A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain

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Xiaojin Li

2013-01-01

Full Text Available Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY and scale-free gene duplication model (SF-GD, that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Theoretical characterization of the topology of connected carbon nanotubes in random networks

International Nuclear Information System (INIS)

Heitz, Jerome; Leroy, Yann; Hebrard, Luc; Lallement, Christophe

2011-01-01

In recent years, a lot of attention has been paid to carbon nanotube (CNT) networks and their applications to electronic devices. Many studies concentrate on the percolation threshold and the characterization of the conduction in such materials. Nevertheless, no theoretical study has yet attempted to characterize the CNT features inside finite size CNT networks. We present a theoretical approach based on geometrical and statistical considerations. We demonstrate the possibility of explicitly determining some relations existing between two neighbor CNTs and their contact efficiency in random networks of identical CNTs. We calculate the contact probability of rigid identical CNTs and we obtain a probability of 0.2027, which turns out to be independent of the CNT density. Based on this probability, we establish also the dependence of the number of contacts per CNT as a function of the CNT density. All the theoretical results are validated by very good agreement with Monte Carlo simulations.

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

Science.gov (United States)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Park, June; Jhon, Young Min; Seong, Maeng-Je; Hong, Seunghun

2010-02-01

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of ~1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

Energy Technology Data Exchange (ETDEWEB)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Hong, Seunghun [Department of Physics and Astronomy, Seoul National University, Shilim-Dong, Kwanak-Gu, Seoul 151-742 (Korea, Republic of); Park, June; Seong, Maeng-Je [Department of Physics, Chung-Ang University, Heukseok-Dong, Dongjak-Gu, Seoul 156-756 (Korea, Republic of); Jhon, Young Min, E-mail: mseong@cau.ac.kr, E-mail: shong@phya.snu.ac.kr [Korea Institute of Science and Technology, Hawolgok-Dong, Seongbuk-Gu, Seoul 136-791 (Korea, Republic of)

2010-02-05

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of {approx}1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

International Nuclear Information System (INIS)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Hong, Seunghun; Park, June; Seong, Maeng-Je; Jhon, Young Min

2010-01-01

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of ∼1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

Game-theoretic cooperativity in networks of self-interested units

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Barto, Andrew G.

1986-08-01

The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.

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Parras, Juan; Zazo, Santiago

2018-01-30

We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

LPI Optimization Framework for Target Tracking in Radar Network Architectures Using Information-Theoretic Criteria

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Chenguang Shi

2014-01-01

Full Text Available Widely distributed radar network architectures can provide significant performance improvement for target detection and localization. For a fixed radar network, the achievable target detection performance may go beyond a predetermined threshold with full transmitted power allocation, which is extremely vulnerable in modern electronic warfare. In this paper, we study the problem of low probability of intercept (LPI design for radar network and propose two novel LPI optimization schemes based on information-theoretic criteria. For a predefined threshold of target detection, Schleher intercept factor is minimized by optimizing transmission power allocation among netted radars in the network. Due to the lack of analytical closed-form expression for receiver operation characteristics (ROC, we employ two information-theoretic criteria, namely, Bhattacharyya distance and J-divergence as the metrics for target detection performance. The resulting nonconvex and nonlinear LPI optimization problems associated with different information-theoretic criteria are cast under a unified framework, and the nonlinear programming based genetic algorithm (NPGA is used to tackle the optimization problems in the framework. Numerical simulations demonstrate that our proposed LPI strategies are effective in enhancing the LPI performance for radar network.

Wireless Networks under a Backoff Attack: A Game Theoretical Perspective

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Juan Parras

2018-01-01

Full Text Available We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.

A study of brain networks associated with swallowing using graph-theoretical approaches.

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Bo Luan

Full Text Available Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, [Formula: see text] years of age. To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.

A NETWORK-THEORETICAL APPROACH TO UNDERSTANDING INTERSTELLAR CHEMISTRY

International Nuclear Information System (INIS)

Jolley, Craig C.; Douglas, Trevor

2010-01-01

Recent years have seen dramatic advances in computational models of chemical processes in the interstellar medium (ISM). Typically, these models have been used to calculate changes in chemical abundances with time; the calculated abundances can then be compared with chemical abundances derived from observations. In this study, the output from an astrochemical simulation has been used to generate directed graphs with weighted edges; these have been analyzed with the tools of network theory to uncover whole-network properties of reaction systems in dark molecular clouds. The results allow the development of a model in which global network properties can be rationalized in terms of the basic physical properties of the reaction system. The ISM network exhibits an exponential degree distribution, which is likely to be a generic feature of chemical networks involving a broad range of reaction rate constants. While species abundances span several orders of magnitude, the formation and destruction rates for most species are approximately balanced-departures from this rule indicate species (such as CO) that play a critical role in shaping the dynamics of the system. Future theoretical or observational studies focusing on individual molecular species will be able to situate them in terms of their role in the complete system or quantify the degree to which they deviate from the typical system behavior.

