Dynamical Systems Theory for Transparent Symbolic Computation in Neuronal Networks

    OpenAIRE

    Carmantini, Giovanni Sirio

    2017-01-01

    In this thesis, we explore the interface between symbolic and dynamical system computation, with particular regard to dynamical system models of neuronal networks. In doing so, we adhere to a definition of computation as the physical realization of a formal system, where we say that a dynamical system performs a computation if a correspondence can be found between its dynamics on a vectorial space and the formal system’s dynamics on a symbolic space. Guided by this definition, we characterize...

  18. Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior

    OpenAIRE

    Nicholas A Christakis; Fowler, James H.

    2011-01-01

    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 ...

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

    OpenAIRE

    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 research setting, we investigate, in four empirical papers using different sources and methods, how innovative behavior can be supported, influenced, or changed. Within this context, we concentrate ...

  20. 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.

  1. A Balanced Theory of Sourcing, Collaboration and Networks

    OpenAIRE

    Nooteboom, Bart

    2002-01-01

    textabstractIn a synthesis of recent advances, this article gives a fresh, balanced theory of inter-organizational relations. It integrates competence and governance perspectives. It considers the choice between mergers/acquisitions and alliances. It offers a toolbox of instruments to govern relational risk, and the contingencies for their selection. Relationships can last too long. Therefore, the article also looks at how to end relationships. Beyond dyads of collaborating firms, it includes...

  2. 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.

  3. Information theory in systems biology. Part II: protein-protein interaction and signaling networks.

    Science.gov (United States)

    Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali

    2016-03-01

    By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. 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.

  5. Functional neural networks of honesty and dishonesty in children: Evidence from graph theory analysis.

    Science.gov (United States)

    Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang

    2017-09-21

    The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Wang, Xin; Wang, Ying; Sun, Hongbin

    2016-01-01

    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.

  9. 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.

  10. 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.

  11. Change Agents, Networks, and Institutions: A Contingency Theory of Organizational Change

    OpenAIRE

    Battilana, Julie; Casciaro, Tiziana

    2012-01-01

    We develop a contingency theory for how structural closure in a network, defined as the extent to which an actor’s network contacts are connected to one another, affects the initiation and adoption of change in organizations. Using longitudinal survey data supplemented with eight in-depth case studies, we analyze 68 organizational change initiatives undertaken in the United Kingdom’s National Health Service. We show that low levels of structural closure (i.e., structural holes) in a change ag...

  12. Tracing structure, tie Strength, and cognitive networks in LMX theory and research

    OpenAIRE

    Sparrowe, Raymond T.; Emery, Cécile

    2015-01-01

    This chapter reflects on the growing relationship between Leader–Member Exchange (LMX) theory and research and social network analysis. We first discuss the themes of structure and tie strength in relation to several of the theoretical formulations of LMX theory that have served as the foundation for subsequent research. This section proceeds chronologically, beginning with the earliest work on the Vertical Dyad Linkage (as the LMX perspective was initially known) and concluding with recent e...

  13. Power system cascading risk assessment based on complex network theory

    Science.gov (United States)

    Wang, Zhuoyang; Hill, David J.; Chen, Guo; Dong, Zhao Yang

    2017-09-01

    When a single failure occurs in a vulnerable part of a power system, this may cause a large area cascading event. Therefore, an advanced method that can assess the risks during cascading events is needed. In this paper, an improved complex network model for power system risk assessment is proposed. Risk is defined by consequence and probability of the failures in this model, which are affected by both power factors and network structure. Compared with existing risk assessment models, the proposed one can evaluate the risk of the system comprehensively during a cascading event by combining the topological and electrical information. A new cascading event simulation module is adopted to identify the power grid cascading chain from a system-level view. In addition, simulations are investigated on the IEEE 14 bus system and IEEE 39 bus system respectively to illustrate the performance of the proposed module. The simulation results demonstrate that the proposed method is effective in a power grid risk assessment during cascading event.

  14. Associative nature of event participation dynamics: A network theory approach

    Science.gov (United States)

    Smiljanić, Jelena; Mitrović Dankulov, Marija

    2017-01-01

    The affiliation with various social groups can be a critical factor when it comes to quality of life of each individual, making such groups an essential element of every society. The group dynamics, longevity and effectiveness strongly depend on group’s ability to attract new members and keep them engaged in group activities. It was shown that high heterogeneity of scientist’s engagement in conference activities of the specific scientific community depends on the balance between the numbers of previous attendances and non-attendances and is directly related to scientist’s association with that community. Here we show that the same holds for leisure groups of the Meetup website and further quantify individual members’ association with the group. We examine how structure of personal social networks is evolving with the event attendance. Our results show that member’s increasing engagement in the group activities is primarily associated with the strengthening of already existing ties and increase in the bonding social capital. We also show that Meetup social networks mostly grow trough big events, while small events contribute to the groups cohesiveness. PMID:28166305

  15. 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.

  16. Massive-Scale Gene Co-Expression Network Construction and Robustness Testing Using Random Matrix Theory

    Science.gov (United States)

    Isaacson, Sven; Luo, Feng; Feltus, Frank A.; Smith, Melissa C.

    2013-01-01

    The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust. PMID:23409071

  17. Associative nature of event participation dynamics: a network theory approach

    CERN Document Server

    Smiljanić, Jelena

    2016-01-01

    Affiliation with various social groups can be a critical factor when it comes to quality of life of every individual, making these groups an essential element of every society. The group dynamics, longevity and effectiveness strongly depend on group's ability to attract new members and keep them engaged in group activities. It was shown that high heterogeneity of scientist's engagement in conference activities of the specific scientific community depends on the balance between the number of previous attendance and non-attendance and is directly related to scientist's association with that community. Here we show that the same holds for leisure groups of Meetup website and further quantify member's association with the group. We examine how structure of personal social networks is evolving with event attendance. Our results show that member's increasing engagement in group activities is primarily associated with the strengthening of already existing ties and increase of bonding social capital. We also show tha...

  18. Delinquency, Social Skills and the Structure of Peer Relations: Assessing Criminological Theories by Social Network Theory

    Science.gov (United States)

    Smangs, Mattias

    2010-01-01

    This article explores the plausibility of the conflicting theoretical assumptions underlying the main criminological perspectives on juvenile delinquents, their peer relations and social skills: the social ability model, represented by Sutherland's theory of differential associations, and the social disability model, represented by Hirschi's…

  19. Wilson punctured network defects in 2D q-deformed Yang-Mills theory

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Noriaki [Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo,Kashiwa, Chiba 277-8583 (Japan)

    2016-12-14

    In the context of class S theories and 4D/2D duality relations there, we discuss the skein relations of general topological defects on the 2D side which are expected to be counterparts of composite surface-line operators in 4D class S theory. Such defects are geometrically interpreted as networks in a three dimensional space. We also propose a conjectural computational procedure for such defects in two dimensional SU(N) topological q-deformed Yang-Mills theory by interpreting it as a statistical mechanical system associated with ideal triangulations.

  20. A network theory approach for a better understanding of overland flow connectivity

    Science.gov (United States)

    Masselink, Rens; Heckmann, Tobias; Temme, Arnaud; Anders, Niels; Keesstra, Saskia

    2016-04-01

    Hydrological connectivity describes the physical coupling, or linkages of different elements within a landscape regarding (sub)surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for e.g. habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has been recognised within the scientific community as well, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterise overland flow connectivity dynamics on hillslopes in a humid sub-Mediterranean environment by using a combination of high-resolution digital-terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow on agricultural areas and semi-natural shrubs areas. Positive correlations between connectivity and precipitation characteristics were found, while negative correlations between connectivity and soil moisture were found, probably due to soil water repellency. The combination of a structural network to determine potential connectivity with dynamic networks to determine the actual connectivity proved a powerful tool in analysing overland flow connectivity.

  1. Can We Control Contaminant Transport In Hydrologic Networks? Application Of Control Theory Concepts To Watershed Management

    Science.gov (United States)

    Yeghiazarian, L.; Riasi, M. S.

    2016-12-01

    Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.

  2. 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.

  3. 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.

  4. 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

    2016-01-01

    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. PMID:27367700

  5. 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,

  6. 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.

  7. 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.

  8. 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

  9. Fragmentation network of doubly charged methionine: Interpretation using graph theory

    Science.gov (United States)

    Ha, D. T.; Yamazaki, K.; Wang, Y.; Alcamí, M.; Maeda, S.; Kono, H.; Martín, F.; Kukk, E.

    2016-09-01

    The fragmentation of doubly charged gas-phase methionine (HO2CCH(NH2)CH2CH2SCH3) is systematically studied using the self-consistent charge density functional tight-binding molecular dynamics (MD) simulation method. We applied graph theory to analyze the large number of the calculated MD trajectories, which appears to be a highly effective and convenient means of extracting versatile information from the large data. The present theoretical results strongly concur with the earlier studied experimental ones. Essentially, the dication dissociates into acidic group CO2H and basic group C4NSH10. The former may carry a single or no charge and stays intact in most cases, whereas the latter may hold either a single or a double charge and tends to dissociate into smaller fragments. The decay of the basic group is observed to follow the Arrhenius law. The dissociation pathways to CO2H and C4NSH10 and subsequent fragmentations are also supported by ab initio calculations.

  10. 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.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Hong Zhang

    2015-01-01

    Full Text Available 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

  13. 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

  14. 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

  15. Team Sports Performance Analysed Through the Lens of Social Network Theory: Implications for Research and Practice.

    Science.gov (United States)

    Ribeiro, João; Silva, Pedro; Duarte, Ricardo; Davids, Keith; Garganta, Júlio

    2017-09-01

    This paper discusses how social network analyses and graph theory can be implemented in team sports performance analyses to evaluate individual (micro) and collective (macro) performance data, and how to use this information for designing practice tasks. Moreover, we briefly outline possible limitations of social network studies and provide suggestions for future research. Instead of cataloguing discrete events or player actions, it has been argued that researchers need to consider the synergistic interpersonal processes emerging between teammates in competitive performance environments. Theoretical assumptions on team coordination prompted the emergence of innovative, theoretically driven methods for assessing collective team sport behaviours. Here, we contribute to this theoretical and practical debate by re-conceptualising sports teams as complex social networks. From this perspective, players are viewed as network nodes, connected through relevant information variables (e.g. a ball-passing action), sustaining complex patterns of interaction between teammates (e.g. a ball-passing network). Specialised tools and metrics related to graph theory could be applied to evaluate structural and topological properties of interpersonal interactions of teammates, complementing more traditional analysis methods. This innovative methodology moves beyond the use of common notation analysis methods, providing a richer understanding of the complexity of interpersonal interactions sustaining collective team sports performance. The proposed approach provides practical applications for coaches, performance analysts, practitioners and researchers by establishing social network analyses as a useful approach for capturing the emergent properties of interactions between players in sports teams.

  16. 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.

  17. Cyberspace Assurance Metrics: Utilizing Models of Networks, Complex Systems Theory, Multidimensional Wavelet Analysis, and Generalized Entrophy Measures

    National Research Council Canada - National Science Library

    Johnson, Joseph E; Gudkov, Vladimir

    2005-01-01

    ... as continuous group theory and Markov processes. Based upon this research he has proposed that entropy metrics, and the associated cluster analysis of the network so measured by these metrics, can be useful indicators of aberrant processes and behavior. Other team members have obtained important connections using higher order Renyi entropy metrics, and complexity theory to both monitor real networks and to study networks by simulation.

  18. 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

    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......, affordable loss, and other key concepts from this theoretical perspective. Drawing upon actor-network theory (ANT), this study demonstrates how different framing and support devices implicate different human and non-human actors in changing interpositions within the entrepreneurial process. Design...... interviews. This design allows the authors to focus on how the project emerges and is continuously supported by allies but is sometimes not supported by various human and non-human actors. Findings This study demonstrates that the entrepreneurial project undertaken by the entrepreneurial network changes...

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

    Directory of Open Access Journals (Sweden)

    Rodica Ioana Lung

    Full Text Available 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.

  20. 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.

  1. Strengthening prevention program theories and evaluations: contributions from social network analysis.

    Science.gov (United States)

    Gest, Scott D; Osgood, D Wayne; Feinberg, Mark E; Bierman, Karen L; Moody, James

    2011-12-01

    A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools' organizational, cultural or instructional systems that influence children's relationships), or implicitly (e.g., by altering behavioral norms designed to influence children's social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science--both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts.

  2. Using Social Networks Theory as a Complementary Perspective to the Study of Organizational Change

    Directory of Open Access Journals (Sweden)

    Manuel Portugal Ferreira

    2011-04-01

    Full Text Available This paper contributes to the literature on organizational change by examining organizations as social entities embedded in inter-organizational networks. In contrast with extant research that focuses on macro environmental and internal factors to explain organizational change, we put forth the social network surrounding the firm as a major driver of any change process. Specifically, we examine organizational change as driven by the organizations’ positions and relations in an interorganizational network, and advance a set of theory driven propositions on innovation, imitation, inertia, structural equivalence and structural positioning. Our conceptual discussion demonstrates that inter-organizational networks are important in complementing the macro-environment and internal organizational factors for the study of organizational changes. We conclude with a discussion on normative implications for organizations and avenues for future research.

  3. Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

    Science.gov (United States)

    Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

    2017-01-01

    Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

  4. 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.

  5. 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

  6. Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy.

    Science.gov (United States)

    Gleichgerrcht, Ezequiel; Kocher, Madison; Bonilha, Leonardo

    2015-11-01

    The assessment of neural networks in epilepsy has become increasingly relevant in the context of translational research, given that localized forms of epilepsy are more likely to be related to abnormal function within specific brain networks, as opposed to isolated focal brain pathology. It is notable that variability in clinical outcomes from epilepsy treatment may be a reflection of individual patterns of network abnormalities. As such, network endophenotypes may be important biomarkers for the diagnosis and treatment of epilepsy. Despite its exceptional potential, measuring abnormal networks in translational research has been thus far constrained by methodologic limitations. Fortunately, recent advancements in neuroscience, particularly in the field of connectomics, permit a detailed assessment of network organization, dynamics, and function at an individual level. Data from the personal connectome can be assessed using principled forms of network analyses based on graph theory, which may disclose patterns of organization that are prone to abnormal dynamics and epileptogenesis. Although the field of connectomics is relatively new, there is already a rapidly growing body of evidence to suggest that it can elucidate several important and fundamental aspects of abnormal networks to epilepsy. In this article, we provide a review of the emerging evidence from connectomics research regarding neural network architecture, dynamics, and function related to epilepsy. We discuss how connectomics may bring together pathophysiologic hypotheses from conceptual and basic models of epilepsy and in vivo biomarkers for clinical translational research. By providing neural network information unique to each individual, the field of connectomics may help to elucidate variability in clinical outcomes and open opportunities for personalized medicine approaches to epilepsy. Connectomics involves complex and rich data from each subject, thus collaborative efforts to enable the

  7. 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.

  8. A quantitative theory of the functions of the hippocampal CA3 network in memory.

    Science.gov (United States)

    Rolls, Edmund T

    2013-01-01

    A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory.

  9. 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.

  10. On the Contributions of a Network Approach to Personality Theory and Research.

    Science.gov (United States)

    Furr, R Michael; Fleeson, William; Anderson, Michelle; Arnold, Elizabeth Mayfield

    2012-07-01

    Understanding personality structure and processes is one of the most fundamental goals in personality psychology. The network approach presented by Cramer et al. represents a useful path toward this goal, and we address two facets of their approach. First, we examine the possibility that it solves the problem of breadth, which has inhibited the integration of trait theory with social cognitive theory. Second, we evaluate the value and usability of their proposed method (qgraph), doing so by conducting idiographic analyses of the symptom structure of Borderline Personality Disorder.

  11. Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy.

    Science.gov (United States)

    Bernhardt, Boris C; Bonilha, Leonardo; Gross, Donald W

    2015-09-01

    Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Application of Chaos Theory and Artificial Neural Networks to Evaluate Evaporation from Lake's Water Surface

    Directory of Open Access Journals (Sweden)

    Saeed Farzin

    2017-06-01

    Full Text Available Introduction: Dynamic nature of hydrological phenomena and the limited availability of appropriate mathematical tools caused the most previous studies in this field led to the random and the probabilistic approach. So selection the best model for evaluation of these phenomena is essential and complex. Nowadays different models are used for evaluation and prediction of hydrological phenomena. Damle and Yalcin (2007 estimated river runoff by chaos theory. khatibi et al (2012 used artificial neural network and gene expression programming to predict relative humidity. Zounemat and Kisi (2015 evaluated chaotic behavior of marine wind-wave system of Caspian sea. One of the important hydrological phenomena is evaporation, especially in lakes. The investigation of deterministic and stochastic behavior of water evaporation values in the lakes in order to select the best simulation approach and capable of prediction is an important and controversial issue that has been studied in this research. Materials and Methods: In the present paper, monthly values of evaporation are evaluated by two different models. Chaos theory and artificial neural network are used for the analysis of stochastic behavior and capability of prediction of water evaporation values in the Urmia Lake in northwestern of Iran. In recent years, Urmia Lake has unpleasant changes and drop in water level due to inappropriate management and climate change. One of the important factors related to climate change, is evaporation. Urmia Lake is a salt lake, and because of existence valuable ecology, environmental issues and maintenance of ecosystems of this lake are very important. So evaporation can have an essential role in the salinity, environmental and the hydrological cycle of the lake. In this regard, according to the ability of chaos theory and artificial neural network to analysis nonlinear dynamic systems; monthly values of evaporation, during a 40-year period, are investigated and then

  13. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory

    Science.gov (United States)

    Luo, Feng; Yang, Yunfeng; Zhong, Jianxin; Gao, Haichun; Khan, Latifur; Thompson, Dorothea K; Zhou, Jizhong

    2007-01-01

    Background Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many individual functional modules. Defining co-expression networks without ambiguity based on genome-wide microarray data is difficult and current methods are not robust and consistent with different data sets. This is particularly problematic for little understood organisms since not much existing biological knowledge can be exploited for determining the threshold to differentiate true correlation from random noise. Random matrix theory (RMT), which has been widely and successfully used in physics, is a powerful approach to distinguish system-specific, non-random properties embedded in complex systems from random noise. Here, we have hypothesized that the universal predictions of RMT are also applicable to biological systems and the correlation threshold can be determined by characterizing the correlation matrix of microarray profiles using random matrix theory. Results Application of random matrix theory to microarray data of S. oneidensis, E. coli, yeast, A. thaliana, Drosophila, mouse and human indicates that there is a sharp transition of nearest neighbour spacing distribution (NNSD) of correlation matrix after gradually removing certain elements insider the matrix. Testing on an in silico modular model has demonstrated that this transition can be used to determine the correlation threshold for revealing modular co-expression networks. The co-expression network derived from yeast cell cycling microarray data is supported by gene annotation. The topological properties of the resulting co-expression network agree well with the general properties of biological networks. Computational evaluations have showed that RMT approach is sensitive and robust. Furthermore, evaluation on sampled expression data of an in silico modular gene system has showed that under-sampled expressions do not affect the

  14. Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory.