On the design of a hierarchical SS7 network: A graph theoretical approach

Science.gov (United States)

Krauss, Lutz; Rufa, Gerhard

1994-04-01

This contribution is concerned with the design of Signaling System No. 7 networks based on graph theoretical methods. A hierarchical network topology is derived by combining the advantage of the hierarchical network structure with the realization of node disjoint routes between nodes of the network. By using specific features of this topology, we develop an algorithm to construct circle-free routing data and to assure bidirectionality also in case of failure situations. The methods described are based on the requirements that the network topology, as well as the routing data, may be easily changed.

A game theoretic investigation of deception in network security

Energy Technology Data Exchange (ETDEWEB)

Carroll, Thomas E.; Grosu, Daniel

2010-12-03

We perform a game theoretic investigation of the effects of deception on the interactions between an attacker and a defender of a computer network. The defender can employ camouflage by either disguising a normal system as a honeypot or by disguising a honeypot as a normal system. We model the interactions between defender and attacker using a signaling game, a non-cooperative two player dynamic game of incomplete information. For this model, we determine which strategies admit perfect Bayesian equilibria. These equilibria are refined Nash equilibria in which neither the defender nor the attacker will unilaterally choose to deviate from their strategies. Finally, we discuss the benefits of employing deceptive equilibrium strategies in the defense of a computer network.

Theoretical Guidelines for the Utilization of Instructional Social Networking Websites

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Ilker YAKIN

2015-10-01

Full Text Available interaction and communication technologies. Indeed, there has been an emerging movement in the interaction and communication technologies. More specifically, the growth of Web 2.0 technologies has acted as a catalyst for change in the disciplines of education. The social networking websites have gained popularity in recent years; therefore, many research studies have been conducted to explain how the use of social networking websites for instructional purposes. For the best practices, it is essential to understand theories associated with social networking studies because related theories for any subject may provide insights and guideline for professionals and researchers. This theoretical paper was designed to offer a road map through the literature in relation to the utilization of social networking websites by presenting main understandings of theories associated with social networking. The Uses and Gratification Theory, social network theory, connectives, and constructivism were selected to serve as a basis for designing social networking studies regarding instructional purposes. Moreover, common attributes of the theories and specific application areas were also discussed. This paper contributes to this emerging movement by explaining the role of these theories for researchers and practitioners to find ways to beneficially integrate them into their future research endeavors

Overcoming Blockages to Collective Innovation in Digital Infrastructures

DEFF Research Database (Denmark)

Rukanova, Boriana; Reuver, Mark; Henningsson, Stefan

2017-01-01

Decentralized digital technologies increasingly enable multiple organizations to co-create digital infrastructures. However, collective innovation processes often come to a stand-still because of conflicting interests and business models. While existing research suggests various factors that block...... collective innovation processes, there is still little understanding of how organizations can overcome these blockages. In this paper, we identify patterns that explain how organizations overcome blockages of collective innovation processes for digital infrastructures. We follow a processual approach...... and develop a conceptual framework based on collective action theory. We evaluate the framework through a longitudinal case study on mobile payment infrastructure development. We find various reconfiguration processes that organizations use to overcome blockages of collective innovation. Theoretically...

Field-theoretic approach to fluctuation effects in neural networks

International Nuclear Information System (INIS)

Buice, Michael A.; Cowan, Jack D.

2007-01-01

A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience

Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

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Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

2016-01-01

Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

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Lindsay eRutter

2013-07-01

Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

Game Theoretic Centrality Analysis of Terrorist Networks : The Cases of Jemaah Islamiyah and Al Qaeda

NARCIS (Netherlands)

Lindelauf, R.; Hamers, H.J.M.; Husslage, B.G.M.

2011-01-01

The identification of key players in a terrorist network can lead to prevention of attacks, due to efficient allocation of surveillance means or isolation of key players in order to destabilize the network. In this paper we introduce a game theoretic approach to identify key players in terrorist

Game Theoretical Analysis on Cooperation Stability and Incentive Effectiveness in Community Networks.

Science.gov (United States)

Song, Kaida; Wang, Rui; Liu, Yi; Qian, Depei; Zhang, Han; Cai, Jihong

2015-01-01

Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.

Game Theoretical Analysis on Cooperation Stability and Incentive Effectiveness in Community Networks.

Directory of Open Access Journals (Sweden)

Kaida Song

Full Text Available Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.

The Governmentality of Meta-governance : Identifying Theoretical and Empirical Challenges of Network Governance in the Political Field of Security and Beyond

OpenAIRE

Larsson, Oscar

2015-01-01

Meta-governance recently emerged in the field of governance as a new approach which claims that its use enables modern states to overcome problems associated with network governance. This thesis shares the view that networks are an important feature of contemporary politics which must be taken seriously, but it also maintains that networks pose substantial analytical and political challenges. It proceeds to investigate the potential possibilities and problems associated with meta-governance o...

A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

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Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

2017-01-01

Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks.

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Yang, Liu; Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang

2017-11-17

Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced.

Theoretical approaches of online social network interventions and implications for behavioral change: a systematic review.

Science.gov (United States)

Arguel, Amaël; Perez-Concha, Oscar; Li, Simon Y W; Lau, Annie Y S

2018-02-01

The aim of this review was to identify general theoretical frameworks used in online social network interventions for behavioral change. To address this research question, a PRISMA-compliant systematic review was conducted. A systematic review (PROSPERO registration number CRD42014007555) was conducted using 3 electronic databases (PsycINFO, Pubmed, and Embase). Four reviewers screened 1788 abstracts. 15 studies were selected according to the eligibility criteria. Randomized controlled trials and controlled studies were assessed using Cochrane Collaboration's "risk-of-bias" tool, and narrative synthesis. Five eligible articles used the social cognitive theory as a framework to develop interventions targeting behavioral change. Other theoretical frameworks were related to the dynamics of social networks, intention models, and community engagement theories. Only one of the studies selected in the review mentioned a well-known theory from the field of health psychology. Conclusions were that guidelines are lacking in the design of online social network interventions for behavioral change. Existing theories and models from health psychology that are traditionally used for in situ behavioral change should be considered when designing online social network interventions in a health care setting. © 2016 John Wiley & Sons, Ltd.

Graph theoretical analysis of functional network for comprehension of sign language.

Science.gov (United States)

Liu, Lanfang; Yan, Xin; Liu, Jin; Xia, Mingrui; Lu, Chunming; Emmorey, Karen; Chu, Mingyuan; Ding, Guosheng

2017-09-15

Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t (24) =2.379, p=0.026), small-worldness (t (24) =2.604, p=0.016) and modularity (t (24) =3.513, p=0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action. Copyright © 2017 Elsevier B.V. All rights reserved.

Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease

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LIU Xue-na

2012-08-01

Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.

Re-Vitalizing Worthiness: A theory of overcoming suicidality

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Evelyn Gordon, RPN, Reg. Fam. Ther. & Sup. (FTAI, MSc, Ph.D.

2011-06-01

Full Text Available Rates of suicide and suicidality have risen in many countries in recent years and in Ireland this trend has been particularly evident among young men (NOSP, 2005, focusing attention on how best to respond to this group. Although mental health professionals have been identified as a key group to respond to the suicidal person, it has been suggested that they are ill-prepared for working in this area (Maltsberger & Goldblatt, 1996; Ting et al., 2006; Cutcliffe & Stevenson, 2007. This study aimed to address these issues by developing a theoretical understanding of suicidality among young men to inform professional practice. Using Classic Grounded Theory (Glaser & Strauss, 1967, in-depth one-to-one interviews were conducted with 17 young men who had been suicidal and had been in contact with the mental health services. The substantive theory that emerged, re-vitalizing worthiness in overcoming suicidality, describes the psychosocial process that young men go through to resolve their main concern, which centres on their painful pull between life and death. Overcoming suicidality involves moving from a death orientation to a life orientation while incorporating the inevitability of death into their new sense of being. This transition entails identity re-configuration whereby young men emerge as individuals of value who are deserving of life. The process is influenced significantly by personal insights and interpersonal interactions that influence their suicide trajectories and life pathways. The theory contributes to the fields of suicidology and mental health by providing a theoretical understanding of overcoming suicidality and identifying professional and social practices that facilitate and impede this process.

New Theoretical Analysis of the LRRM Calibration Technique for Vector Network Analyzers

OpenAIRE

Purroy Martín, Francesc; Pradell i Cara, Lluís

2001-01-01

In this paper, a new theoretical analysis of the four-standards line-reflect-reflect-match (LRRM) vector network-analyzer (VNA) calibration technique is presented. As a result, it is shown that the reference-impedance (to which the LRRM calibration is referred) cannot generally be defined whenever nonideal standards are used. Based on this consideration, a new algorithm to determine the on-wafer match standard is proposed that improves the LRRM calibration accuracy. Experimental verification ...

Power allocation for target detection in radar networks based on low probability of intercept: A cooperative game theoretical strategy

Science.gov (United States)

Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang

2017-08-01

Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.

Overcoming uncertainty for within-network relational machine learning

OpenAIRE

Pfeiffer, Joseph J.

2015-01-01

People increasingly communicate through email and social networks to maintain friendships and conduct business, as well as share online content such as pictures, videos and products. Relational machine learning (RML) utilizes a set of observed attributes and network structure to predict corresponding labels for items; for example, to predict individuals engaged in securities fraud, we can utilize phone calls and workplace information to make joint predictions over the individuals. However, in...