    Science.gov (United States)

    Luo, Feng; Yang, Yunfeng; Zhong, Jianxin; Gao, Haichun; Khan, Latifur; Thompson, Dorothea K; Zhou, Jizhong

    2007-08-14

    Large-scale sequencing of entire genomes has ushered in a new age in biology. One of the next grand challenges is to dissect the cellular networks consisting of many individual functional modules. Defining co-expression networks without ambiguity based on genome-wide microarray data is difficult and current methods are not robust and consistent with different data sets. This is particularly problematic for little understood organisms since not much existing biological knowledge can be exploited for determining the threshold to differentiate true correlation from random noise. Random matrix theory (RMT), which has been widely and successfully used in physics, is a powerful approach to distinguish system-specific, non-random properties embedded in complex systems from random noise. Here, we have hypothesized that the universal predictions of RMT are also applicable to biological systems and the correlation threshold can be determined by characterizing the correlation matrix of microarray profiles using random matrix theory. Application of random matrix theory to microarray data of S. oneidensis, E. coli, yeast, A. thaliana, Drosophila, mouse and human indicates that there is a sharp transition of nearest neighbour spacing distribution (NNSD) of correlation matrix after gradually removing certain elements insider the matrix. Testing on an in silico modular model has demonstrated that this transition can be used to determine the correlation threshold for revealing modular co-expression networks. The co-expression network derived from yeast cell cycling microarray data is supported by gene annotation. The topological properties of the resulting co-expression network agree well with the general properties of biological networks. Computational evaluations have showed that RMT approach is sensitive and robust. Furthermore, evaluation on sampled expression data of an in silico modular gene system has showed that under-sampled expressions do not affect the recovery of gene

  15. A complex network theory approach for optimizing contamination warning sensor location in water distribution networks

    OpenAIRE

    Nazempour, Rezvan; Monfared, Mohammad Ali Saniee; Zio, Enrico

    2016-01-01

    Drinking water for human health and well-being is crucial. Accidental and intentional water contamination can pose great danger to consumers. Optimal design of a system that can quickly detect the presence of contamination in a water distribution network is very challenging for technical and operational reasons. However, on the one hand improvement in chemical and biological sensor technology has created the possibility of designing efficient contamination detection systems. On the other hand...

  16. Contextualized Network Analysis: Theory and Methods for Networks with Node Covariates

    Science.gov (United States)

    Binkiewicz, Norbert M.

    Biological and social systems consist of myriad interacting units. The interactions can be intuitively represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as neuroconnectomics, social networks, and genomics, graph data is accompanied by contextualizing measures on each node. We leverage these node covariates to help uncover latent communities, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model called the node contextualized stochastic blockmodel, including a bound on the mis-clustering rate. For most simulated conditions, covariate assisted spectral clustering yields superior results relative to both regularized spectral clustering without node covariates and an adaptation of canonical correlation analysis. We apply covariate assisted spectral clustering to large brain graphs derived from diffusion MRI, using the node locations or neurological regions as covariates. In both cases, covariate assisted spectral clustering yields clusters that are easier to interpret neurologically. A low rank update algorithm is developed to reduce the computational cost of determining the tuning parameter for covariate assisted spectral clustering. As simulations demonstrate, the low rank update algorithm increases the speed of covariate assisted spectral clustering up to ten-fold, while practically matching the clustering performance of the standard algorithm. Graphs with node attributes are sometimes accompanied by ground truth labels that align closely with the latent communities in the graph. We consider the example of a mouse retina neuron network accompanied by the neuron spatial location and neuronal cell types. In this example, the neuronal cell type is considered a ground truth label. Current approaches for defining neuronal cell type vary

  17. Taking data seriously: the value of actor-network theory in rethinking patient experience data.

    Science.gov (United States)

    Desai, Amit; Zoccatelli, Giulia; Adams, Mary; Allen, Davina; Brearley, Sally; Rafferty, Anne Marie; Robert, Glenn; Donetto, Sara

    2017-04-01

    Hospitals are awash with patient experience data, much of it collected with the ostensible purpose of improving the quality of patient care. However, there has been comparatively little consideration of the nature and capacities of data itself. Using insights from actor-network theory, we propose that paying attention to patient experience data as having agency in particular hospital interactions allows us to better trace how and in what circumstances data lead (or fail to lead) to quality improvement.

  18. Partial orders for zero-sum arrays with applications to network theory

    OpenAIRE

    Liu, Yunjun; Rousseau, Ronald; Egghe, Leo

    2017-01-01

    In this contribution we study partial orders in the set of zero-sum arrays. Concretely, these partial orders relate to local and global hierarchy and dominance theories. The exact relation between hierarchy and dominance curves is explained. Based on this investigation we design a new approach for measuring dominance or stated otherwise, power structures, in networks. A new type of Lorenz curve to measure dominance or power is proposed, and used to illustrate intrinsic characteristics of netw...

  19. 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.

  20. 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.

  1. 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.

  2. Analysing human mobility patterns of hiking activities through complex network theory.

    Science.gov (United States)

    Lera, Isaac; Pérez, Toni; Guerrero, Carlos; Eguíluz, Víctor M; Juiz, Carlos

    2017-01-01

    The exploitation of high volume of geolocalized data from social sport tracking applications of outdoor activities can be useful for natural resource planning and to understand the human mobility patterns during leisure activities. This geolocalized data represents the selection of hike activities according to subjective and objective factors such as personal goals, personal abilities, trail conditions or weather conditions. In our approach, human mobility patterns are analysed from trajectories which are generated by hikers. We propose the generation of the trail network identifying special points in the overlap of trajectories. Trail crossings and trailheads define our network and shape topological features. We analyse the trail network of Balearic Islands, as a case of study, using complex weighted network theory. The analysis is divided into the four seasons of the year to observe the impact of weather conditions on the network topology. The number of visited places does not decrease despite the large difference in the number of samples of the two seasons with larger and lower activity. It is in summer season where it is produced the most significant variation in the frequency and localization of activities from inland regions to coastal areas. Finally, we compare our model with other related studies where the network possesses a different purpose. One finding of our approach is the detection of regions with relevant importance where landscape interventions can be applied in function of the communities.

  3. 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.

  4. Theory of electromagnetic transmission structures. I - Relativistic foundation and network formalisms

    Science.gov (United States)

    Gabriel, G. J.

    1980-01-01

    A new theorem on a class of four-dimensional skew-symmetric tensors is demonstrated. Coupled with the relativistic covariant form of Maxwell's equations, this theorem consolidates the classifications of guided waves by combining the three types - TE, TM, TEM - under a uniform condition applied to the generating four-potential which is Lorentz invariant. Each type corresponds to a potential of which a pair of the four components vanishes in a particular frame. Through appropriate normalization conditions, the resulting time-domain equations for the field amplitudes are readily reduced to modified telegraphist equations, which in turn lead to distributed network representations for each of the three types. The ambiguity of distributed network formalisms in general is elucidated and the concept of network parameter densities such as traditionally employed in TEM transmission line theory is questioned.

  5. 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...

  6. 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.

  7. 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.

  8. The Elastic Behaviour of Sintered Metallic Fibre Networks: A Finite Element Study by Beam Theory.

    Directory of Open Access Journals (Sweden)

    Wolfram A Bosbach

    Full Text Available The finite element method has complimented research in the field of network mechanics in the past years in numerous studies about various materials. Numerical predictions and the planning efficiency of experimental procedures are two of the motivational aspects for these numerical studies. The widespread availability of high performance computing facilities has been the enabler for the simulation of sufficiently large systems.In the present study, finite element models were built for sintered, metallic fibre networks and validated by previously published experimental stiffness measurements. The validated models were the basis for predictions about so far unknown properties.The finite element models were built by transferring previously published skeletons of fibre networks into finite element models. Beam theory was applied as simplification method.The obtained material stiffness isn't a constant but rather a function of variables such as sample size and boundary conditions. Beam theory offers an efficient finite element method for the simulated fibre networks. The experimental results can be approximated by the simulated systems. Two worthwhile aspects for future work will be the influence of size and shape and the mechanical interaction with matrix materials.

  9. Understanding cancer complexome using networks, spectral graph theory and multilayer framework

    Science.gov (United States)

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K.; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-01

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  10. Analytical theory of polymer-network-mediated interaction between colloidal particles.

    Science.gov (United States)

    Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika

    2012-06-26

    Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented.

  11. The Elastic Behaviour of Sintered Metallic Fibre Networks: A Finite Element Study by Beam Theory.

    Science.gov (United States)

    Bosbach, Wolfram A

    2015-01-01

    The finite element method has complimented research in the field of network mechanics in the past years in numerous studies about various materials. Numerical predictions and the planning efficiency of experimental procedures are two of the motivational aspects for these numerical studies. The widespread availability of high performance computing facilities has been the enabler for the simulation of sufficiently large systems. In the present study, finite element models were built for sintered, metallic fibre networks and validated by previously published experimental stiffness measurements. The validated models were the basis for predictions about so far unknown properties. The finite element models were built by transferring previously published skeletons of fibre networks into finite element models. Beam theory was applied as simplification method. The obtained material stiffness isn't a constant but rather a function of variables such as sample size and boundary conditions. Beam theory offers an efficient finite element method for the simulated fibre networks. The experimental results can be approximated by the simulated systems. Two worthwhile aspects for future work will be the influence of size and shape and the mechanical interaction with matrix materials.

  12. Understanding cancer complexome using networks, spectral graph theory and multilayer framework.

    Science.gov (United States)

    Rai, Aparna; Pradhan, Priodyuti; Nagraj, Jyothi; Lohitesh, K; Chowdhury, Rajdeep; Jalan, Sarika

    2017-02-03

    Cancer complexome comprises a heterogeneous and multifactorial milieu that varies in cytology, physiology, signaling mechanisms and response to therapy. The combined framework of network theory and spectral graph theory along with the multilayer analysis provides a comprehensive approach to analyze the proteomic data of seven different cancers, namely, breast, oral, ovarian, cervical, lung, colon and prostate. Our analysis demonstrates that the protein-protein interaction networks of the normal and the cancerous tissues associated with the seven cancers have overall similar structural and spectral properties. However, few of these properties implicate unsystematic changes from the normal to the disease networks depicting difference in the interactions and highlighting changes in the complexity of different cancers. Importantly, analysis of common proteins of all the cancer networks reveals few proteins namely the sensors, which not only occupy significant position in all the layers but also have direct involvement in causing cancer. The prediction and analysis of miRNAs targeting these sensor proteins hint towards the possible role of these proteins in tumorigenesis. This novel approach helps in understanding cancer at the fundamental level and provides a clue to develop promising and nascent concept of single drug therapy for multiple diseases as well as personalized medicine.

  13. 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

  14. 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.

  15. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare

    National Research Council Canada - National Science Library

    Cresswell, Kathrin M; Worth, Allison; Sheikh, Aziz

    2010-01-01

    .... We argue that health services research, and in particular evaluations of complex IT systems in health service organisations, may benefit from being informed by Actor-Network Theory perspectives...

  16. 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.

  17. Unpacking complexity in public health interventions with the Actor-Network Theory.

    Science.gov (United States)

    Bilodeau, Angèle; Potvin, Louise

    2016-08-04

    This article proposes a sociologically informed theoretical and methodological framework to address the complexity of public health interventions (PHI). It first proposes three arguments in favour of using the Actor-Network Theory (ANT) for the framework. ANT: (1) deals with systems made of human and non-human entities and proposes a relational view of action; (2) provides an understanding of the intervention-context interactions and (3) is a tool for opening the intervention's black box. Three principles derived from ANT addressing theoretical problems with conceptualisation of PHI as complex systems are proposed: (1) to focus on the process of connecting the network entities instead of their stabilised form; (2) both human and non-human entities composing networks have performative capacities and (3) network and intervention shape one another. Three methodological guidelines are further derived: (1) the researcher's task consists in documenting the events that transform the network and intervention; (2) events must be ordered chronologically to represent the intervention's evolution and (3) a broad range of data is needed to capture complex interventions' evolution. Using ANT as a guide, this paper helps reconcile technicist and social views of PHI and provides a mean to integrate process and effect studies of interventions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  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. 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.

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

    Science.gov (United States)

    van Wijk, Bernadette C M; Stam, Cornelis J; Daffertshofer, Andreas

    2010-10-28

    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.

  2. 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.

  3. 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.

  4. Research progress of multimodal MRI and complex network analysis based on graph theory in Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Ming-jin MEI

    2017-01-01

    Full Text Available Parkinson's disease (PD is a common progressive neurodegenerative disease and is mainly caused by dopamine neuron degeneration in the substantia nigra pars compacta of the human brain. It has become "the third killer" after tumor and cardio-cerebrovascular disease in middle-aged and elderly people at present. In recent years, the development of multimodal MRI [including structural MRI (sMRI, functional MRI (fMRI, diffusion tension imaging (DTI, etc.] and the introduction of complex network analysis based on graph theory provide a new and effective method for researchers to explore the changes of brain structure and function in PD patients. The article mainly reviews the research progress of structural and functional brain networks in PD patients that are established based on multimodal MRI and complex network analysis based on graph theory, so as to provide new imaging markers for the early diagnosis of PD. DOI: 10.3969/j.issn.1672-6731.2017.01.004

  5. 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.

  6. 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.

  7. 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 (ptheory of mind performance were both associated with altered connectivity of default regions within the patient group (ptheory of mind 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.

  8. 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.

  9. [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.

  10. Toward an Analytical and Methodological Understanding of Actor-Network Theory

    Directory of Open Access Journals (Sweden)

    Sharon Jackson

    2015-02-01

    Full Text Available Actor-Network theory (ANT is well developed within social studies of science and technology. The last two decades have seen an increasing awareness and interest in ANT within the social sciences and it has increasingly been invoked to theorise the role of ‘nonhumans’ in social life.  In this respect the conceptual repertoire of ANT has been increasingly drawn upon to examine the relational dimensions between artefacts and people. Despite this the use of ANT as an analytical and/or methodological approach occupies a peripheral within social science research.  In part, the reticence towards ANT may be explained by its lack of theoretical unity. Analytically and methodologically the application of ANT and thought which is closely associated with the approach is considerably varied. ANT informed research often differs quite considerably in terms of methodological approach and style of analyses. This is further complicated by the disparate emphases of ANT proponents and the proliferation of different versions of ANT. Thus, there is no generic way to ‘apply’ actor-network theory and it lacks methodological prescription. This article intends to articulate the analytical and methodological possibilities of ANT. For those who are encountering ANT for the first time or for whom ANT has been regarded as a somewhat left field and inaccessible theory obscured by its own vocabularies and heterogeneity this article may provide a useful conceptual map through which the key elements of ANT can be navigated.

  11. 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

  12. Beyond the Player: A User-Centered Approach to Analyzing Digital Games and Players Using Actor-Network Theory

    Science.gov (United States)

    Hung, Aaron Chia Yuan

    2016-01-01

    The paper uses actor-network theory (ANT) to analyze the sociotechnical networks of three groups of adolescents who played online games in different physical and social contexts. These include: an internet café, which allowed the players to be co-present; a personal laptop, which gave the player more control over how he played; and at home through…

  13. 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.

  14. Flaw-tolerance of nonlocal discrete systems and interpretation according to network theory

    Directory of Open Access Journals (Sweden)

    A. Infuso

    2014-07-01

    Full Text Available Discrete systems are modeled as a network of nodes (particles, molecules, or atoms linked by nonlinear springs to simulate the action of van der Waals forces. Such systems are nonlocal if links connecting non-adjacent nodes are introduced. For their topological characterization, a nonlocality index (NLI inspired by network theory is proposed. The mechanical response of 1D and 2D nonlocal discrete systems is predicted according to finite element (FE simulations based on a nonlinear spring element for large displacements implemented in the FE programme FEAP. Uniaxial force-displacement responses of intact and defective systems (with links or nodes removed are numerically simulated. Strain localization phenomena, size-scale effects and the ability to tolerate defects are investigated by varying the degree of nonlocality.

  15. 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....

  16. Performing Sociology Through Actor-Network Theory: From Impressionist Cartography to the Dirtiness of Mediations

    Directory of Open Access Journals (Sweden)

    Daniel Muriel

    2011-03-01

    Full Text Available In this paper I try to outline the existence of certain problems I have found during my research work, within sociology discipline, when it comes to follow some of the main threads of the complex fabric that constitutes the Actor-Network Theory (ANT. In the same way, I suggest some possible subterfuges to go around those problems. Two are the problems and two are the subterfuges as well destined to tackle them. On the one hand, I face the problem of the magnitude and fidelity that ANT's descriptions demand, thoroughly detailed and local, which clashes with the requirements of sociological theory that seeks abstractions and regularities. The subterfuge I propose is the one called "impressionist cartography". On the other hand, I bump into the difficulty of the irreversibility of mediations and the sanitized representations carried out, sometimes, by ANT. In order to fight this, I use the subterfuge oriented to adopt the premise of the "inevitable dirtiness of mediations".

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Maha Abdelhaq

    Full Text Available 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.

  19. Brain network connectivity in women exposed to intimate partner violence: a graph theory analysis study.

    Science.gov (United States)

    Roos, Annerine; Fouche, Jean-Paul; Stein, Dan J

    2016-10-18

    Evidence suggests that women who suffer from intimate partner violence (IPV) and posttraumatic stress disorder (PTSD) have structural and functional alterations in specific brain regions. Yet, little is known about how brain connectivity may be altered in individuals with IPV, but without PTSD. Women exposed to IPV (n = 18) and healthy controls (n = 18) underwent structural brain imaging using a Siemens 3T MRI. Global and regional brain network connectivity measures were determined, using graph theory analyses. Structural covariance networks were created using volumetric and cortical thickness data after controlling for intracranial volume, age and alcohol use. Nonparametric permutation tests were used to investigate group differences. Findings revealed altered connectivity on a global and regional level in the IPV group of regions involved in cognitive-emotional control, with principal involvement of the caudal anterior cingulate, the middle temporal gyrus, left amygdala and ventral diencephalon that includes the thalamus. To our knowledge, this is the first evidence showing different brain network connectivity in global and regional networks in women exposed to IPV, and without PTSD. Altered cognitive-emotional control in IPV may underlie adaptive neural mechanisms in environments characterized by potentially dangerous cues.

  20. Data collection method for mobile sensor networks based on the theory of thermal fields.

    Science.gov (United States)

    Macuha, Martin; Tariq, Muhammad; Sato, Takuro

    2011-01-01

    Many sensor applications are aimed for mobile objects, where conventional routing approaches of data delivery might fail. Such applications are habitat monitoring, human probes or vehicular sensing systems. This paper targets such applications and proposes lightweight proactive distributed data collection scheme for Mobile Sensor Networks (MSN) based on the theory of thermal fields. By proper mapping, we create distribution function which allows considering characteristics of a sensor node. We show the functionality of our proposed forwarding method when adapted to the energy of sensor node. We also propose enhancement in order to maximize lifetime of the sensor nodes. We thoroughly evaluate proposed solution and discuss the tradeoffs.

  1. Finite-temperature field theory and quantum noise in an electrical network

    Energy Technology Data Exchange (ETDEWEB)

    Garavaglia, T.

    1988-10-15

    Finite-temperature (0less than or equal toTtheory with an effective spectral Lagrangian density formulation is used to study quantum noise in an electrical network. Solutions for the finite second moments that satisfy the uncertainty principle bound are given for a dissipative quantum oscillator. A regularization method, based on the analysis of a semi-infinite low-pass filter, is employed, and it leads to results which differ from those of the Drude model. To illustrate the FTF method, an example is given using an ideal finite-temperature coherent state.

  2. Connecting game theory and evolutionary network control for the computational control of soccer matches

    Directory of Open Access Journals (Sweden)

    Alessandro Ferrarini

    2015-03-01

    Full Text Available Game theory, also known as interactive decision theory, is an umbrella term for the logical side of decision science, including both human and non-human events. In this paper a new game theory model is introduced in order to tame complex human events like soccer matches. Soccer-Decoder is a math algorithm recently introduced in order to simulate soccer matches by merging together 3 scientific methods: game theory, differential calculus and stochastic simulations. The philosophy behind Soccer-Decoder is that even very complex real world events, when turned into their irreducible essence, can be understood and predicted. In this work, Soccer-Decoder is combined with Evolutionary Network Control in order to provide a proficient tool to decide the most proper game strategies for determining winning strategies in soccer events. An illustrative example is given. The ratio behind this work is that even very complex real world events can be simulated and then controlled when using appropriate scientific tools.

  3. 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.

  4. Social network theory applied to resting-state fMRI connectivity data in the identification of epilepsy networks with iterative feature selection.

    Science.gov (United States)

    Zhang, Xiaohui; Tokoglu, Fuyuze; Negishi, Michiro; Arora, Jagriti; Winstanley, Scott; Spencer, Dennis D; Constable, R Todd

    2011-07-15

    Epilepsy is a brain disorder usually associated with abnormal cortical and/or subcortical functional networks. Exploration of the abnormal network properties and localization of the brain regions involved in human epilepsy networks are critical for both the understanding of the epilepsy networks and planning therapeutic strategies. Currently, most localization of seizure networks come from ictal EEG observations. Functional MRI provides high spatial resolution together with more complete anatomical coverage compared with EEG and may have advantages if it can be used to identify the network(s) associated with seizure onset and propagation. Epilepsy networks are believed to be present with detectable abnormal signatures even during the interictal state. In this study, epilepsy networks were investigated using resting-state fMRI acquired with the subjects in the interictal state. We tested the hypothesis that social network theory applied to resting-state fMRI data could reveal abnormal network properties at the group level. Using network data as input to a classification algorithm allowed separation of medial temporal lobe epilepsy (MTLE) patients from normal control subjects indicating the potential value of such network analyses in epilepsy. Five local network properties obtained from 36 anatomically defined ROIs were input as features to the classifier. An iterative feature selection strategy based on the classification efficiency that can avoid 'over-fitting' is proposed to further improve the classification accuracy. An average sensitivity of 77.2% and specificity of 83.86% were achieved via 'leave one out' cross validation. This finding of significantly abnormal network properties in group level data confirmed our initial hypothesis and provides motivation for further investigation of the epilepsy process at the network level. Copyright © 2011 Elsevier B.V. All rights reserved.

  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. 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.

  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. Mapping the neuropsychological profile of temporal lobe epilepsy using cognitive network topology and graph theory.

    Science.gov (United States)

    Kellermann, Tanja S; Bonilha, Leonardo; Eskandari, Ramin; Garcia-Ramos, Camille; Lin, Jack J; Hermann, Bruce P

    2016-10-01

    Normal cognitive function is defined by harmonious interaction among multiple neuropsychological domains. Epilepsy has a disruptive effect on cognition, but how diverse cognitive abilities differentially interact with one another compared with healthy controls (HC) is unclear. This study used graph theory to analyze the community structure of cognitive networks in adults with temporal lobe epilepsy (TLE) compared with that in HC. Neuropsychological assessment was performed in 100 patients with TLE and 82 HC. For each group, an adjacency matrix was constructed representing pair-wise correlation coefficients between raw scores obtained in each possible test combination. For each cognitive network, each node corresponded to a cognitive test; each link corresponded to the correlation coefficient between tests. Global network structure, community structure, and node-wise graph theory properties were qualitatively assessed. The community structure in patients with TLE was composed of fewer, larger, more mixed modules, characterizing three main modules representing close relationships between the following: 1) aspects of executive function (EF), verbal and visual memory, 2) speed and fluency, and 3) speed, EF, perception, language, intelligence, and nonverbal memory. Conversely, controls exhibited a relative division between cognitive functions, segregating into more numerous, smaller modules consisting of the following: 1) verbal memory, 2) language, perception, and intelligence, 3) speed and fluency, and 4) visual memory and EF. Overall node-wise clustering coefficient and efficiency were increased in TLE. Adults with TLE demonstrate a less clear and poorly structured segregation between multiple cognitive domains. This panorama suggests a higher degree of interdependency across multiple cognitive domains in TLE, possibly indicating compensatory mechanisms to overcome functional impairments. Copyright © 2016 Elsevier Inc. All rights reserved.

  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. Connectivity in a Karst System Using Electrical Resistivity Tomography and Network Theory.

    Science.gov (United States)

    Gómez-Nicolás, Mariana; Rebolledo-Vieyra, Mario; Canto-Lugo, Efrain; Huerta-Quintanilla, Rodrigo; Ochoa-Sandoval, Pablo

    2017-11-29

    The Ring of Cenotes (RC) is an alignment of numerous cenotes (sinkholes) in a semicircular form (with a radius of 100 km) located in northwestern Yucatán, México. The formation roughly coincides with a concentric ring that corresponds to a buried structure, which has been identified as the product of a meteor impact, known as the Chicxulub crater. Secondary permeability generated by the fracturing and faulting of the sedimentary sequence in the Chicxulub crater has favored the karstification process and therefore the development of underground rivers that transport water from the mainland to the sea. This study implements the network theory to study the hydrological connectivity between a group of 11 cenotes within the RC. Eight electrical resistivity tomography transects were used as an empirical basis. Each transect was acquired directly in the field using the SuperSting R1/IP equipment with a dipole-dipole configuration. An adapted version of the reliability algorithm for communication networks was used as a theoretical model. We found evidence of the existence of water cavities in the study area. We made a network from the data and assigned connection probabilities among cenotes as a function of the separation length and the number of water cavities, as well as their size. © 2017, National Ground Water Association.

  11. A new measure based on degree distribution that links information theory and network graph analysis.

    Science.gov (United States)

    Hadley, Michael W; McGranaghan, Matt F; Willey, Aaron; Liew, Chun Wai; Reynolds, Elaine R

    2012-06-24

    Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system's capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties.

  12. Threshold selection in gene co-expression networks using spectral graph theory techniques.

    Science.gov (United States)

    Perkins, Andy D; Langston, Michael A

    2009-10-08

    Gene co-expression networks are often constructed by computing some measure of similarity between expression levels of gene transcripts and subsequently applying a high-pass filter to remove all but the most likely biologically-significant relationships. The selection of this expression threshold necessarily has a significant effect on any conclusions derived from the resulting network. Many approaches have been taken to choose an appropriate threshold, among them computing levels of statistical significance, accepting only the top one percent of relationships, and selecting an arbitrary expression cutoff. We apply spectral graph theory methods to develop a systematic method for threshold selection. Eigenvalues and eigenvectors are computed for a transformation of the adjacency matrix of the network constructed at various threshold values. From these, we use a basic spectral clustering method to examine the set of gene-gene relationships and select a threshold dependent upon the community structure of the data. This approach is applied to two well-studied microarray data sets from Homo sapiens and Saccharomyces cerevisiae. This method presents a systematic, data-based alternative to using more artificial cutoff values and results in a more conservative approach to threshold selection than some other popular techniques such as retaining only statistically-significant relationships or setting a cutoff to include a percentage of the highest correlations.

  13. ‘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.

  14. 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.

  15. 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.

  16. 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.

  17. A new measure based on degree distribution that links information theory and network graph analysis

    Science.gov (United States)

    2012-01-01

    Background Detailed connection maps of human and nonhuman brains are being generated with new technologies, and graph metrics have been instrumental in understanding the general organizational features of these structures. Neural networks appear to have small world properties: they have clustered regions, while maintaining integrative features such as short average pathlengths. Results We captured the structural characteristics of clustered networks with short average pathlengths through our own variable, System Difference (SD), which is computationally simple and calculable for larger graph systems. SD is a Jaccardian measure generated by averaging all of the differences in the connection patterns between any two nodes of a system. We calculated SD over large random samples of matrices and found that high SD matrices have a low average pathlength and a larger number of clustered structures. SD is a measure of degree distribution with high SD matrices maximizing entropic properties. Phi (Φ), an information theory metric that assesses a system’s capacity to integrate information, correlated well with SD - with SD explaining over 90% of the variance in systems above 11 nodes (tested for 4 to 13 nodes). However, newer versions of Φ do not correlate well with the SD metric. Conclusions The new network measure, SD, provides a link between high entropic structures and degree distributions as related to small world properties. PMID:22726594

  18. 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.

  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. Perturbation waves in proteins and protein networks: Applications of percolation and game theories in signaling and drug design

    CERN Document Server

    Antal, Miklos A; Csermely, Peter

    2008-01-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.

  1. Analysis of oversized sliding waveguide by mode matching and multi-mode network theory

    Energy Technology Data Exchange (ETDEWEB)

    Ohkubo, K.; Kubo, S.; Idei, H.; Shimozuma, T.; Yoshimura, Y.; Sato, M.; Takita, Y. [National Inst. for Fusion Science, Toki, Gifu (Japan); Leuterer, F. [Max-Planck Institut fuer Plasmaphysik, Garching (Germany)

    2000-12-01

    Transmission and reflection coefficients of HE{sub 11} hybrid modes in the sliding waveguide are discussed on the basis of mode matching method and multi-mode network theory. The sliding waveguide is composed of the corrugated waveguide with 88.9 mm{phi} and the smooth-wall waveguide with 110 mm{phi} in inner diameter. It is confirmed that the decrease in power of <0.2% at 84 GHz is obtained for 2 cm in gap of the sliding waveguide. At the sliding length near multi-half-wavelength in vacuum, transmission and reflection powers in the sliding waveguide change slightly, because the very small amount of standing wave of higher-order TE or TM modes is produced resonantly. (author)

  2. Electromagnetic game modeling through Tensor Analysis of Networks and Game Theory

    Science.gov (United States)

    Maurice, Olivier; Reineix, Alain; Lalléchère, Sébastien

    2014-10-01

    A complex system involves events coming from natural behaviors. Whatever is the complicated face of machines, they are still far from the complexity of natural systems. Currently, economy is one of the rare science trying to find out some ways to model human behavior. These attempts involve game theory and psychology. Our purpose is to develop a formalism able to take in charge both game and hardware modeling. We first present the Tensorial Analysis of Networks, used for the material part of the system. Then, we detail the mathematical objects defined in order to describe the evolution of the system and its gaming side. To illustrate the discussion we consider the case of a drone whose electronic can be disturbed by a radar field, but this drone must fly as near as possible close to this radar.

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

    OpenAIRE

    Eveleens, Chris P.; Frank J. van Rijnsoever; 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 ...

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Maike Schindler

    2016-12-01

    Full Text Available 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 domain-general theory on giftedness as an interplay of creativity, above-average ability, and task commitment; and Krutetskii’s mathematics-specific theory on gifted students’ abilities. In a “proof of concept”, we illustrate how the abilities offered in Krutetskii’s theory can be mapped to the three traits described by Renzulli. This is realized through a mapping process in which two raters independently mapped the abilities offered by Krutetskii to Renzulli’s traits. The results of this mapping give first insights into (a possible mappings of Krutetskii’s abilities to Renzulli’s traits and, thus, (b a possible domain-specific specification of Renzulli’s theory. This mapping hints at interesting potential phenomena: in Krutetskii’s theory, above-average ability appears to be the trait that predominantly is addressed, whereas creativity and especially task-commitment seem less represented. Our mapping demonstrates what a mathematics-specific specification of Renzulli’s theory can look like. Finally, we elaborate on the consequences of our findings, restrictions of our methodology, and on possible future research.

  6. 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.

  7. 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

  8. Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling.

    Science.gov (United States)

    Otero-Muras, Irene; Yordanov, Pencho; Stelling, Joerg

    2017-04-01

    Bistability has important implications in signaling pathways, since it indicates a potential cell decision between alternative outcomes. We present two approaches developed in the framework of the Chemical Reaction Network Theory for easy and efficient search of multiple steady state behavior in signaling networks (both with and without mass conservation), and apply them to search for sources of bistability at different levels of the interferon signaling pathway. Different type I interferon subtypes and/or doses are known to elicit differential bioactivities (ranging from antiviral, antiproliferative to immunomodulatory activities). How different signaling outcomes can be generated through the same receptor and activating the same JAK/STAT pathway is still an open question. Here, we detect bistability at the level of early STAT signaling, showing how two different cell outcomes are achieved under or above a threshold in ligand dose or ligand-receptor affinity. This finding could contribute to explain the differential signaling (antiviral vs apoptotic) depending on interferon dose and subtype (α vs β) observed in type I interferons.

  9. Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.

    Science.gov (United States)

    Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Khan, Sehresh; Manganotti, Paolo; Menegaz, Gloria

    2017-09-01

    The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph theory to high-density electroencephalographic recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes. First a distributed linear inverse solution, constrained to the individual grey matter, was applied to the averaged spikes and the mean source activity over 112 regions, as identified by the Harvard-Oxford Atlas, was calculated. Then, the ADTF, a dynamic measure of causality, was used to quantify the connectivity strength between pairs of regions acting as nodes in the graph, and the measure of node centrality was derived. The proposed analysis was effective in detecting the focal regions as well as in characterizing the dynamics of the spike propagation, providing evidence of the fact that the node centrality is a reliable feature for the identification of the epileptogenic zones. Validation was performed by multimodal analysis as well as from surgical outcomes. In conclusion, the time-variant connectivity analysis applied to the epileptic patients can distinguish the generator of the abnormal activity from the propagation spread and identify the connectivity pattern over time.

  10. 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.

  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. Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

    Science.gov (United States)

    Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

    2015-01-01

    Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

  13. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare.

    Science.gov (United States)

    Cresswell, Kathrin M; Worth, Allison; Sheikh, Aziz

    2010-11-01

    Actor-Network Theory (ANT) is an increasingly influential, but still deeply contested, approach to understand humans and their interactions with inanimate objects. We argue that health services research, and in particular evaluations of complex IT systems in health service organisations, may benefit from being informed by Actor-Network Theory perspectives. Despite some limitations, an Actor-Network Theory-based approach is conceptually useful in helping to appreciate the complexity of reality (including the complexity of organisations) and the active role of technology in this context. This can prove helpful in understanding how social effects are generated as a result of associations between different actors in a network. Of central importance in this respect is that Actor-Network Theory provides a lens through which to view the role of technology in shaping social processes. Attention to this shaping role can contribute to a more holistic appreciation of the complexity of technology introduction in healthcare settings. It can also prove practically useful in providing a theoretically informed approach to sampling (by drawing on informants that are related to the technology in question) and analysis (by providing a conceptual tool and vocabulary that can form the basis for interpretations). We draw on existing empirical work in this area and our ongoing work investigating the integration of electronic health record systems introduced as part of England's National Programme for Information Technology to illustrate salient points. Actor-Network Theory needs to be used pragmatically with an appreciation of its shortcomings. Our experiences suggest it can be helpful in investigating technology implementations in healthcare settings.

  14. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare

    Directory of Open Access Journals (Sweden)

    Sheikh Aziz

    2010-11-01

    Full Text Available Abstract Background Actor-Network Theory (ANT is an increasingly influential, but still deeply contested, approach to understand humans and their interactions with inanimate objects. We argue that health services research, and in particular evaluations of complex IT systems in health service organisations, may benefit from being informed by Actor-Network Theory perspectives. Discussion Despite some limitations, an Actor-Network Theory-based approach is conceptually useful in helping to appreciate the complexity of reality (including the complexity of organisations and the active role of technology in this context. This can prove helpful in understanding how social effects are generated as a result of associations between different actors in a network. Of central importance in this respect is that Actor-Network Theory provides a lens through which to view the role of technology in shaping social processes. Attention to this shaping role can contribute to a more holistic appreciation of the complexity of technology introduction in healthcare settings. It can also prove practically useful in providing a theoretically informed approach to sampling (by drawing on informants that are related to the technology in question and analysis (by providing a conceptual tool and vocabulary that can form the basis for interpretations. We draw on existing empirical work in this area and our ongoing work investigating the integration of electronic health record systems introduced as part of England's National Programme for Information Technology to illustrate salient points. Summary Actor-Network Theory needs to be used pragmatically with an appreciation of its shortcomings. Our experiences suggest it can be helpful in investigating technology implementations in healthcare settings.