Getting Embedded in Industry Networks Abroad

DEFF Research Database (Denmark)

Gretzinger, Susanne; Dyhr Ulrich, Anna Marie; Hollensen, Svend

(Hollensen, 2017). This research project aims to explain how the “incubator” can support the acquisition of lacking experiental knowledge and facilitate the process of getting embedded in markets or industrial networks abroad. Theoretical foundation This paper adopts an industrial network approach in line......Expanding to markets abroad is a vital opportunity to stabilize and/or expand a company’s revenues. Companies who suffer from small domestic markets try to overcome competitive pressures by entering new markets (Korsakine and Tvaronaviciene, 2012). In particular, the attention for SMEs to increase...... their activities abroad has turned to the potential of accessing emerging markets with faster growth like the BRIC countries (Brazil, Russia, India and China) in response to the saturation of domestic and European markets (Neupert, et al. 2006, Ulrich, et al., 2014). However, the challenges associated...

A large scale analysis of information-theoretic network complexity measures using chemical structures.

Directory of Open Access Journals (Sweden)

Matthias Dehmer

Full Text Available This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g., we want to examine which kind of structural information they detect. Therefore, our main contribution is to shed light on the relatedness between some selected information measures for graphs by performing a large scale analysis using chemical networks. Starting from several sets containing real and synthetic chemical structures represented by graphs, we study the relatedness between a classical (partition-based complexity measure called the topological information content of a graph and some others inferred by a different paradigm leading to partition-independent measures. Moreover, we evaluate the uniqueness of network complexity measures numerically. Generally, a high uniqueness is an important and desirable property when designing novel topological descriptors having the potential to be applied to large chemical databases.

Investigation on the use of artificial neural networks to overcome the effects of environmental and operational changes on guided waves monitoring

Science.gov (United States)

El Mountassir, M.; Yaacoubi, S.; Dahmene, F.

2015-07-01

Intelligent feature extraction and advanced signal processing techniques are necessary for a better interpretation of ultrasonic guided waves signals either in structural health monitoring (SHM) or in nondestructive testing (NDT). Such signals are characterized by at least multi-modal and dispersive components. In addition, in SHM, these signals are closely vulnerable to environmental and operational conditions (EOCs), and can be severely affected. In this paper we investigate the use of Artificial Neural Network (ANN) to overcome these effects and to provide a reliable damage detection method with a minimal of false indications. An experimental case of study (full scale pipe) is presented. Damages sizes have been increased and their shapes modified in different steps. Various parameters such as the number of inputs and the number of hidden neurons were studied to find the optimal configuration of the neural network.

Wireless Information-Theoretic Security in an Outdoor Topology with Obstacles: Theoretical Analysis and Experimental Measurements

Directory of Open Access Journals (Sweden)

Dagiuklas Tasos

2011-01-01

Full Text Available This paper presents a Wireless Information-Theoretic Security (WITS scheme, which has been recently introduced as a robust physical layer-based security solution, especially for infrastructureless networks. An autonomic network of moving users was implemented via 802.11n nodes of an ad hoc network for an outdoor topology with obstacles. Obstructed-Line-of-Sight (OLOS and Non-Line-of-Sight (NLOS propagation scenarios were examined. Low-speed user movement was considered, so that Doppler spread could be discarded. A transmitter and a legitimate receiver exchanged information in the presence of a moving eavesdropper. Average Signal-to-Noise Ratio (SNR values were acquired for both the main and the wiretap channel, and the Probability of Nonzero Secrecy Capacity was calculated based on theoretical formula. Experimental results validate theoretical findings stressing the importance of user location and mobility schemes on the robustness of Wireless Information-Theoretic Security and call for further theoretical analysis.

S-curve networks and an approximate method for estimating degree distributions of complex networks

Science.gov (United States)

Guo, Jin-Li

2010-12-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

S-curve networks and an approximate method for estimating degree distributions of complex networks

International Nuclear Information System (INIS)

Guo Jin-Li

2010-01-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research. (general)

Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

Science.gov (United States)

Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R

2017-08-15

The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.

THEORETICAL EVALUATION OF NONLINEAR EFFECTS ON OPTICAL WDM NETWORKS WITH VARIOUS FIBER TYPES

Directory of Open Access Journals (Sweden)

YASIN M. KARFAA

2010-09-01

Full Text Available A theoretical study is carried out to evaluate the performance of an opticalwavelength division multiplexing (WDM network transmission system in the presenceof crosstalk due to optical fiber nonlinearities. The most significant nonlinear effects inthe optical fiber which are Cross-Phase Modulation (XPM, Four-Wave Mixing (FWM,and Stimulated Raman Scattering (SRS are investigated. Four types of optical fiber areincluded in the analysis; these are: single-mode fiber (SMF, dispersion compensationfiber (DCF, non-zero dispersion fiber (NZDF, and non-zero dispersion shifted fiber(NZDSF. The results represent the standard deviation of nonlinearity induced crosstalknoise power due to FWM and SRS, XPM power penalty for SMF, DCF, NZDF, andNZDSF types of fiber, besides the Bit Error Rate (BER for the three nonlinear effectsusing standard fiber type (SMF. It is concluded that three significant fiber nonlinearitiesare making huge limitations against increasing the launched power which is desired,otherwise, lower values of launched power limit network expansion including length,distance, covered areas, and number of users accessing the WDM network, unlesssuitable precautions are taken to neutralize the nonlinear effects. Besides, various fibertypes are not behaving similarly towards network parameters.