  15. Learning about a Fish from an ANT: Actor Network Theory and Science Education in the Postgenomic Era

    Science.gov (United States)

    Pierce, Clayton

    2015-01-01

    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…

  16. Blogs and Social Network Sites as Activity Systems: Exploring Adult Informal Learning Process through Activity Theory Framework

    Science.gov (United States)

    Heo, Gyeong Mi; Lee, Romee

    2013-01-01

    This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…

  17. 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…

  18. A Cooperative Control Method for Fully Mechanized Mining Machines Based on Fuzzy Logic Theory and Neural Networks

    Directory of Open Access Journals (Sweden)

    Chao Tan

    2015-01-01

    Full Text Available In a fully mechanized mining face, the coordinated control of coal mining machines has a significant promoting effect to perfect the mining environment and improve the efficiency of coal production and has become a research focus all over the world. In this paper, a cooperative control method based on the integration of fuzzy logic theory and neural networks was proposed. The improved Elman neural network (ENN through a threshold strategy was presented to predict the running parameters of coal mining machines. On the basis of coupling analysis of coal mining machines, the expert knowledge base of scraper conveyor was established based on fuzzy logic theory. Furthermore, the probabilistic neural network (PNN was applied to evaluate the running status of scraper conveyor, and the cooperative control flow was designed and analyzed. Finally, a simulation example was provided and the comparison results illustrated that the proposed method was feasible and superior to the manual control.

  19. 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.

  20. 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.

  1. 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.

  2. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  3. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

    Full Text Available Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the

  4. 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.

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

    Science.gov (United States)

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

    2017-01-01

    Abstract 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. PMID:28398578

  6. 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.

  7. 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

  8. 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.

  9. Cooperation and deception recruit different subsets of the theory-of-mind network.

    Directory of Open Access Journals (Sweden)

    Silke Lissek

    Full Text Available The term "theory of mind" (ToM describes an evolved psychological mechanism that is necessary to represent intentions and expectations in social interaction. It is thus involved in determining the proclivity of others to cooperate or defect. While in cooperative settings between two parties the intentions and expectations of the protagonists match, they diverge in deceptive scenarios, in which one protagonist is intentionally manipulated to hold a false belief about the intention of the other. In a functional magnetic resonance imaging paradigm using cartoons showing social interactions (including the outcome of the interaction between two or three story characters, respectively, we sought to determine those brain areas of the ToM network involved in reasoning about cooperative versus deceptive interactions. Healthy volunteers were asked to reflect upon the protagonists' intentions and expectations in cartoons depicting cooperation, deception or a combination of both, where two characters cooperated to deceive a third. Reasoning about the mental states of the story characters yielded substantial differences in activation patterns: both deception and cooperation activated bilateral temporoparietal junction, parietal and cingulate regions, while deception alone additionally recruited orbitofrontal and medial prefrontal regions. These results indicate an important role for prefrontal cortex in processing a mismatch between a character's intention and another's expectations as required in complex social interactions.

  10. The theory of planned behavior applied to young people's use of social networking Web sites.

    Science.gov (United States)

    Pelling, Emma L; White, Katherine M

    2009-12-01

    Despite the increasing popularity of social networking Web sites (SNWs), very little is known about the psychosocial variables that predict people's use of these Web sites. The present study used an extended model of the theory of planned behavior (TPB), including the additional variables of self-identity and belongingness, to predict high-level SNW use intentions and behavior in a sample of young people ages 17 to 24 years. Additional analyses examined the impact of self-identity and belongingness on young people's addictive tendencies toward SNWs. University students (N = 233) completed measures of the standard TPB constructs (attitude, subjective norm, and perceived behavioral control), the additional predictor variables (self-identity and belongingness), demographic variables (age, gender, and past behavior), and addictive tendencies. One week later, they reported their engagement in high-level SNW use during the previous week. Regression analyses partially supported the TPB: attitude and subjective norm significantly predicted intentions to engage in high-level SNW use with intention significantly predicting behavior. Self-identity, but not belongingness, significantly contributed to the prediction of intention and, unexpectedly, behavior. Past behavior also significantly predicted intention and behavior. Self-identity and belongingness significantly predicted addictive tendencies toward SNWs. Overall, the present study revealed that high-level SNW use is influenced by attitudinal, normative, and self-identity factors, findings that can be used to inform strategies that aim to modify young people's high levels of use or addictive tendencies for SNWs.

  11. 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.

  12. Operational Risk Assessment of Distribution Network Equipment Based on Rough Set and D-S Evidence Theory

    Directory of Open Access Journals (Sweden)

    Cunbin Li

    2013-01-01

    Full Text Available With the increasing complication, compaction, and automation of distribution network equipment, a small failure will cause an outbreak chain reaction and lead to operational risk in the power distribution system, even in the whole power system. Therefore, scientific assessment of power distribution equipment operation risk is significant to the security of power distribution system. In order to get the satisfactory assessment conclusions from the complete and incomplete information and improve the assessment level, an operational risk assessment model of distribution network equipment based on rough set and D-S evidence theory was built. In this model, the rough set theory was used to simplify and optimize the operation risk assessment indexes of distribution network equipment and the evidence D-S theory was adopted to combine the optimal indexes. At last, the equipment operational risk level was obtained from the basic probability distribution decision. Taking the transformer as an example, this paper compared the assessment result obtained from the method proposed in this paper with that from the ordinary Rogers ratio method and discussed the application of the proposed method. It proved that the method proposed in this paper is feasible, efficient, and provides a new way to assess the distribution network equipment operational risk.

  13. Analytical transport network theory to guide the design of 3-D microstructural networks in energy materials: Part 2. Flow with reactions

    Science.gov (United States)

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

    2017-12-01

    We extend the fully analytical, heuristic "Analytical Transport Network Model" for steady-state, diffusive flow in a 3-D network to account for surface reactions. In the limit of negligible reactions, the model reduces to the conserved flow solution. The extension does not increase the time required to run the model, which in Part 1 was shown to be 0.5-1.5 and 5-6 orders of magnitude faster than electrochemical fin (ECF) theory and finite element analysis (FEA) for conserved flow, respectively. The model is compared to reacting-flow ECF and FEA as well as to experiments and is demonstrated as a potentially useful heuristic for understanding the influence of morphology and topology on reactive-diffusive flow through a 3-D microstructural network.

  14. Effect of resting-state functional MR imaging duration on stability of graph theory metrics of brain network connectivity.

    Science.gov (United States)

    Whitlow, Christopher T; Casanova, Ramon; Maldjian, Joseph A

    2011-05-01

    To investigate the effect of resting-state (RS) functional magnetic resonance (MR) imaging blood oxygen level-dependent (BOLD) signal acquisition duration on stability of computed graph theory metrics of brain network connectivity. An institutional ethics committee approved this study, and informed consent was obtained. BOLD signal (7.5 minutes worth) was obtained from 30 subjects and truncated into 30-second time bins that ranged from 1.5 to 7.5 minutes. A binarized adjacency matrix for each subject and acquisition duration was generated at network costs between 0.1 and 0.5, where network cost is defined as the ratio of the number of edges (connections) in a network to the maximum possible number of edges. Measures of correlation coefficient stability associated with functional connectivity matrices (correlation coefficient standard deviation [SD] and correlation threshold) and associated graph theory metrics (small worldness, local efficiency, and global efficiency) were computed for each subject at each BOLD signal acquisition duration. Computations were implemented with a 15-node 30-core computer cluster to enable analysis of the approximately 2000 resulting brain networks. Analysis of variance and posthoc analyses were conducted to identify differences between time bins for each measure. Small worldness, local efficiency, and global efficiency stabilized after 2 minutes of BOLD signal acquisition, whereas correlation coefficient data from functional connectivity matrices (correlation coefficient SD and cost-associated threshold) stabilized after 5 minutes of BOLD signal acquisition. Graph theory metrics of brain network connectivity (small worldness, local efficiency, and global efficiency) may be accurately computed from as little as 1.5-2.0 minutes of RS functional MR imaging BOLD signal. As such, implementation of these methods in the context of time-constrained clinical imaging protocols may be feasible and cost-effective. http

  15. 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.

  16. 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. .

  17. 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

  18. 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.

  19. Deciding on Innovation at a Railway Network Operator : A Grounded Theory Approach

    NARCIS (Netherlands)

    Van den Hoogen, J.; Meijer, S.A.

    2012-01-01

    Innovation at a railway network operator depends on the decision-making processes in the daily work of operational professionals and staff. This paper is about innovative measures at a railway network operator, required to increase capacity on the railway network without investing in expensive

  20. Post Disaster Governance, Complexity and Network Theory: Evidence from Aceh, Indonesia After the Indian Ocean Tsunami 2004.

    Science.gov (United States)

    Lassa, Jonatan A

    2015-07-01

    This research aims to understand the organizational network typology of large--scale disaster intervention in developing countries and to understand the complexity of post--disaster intervention, through the use of network theory based on empirical data from post--tsunami reconstruction in Aceh, Indonesia, during 2005/-2007. The findings suggest that the ' degrees of separation' (or network diameter) between any two organizations in the field is 5, thus reflecting 'small- world' realities and therefore making no significant difference with the real human networks, as found in previous experiments. There are also significant loops in the network reflecting the fact that some actors tend to not cooperate, which challenges post- disaster coordination. The findings show the landscape of humanitarian actors is not randomly distributed. Many actors were connected to each other through certain hubs, while hundreds of actors make 'scattered' single 'principal--client' links. The paper concludes that by understanding the distribution of degree, centrality, 'degrees of separation' and visualization of the network, authorities can improve their understanding of the realities of coordination, from macro to micro scales.

  1. 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.

  2. Graph theory analysis of cortical thickness networks in adolescents with d-transposition of the great arteries.

    Science.gov (United States)

    Watson, Christopher G; Stopp, Christian; Newburger, Jane W; Rivkin, Michael J

    2018-02-01

    Adolescents with d-transposition of the great arteries (d-TGA) who had the arterial switch operation in infancy have been found to have structural brain differences compared to healthy controls. We used cortical thickness measurements obtained from structural brain MRI to determine group differences in global brain organization using a graph theoretical approach. Ninety-two d-TGA subjects and 49 controls were scanned using one of two identical 1.5-Tesla MRI systems. Mean cortical thickness was obtained from 34 regions per hemisphere using Freesurfer. A linear model was used for each brain region to adjust for subject age, sex, and scanning location. Structural connectivity for each group was inferred based on the presence of high inter-regional correlations of the linear model residuals, and binary connectivity matrices were created by thresholding over a range of correlation values for each group. Graph theory analysis was performed using packages in R. Permutation tests were performed to determine significance of between-group differences in global network measures. Within-group connectivity patterns were qualitatively different between groups. At lower network densities, controls had significantly more long-range connections. The location and number of hub regions differed between groups: controls had a greater number of hubs at most network densities. The control network had a significant rightward asymmetry compared to the d-TGA group at all network densities. Using graph theory analysis of cortical thickness correlations, we found differences in brain structural network organization among d-TGA adolescents compared to controls. These may be related to the white matter and gray matter differences previously found in this cohort, and in turn may be related to the cognitive deficits this cohort presents.

  3. 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.

  4. 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.

  5. 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.

  6. Assessing the Predictors of Intention and Behavior in Using Virtual Social Networks Among Students of the Yazd University of Medical Sciences Based on the Theory of Planned Behavior

    National Research Council Canada - National Science Library

    Zahra Khazir; Morad ali Zareipour; Mahdi Abdolkarimi; Arefeh Dehghani tafti; Tahereh Rahimi

    2017-01-01

    .... The present study was to determine predictive factors of virtual social networks among students of Yazd university of medical sciences based on the constructs of the Theory of Planned Behavior. Methods...

  7. Graph theory analysis of cortical-subcortical networks in late-life depression.

    Science.gov (United States)

    Ajilore, Olusola; Lamar, Melissa; Leow, Alex; Zhang, Aifeng; Yang, Shaolin; Kumar, Anand

    2014-02-01

    Late-life major depression (LLD) is characterized by distinct epidemiologic and psychosocial factors, as well as medical comorbidities that are associated with specific neuroanatomical differences. The purpose of this study was to use interregional correlations of cortical and subcortical volumes to examine cortical-subcortical structural network properties in subjects with LLD compared with healthy comparison subjects. This was a cross-sectional neuroimaging study conducted in the general community. We recruited 73 healthy elderly comparison subjects and 53 subjects with LLD who volunteered in response to advertisements. Brain network connectivity measures were generated by correlating regional volumes after controlling for age, gender, and intracranial volume by using the Brain Connectivity Toolbox. Results for overall network strength revealed that LLD networks showed a greater magnitude of associations for both positive and negative correlation weights compared with healthy elderly networks. LLD networks also demonstrated alterations in brain network structure compared with healthy comparison subjects. LLD networks were also more vulnerable to targeted attacks compared with healthy elderly comparison subjects, and this vulnerability was attenuated when controlling for white matter alterations. Overall, this study demonstrates that cortical-subcortical network properties are altered in LLD and may reflect the underlying neuroanatomical vulnerabilities of the disorder. Copyright © 2014 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  8. 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.

  9. Direct Gaze Elicits Atypical Activation of the Theory-of-Mind Network in Autism Spectrum Conditions

    National Research Council Canada - National Science Library

    von dem Hagen, Elisabeth A.H; Stoyanova, Raliza S; Rowe, James B; Baron-Cohen, Simon; Calder, Andrew J

    2014-01-01

    .... 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...

  10. Semantic network mapping of religious material: testing multi-agent computer models of social theories against real-world data.

    Science.gov (United States)

    Lane, Justin E

    2015-11-01

    Agent-based modeling allows researchers to investigate theories of complex social phenomena and subsequently use the model to generate new hypotheses that can then be compared to real-world data. However, computer modeling has been underutilized in regard to the understanding of religious systems, which often require very complex theories with multiple interacting variables (Braxton et al. in Method Theory Study Relig 24(3):267-290, 2012. doi: 10.1163/157006812X635709 ; Lane in J Cogn Sci Relig 1(2):161-180, 2013). This paper presents an example of how computer modeling can be used to explore, test, and further understand religious systems, specifically looking at one prominent theory of religious ritual. The process is continuous: theory building, hypothesis generation, testing against real-world data, and improving the model. In this example, the output of an agent-based model of religious behavior is compared against real-world religious sermons and texts using semantic network analysis. It finds that most religious materials exhibit unique scale-free small-world properties and that a concept's centrality in a religious schema best predicts its frequency of presentation. These results reveal that there adjustments need to be made to existing models of religious ritual systems and provide parameters for future models. The paper ends with a discussion of implications for a new multi-agent model of doctrinal ritual behaviors as well as propositions for further interdisciplinary research concerning the multi-agent modeling of religious ritual behaviors.

  11. 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

  12. Networks of recurrent events, a theory of records, and an application to finding causal signatures in seismicity

    Science.gov (United States)

    Davidsen, Jörn; Grassberger, Peter; Paczuski, Maya

    2008-06-01

    We propose a method to search for signs of causal structure in spatiotemporal data making minimal a priori assumptions about the underlying dynamics. To this end, we generalize the elementary concept of recurrence for a point process in time to recurrent events in space and time. An event is defined to be a recurrence of any previous event if it is closer to it in space than all the intervening events. As such, each sequence of recurrences for a given event is a record breaking process. This definition provides a strictly data driven technique to search for structure. Defining events to be nodes, and linking each event to its recurrences, generates a network of recurrent events. Significant deviations in statistical properties of that network compared to networks arising from (acausal) random processes allows one to infer attributes of the causal dynamics that generate observable correlations in the patterns. We derive analytically a number of properties for the network of recurrent events composed by a random process in space and time. We extend the theory of records to treat not only the variable where records happen, but also time as continuous. In this way, we construct a fully symmetric theory of records leading to a number of results. Those analytic results are compared in detail to the properties of a network synthesized from time series of epicenter locations for earthquakes in Southern California. Significant disparities from the ensemble of acausal networks that can be plausibly attributed to the causal structure of seismicity are as follows. (1) Invariance of network statistics with the time span of the events considered. (2) The appearance of a fundamental length scale for recurrences, independent of the time span of the catalog, which is consistent with observations of the “rupture length.” (3) Hierarchy in the distances and times of subsequent recurrences. As expected, almost all of the statistical properties of a network constructed from a

  13. Modeling of regulatory networks: theory and applications in the study of the Drosophila circadian clock.

    Science.gov (United States)

    Scribner, Elizabeth Y; Fathallah-Shaykh, Hassan M

    2011-01-01

    Biological networks can be very complex. Mathematical modeling and simulation of regulatory networks can assist in resolving unanswered questions about these complex systems, which are often impossible to explore experimentally. The network regulating the Drosophila circadian clock is particularly amenable to such modeling given its complexity and what we call the clockwork orange (CWO) anomaly. CWO is a protein whose function in the network as an indirect activator of genes per, tim, vri, and pdp1 is counterintuitive--in isolated experiments, CWO inhibits transcription of these genes. Although many different types of modeling frameworks have recently been applied to the Drosophila circadian network, this chapter focuses on the application of continuous deterministic dynamic modeling to this network. In particular, we present three unique systems of ordinary differential equations that have been used to successfully model different aspects of the circadian network. The last model incorporates the newly identified protein CWO, and we explain how this model's unique mathematical equations can be used to explore and resolve the CWO anomaly. Finally, analysis of these equations gives rise to a new network regulatory rule, which clarifies the unusual role of CWO in this dynamical system. © 2011 Elsevier Inc. All rights reserved.

  14. Toward a theory of extended contact : The incentives and opportunities for bridging across network communities

    NARCIS (Netherlands)

    Sytch, M.; Tatarynowicz, A.; Gulati, R.

    2012-01-01

    This study investigates the determinants of bridging ties within networks of interconnected firms. Bridging ties are defined as nonredundant connections between firms located in different network communities. We highlight how firms can enter into these relationships because of the incentives and

  15. Modular Structures, Robustness and Protection of Complex Networks : Theory, Complexity and Algorithms

    NARCIS (Netherlands)

    Trajanovski, S.

    2014-01-01

    Community structure is observed in many real-world networks, such as (online) social networks, where groups of friends of a certain person are often also friends of each other. Newman's modularity has been explored as an important quantitative metric for communities and clusters detection in

  16. Examining Intrinsic Thalamic Resting State Networks Using Graph Theory Analysis : Implications for mTBI detection

    Science.gov (United States)

    2012-08-01

    Lippincott, Williams and Wilkins, 2010. [14] E.R. Kandel , J.H. Schwartz, and T.M. Jessell, Principles of Neural Science, 4th ed., New York, NY, USA...Network homogeneity reveals decreased integrity of default-mode network in ADHD”, J Neuroscience Met. Vol. 169, no. 1, pp. 249-254, 2008. [25

  17. 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

    2017-03-13

    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.

  18. Modeling a heterogeneous network with TCP connections using fluid flow approximation and queuing theory

    Science.gov (United States)

    Hisamatu, Hiroyuki; Ohsaki, Hiroyuki; Murata, Masayuki

    2003-08-01

    In the current Internet, most of the traffic is transmitted by TCP (Transmission Control Protocol). In our previous work, we have proposed a modeling approach for the entire network, including TCP congestion control mechanisms operating at source hosts and the network seen by TCP connections, as a single feedback system. However, our analytic model is limited to a simple network, where TCP connections have the identical propagation delay. In this paper, we therefore extend our analytic approach to a more generic network, where multiple TCP connections are allowed to have different propagation delays. We derive the packet loss probability in the network, the throughput and the average round-trip time of each TCP connection in steady state. By presenting several numerical examples, we quantitatively investigate how the fairness among TCP connections is degraded when multiple TCP connections with different propagation delays share the single bottleneck link.

  19. Construction of citrus gene coexpression networks from microarray data using random matrix theory

    Science.gov (United States)

    Du, Dongliang; Rawat, Nidhi; Deng, Zhanao; Gmitter, Fred G.

    2015-01-01

    After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus. PMID:26504573

  20. Combining Partial Directed Coherence and Graph Theory to Analyse Effective Brain Networks of Different Mental Tasks.

    Science.gov (United States)

    Huang, Dengfeng; Ren, Aifeng; Shang, Jing; Lei, Qiao; Zhang, Yun; Yin, Zhongliang; Li, Jun; von Deneen, Karen M; Huang, Liyu

    2016-01-01

    The aim of this study is to qualify the network properties of the brain networks between two different mental tasks (play task or rest task) in a healthy population. EEG signals were recorded from 19 healthy subjects when performing different mental tasks. Partial directed coherence (PDC) analysis, based on Granger causality (GC), was used to assess the effective brain networks during the different mental tasks. Moreover, the network measures, including degree, degree distribution, local and global efficiency in delta, theta, alpha, and beta rhythms were calculated and analyzed. The local efficiency is higher in the beta frequency and lower in the theta frequency during play task whereas the global efficiency is higher in the theta frequency and lower in the beta frequency in the rest task. This study reveals the network measures during different mental states and efficiency measures may be used as characteristic quantities for improvement in attentional performance.

  1. Performance Analysis of an Energy Efficient Femtocell Network Using Queuing Theory

    Directory of Open Access Journals (Sweden)

    Wanod Kumar

    2013-07-01

    Full Text Available The energy expenditure of cellular networks is increasing rapidly due to high demand of data services by the subscribers. This subsequently gives rise to the CO2 emission which is a critical issue nowadays. A hybrid cellular network comprised of macrocell and several femtocells is required to achieve reliability, continuous connectivity, and energy efficiency. To address the issue of energy efficiency, in this paper we present a queuing model of an energy efficient femtocell network. The transmission of data traffic in this type of network is modeled using M/M/1 queue where server FAP (Femtocell Access Point takes vacation to save energy during inactivity period. The network model is solved using a MGM (Matrix Geometric Method. The performance of the system is evaluated in terms of average system delay and power savings for different sleep cycle durations. Results reveal that the maximum energy can be saved with higher sleep cycle duration at a cost of increased system delay

  2. 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.

  3. Hybrid protection algorithms based on game theory in multi-domain optical networks

    Science.gov (United States)

    Guo, Lei; Wu, Jingjing; Hou, Weigang; Liu, Yejun; Zhang, Lincong; Li, Hongming

    2011-12-01

    With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user's utility, the network operator's utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator's utility, while IEP has better user's utility.

  4. Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory.

    Science.gov (United States)

    Durán, Claudio; Daminelli, Simone; Thomas, Josephine M; Haupt, V Joachim; Schroeder, Michael; Cannistraci, Carlo Vittorio

    2017-04-26

    The bipartite network representation of the drug-target interactions (DTIs) in a biosystem enhances understanding of the drugs' multifaceted action modes, suggests therapeutic switching for approved drugs and unveils possible side effects. As experimental testing of DTIs is costly and time-consuming, computational predictors are of great aid. Here, for the first time, state-of-the-art DTI supervised predictors custom-made in network biology were compared-using standard and innovative validation frameworks-with unsupervised pure topological-based models designed for general-purpose link prediction in bipartite networks. Surprisingly, our results show that the bipartite topology alone, if adequately exploited by means of the recently proposed local-community-paradigm (LCP) theory-initially detected in brain-network topological self-organization and afterwards generalized to any complex network-is able to suggest highly reliable predictions, with comparable performance with the state-of-the-art-supervised methods that exploit additional (non-topological, for instance biochemical) DTI knowledge. Furthermore, a detailed analysis of the novel predictions revealed that each class of methods prioritizes distinct true interactions; hence, combining methodologies based on diverse principles represents a promising strategy to improve drug-target discovery. To conclude, this study promotes the power of bio-inspired computing, demonstrating that simple unsupervised rules inspired by principles of topological self-organization and adaptiveness arising during learning in living intelligent systems (like the brain) can efficiently equal perform complicated algorithms based on advanced, supervised and knowledge-based engineering. © The Author 2017. Published by Oxford University Press.

  5. 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.

  6. 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…

  7. The theory of networks of single server queues and the tandem queue model

    Directory of Open Access Journals (Sweden)

    Pierre Le Gall

    1997-01-01

    Full Text Available We consider the stochastic behavior of networks of single server queues when successive service times of a given customer are highly correlated. The study is conducted in two particular cases: 1 networks in heavy traffic, and 2 networks in which all successive service times have the same value (for a given customer, in order to avoid the possibility of breaking up the busy periods. We then show how the local queueing delay (for an arbitrary customer can be derived through an equivalent tandem queue on the condition that one other local queueing delay is added: the jitter delay due to the independence of partial traffic streams.

  8. First principles and effective theory approaches to dynamics of complex networks

    Science.gov (United States)

    Dehmamy, Nima

    This dissertation concerns modeling two aspects of dynamics of complex networks: (1) response dynamics and (2) growth and formation. A particularly challenging class of networks are ones in which both nodes and links are evolving over time -- the most prominent example is a financial network. In the first part of the dissertation we present a model for the response dynamics in networks near a metastable point. We start with a Landau-Ginzburg approach and show that the most general lowest order Lagrangians for dynamical weighted networks can be used to derive conditions for stability under external shocks. Using a closely related model, which is easier to solve numerically, we propose a powerful and intuitive set of equations for response dynamics of financial networks. We find the stability conditions of the model and find two phases: "calm" phase , in which changes are sub-exponential and where the system moves to a new, close-by equilibrium; "frantic" phase, where changes are exponential, with negative blows resulting in crashes and positive ones leading to formation of "bubbles". We empirically verify these claims by analyzing data from Eurozone crisis of 2009-2012 and stock markets. We show that the model correctly identifies the time-line of the Eurozone crisis, and in the stock market data it correctly reproduces the auto-correlations and phases observed in the data. The second half of the dissertation addresses the following question: Do networks that form due to local interactions (local in real space, or in an abstract parameter space) have characteristics different from networks formed of random or non-local interactions? Using interacting fields obeying Fokker-Planck equations we show that many network characteristics such as degree distribution, degree-degree correlation and clustering can either be derived analytically or there are analytical bounds on their behaviour. In particular, we derive recursive equations for all powers of the ensemble average

  9. Designing a delay-based adaptive congestion control mechanism using control theory and system identification for TCP/IP networks

    Science.gov (United States)

    Morita, Mitsushige; Ohsaki, Hiroyuki; Murata, Masayuki

    2002-07-01

    In the Internet, TCP (Transmission Control Protocol) has been used as an end-to-end congestion control mechanism. Of all several TCP implementations, TCP Reno is the most popular implementation. TCP Reno uses a loss-based approach since it estimates the severity of congestion by detecting packet losses in the network. On the contrary, another implementation called TCP Vegas uses a delay-based approach. The main advantage of a delay-based approach is, if it is properly designed, packet losses can be prevented by anticipating impending congestion from increasing packet delays. However, TCP Vegas was designed using not a theoretical approach but an ad hock one. In this paper, we therefore design a delay-based congestion control mechanism by utilizing the classical control theory. Our rate-based congestion control mechanism dynamically adjusts the packet transmission rate to stabilize the round-trip time for utilizing the network resources and also for preventing packet losses in the network. Presenting several simulation results in two network configurations, we quantitatively show the robustness and the effectiveness of our delay-based congestion control mechanism.

  10. Using social networks theory as a complementary perspective to the study of organizational change

    OpenAIRE

    Manuel Portugal Ferreira; Sungu Armagan

    2011-01-01

    This paper contributes to the literature on organizational change by examining organizations as social entities embedded in inter-organizational networks. In contrast with extant research that focuses on macro environmental and internal factors to explain organizational change, we put forth the social network surrounding the firm as a major driver of any change process. Specifically, we examine organizational change as driven by the organizations' positions and relations in an interorganizati...

  11. Complexity, theory and praxis: researching collaborative learning and tutoring processes in a networked learning community

    OpenAIRE

    de Laat, M.; Lally, V.

    2004-01-01

    This paper explores the complexity of researching networked learning and tutoring on two levels. Firstly, on the theoretical level, we argue that the nature of praxis in networked environments (that is, learning and tutoring) is so complex that no single theoretical model, among those currently available, is a sufficiently powerful, descriptively, rhetorically, inferentially or in its application to real contexts, to provide a framework for a research agenda that takes into account the key as...

  12. A Monte Carlo EM approach for partially observable diffusion processes: theory and applications to neural networks.

    Science.gov (United States)

    Movellan, Javier R; Mineiro, Paul; Williams, R J

    2002-07-01

    We present a Monte Carlo approach for training partially observable diffusion processes. We apply the approach to diffusion networks, a stochastic version of continuous recurrent neural networks. The approach is aimed at learning probability distributions of continuous paths, not just expected values. Interestingly, the relevant activation statistics used by the learning rule presented here are inner products in the Hilbert space of square integrable functions. These inner products can be computed using Hebbian operations and do not require backpropagation of error signals. Moreover, standard kernel methods could potentially be applied to compute such inner products. We propose that the main reason that recurrent neural networks have not worked well in engineering applications (e.g., speech recognition) is that they implicitly rely on a very simplistic likelihood model. The diffusion network approach proposed here is much richer and may open new avenues for applications of recurrent neural networks. We present some analysis and simulations to support this view. Very encouraging results were obtained on a visual speech recognition task in which neural networks outperformed hidden Markov models.

  13. 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.

  14. 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.

  15. 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.

  16. A Network Based Theory of Health Systems and Cycles of Well-being.

    Science.gov (United States)

    Rhodes, Michael Grant

    2013-06-01

    There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign) health and well-being systems we know today. But the core of a truly 'complex adaptive system' can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable.

  17. Dynamical complex network theory applied to the therapeutics of brain malignancies

    Science.gov (United States)

    Meyer-Bäse, Anke; Fratte, Daniel; Barbu, Adrian; Pinker-Domenig, Katja

    2015-05-01

    An important problem in modern therapeutics at the metabolomic, transcriptomic or phosphoproteomic level remains to identify therapeutic targets in a plentitude of high-throughput data from experiments relevant to a variety of diseases. This paper presents the application of novel graph algorithms and modern control solutions applied to the graph networks resulting from specific experiments to discover disease-related pathways and drug targets in glioma cancer stem cells (GSCs). The theoretical frameworks provides us with the minimal number of "driver nodes" necessary to determine the full control over the obtained graph network in order to provide a change in the network's dynamics from an initial state (disease) to a desired state (non-disease). The achieved results will provide biochemists with techniques to identify more metabolic regions and biological pathways for complex diseases, and design and test novel therapeutic solutions.

  18. Risk Assessment of Distribution Network Based on Random set Theory and Sensitivity Analysis

    Science.gov (United States)

    Zhang, Sh; Bai, C. X.; Liang, J.; Jiao, L.; Hou, Z.; Liu, B. Zh

    2017-05-01

    Considering the complexity and uncertainty of operating information in distribution network, this paper introduces the use of random set for risk assessment. The proposed method is based on the operating conditions defined in the random set framework to obtain the upper and lower cumulative probability functions of risk indices. Moreover, the sensitivity of risk indices can effectually reflect information about system reliability and operating conditions, and by use of these information the bottlenecks that suppress system reliability can be found. The analysis about a typical radial distribution network shows that the proposed method is reasonable and effective.

  19. Network coding and evolutionary theory for performance enhancement in wireless cooperative clusters

    DEFF Research Database (Denmark)

    Militano, Leonardo; Fitzek, Frank; Iera, Antonio

    2010-01-01

    , portions of a file to be successively exchanged among all cluster members over wireless local area network (WLAN) links. Besides showing the beneficial effects of cooperation, this paper also focuses on the performance enhancement that can be achieved when using the network coding paradigm, whose...... are investigated and an ad hoc conceived Genetic Algorithm (GA) designed. Either the service time (the time needed for all nodes to receive the complete file) or the energy consumption for the nodes is used as objective function, showing in both cases the fast convergence for the algorithm that makes it preferable...

  20. The Use of Social Networking to Increase Yield: Applying Persistence Theory to the Graduate Admissions Process

    Science.gov (United States)

    Wright, Russell W.

    2012-01-01

    This quantitative study explored the connection between the use of a private social networking website during the graduate admissions process at a law school in the southeastern United States and the decision to matriculate or withdraw from the program. A theoretical model of persistence over time within the graduate admissions process was…

  1. A Review of Verb Network Strengthening Treatment: Theory, Methods, Results, and Clinical Implications

    Science.gov (United States)

    Edmonds, Lisa A.

    2016-01-01

    This article examines Verb Network Strengthening Treatment (VNeST), a relatively new treatment approach for anomia in people with aphasia. The VNeST protocol aims to promote generalization to increased lexical retrieval of untrained words across a hierarchy of linguistic tasks, including single-word naming of nouns and verbs, sentence production,…

  2. Towards a long-term integrated monitoring programme in Europe: network design in theory and practice.

    Science.gov (United States)

    Parr, T W; Ferretti, M; Simpson, I C; Forsius, M; Kovács-Láng, E

    2002-09-01

    Long-term integrated monitoring is an important approach for investigating, detecting and predicing the effects of environmental changes. Currently. European freshwaters, glaciers, forests and other natural and semi-natural ecosystems and habitats are monitored by a number of networks established by different organisations. However, many monitoring programmes have a narrow focus (e.g. targeting individual ecosystems) and most have different measurement protocols and sampling design. This has resulted in poor integration of ecosystem monitoring at a European level, leading to some overlapping of efforts and a lack of harmonised data to inform policy decisions. The need for a consistent pan-European long-term integrated monitoring of terrestrial systems programme is recognised in the scientific community. However, the design of such a system can be problematic, not least because of the constraints imposed by the need to make maximum use of existing sites and networks. Based on the outcomes of the NoLIMITS project (Networking of Long-term Integrated Monitoring in Terrestrial Systems). this article reviews issues that should be addressed in designing a programme based on existing monitoring sites and networks. Four major design issues are considered: (i) users' requirements, (ii) the need to address multiple objectives, (iii) role of existing sites and (iv) operational aspects.

  3. The development of adolescents’ friendships and antipathies: A longitudinal multivariate network test of balance theory

    NARCIS (Netherlands)

    Rambaran, J.A.; Dijkstra, J.K.; Munniksma, A.; Cillessen, A.H.N.

    2015-01-01

    We examined the interplay between friendship (best friend) and antipathy (dislike) relationships among adolescents (N = 480; 11-14 years) in two US middle schools over three years (grades 6, 7, and 8). Using longitudinal multivariate network analysis (RSiena), the effects of friendships on

  4. Opening the black box of quality improvement collaboratives: An Actor-Network theory approach

    NARCIS (Netherlands)

    T. Broer (Tineke); A.P. Nieboer (Anna); R.A. Bal (Roland)

    2010-01-01

    textabstractBackground. 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

  5. Network representation of protein interactions: Theory of graph description and analysis.

    Science.gov (United States)

    Kurzbach, Dennis

    2016-09-01

    A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue-resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three-dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin. © 2016 The Protein Society.

  6. The Situation Awareness Weighted Network (SAWN) model and method: Theory and application.

    Science.gov (United States)

    Kalloniatis, Alexander; Ali, Irena; Neville, Timothy; La, Phuong; Macleod, Iain; Zuparic, Mathew; Kohn, Elizabeth

    2017-05-01

    We introduce a novel model and associated data collection method to examine how a distributed organisation of military staff who feed a Common Operating Picture (COP) generates Situation Awareness (SA), a critical component in organisational performance. The proposed empirically derived Situation Awareness Weighted Network (SAWN) model draws on two scientific models of SA, by Endsley involving perception, comprehension and projection, and by Stanton et al. positing that SA exists across a social and semantic network of people and information objects in activities connected across a set of tasks. The output of SAWN is a representation as a weighted semi-bipartite network of the interaction between people ('human nodes') and information artefacts such as documents and system displays ('product nodes'); link weights represent the Endsley levels of SA that individuals acquire from or provide to information objects and other individuals. The SAWN method is illustrated with aggregated empirical data from a case study of Australian military staff undertaking their work during two very different scenarios, during steady-state operations and in a crisis threat context. A key outcome of analysis of the weighted networks is that we are able to quantify flow of SA through an organisation as staff seek to "value-add" in the conduct of their work. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

  7. 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

  8. Neural-network-based depth-resolved multiscale structural optimization using density functional theory and electron diffraction data

    Science.gov (United States)

    Pennington, Robert S.; Coll, Catalina; Estradé, Sònia; Peiró, Francesca; Koch, Christoph T.

    2018-01-01

    Iterative neural-network-based three-dimensional structural optimization of atomic positions over tens of nanometers is performed using transmission electron microscope (TEM) diffraction data simulated from density functional theory (DFT) all-electron densities, thus retrieving parameter variations along the beam direction. We first use experimental data to show that the GPAW DFT code's all-electron densities are considerably more accurate for electron diffraction calculations compared to conventional isolated-atom scattering factors, and they also compare well to Wien2K DFT simulations. This DFT-TEM combination is then integrated into an iterative neural-network-optimization-based algorithm (PRIMES, parameter retrieval and inversion from multiple electron scattering) to retrieve nanometer-scale ferroelectric polarization domains and strain in theoretical bulklike specimens from TEM data. DFT and isolated-atom methods produce substantially different diffraction patterns and retrieved polarization domain parameters, and DFT is sufficient to retrieve strain properties from a silicon specimen simulated using experimentally derived structure factors. Thus, we show that the improved accuracy, fast computation, and intuitive integration make the GPAW DFT code well suited for three-dimensional materials characterization and demonstrate this using an iterative neural-network algorithm that is verifiable on the mesoscale and, with DFT integration, self-consistent on the nanoscale.