A Game-Theoretical Approach to Multimedia Social Networks Security

Science.gov (United States)

Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong

2014-01-01

The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

Science.gov (United States)

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

Community, Collective or Movement? Evaluating Theoretical Perspectives on Network Building

Science.gov (United States)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. What is the most useful theoretical model for conceptualizing the work of the NNOCCI community? This presentation will examine the pros and cons of three perspectives -- community of practice, collective impact, and social movements. The community of practice approach emphasizes use of common tools, support for practice, social learning, and organic development of leadership. A collective impact model focuses on defining common outcomes, aligning activities toward a common goal, structured collaboration. A social movement emphasizes building group identity and creating a sense of group efficacy. This presentation will address how these models compare in terms of their utility in program planning and evaluation, their fit with the unique characteristics of the NNOCCI community, and their relevance to our program goals.

[Overcoming the limitations of the descriptive and categorical approaches in psychiatric diagnosis: a proposal based on Bayesian networks].

Science.gov (United States)

Sorias, Soli

2015-01-01

Efforts to overcome the problems of descriptive and categorical approaches have not yielded results. In the present article, psychiatric diagnosis using Bayesian networks is proposed. Instead of a yes/no decision, Bayesian networks give the probability of diagnostic category inclusion, thereby yielding both a graded, i.e., dimensional diagnosis, and a value of the certainty of the diagnosis. With the use of Bayesian networks in the diagnosis of mental disorders, information about etiology, associated features, treatment outcome, and laboratory results may be used in addition to clinical signs and symptoms, with each of these factors contributing proportionally to their own specificity and sensitivity. Furthermore, a diagnosis (albeit one with a lower probability) can be made even with incomplete, uncertain, or partially erroneous information, and patients whose symptoms are below the diagnostic threshold can be evaluated. Lastly, there is no need of NOS or "unspecified" categories, and comorbid disorders become different dimensions of the diagnostic evaluation. Bayesian diagnoses allow the preservation of current categories and assessment methods, and may be used concurrently with criteria-based diagnoses. Users need not put in extra effort except to collect more comprehensive information. Unlike the Research Domain Criteria (RDoC) project, the Bayesian approach neither increases the diagnostic validity of existing categories nor explains the pathophysiological mechanisms of mental disorders. It, however, can be readily integrated to present classification systems. Therefore, the Bayesian approach may be an intermediate phase between criteria-based diagnosis and the RDoC ideal.

Overcoming challenges

Medline Plus

Full Text Available ... section Back to section menu It's Only Natural Planning ahead Breastfeeding and baby basics Making breastfeeding work ... It's Only Natural Overcoming challenges It's Only Natural Planning ahead Addressing breastfeeding myths Overcoming challenges Common questions ...

Overcoming challenges

Medline Plus

Full Text Available ... breastfeeding Overcoming challenges Common questions about breastfeeding and pain Breastfeeding checklist: How to get a good latch Finding ... myths Overcoming challenges Common questions about breastfeeding and pain Breastfeeding checklist: How to get a good latch Finding ...

WDM networking on a European Scale

DEFF Research Database (Denmark)

Parnis, Noel; Limal, Emmanuel; Hjelme, Dag R.

1998-01-01

Four different topological approaches to designing a pan-European optical network are discussed. For such an ultra-high capacity large-scale network, it is necessary to overcome physical path length limitations and to limit Optical Cross-Connect (OXC) complexity.......Four different topological approaches to designing a pan-European optical network are discussed. For such an ultra-high capacity large-scale network, it is necessary to overcome physical path length limitations and to limit Optical Cross-Connect (OXC) complexity....

PAGANI Toolkit: Parallel graph-theoretical analysis package for brain network big data.

Science.gov (United States)

Du, Haixiao; Xia, Mingrui; Zhao, Kang; Liao, Xuhong; Yang, Huazhong; Wang, Yu; He, Yong

2018-05-01

The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph-theoretical ANalysIs (PAGANI) Toolkit based on a hybrid central processing unit-graphics processing unit (CPU-GPU) framework with a graphical user interface to facilitate the mapping and characterization of high-resolution brain networks. Specifically, the toolkit provides flexible parameters for users to customize computations of graph metrics in brain network analyses. As an empirical example, the PAGANI Toolkit was applied to individual voxel-based brain networks with ∼200,000 nodes that were derived from a resting-state fMRI dataset of 624 healthy young adults from the Human Connectome Project. Using a personal computer, this toolbox completed all computations in ∼27 h for one subject, which is markedly less than the 118 h required with a single-thread implementation. The voxel-based functional brain networks exhibited prominent small-world characteristics and densely connected hubs, which were mainly located in the medial and lateral fronto-parietal cortices. Moreover, the female group had significantly higher modularity and nodal betweenness centrality mainly in the medial/lateral fronto-parietal and occipital cortices than the male group. Significant correlations between the intelligence quotient and nodal metrics were also observed in several frontal regions. Collectively, the PAGANI Toolkit shows high computational performance and good scalability for analyzing connectome big data and provides a friendly interface without the complicated configuration of computing environments, thereby facilitating high-resolution connectomics research in health and disease. © 2018 Wiley Periodicals, Inc.