  9. Abnormal functional resting-state networks in ADHD: graph theory and pattern recognition analysis of fMRI data.

    Science.gov (United States)

    dos Santos Siqueira, Anderson; Biazoli Junior, Claudinei Eduardo; Comfort, William Edgar; Rohde, Luis Augusto; Sato, João Ricardo

    2014-01-01

    The framework of graph theory provides useful tools for investigating the neural substrates of neuropsychiatric disorders. Graph description measures may be useful as predictor variables in classification procedures. Here, we consider several centrality measures as predictor features in a classification algorithm to identify nodes of resting-state networks containing predictive information that can discriminate between typical developing children and patients with attention-deficit/hyperactivity disorder (ADHD). The prediction was based on a support vector machines classifier. The analyses were performed in a multisite and publicly available resting-state fMRI dataset of healthy children and ADHD patients: the ADHD-200 database. Network centrality measures contained little predictive information for the discrimination between ADHD patients and healthy subjects. However, the classification between inattentive and combined ADHD subtypes was more promising, achieving accuracies higher than 65% (balance between sensitivity and specificity) in some sites. Finally, brain regions were ranked according to the amount of discriminant information and the most relevant were mapped. As hypothesized, we found that brain regions in motor, frontoparietal, and default mode networks contained the most predictive information. We concluded that the functional connectivity estimations are strongly dependent on the sample characteristics. Thus different acquisition protocols and clinical heterogeneity decrease the predictive values of the graph descriptors.

  10. 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…

  11. Geographic Theories of Educational Development: Innovation Diffusion Within Informal Interpersonal Networks.

    Science.gov (United States)

    Berry, Brian J. L.

    An examination of geographic theories of social change clarifies how and why Torsten Haagerstrand's ideas have revolutionized geographic thinking, particularly regarding educational change and development, and provides the background for analyzing his models in detail. Haagerstrand developed the first formal geoqraphic model of diffusion…

  12. 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…

  13. A Network Based Theory of Health Systems and Cycles of Well-being

    Directory of Open Access Journals (Sweden)

    Michael Grant Rhodes

    2013-01-01

    Full Text Available There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign health and well-being systems we know today. But the core of a truly ‘complex adaptive system’ can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable.

  14. 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...

  15. Complex-disease networks of trait-associated single-nucleotide polymorphisms (SNPs) unveiled by information theory.

    Science.gov (United States)

    Li, Haiquan; Lee, Younghee; Chen, James L; Rebman, Ellen; Li, Jianrong; Lussier, Yves A

    2012-01-01

    Thousands of complex-disease single-nucleotide polymorphisms (SNPs) have been discovered in genome-wide association studies (GWAS). However, these intragenic SNPs have not been collectively mined to unveil the genetic architecture between complex clinical traits. The authors hypothesize that biological annotations of host genes of trait-associated SNPs may reveal the biomolecular modularity across complex-disease traits and offer insights for drug repositioning. Trait-to-polymorphism (SNPs) associations confirmed in GWAS were used. A novel method to quantify trait-trait similarity anchored in Gene Ontology annotations of human proteins and information theory was developed. The results were then validated with the shortest paths of physical protein interactions between biologically similar traits. A network was constructed consisting of 280 significant intertrait similarities among 177 disease traits, which covered 1438 well-validated disease-associated SNPs. Thirty-nine percent of intertrait connections were confirmed by curators, and the following additional studies demonstrated the validity of a proportion of the remainder. On a phenotypic trait level, higher Gene Ontology similarity between proteins correlated with smaller 'shortest distance' in protein interaction networks of complexly inherited diseases (Spearman ptraits' were similar to one another, as were 'metabolic syndrome traits' (Fisher's exact test p=0.001 and 3.5×10(-7), respectively). An imputed disease network by information-anchored functional similarity from GWAS trait-associated SNPs is reported. It is also demonstrated that small shortest paths of protein interactions correlate with complex-disease function. Taken together, these findings provide the framework for investigating drug targets with unbiased functional biomolecular networks rather than worn-out single-gene and subjective canonical pathway approaches.

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

    Science.gov (United States)

    2015-09-01

    congestion in the second figure. Node 3 is congested due to a DDOS attack, which is indicated by the shift of the phantom node to dominate 3λ and node...Network DMZ Demilitarized Zone AMQ Automated Malware Quarantine SNR Signal-to-Noise Ratio LTI Linear, Time Invariant bps Bits per Second DDOS ...this interface [22]. Examples of business applications are distributed denial of service ( DDOS ) protection, intrusion detection, and usage tracking

  17. A Dynamic Incentive Mechanism for Transmission Expansion in Electricity NetworksTheory, Modeling and Application

    OpenAIRE

    Rosellon, Juan; Weigt, Hannes

    2008-01-01

    This paper examines the Hogan-Rosellón-Vogelsang (2007) (HRV) incentive mechanism for transmission expansion, and tests it for different network topologies. This new mechanism is based upon redefining transmission output in terms of point-to-point transactions or financial transmission rights (FTRs) and applies Vogelsang’s (2001) incentive-regulation logic that proposes rebalancing the variable and fixed parts of a two-part tariff to promote efficient, long-term expansion. We anal...

  18. Prospect Theory for Enhanced Cyber-Physical Security of Drone Delivery Systems: A Network Interdiction Game

    OpenAIRE

    Sanjab, Anibal; Saad, Walid; Başar, Tamer

    2017-01-01

    The use of unmanned aerial vehicles (UAVs) as delivery systems of online goods is rapidly becoming a global norm, as corroborated by Amazon's "Prime Air" and Google's "Project Wing" projects. However, the real-world deployment of such drone delivery systems faces many cyber-physical security challenges. In this paper, a novel mathematical framework for analyzing and enhancing the security of drone delivery systems is introduced. In this regard, a zero-sum network interdiction game is formulat...

  19. 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.

  20. Partnership and measurement: the promise, practice and theory of a successful health social networking strategy.

    Science.gov (United States)

    Montague, Terrence; Nemis-White, Joanna; Cochrane, Bonnie; Meisner, Janice; Trasler, Tessa

    2013-01-01

    Patient health management (PHM) was launched as a promising paradigm to close care gaps, the inequities between usual and best care, for whole patient populations. PHM's core premise was that interventions of multidisciplinary, community-oriented partnerships that used repeated measurement and feedback of provider practices, clinical and economic outcomes and general communication of relevant health knowledge to all stakeholders would continuously make things better. This article reviews the evolution of PHM from its genesis in a series of casual hospital-based networks to its maturation in a province-wide, community-focused, clustered-lattice social network that facilitated the improved clinical and cost-efficient care and outcomes of whole patient populations. The factors underlying PHM's clinical and cost efficacy, specifically its patient-centric social networking structures and integral measurement and knowledge translation processes, offer continuing promise to optimally manage the care of our increasingly aged patient populations, with their high burden of chronic diseases and disproportionately large care gaps. In an era when patients are demanding and leading change, and governments are struggling fiscally, PHM's clinical efficacy and cost-efficiency are especially resonant. Things can be better.

  1. Application of neural networks and information theory to the identification of E. coli transcriptional promoters

    Energy Technology Data Exchange (ETDEWEB)

    Abremski, K. (Du Pont Merck Pharmaceutical Co., Wilmington, DE (USA). Experimental Station); Sirotkin, K. (National Center for Biotechnology Information, Bethesda, MD (USA)); Lapedes, A. (Los Alamos National Lab., NM (USA))

    1991-01-01

    The Humane Genome Project has as its eventual goal the determination of the entire DNA sequence of man, which comprises approximately 3 billion base pairs. An important aspect of this project will be the analysis of the sequence to locate regions of biological importance. New computer methods will be needed to automate and facilitate this task. In this paper, we have investigated use of neural networks for the recognition of functional patterns in biological sequences. The prediction of Escherichia coli transcriptional promoters was chosen as a model system for these studies. Two approaches were employed. In the fist method, a mutual information analysis of promoter and nonpromoter sequences was carried out to demonstrate the informative base positions that help to distinguish promoter sequences from non-promoter sequences. These base positions were than used to train a Perceptron to predict new promoter sequences. In the second method, the experimental knowledge of promoters was used to indicate the important base positions in the sequence. These base positions were used to train a back propagation network with hidden units which represented regions of sequence conservation found in promoters. With both types of networks, prediction of new promoter sequences was greater than 96.9%. 12 refs., 1 fig., 4 tabs.

  2. A statistically-based continuum theory for polymers with transient networks

    Science.gov (United States)

    Vernerey, Franck J.; Long, Rong; Brighenti, Roberto

    2017-10-01

    We present a physics-based theoretical framework to describe the transient mechanical response of polymers undergoing finite deformation. For this, a statistical description of the polymer network is provided by a distribution function that is allowed to evolve in time due to a combination of deformation and chain reconfiguration enabled by transient cross-links. After presenting the evolution law for the chain distribution function, we show that, using classical thermodynamics, one can determine how the entropy, elastic energy and true stress evolve in terms of the network configuration. In particular, we introduce the concept of distribution tensor, which enables a clean transition between the network statistics, its continuum representation and the macroscopic polymer response. In the context of Gaussian statistics, it is further shown that this tensor follows its own evolution law, enabling a simple handling of visco-elastic rubbers. The model degenerates to classical rubber elasticity when cross-links are permanent, while the case of viscous fluids is recovered for fast cross-link kinetics. The generality of the framework as well as its relevance to modeling a number of important dissipative processes occurring in polymers using a continuum approach are also discussed.

  3. Optimizing Natural Gas Networks through Dynamic Manifold Theory and a Decentralized Algorithm: Belgium Case Study

    Science.gov (United States)

    Koch, Caleb; Winfrey, Leigh

    2014-10-01

    Natural Gas is a major energy source in Europe, yet political instabilities have the potential to disrupt access and supply. Energy resilience is an increasingly essential construct and begins with transmission network design. This study proposes a new way of thinking about modelling natural gas flow. Rather than relying on classical economic models, this problem is cast into a time-dependent Hamiltonian dynamics discussion. Traditional Natural Gas constraints, including inelastic demand and maximum/minimum pipe flows, are portrayed as energy functions and built into the dynamics of each pipe flow. Doing so allows the constraints to be built into the dynamics of each pipeline. As time progresses in the model, natural gas flow rates find the minimum energy, thus the optimal gas flow rates. The most important result of this study is using dynamical principles to ensure the output of natural gas at demand nodes remains constant, which is important for country to country natural gas transmission. Another important step in this study is building the dynamics of each flow in a decentralized algorithm format. Decentralized regulation has solved congestion problems for internet data flow, traffic flow, epidemiology, and as demonstrated in this study can solve the problem of Natural Gas congestion. A mathematical description is provided for how decentralized regulation leads to globally optimized network flow. Furthermore, the dynamical principles and decentralized algorithm are applied to a case study of the Fluxys Belgium Natural Gas Network.

  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. 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

  6. 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.

  7. 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.

  8. An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

    Science.gov (United States)

    Young, David; Borland, Ron; Coghill, Ken

    2010-07-01

    Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

  9. Information infrastructure for inter-organizational mental health services: an actor network theory analysis of psychiatric rehabilitation.

    Science.gov (United States)

    Timpka, Toomas; Bång, Magnus; Delbanco, Tom; Walker, Janet

    2007-08-01

    In the supply of mental health services to communities, data and information are managed not only by clinical organizations, but also by welfare state agencies and charities. The aim of this study is to use methods of analysis from actor network theory to identify organizational interventions necessary for the development of an information infrastructure for inter-organizational mental health services. Data was collected in a project aimed at developing an information system that supports inter-organizational psychiatric rehabilitation in a Swedish municipality. Three organizational interventions were identified: an integrated service policy defined by the national government, a common legal framework allowing sharing of high-level client data, and commissioned support for local inter-agency workspaces. It is concluded that organizational interventions must be regarded when configuring an information infrastructure for mental health services. Organizational interventions should also routinely be addressed in systems design methods to be used in inter-organizational settings.

  10. Exploring the Potential Contribution of Actor-Network Theory in Nursing Using the Integration of Nurse Practitioners as an Exemplar

    Directory of Open Access Journals (Sweden)

    Annie Rioux-Dubois

    2016-10-01

    Full Text Available Nurse Practitioners (NPs are clinically effective and safe. They positively influence patient outcomes, and they increase access to care while decreasing health care costs. Despite these significant benefits, NPs can seldom practice to their full scope and often experience interprofessional tensions. The supposed lack of clarity around NPs’ role is often cited as a barrier to seamless integration, despite clear legal and professional delineation. We suggest other factors are at play within the Canadian health care system that explain why, after almost four decades, NPs’ full involvement as equal health care partners and their job satisfaction remain modest at best. New, critical frameworks are needed to uncover the various contingencies that mediate their integration process. This paper explores how Actor-Network Theory (ANT can provide such a framework to analyze contemporary issues in advanced nursing practice. ANT’s main concepts are explored along with their applicability to an examination of NPs’ integration in the Canadian health care system.

  11. 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...

  12. Unravelling the size distribution of social groups with information theory in complex networks

    Science.gov (United States)

    Hernando, A.; Villuendas, D.; Vesperinas, C.; Abad, M.; Plastino, A.

    2010-07-01

    The minimization of Fisher’s information (MFI) approach of Frieden et al. [Phys. Rev. E 60, 48 (1999)] is applied to the study of size distributions in social groups on the basis of a recently established analogy between scale invariant systems and classical gases [Phys. A 389, 490 (2010)]. Going beyond the ideal gas scenario is seen to be tantamount to simulating the interactions taking place, for a competitive cluster growth process, in a scale-free ideal network - a non-correlated network with a connection-degree’s distribution that mimics the scale-free ideal gas density distribution. We use a scaling rule that allows one to classify the final cluster-size distributions using only one parameter that we call the competitiveness, which can be seen as a measure of the strength of the interactions. We find that both empirical city-size distributions and electoral results can be thus reproduced and classified according to this competitiveness-parameter, that also allow us to infer the maximum number of stable social relationships that one person can maintain, known as the Dunbar number, together with its standard deviation. We discuss the importance of this number in connection with the empirical phenomenon known as “six-degrees of separation”. Finally, we show that scaled city-size distributions of large countries follow, in general, the same universal distribution.

  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. 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.

  15. Network science and the human brain: Using graph theory to understand the brain and one of its hubs, the amygdala, in health and disease.

    Science.gov (United States)

    Mears, David; Pollard, Harvey B

    2016-06-01

    Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

  16. 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.

  17. An Index for Measuring Functional Diversity in Plant Communities Based on Neural Network Theory

    Directory of Open Access Journals (Sweden)

    Naiqi Song

    2013-01-01

    Full Text Available Functional diversity in plant communities is a key driver of ecosystem processes. The effective methods for measuring functional diversity are important in ecological studies. A new method based on neural network, self-organizing feature map (SOFM index, was put forward and described. A case application to the study of functional diversity of Phellodendron amurense communities in Xiaolongmen Forest Park of Beijing was carried out in this paper. The results showed that SOFM index was an effective method in the evaluation of functional diversity and its change in plant communities. Significant nonlinear correlations of SOFM index with the common used methods, FAD, MFAD, FDp, FDc, FRic, and FDiv indices, also proved that SOFM index is useful in the studies of functional diversity.

  18. From Cortical Blindness to Conscious Visual Perception: Theories on Neuronal Networks and Visual Training Strategies

    Directory of Open Access Journals (Sweden)

    Vanessa Hadid

    2017-08-01

    Full Text Available Homonymous hemianopia (HH is the most common cortical visual impairment leading to blindness in the contralateral hemifield. It is associated with many inconveniences and daily restrictions such as exploration and visual orientation difficulties. However, patients with HH can preserve the remarkable ability to unconsciously perceive visual stimuli presented in their blindfield, a phenomenon known as blindsight. Unfortunately, the nature of this captivating residual ability is still misunderstood and the rehabilitation strategies in terms of visual training have been insufficiently exploited. This article discusses type I and type II blindsight in a neuronal framework of altered global workspace, resulting from inefficient perception, attention and conscious networks. To enhance synchronization and create global availability for residual abilities to reach visual consciousness, rehabilitation tools need to stimulate subcortical extrastriate pathways through V5/MT. Multisensory bottom-up compensation combined with top-down restitution training could target pre-existing and new neuronal mechanisms to recreate a framework for potential functionality.

  19. From Cortical Blindness to Conscious Visual Perception: Theories on Neuronal Networks and Visual Training Strategies.

    Science.gov (United States)

    Hadid, Vanessa; Lepore, Franco

    2017-01-01

    Homonymous hemianopia (HH) is the most common cortical visual impairment leading to blindness in the contralateral hemifield. It is associated with many inconveniences and daily restrictions such as exploration and visual orientation difficulties. However, patients with HH can preserve the remarkable ability to unconsciously perceive visual stimuli presented in their blindfield, a phenomenon known as blindsight. Unfortunately, the nature of this captivating residual ability is still misunderstood and the rehabilitation strategies in terms of visual training have been insufficiently exploited. This article discusses type I and type II blindsight in a neuronal framework of altered global workspace, resulting from inefficient perception, attention and conscious networks. To enhance synchronization and create global availability for residual abilities to reach visual consciousness, rehabilitation tools need to stimulate subcortical extrastriate pathways through V5/MT. Multisensory bottom-up compensation combined with top-down restitution training could target pre-existing and new neuronal mechanisms to recreate a framework for potential functionality.

  20. 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.

  1. Finite-representation approximation of lattice gauge theories at the continuum limit with tensor networks

    Science.gov (United States)

    Buyens, Boye; Montangero, Simone; Haegeman, Jutho; Verstraete, Frank; Van Acoleyen, Karel

    2017-05-01

    It has been established that matrix product states can be used to compute the ground state and single-particle excitations and their properties of lattice gauge theories at the continuum limit. However, by construction, in this formalism the Hilbert space of the gauge fields is truncated to a finite number of irreducible representations of the gauge group. We investigate quantitatively the influence of the truncation of the infinite number of representations in the Schwinger model, one-flavor QED2 , with a uniform electric background field. We compute the two-site reduced density matrix of the ground state and the weight of each of the representations. We find that this weight decays exponentially with the quadratic Casimir invariant of the representation which justifies the approach of truncating the Hilbert space of the gauge fields. Finally, we compute the single-particle spectrum of the model as a function of the electric background field.

  2. 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

  3. 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.

  4. 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…

  5. Similarities and Dissimilarities in Coauthorship Networks: Gestalt Theory as Explanation for Well-Ordered Collaboration Structures and Production of Scientific Literature.