Theoretical Evaluation of Crosslink Density of Chain Extended Polyurethane Networks Based on Hydroxyl Terminated Polybutadiene and Butanediol and Comparison with Experimental Data

Science.gov (United States)

Sekkar, Venkataraman; Alex, Ancy Smitha; Kumar, Vijendra; Bandyopadhyay, G. G.

2018-01-01

Polyurethane networks between hydroxyl terminated polybutadiene (HTPB) and butanediol (BD) were prepared using toluene diisocyanate (TDI) as the curative. HTPB and BD were taken at equivalent ratios viz.: 1:0, 1:1, 1:2, 1:4, and 1:8. Crosslink density (CLD) was theoretically calculated using α-model equations developed by Marsh. CLD for the polyurethane networks was experimentally evaluated from equilibrium swell and stress-strain data. Young's modulus and Mooney-Rivlin approaches were adopted to calculate CLD from stress-strain data. Experimentally obtained CLD values were enormously higher than theoretical values especially at higher BD/HTPB equivalent ratios. The difference in the theoretical and experimental values for CLD was explained in terms of local crystallization due to the formation of hard segments and hydrogen bonded interactions.

Impaired cerebral blood flow networks in temporal lobe epilepsy with hippocampal sclerosis: A graph theoretical approach.

Science.gov (United States)

Sone, Daichi; Matsuda, Hiroshi; Ota, Miho; Maikusa, Norihide; Kimura, Yukio; Sumida, Kaoru; Yokoyama, Kota; Imabayashi, Etsuko; Watanabe, Masako; Watanabe, Yutaka; Okazaki, Mitsutoshi; Sato, Noriko

2016-09-01

Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE. Copyright © 2016 Elsevier Inc. All rights reserved.

A network approach to overcoming barriers to market engagement for SMEs in energy efficiency initiatives such as the Green Deal

International Nuclear Information System (INIS)

O’Keeffe, Juliette M.; Gilmour, Daniel; Simpson, Edward

2016-01-01

The Green Deal (GD) was launched in 2013 by the UK Government as a market-led scheme to encourage uptake of energy efficiency measures in the UK and create green sector jobs. The scheme closed in July 2015 after 30 months due to government concerns over low uptake and industry standards but additional factors potentially contributed to its failure such as poor scheme design and lack of understanding of the customer and supply chain journey. We explore the role of key delivery agents of GD services, specifically SMEs, and we use the LoCal-Net project as a case study to examine the use of networks to identify and reduce barriers to SME market engagement. We find that SMEs experienced multiple barriers to interaction with the GD such as lack of access to information, training, and confusion over delivery of the scheme but benefited from interaction with the network to access information, improve understanding of the scheme, increasing networking opportunities and forming new business models and partnerships to reduce risk. The importance of SMEs as delivery agents and their role in the design of market-led schemes such as the GD are discussed with recommendations for improving SME engagement in green sector initiatives. - Highlights: • The role of delivery agents should be addressed in voluntary energy reduction schemes. • SMEs attempting to engage in the Green Deal market faced multiple barriers. • Networks can assist in overcoming SME barriers to entry into new green sector markets. • Access to information, contacts and experts are key benefits of business networks. • Policy driven market-led schemes must consider all actors to prevent early failures.

Correlation Networks from Flows. The Case of Forced and Time-Dependent Advection-Diffusion Dynamics.

Directory of Open Access Journals (Sweden)

Liubov Tupikina

Full Text Available Complex network theory provides an elegant and powerful framework to statistically investigate different types of systems such as society, brain or the structure of local and long-range dynamical interrelationships in the climate system. Network links in climate networks typically imply information, mass or energy exchange. However, the specific connection between oceanic or atmospheric flows and the climate network's structure is still unclear. We propose a theoretical approach for verifying relations between the correlation matrix and the climate network measures, generalizing previous studies and overcoming the restriction to stationary flows. Our methods are developed for correlations of a scalar quantity (temperature, for example which satisfies an advection-diffusion dynamics in the presence of forcing and dissipation. Our approach reveals that correlation networks are not sensitive to steady sources and sinks and the profound impact of the signal decay rate on the network topology. We illustrate our results with calculations of degree and clustering for a meandering flow resembling a geophysical ocean jet.

Information-Theoretic Performance Analysis of Sensor Networks via Markov Modeling of Time Series Data.

Science.gov (United States)

Li, Yue; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Yue Li; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Wettergren, Thomas A; Li, Yue; Ray, Asok; Jha, Devesh K

2018-06-01

This paper presents information-theoretic performance analysis of passive sensor networks for detection of moving targets. The proposed method falls largely under the category of data-level information fusion in sensor networks. To this end, a measure of information contribution for sensors is formulated in a symbolic dynamics framework. The network information state is approximately represented as the largest principal component of the time series collected across the network. To quantify each sensor's contribution for generation of the information content, Markov machine models as well as x-Markov (pronounced as cross-Markov) machine models, conditioned on the network information state, are constructed; the difference between the conditional entropies of these machines is then treated as an approximate measure of information contribution by the respective sensors. The x-Markov models represent the conditional temporal statistics given the network information state. The proposed method has been validated on experimental data collected from a local area network of passive sensors for target detection, where the statistical characteristics of environmental disturbances are similar to those of the target signal in the sense of time scale and texture. A distinctive feature of the proposed algorithm is that the network decisions are independent of the behavior and identity of the individual sensors, which is desirable from computational perspectives. Results are presented to demonstrate the proposed method's efficacy to correctly identify the presence of a target with very low false-alarm rates. The performance of the underlying algorithm is compared with that of a recent data-driven, feature-level information fusion algorithm. It is shown that the proposed algorithm outperforms the other algorithm.

The small and rural academic library leveraging resources and overcoming limitations

CERN Document Server

Davis Kendrick, Kaetrena

2016-01-01

Through the use of case studies, research, and practical interviews, The Small or Rural Academic Library: Leveraging Resources and Overcoming Limitations explores how academic librarians in such environments can keep pace with, create, and improve modern library practices and services, network with colleagues, and access continuing education and professional development opportunities.

Game theoretic approaches for spectrum redistribution

CERN Document Server

Wu, Fan

2014-01-01

This brief examines issues of spectrum allocation for the limited resources of radio spectrum. It uses a game-theoretic perspective, in which the nodes in the wireless network are rational and always pursue their own objectives. It provides a systematic study of the approaches that can guarantee the system's convergence at an equilibrium state, in which the system performance is optimal or sub-optimal. The author provides a short tutorial on game theory, explains game-theoretic channel allocation in clique and in multi-hop wireless networks and explores challenges in designing game-theoretic m

A game theoretical approach for QoS provisioning in heterogeneous networks

Directory of Open Access Journals (Sweden)

A.S.M. Zadid Shifat

2015-09-01

Full Text Available With the proliferation of mobile phone users, interference management is a big concern in this neoteric years. To cope with this problem along with ensuring better Quality of Service (QoS, femtocell plays an imperious preamble in heterogeneous networks (HetNets for some of its noteworthy characteristics. In this paper, we propose a game theoretic algorithm along with dynamic channel allocation and hybrid access mechanism with self-organizing power control scheme. With a view to resolving prioritized access issue, the concept of primary and secondary users is applied. Existence of pure strategy Nash equilibrium (NE has been investigated and comes to a perfection that our proposed scheme can be adopted both increasing capacity and increasing revenue of operators considering optimal price for consumers.

Category theoretic analysis of hierarchical protein materials and social networks.

Directory of Open Access Journals (Sweden)

David I Spivak

Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

JongHyup Lee

2016-08-01

Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

Science.gov (United States)

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Game-theoretic modeling of curtailment rules and network investments with distributed generation

International Nuclear Information System (INIS)

Andoni, Merlinda; Robu, Valentin; Früh, Wolf-Gerrit; Flynn, David

2017-01-01

to validate our model. We show that charging a transmission fee as a proportion of the feed-in tariff price between 15% and 75% would allow both investors to implement their projects and achieve desirable distribution of the profit. Overall, our results show how using game-theoretic tools can help network operators to bridge the knowledge gap about setting the optimal curtailment rule and determining transmission charges for private network infrastructure.

Towards an Irritable Bowel Syndrome Control System Based on Artificial Neural Networks

Science.gov (United States)

Podolski, Ina; Rettberg, Achim

To solve health problems with medical applications that use complex algorithms is a trend nowadays. It could also be a chance to help patients with critical problems caused from nerve irritations to overcome them and provide a better living situation. In this paper a system for monitoring and controlling the nerves from the intestine is described on a theoretical basis. The presented system could be applied to the irritable bowel syndrome. For control a neural network is used. The advantages for using a neural network for the control of irritable bowel syndrome are the adaptation and learning. These two aspects are important because the syndrome behavior varies from patient to patient and have also concerning the time a lot of variations with respect to each patient. The developed neural network is implemented and can be simulated. Therefore, it can be shown how the network monitor and control the nerves for individual input parameters.