    Science.gov (United States)

    Kretschmer, Hildrun

    2002-01-01

    Based on Gestalt theory, the author assumes the existence of a field-force equilibrium to explain how, according to the conciseness principle, mathematically precise gestalts could exist in coauthorship networks. Develops a mathematical function to describe these gestalts in scientific literature and discusses structural characteristics of…

  6. The Changing Landscape of Literacy Curriculum in a Sino-Canada Transnational Education Programme: An Actor-Network Theory Informed Case Study

    Science.gov (United States)

    Zhang, Zheng; Heydon, Rachel

    2016-01-01

    This paper concerns an exploratory and interpretive case study of the literacy curricula in a Canadian transnational education programme (Pseudonym: SCS) delivered in China where Ontario secondary school curricula were used at the same time as the Chinese national high school curricula. Using ethnographic tools and actor-network theory, the study…

  7. 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.

  8. 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.

  9. 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.

  10. Dynamics of influence processes on networks: Complete mean-field theory; the roles of response functions, connectivity, and synchrony; and applications to social contagion

    CERN Document Server

    Harris, Kameron Decker; Dodds, Peter Sheridan

    2013-01-01

    We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. Allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean field theory for random networks and show this predicts that the dynamics on the network are a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and non-conformity by incorporating an off-threshold into standard threshold models of social contagion. In this way we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "li...

  11. Actor-network theory and the OSCE: formulating a new research agenda for a post-psychometric era.

    Science.gov (United States)

    Bearman, Margaret; Ajjawi, Rola

    2017-10-12

    The Objective Structured Clinical Examination (OSCE) is a ubiquitous part of medical education, although there is some debate about its value, particularly around possible impact on learning. Literature and research regarding the OSCE is most often situated within the psychometric or competency discourses of assessment. This paper describes an alternative approach: Actor-network-theory (ANT), a sociomaterial approach to understanding practice and learning. ANT provides a means to productively examine tensions and limitations of the OSCE, in part through extending research to include social relationships and physical objects. Using a narrative example, the paper suggests three ANT-informed insights into the OSCE. We describe: (1) exploring the OSCE as a holistic combination of people and objects; (2) thinking about the influences a checklist can exert over the OSCE; and (3) the implications of ANT educational research for standardisation within the OSCE. We draw from this discussion to provide a practical agenda for ANT research into the OSCE. This agenda promotes new areas for exploration in an often taken-for-granted assessment format.

  12. 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.

  13. 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.

  14. 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

  15. The use of artificial neural networks and multiple linear regression in modeling work-health relationships: translating theory into analytical practice

    OpenAIRE

    Karanika-Murray, M; Cox, T

    2010-01-01

    Although psychological theory acknowledges the existence of complex systems and the importance of nonlinear effects, linear statistical models have been traditionally used to examine relationships between environmental stimuli and outcomes. The way we analyse these relationships does not seem to reflect the way we conceptualize them. The present study investigated the application of connectionism (artificial neural networks) to modelling the relationships between work characteristics and empl...

  16. How Managers Can Conduct Planned Change in Self-organising Systems: Actor Network Theory as a Perspective to Manager¡¯s Actions

    OpenAIRE

    Robert J. Blomme

    2012-01-01

    This article discusses why the majority of change initiatives in organisations fail in accomplishing the intended goals and expectations defined by its members and gives directions for a new perspective of organisational change and the leadership role of managers in this. First this paper carries out a literature review of notions from Weick¡¯s sensemaking concept and Actor Network Theory to develop a perspective of emergent organisational change and the role played by managers. The limitatio...

  17. A density-functional theory-based neural network potential for water clusters including van der Waals corrections.

    Science.gov (United States)

    Morawietz, Tobias; Behler, Jörg

    2013-08-15

    The fundamental importance of water for many chemical processes has motivated the development of countless efficient but approximate water potentials for large-scale molecular dynamics simulations, from simple empirical force fields to very sophisticated flexible water models. Accurate and generally applicable water potentials should fulfill a number of requirements. They should have a quality close to quantum chemical methods, they should explicitly depend on all degrees of freedom including all relevant many-body interactions, and they should be able to describe molecular dissociation and recombination. In this work, we present a high-dimensional neural network (NN) potential for water clusters based on density-functional theory (DFT) calculations, which is constructed using clusters containing up to 10 monomers and is in principle able to meet all these requirements. We investigate the reliability of specific parametrizations employing two frequently used generalized gradient approximation (GGA) exchange-correlation functionals, PBE and RPBE, as reference methods. We find that the binding energy errors of the NN potentials with respect to DFT are significantly lower than the typical uncertainties of DFT calculations arising from the choice of the exchange-correlation functional. Further, we examine the role of van der Waals interactions, which are not properly described by GGA functionals. Specifically, we incorporate the D3 scheme suggested by Grimme (J. Chem. Phys. 2010, 132, 154104) in our potentials and demonstrate that it can be applied to GGA-based NN potentials in the same way as to DFT calculations without modification. Our results show that the description of small water clusters provided by the RPBE functional is significantly improved if van der Waals interactions are included, while in case of the PBE functional, which is well-known to yield stronger binding than RPBE, van der Waals corrections lead to overestimated binding energies.

  18. Epistemology and Networking Theories

    Science.gov (United States)

    Kidron, Ivy

    2016-01-01

    A theoretical reflection on epistemology is presented. The important role of epistemological analysis in research in mathematics education is discussed. I analyze the epistemological evolution as a consequence of the changes in the mathematical culture and demonstrate how the epistemological analysis is tightly linked to the cultural dimension.…

  19. A fibril-based structural constitutive theory reveals the dominant role of network characteristics on the mechanical behavior of fibroblast-compacted collagen gels.

    Science.gov (United States)

    Feng, Zhonggang; Ishiguro, Yuki; Fujita, Kyohei; Kosawada, Tadashi; Nakamura, Takao; Sato, Daisuke; Kitajima, Tatsuo; Umezu, Mitsuo

    2015-10-01

    In this paper, we present a general, fibril-based structural constitutive theory which accounts for three material aspects of crosslinked filamentous materials: the single fibrillar force response, the fibrillar network model, and the effects of alterations to the fibrillar network. In the case of the single fibrillar response, we develop a formula that covers the entropic and enthalpic deformation regions, and introduce the relaxation phase to explain the observed force decay after crosslink breakage. For the filamentous network model, we characterize the constituent element of the fibrillar network in terms its end-to-end distance vector and its contour length, then decompose the vector orientation into an isotropic random term and a specific alignment, paving the way for an expanded formalism from principal deformation to general 3D deformation; and, more important, we define a critical core quantity over which macroscale mechanical characteristics can be integrated: the ratio of the initial end-to-end distance to the contour length (and its probability function). For network alterations, we quantitatively treat changes in constituent elements and relate these changes to the alteration of network characteristics. Singular in its physical rigor and clarity, this constitutive theory can reproduce and predict a wide range of nonlinear mechanical behavior in materials composed of a crosslinked filamentous network, including: stress relaxation (with dual relaxation coefficients as typically observed in soft tissues); hysteresis with decreasing maximum stress under serial cyclic loading; strain-stiffening under uniaxial tension; the rupture point of the structure as a whole; various effects of biaxial tensile loading; strain-stiffening under simple shearing; the so-called "negative normal stress" phenomenon; and enthalpic elastic behaviors of the constituent element. Applied to compacted collagen gels, the theory demonstrates that collagen fibrils behave as enthalpic

  20. 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.

  1. 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.

  2. Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study.

    Science.gov (United States)

    Jiang, Wenyu; Li, Jianping; Chen, Xuemei; Ye, Wei; Zheng, Jinou

    2017-01-01

    Previous studies have shown that temporal lobe epilepsy (TLE) involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE) patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.

  3. Disrupted Structural and Functional Networks and Their Correlation with Alertness in Right Temporal Lobe Epilepsy: A Graph Theory Study

    Directory of Open Access Journals (Sweden)

    Wenyu Jiang

    2017-05-01

    Full Text Available Previous studies have shown that temporal lobe epilepsy (TLE involves abnormal structural or functional connectivity in specific brain areas. However, limited comprehensive studies have been conducted on TLE associated changes in the topological organization of structural and functional networks. Additionally, epilepsy is associated with impairment in alertness, a fundamental component of attention. In this study, structural networks were constructed using diffusion tensor imaging tractography, and functional networks were obtained from resting-state functional MRI temporal series correlations in 20 right temporal lobe epilepsy (rTLE patients and 19 healthy controls. Global network properties were computed by graph theoretical analysis, and correlations were assessed between global network properties and alertness. The results from these analyses showed that rTLE patients exhibit abnormal small-world attributes in structural and functional networks. Structural networks shifted toward more regular attributes, but functional networks trended toward more random attributes. After controlling for the influence of the disease duration, negative correlations were found between alertness, small-worldness, and the cluster coefficient. However, alertness did not correlate with either the characteristic path length or global efficiency in rTLE patients. Our findings show that disruptions of the topological construction of brain structural and functional networks as well as small-world property bias are associated with deficits in alertness in rTLE patients. These data suggest that reorganization of brain networks develops as a mechanism to compensate for altered structural and functional brain function during disease progression.

  4. 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

  5. Discriminating micropathogen lineages and their reticulate evolution through graph theory-based network analysis: the case of Trypanosoma cruzi, the agent of Chagas disease.

    Science.gov (United States)

    Arnaud-Haond, Sophie; Moalic, Yann; Barnabé, Christian; Ayala, Francisco José; Tibayrenc, Michel

    2014-01-01

    Micropathogens (viruses, bacteria, fungi, parasitic protozoa) share a common trait, which is partial clonality, with wide variance in the respective influence of clonality and sexual recombination on the dynamics and evolution of taxa. The discrimination of distinct lineages and the reconstruction of their phylogenetic history are key information to infer their biomedical properties. However, the phylogenetic picture is often clouded by occasional events of recombination across divergent lineages, limiting the relevance of classical phylogenetic analysis and dichotomic trees. We have applied a network analysis based on graph theory to illustrate the relationships among genotypes of Trypanosoma cruzi, the parasitic protozoan responsible for Chagas disease, to identify major lineages and to unravel their past history of divergence and possible recombination events. At the scale of T. cruzi subspecific diversity, graph theory-based networks applied to 22 isoenzyme loci (262 distinct Multi-Locus-Enzyme-Electrophoresis -MLEE) and 19 microsatellite loci (66 Multi-Locus-Genotypes -MLG) fully confirms the high clustering of genotypes into major lineages or "near-clades". The release of the dichotomic constraint associated with phylogenetic reconstruction usually applied to Multilocus data allows identifying putative hybrids and their parental lineages. Reticulate topology suggests a slightly different history for some of the main "near-clades", and a possibly more complex origin for the putative hybrids than hitherto proposed. Finally the sub-network of the near-clade T. cruzi I (28 MLG) shows a clustering subdivision into three differentiated lesser near-clades ("Russian doll pattern"), which confirms the hypothesis recently proposed by other investigators. The present study broadens and clarifies the hypotheses previously obtained from classical markers on the same sets of data, which demonstrates the added value of this approach. This underlines the potential of graph

  6. 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.

  7. 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.

  8. Dissecting the social brain: Introducing the EmpaToM to reveal distinct neural networks and brain-behavior relations for empathy and Theory of Mind.

    Science.gov (United States)

    Kanske, Philipp; Böckler, Anne; Trautwein, Fynn-Mathis; Singer, Tania

    2015-11-15

    Successful social interactions require both affect sharing (empathy) and understanding others' mental states (Theory of Mind, ToM). As these two functions have mostly been investigated in isolation, the specificity of the underlying neural networks and the relation of these networks to the respective behavioral indices could not be tested. Here, we present a novel fMRI paradigm (EmpaToM) that independently manipulates both empathy and ToM. Experiments 1a/b (N=90) validated the task with established empathy and ToM paradigms on a behavioral and neural level. Experiment 2 (N=178) employed the EmpaToM and revealed clearly separable neural networks including anterior insula for empathy and ventral temporoparietal junction for ToM. These distinct networks could be replicated in task-free resting state functional connectivity. Importantly, brain activity in these two networks specifically predicted the respective behavioral indices, that is, inter-individual differences in ToM related brain activity predicted inter-individual differences in ToM performance, but not empathic responding, and vice versa. Taken together, the validated EmpaToM allows separation of affective and cognitive routes to understanding others. It may thus benefit future clinical, developmental, and intervention studies on identifying selective impairments and improvement in specific components of social cognition. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Application of network theory to mark recapture data allows insights into population structure of two Heliconius species

    Directory of Open Access Journals (Sweden)

    Luciana L.F. de Lima

    2015-06-01

    Full Text Available By noting the spatial location of captured individuals mark-recapture studies create a collection of discrete events spread in space and time. This setup is appropriate for network modeling where the vertices (or nodes are the points of capture and links are established whenever a recapture occurs. Applying network analytical tools, it is possible to ascertain aspects of spatial structure and generate predictions regarding the likely causes of structure in the network. We studied the spatial network of two tropical butterfly species, Heliconius erato and H. melpomene, using a mark-recapture database from a 2-year survey in an Atlantic Forest remnant in Brazil. The overall network structure of both species was similar in number of vertices and average connectivity. Heliconius erato had a smaller, more disconnected network structure, suggesting shorter traveling paths. The distribution of connectivity of both species was better adjusted by a power-law distribution. We found hubs in both species; hubs are points of high capture and their location is correlated with the location of flowering plants visited by adults. In complex systems, hub elimination can have a notable collapsing effect in network structure. Because resource hubs are important for butterfly network organization we suggest management as well as experimental tests with regards to the role of resource hotspots for population structure.

  10. The activation of theory of mind network differentiates between point-to-self and point-to-other verbal jokes: an fMRI study.

    Science.gov (United States)

    Feng, Shengchuang; Ye, Xiang; Mao, Lihua; Yue, Xiaodong

    2014-04-03

    The mind-reading hypothesis of humor and the inner eye theory of laughter both claim that readers' mentalizing about characters in jokes is essential for perceiving humor. On the basis of this notion, we hypothesized that point-to-other verbal jokes (in which one character said funny things about the other character) induced more theory of mind (ToM) processing than point-to-self verbal jokes (in which one character said funny things about him/herself to the other character). Our hypothesis was tested by comparing percent signal changes of these two conditions in six core components of the ToM neural network. A whole-brain analysis was also conducted. Results from both the region of interest (ROI) analysis and the whole-brain analysis show that theory of mind network is more activated when subjects read point-to-other jokes than when they read point-to-self jokes. Moreover, the whole-brain results provide support for the viewpoint that the right hemisphere, especially the right frontal lobe, is important in ToM and humor processing. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  11. 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

  12. 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

  13. 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...

  14. 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.

  15. 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.

  16. Cyberspace Assurance Metrics: Utilizing Models of Networks, Complex Systems Theory, Multidimensional Wavelet Analysis, and Generalized Entrophy Measures

    National Research Council Canada - National Science Library

    Johnson, Joseph E; Gudkov, Vladimir

    2005-01-01

    .... The PI, under the funding of this grant, has discovered a strong connection between the topological specification of a network in the form of a connection matrix and the branches of mathematics known...

  17. 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...

  18. 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.

  19. 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...

  20. Analysis of Pull-In Instability of Geometrically Nonlinear Microbeam Using Radial Basis Artificial Neural Network Based on Couple Stress Theory

    Directory of Open Access Journals (Sweden)

    Mohammad Heidari

    2014-01-01

    Full Text Available The static pull-in instability of beam-type microelectromechanical systems (MEMS is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS.

  1. Analysis of pull-in instability of geometrically nonlinear microbeam using radial basis artificial neural network based on couple stress theory.

    Science.gov (United States)

    Heidari, Mohammad; Heidari, Ali; Homaei, Hadi

    2014-01-01

    The static pull-in instability of beam-type microelectromechanical systems (MEMS) is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS.

  2. 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....

  3. Stem Cell Networks

    OpenAIRE

    Werner, Eric

    2016-01-01

    We present a general computational theory of stem cell networks and their developmental dynamics. Stem cell networks are special cases of developmental control networks. Our theory generates a natural classification of all possible stem cell networks based on their network architecture. Each stem cell network has a unique topology and semantics and developmental dynamics that result in distinct phenotypes. We show that the ideal growth dynamics of multicellular systems generated by stem cell ...

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

    NARCIS (Netherlands)

    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

  5. 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.

  6. Publications of the Jet Propulsion Laboratory, January through December 1974. [deep space network, Apollo project, information theory, and space exploration

    Science.gov (United States)

    1975-01-01

    Formalized technical reporting is described and indexed, which resulted from scientific and engineering work performed, or managed, by the Jet Propulsion Laboratory. The five classes of publications included are technical reports, technical memorandums, articles from the bimonthly Deep Space Network Progress Report, special publications, and articles published in the open literature. The publications are indexed by author, subject, and publication type and number.

  7. 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.

  8. 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…

  9. Linguistic Politeness and Interpersonal Ties among Bengalis on the Social Network Site Orkut[R]: The Bulge Theory Revisited

    Science.gov (United States)

    Das, Anupam

    2010-01-01

    This study examined linguistic politeness behaviors and their relationship to social distance among members of a diasporic Bengali community on the social network site "Orkut"[R]. Using data from computer-mediated communication (CMC), specifically text messages posted on "Orkut"[R] "scrapbooks," it developed a method to test the claims of the…

  10. 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

  11. 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.

  12. Pessoas sem voz, redes indizíveis e grupos descartáveis: os limites da teoria do actor-rede Voiceless people, unnamable networks and disposable groups: the limits of actor-network theory

    Directory of Open Access Journals (Sweden)

    José Manuel de Oliveira Mendes

    2010-01-01

    Full Text Available Neste artigo procede-se a uma reflexão crítica sobre a teoria do actor-rede de Michel Callon e Bruno Latour. Salienta-se a necessidade de incorporar no estudo do social as emoções e a imponderabilidade.Tendo como referência a análise de situações de catástrofe ou de acontecimentos extremos, propõe-se uma reflexão sobre o trabalho político que coloca fora das redes sociais, como irrecuperáveis e descartáveis, todos os que não criam ou não possuem valor na perspectiva hegemónica e que, por conseguinte, não são construídos como portadores de direitos sociais e políticos, tornando-se invisíveis e ausentes das análises convencionais propostas pela teoria do actor-rede.In this paper a critical analysis of Bruno Latour and Michel Callon’s actor-network theory is proposed. It is argued that studies about the social must incorporate emotions and imponderability. Focusing on the analysis of catastrophes and extreme events, a reflection on the political work that excludes from the social networks, as irretrievable and disposable, all those that do not create or do not carry value in the hegemonic perspective and, therefore, are not construed as having social and political rights is presented. These irretrievable and disposable persons and groups become invisible and absent in the conventional analyses proposed by actor-network theory.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Flows of worship in the network society: liminality as heuristic concept in Practical Theology beyond action theory

    Directory of Open Access Journals (Sweden)

    M. Barnard

    2010-07-01

    Full Text Available In this article it is demonstrated why and how liminality has developed into a key concept in Practical Theology, in particular in Liturgical Studies.  Liminality began its voyage at the beginning of the 20th century as indication of the phase “betwixt and between” distinguished social and spatial stages in rites of passage (Van Gennep, 1960. Among its defining qualities were autonomy and in-stability. In the sixties it developed into a more permanent state, in which “communitas” could come into being as a marginal form of human interrelatedness (Turner, 1995. In the network society of the 21st century liminality has accomplished its journey by moving to the centre of society, pushing structured human interrelatedness to the “margin”, or more precisely to the local, regional, national or categorical (religious, gender, sexual preference, etc. domain (Castells, 2000a; 2004; 2000b. Hu-man society is built around a centre of the stability of the unstable.  This also holds for Christian faith and for liturgy. Christian ritual is performed across (worldwide networks and in independent groups and churches by anyone who chooses to do so. There is no liturgical elite anymore; it is principally a popular move-ment characterised by “plural authority structures”. The acade-mic heuristic power of liminality is finally demonstrated in two liturgical cases.

  2. 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.   

  3. Fragment Assembly Approach Based on Graph/Network Theory with Quantum Chemistry Verifications for Assigning Multidimensional NMR Signals in Metabolite Mixtures.

    Science.gov (United States)

    Ito, Kengo; Tsutsumi, Yu; Date, Yasuhiro; Kikuchi, Jun

    2016-04-15

    The abundant observation of chemical fragment information for molecular complexities is a major advantage of biological NMR analysis. Thus, the development of a novel technique for NMR signal assignment and metabolite identification may offer new possibilities for exploring molecular complexities. We propose a new signal assignment approach for metabolite mixtures by assembling H-H, H-C, C-C, and Q-C fragmental information obtained by multidimensional NMR, followed by the application of graph and network theory. High-speed experiments and complete automatic signal assignments were achieved for 12 combined mixtures of (13)C-labeled standards. Application to a (13)C-labeled seaweed extract showed 66 H-C, 60 H-H, 326 C-C, and 28 Q-C correlations, which were successfully assembled to 18 metabolites by the automatic assignment. The validity of automatic assignment was supported by quantum chemical calculations. This new approach can predict entire metabolite structures from peak networks of biological extracts.

  4. Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory

    Directory of Open Access Journals (Sweden)

    Lei Si

    2015-11-01

    Full Text Available In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN and the Dempster-Shafer (DS theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs based on the ensemble empirical mode decomposition (EEMD. In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.

  5. Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory.

    Science.gov (United States)

    Si, Lei; Wang, Zhongbin; Liu, Xinhua; Tan, Chao; Xu, Jing; Zheng, Kehong

    2015-11-13

    In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system.

  6. TV programme presentations: Bang Goes the Theory by BBC (2010) and Beyond the Atom with John Ellis by Redes and Science Networks (2010)

    CERN Multimedia

    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...

  7. Understanding Local and Macroscopic Electron Mobilities in the Fullerene Network of Conjugated Polymer-based Solar Cells. Time-Resolved Microwave Conductivity and Theory

    Energy Technology Data Exchange (ETDEWEB)

    Aguirre, Jordan C. [Univ. of California, Los Angeles, CA (United States); Arntsen, Christopher D. [Univ. of California, Los Angeles, CA (United States); Hernandez, Samuel [Univ. of California, Los Angeles, CA (United States); Huber, Rachel [Univ. of California, Los Angeles, CA (United States); Nardes, Alexandre M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Halim, Merissa [Univ. of California, Los Angeles, CA (United States); Kilbride, Daniel [Univ. of California, Los Angeles, CA (United States); Rubin, Yves [Univ. of California, Los Angeles, CA (United States); Tolbert, Sarah H. [Univ. of California, Los Angeles, CA (United States); Kopidakis, Nikos [National Renewable Energy Lab. (NREL), Golden, CO (United States); Schwartz, Benjamin J. [Univ. of California, Los Angeles, CA (United States); Neuhauser, Daniel [Univ. of California, Los Angeles, CA (United States)

    2013-09-23

    The efficiency of bulk heterojunction (BHJ) organic photovoltaics is sensitive to the morphology of the fullerene network that transports electrons through the device. This sensitivity makes it difficult to distinguish the contrasting roles of local electron mobility (how easily electrons can transfer between neighboring fullerene molecules) and macroscopic electron mobility (how well-connected is the fullerene network on device length scales) in solar cell performance. In this work, a combination of density functional theory (DFT) calculations, flash-photolysis time-resolved microwave conductivity (TRMC) experiments, and space-charge-limit current (SCLC) mobility estimates are used to examine the roles of local and macroscopic electron mobility in conjugated polymer/fullerene BHJ photovoltaics. The local mobility of different pentaaryl fullerene derivatives (so-called ‘shuttlecock’ molecules) is similar, so that differences in solar cell efficiency and SCLC mobilities result directly from the different propensities of these molecules to self-assemble on macroscopic length scales. These experiments and calculations also demonstrate that the local mobility of phenyl-C60 butyl methyl ester (PCBM) is an order of magnitude higher than that of other fullerene derivatives, explaining why PCBM has been the acceptor of choice for conjugated polymer BHJ devices even though it does not form an optimal macroscopic network. The DFT calculations indicate that PCBM's superior local mobility comes from the near-spherical nature of its molecular orbitals, which allow strong electronic coupling between adjacent molecules. In combination, DFT and TRMC techniques provide a tool for screening new fullerene derivatives for good local mobility when designing new molecules that can improve on the macroscopic electron mobility offered by PCBM.

  8. 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.

  9. Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks.

    Science.gov (United States)

    Nunez, P L; Wingeier, B M; Silberstein, R B

    2001-07-01

    A theoretical framework supporting experimental measures of dynamic properties of human EEG is proposed with emphasis on distinct alpha rhythms. Robust relationships between measured dynamics and cognitive or behavioral conditions are reviewed, and proposed physiological bases for EEG at cellular levels are considered. Classical EEG data are interpreted in the context of a conceptual framework that distinguishes between locally and globally dominated dynamic processes, as estimated with coherence or other measures of phase synchronization. Macroscopic (scalp) potentials generated by cortical current sources are described at three spatial scales, taking advantage of the columnar structure of neocortex. New EEG data demonstrate that both globally coherent and locally dominated behavior can occur within the alpha band, depending on narrow band frequency, spatial measurement scale, and brain state. Quasi-stable alpha phase structures consistent with global standing waves are observed. At the same time, alpha and theta phase locking between cortical regions during mental calculations is demonstrated, consistent with neural network formation. The brain-binding problem is considered in the context of EEG dynamic behavior that generally exhibits both of these local and global aspects. But specific experimental designs and data analysis methods may severely bias physiological interpretations in either local or global directions. Copyright 2001 Wiley-Liss, Inc.

  10. 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.

  11. 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

  12. Maneiras de pesquisar no cotidiano: contribuição da teoria do ator-rede Ways of researching everyday life: the actor-network theory contribution

    Directory of Open Access Journals (Sweden)

    Ronald João Jacques Arendt

    2008-01-01

    Full Text Available A partir da temática geral do XI Simpósio da ANPEPP"Maneiras de pesquisar no cotidiano: contribuições para a formação em pesquisa em Psicologia", e tendo em vista a participação do autor no GT "Cotidiano e Práticas Sociais" da ANPEPP, este texto busca descrever a prática de formação em pesquisa a partir da teoria do ator-rede. Após efetuar a recensão de um texto de Bruno Latour, um diálogo entre um professor e um aluno em que são expostas as principais características da prática de pesquisa no âmbito desta abordagem, o autor busca precisar o posicionamento epistemológico-metodológico da referida teoria assim como suas raízes fundadas na filosofia pragmática, descrevendo sucintamente algumas proposições de William James e John Dewey.Using the actor-network theory, this paper describes the practices of becoming educated in research, based on the general subject of the XI ANPPEP Symposium "Ways of searching in everyday life: contributions to the formation of research in Psychology", considering that the author was a participant in the ANPEPP work group "Everyday life and Social Practices". After summarizing a paper of Bruno Latour, a dialogue between a professor and a student in which the main characteristics of the research practice in this approach are outlined, the author exposes in a more accurate manner the epistemological and methodological positioning of the referred theory and its pragmatic philosophical roots, describing briefly some propositions of William James and John Dewey.

  13. 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

  14. On the origin of Gaussian network theory in the thermo/chemo-responsive shape memory effect of amorphous polymers undergoing photo-elastic transition

    Science.gov (United States)

    Lu, Haibao; Huang, Wei Min; Leng, Jinsong

    2016-06-01

    Amorphous polymers are normally isotropic in their physical properties, however, upon stress their structural randomness is disturbed and they become anisotropic. There is a close connection between the optical anisotropy and the elastic (or mechanical) anisotropy, since both are related to the type of symmetry exhibited by the molecular structure. On the origin of Gaussian network theory, a phenomenological constitutive framework was proposed to study the photo-elastic transition and working mechanism of the thermo-/chemo-responsive shape-memory effect (SME) in amorphous shape memory polymers (SMPs). Optically refractive index was initially employed to couple the stress, strain and the anisotropy of the random link in macromolecule chain. Based on the Arrhenius law, a constitutive framework was then applied for the temperature dependence of optical (or elastic or mechanical) anisotropy according to the fictive temperature parameter. Finally, the phenomenological photo-elastic model was proposed to quantitatively identify the influential factors behind the thermo-/chemo-responsive SME in SMPs, of which the shape recovery behavior is predicted and verified by the available experimental data reported in the literature.

  15. 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.

  16. Regulação dos setores em rede para além dos valores econômicos: uma análise das políticas de interconexão IP para suporte a serviços de voz na União Europeia a partir das Teorias do Interesse Público / Regulating Network Industries beyond Economic Theories: An Analysis of IP Interconnection Policies to Support Voice Services in the EU from the perspective of Public Interest Theories

    National Research Council Canada - National Science Library

    Victor Oliveira Fernandes

    2017-01-01

    Purpose – The study aims to analyze the extent to which economic theories of network industries could anticipate the behavior of regulators regarding the promotion of network access and interconnection...

  17. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

    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...... 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...... argue that understanding meaning-making and ‘networked identities’ may be relevant analytic entry points in navigating the challenges....

  18. 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

  19. Translation Theory 'Translated'

    DEFF Research Database (Denmark)

    Wæraas, Arild; Nielsen, Jeppe

    2016-01-01

    common theoretical approaches to translation within the organization and management discipline: actor-network theory, knowledge-based theory, and Scandinavian institutionalism. Although each of these approaches already has borne much fruit in research, the literature is diverse and somewhat fragmented......, but also overlapping. We discuss the ways in which the three versions of translation theory may be combined and enrich each other so as to inform future research, thereby offering a more complete understanding of translation in and across organizational settings....

  20. Collaboration and entanglement: An actor-network theory analysis of team-based intraprofessional care for patients with advanced heart failure.

    Science.gov (United States)

    McDougall, A; Goldszmidt, M; Kinsella, E A; Smith, S; Lingard, L

    2016-09-01

    Despite calls for more interprofessional and intraprofessional team-based approaches in healthcare, we lack sufficient understanding of how this happens in the context of patient care teams. This multi-perspective, team-based interview study examined how medical teams negotiated collaborative tensions. From 2011 to 2013, 50 patients across five sites in three Canadian provinces were interviewed about their care experiences and were asked to identify members of their health care teams. Patient-identified team members were subsequently interviewed to form 50 "Team Sampling Units" (TSUs), consisting of 209 interviews with patients, caregivers and healthcare providers. Results are gathered from a focused analysis of 13 TSUs where intraprofessional collaborative tensions involved treating fluid overload, or edema, a common HF symptom. Drawing on actor-network theory (ANT), the analysis focused on intraprofessional collaboration between specialty care teams in cardiology and nephrology. The study found that despite a shared narrative of common purpose between cardiology teams and nephrology teams, fluid management tools and techniques formed sites of collaborative tension. In particular, care activities involved asynchronous clinical interpretations, geographically distributed specialist care, fragmented forms of communication, and uncertainty due to clinical complexity. Teams 'disentangled' fluid in order to focus on its physiological function and mobilisation. Teams also used distinct 'framings' of fluid management that created perceived collaborative tensions. This study advances collaborative entanglement as a conceptual framework for understanding, teaching, and potentially ameliorating some of the tensions that manifest during intraprofessional care for patients with complex, chronic disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Valuation Networks and Conditional Independence

    OpenAIRE

    Shenoy, Prakash P.

    2013-01-01

    Valuation networks have been proposed as graphical representations of valuation-based systems (VBSs). The VBS framework is able to capture many uncertainty calculi including probability theory, Dempster-Shafer's belief-function theory, Spohn's epistemic belief theory, and Zadeh's possibility theory. In this paper, we show how valuation networks encode conditional independence relations. For the probabilistic case, the class of probability models encoded by valuation networks includes undirect...

  2. 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

  3. Fundamentals of Stochastic Networks

    CERN Document Server

    Ibe, Oliver C

    2011-01-01

    An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi

  4. 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...

  5. 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....

  6. 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....

  7. 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

  8. Techniques for Modelling Network Security

    OpenAIRE

    Lech Gulbinovič

    2012-01-01

    The article compares modelling techniques for network security, including the theory of probability, Markov processes, Petri networks and application of stochastic activity networks. The paper introduces the advantages and disadvantages of the above proposed methods and accepts the method of modelling the network of stochastic activity as one of the most relevant. The stochastic activity network allows modelling the behaviour of the dynamic system where the theory of probability is inappropri...

  9. 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.

  10. 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.

  11. Networks in Cognitive Science

    CERN Document Server

    Baronchelli, Andrea; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

    2013-01-01

    Networks of interconnected nodes have long played a key role in cognitive science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions or collaborations among scientists. Today, the inclusion of network theory into cognitive sciences, and the expansion of complex systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the cognitive sciences.

  12. Layered Wyner-Ziv video coding.

    Science.gov (United States)

    Xu, Qian; Xiong, Zixiang

    2006-12-01

    Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks.

  13. Network Centric Warfare Implementation and Assessment

    National Research Council Canada - National Science Library

    Braunlinger, Thomas K

    2005-01-01

    ...) Are the military services implementing the network-centric warfare concept?, and (3) Is the network-centric warfare concept a new theory of warfare or rather a modification or extension of previous theories...

  14. Large networks and graph limits

    CERN Document Server

    Lovász, László

    2012-01-01

    Recently, it became apparent that a large number of the most interesting structures and phenomena of the world can be described by networks. Developing a mathematical theory of very large networks is an important challenge. This book describes one recent approach to this theory, the limit theory of graphs, which has emerged over the last decade. The theory has rich connections with other approaches to the study of large networks, such as "property testing" in computer science and regularity partition in graph theory. It has several applications in extremal graph theory, including the exact for

  15. Waltz's Theory of Theory

    DEFF Research Database (Denmark)

    Wæver, Ole

    2009-01-01

    Kenneth N. Waltz's 1979 book, Theory of International Politics, is the most influential in the history of the discipline. It worked its effects to a large extent through raising the bar for what counted as theoretical work, in effect reshaping not only realism but rivals like liberalism and refle......Kenneth N. Waltz's 1979 book, Theory of International Politics, is the most influential in the history of the discipline. It worked its effects to a large extent through raising the bar for what counted as theoretical work, in effect reshaping not only realism but rivals like liberalism...... and reflectivism. Yet, ironically, there has been little attention to Waltz's very explicit and original arguments about the nature of theory. This article explores and explicates Waltz's theory of theory. Central attention is paid to his definition of theory as ‘a picture, mentally formed' and to the radical anti......-empiricism and anti-positivism of his position. Followers and critics alike have treated Waltzian neorealism as if it was at bottom a formal proposition about cause-effect relations. The extreme case of Waltz being so victorious in the discipline, and yet being consistently mis-interpreted on the question of theory...

  16. A Grounded Theory Study of the Risks and Benefits Associated with the Use of Online Social Networking Applications in a Military Organization

    Science.gov (United States)

    Webb, James O., Jr.

    2012-01-01

    There is a perception that there are risks and benefits associated with the use of online social networking media within a military organization. This research study explored this perception by investigating how employees use social networking applications and their perceptions of the benefits they receive. The study also assessed the measures…

  17. INTERFERENCIA SINTÁCTICA ESPAÑOL-ALEMÁN: UNA APROXIMACIÓN DESDE LA TEORÍA DE REDES RELACIONALES SPANISH-GERMAN SYNTACTIC INTERFERENCE. AN APPROACH FROM THE RELATIONAL NETWORK THEORY

    Directory of Open Access Journals (Sweden)

    Matías Guzmán Naranjo

    2012-01-01

    Full Text Available En el presente trabajo se compara la capacidad para explicar los fenómenos de interferencia sintáctica del Programa Minimalista y la teoría de redes relacionales-gramática de construcciones, teniendo en cuenta tanto los aspectos teóricos y formales, así como datos empíricos. Los resultados muestran que, en términos generales, el programa minimalista tiene falencias notables en el campo de la adquisición de la sintaxis de una segunda lengua y no puede explicar los fenómenos de interferencia sintáctica. Por otro lado, la integración de la teoría de redes relacionales y la gramática de construcciones ofrece una alternativa plausible para explicar la interferencia sintáctica.This paper looks at the explanatory adequacy concerning interference phenomena in second language acquisition of the Minimalist Program and the Relational Network Theory-Construction Grammar. Both, formal and theoretical aspects of these theories, as well as empirical data were taken in account. Results show that the Minimalist Program can’t fully explain how the acquisition of a second language syntax works, nor the Interference Phenomena present in the process. On the other hand, the joint use of Relational Network Theory and CG offers a good and plausible alternative for explaining Interference Phenomena.

  18. 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.)

  19. Exploring Impact: Negative Effects of Social Networks

    OpenAIRE

    Egbert, Henrik; Sedlarski, Teodor

    2011-01-01

    he sociological literature on social networks emphasizes by and large positive network effects. Negative effects of such networks are discussed rather rarely. This paper tackles negative effects by applying economic theory, particularly neoclassical theory, new institutional theory and the results from experimental economics to the concept of social networks. In the paper it is assumed that social networks are exclusive and since exclusiveness affects the allocation of resources, negative ext...

  20. 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…