Information Theoretic-Learning Auto-Encoder

OpenAIRE

Santana, Eder; Emigh, Matthew; Principe, Jose C

2016-01-01

We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternative to variational autoencoding bayes, adversarial autoencoders and generative adversarial networks for randomly generating sample data without explicitly defining a partition function. This paper also formalizes, generative moment matching networks under the ITL framework.

Game theoretic analysis of congestion, safety and security networks, air traffic and emergency departments

CERN Document Server

Zhuang, Jun

2015-01-01

Maximizing reader insights into the roles of intelligent agents in networks, air traffic and emergency departments, this volume focuses on congestion in systems where safety and security are at stake, devoting special attention to applying game theoretic analysis of congestion to: protocols in wired and wireless networks; power generation, air transportation and emergency department overcrowding. Reviewing exhaustively the key recent research into the interactions between game theory, excessive crowding, and safety and security elements, this book establishes a new research angle by illustrating linkages between the different research approaches and serves to lay the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs – which may be in parallel, series, interlinked, or interdependent, with flows one way or both way...

Game-Theoretic Social-Aware Resource Allocation for Device-to-Device Communications Underlaying Cellular Network

Directory of Open Access Journals (Sweden)

Lei Wang

2018-01-01

Full Text Available Device-to-Device communication underlaying cellular network can increase the spectrum efficiency due to direct proximity communication and frequency reuse. However, such performance improvement is influenced by the power interference caused by spectrum sharing and social characteristics in each social community jointly. In this investigation, we present a dynamic game theory with complete information based D2D resource allocation scheme for D2D communication underlaying cellular network. In this resource allocation method, we quantify both the rate influence from the power interference caused by the D2D transmitter to cellular users and rate enhancement brought by the social relationships between mobile users. Then, the utility function maximization game is formulated to optimize the overall transmission rate performance of the network, which synthetically measures the final influence from both power interference and sociality enhancement. Simultaneously, we discuss the Nash Equilibrium of the proposed utility function maximization game from a theoretical point of view and further put forward a utility priority searching algorithm based resource allocation scheme. Simulation results show that our proposed scheme attains better performance compared with the other two advanced proposals.

High-efficiency free-form condenser overcoming rotational symmetry limitations.

Science.gov (United States)

Miñano, Juan C; Benítez, Pablo; Blen, José; Santamaría, Asunción

2008-12-08

Conventional condensers using rotational symmetric devices perform far from their theoretical limits when transferring optical power from sources such as arc lamps or halogen bulbs to the rectangular entrance of homogenizing prisms (target). We present a free-form condenser design (calculated with the SMS method) that overcomes the limitations inherent to rotational devices and can send to the target 1.8 times the power sent by an equivalent elliptical condenser for a 4:1 target aspect ratio and 1.5 times for 16:9 target and for practical values of target etendue.

A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks.

Science.gov (United States)

Mezher, Ahmad Mohamad; Igartua, Mónica Aguilar; de la Cruz Llopis, Luis J; Pallarès Segarra, Esteve; Tripp-Barba, Carolina; Urquiza-Aguiar, Luis; Forné, Jordi; Sanvicente Gargallo, Emilio

2015-04-17

The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.

A Multi-User Game-Theoretical Multipath Routing Protocol to Send Video-Warning Messages over Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Ahmad Mohamad Mezher

2015-04-01

Full Text Available The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc. could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.

Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients

International Nuclear Information System (INIS)

Wang, Jieqiong; Li, Ting; Xian, Junfang; Wang, Ningli; He, Huiguang

2016-01-01

Most previous glaucoma studies with resting-state fMRI have focused on the neuronal activity in the individual structure of the brain, yet ignored the functional communication of anatomically separated structures. The purpose of this study is to investigate the efficiency of the functional communication change or not in glaucoma patients. We applied the resting-state fMRI data to construct the connectivity network of 25 normal controls and 25 age-gender-matched primary open angle glaucoma patients. Graph theoretical analysis was performed to assess brain network pattern differences between the two groups. No significant differences of the global network measures were found between the two groups. However, the local measures were radically reorganized in glaucoma patients. Comparing with the hub regions in normal controls' network, we found that six hub regions disappeared and nine hub regions appeared in the network of patients. In addition, the betweenness centralities of two altered hub regions, right fusiform gyrus and right lingual gyrus, were significantly correlated with the visual field mean deviation. Although the efficiency of functional communication is preserved in the brain network of the glaucoma at the global level, the efficiency of functional communication is altered in some specialized regions of the glaucoma. (orig.)

Graph theoretical analysis reveals the reorganization of the brain network pattern in primary open angle glaucoma patients

Energy Technology Data Exchange (ETDEWEB)

Wang, Jieqiong [Chinese Academy of Sciences, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Beijing (China); Li, Ting; Xian, Junfang [Capital Medical University, Department of Radiology, Beijing Tongren Hospital, Beijing (China); Wang, Ningli [Capital Medical University, Department of Ophthalmology, Beijing Tongren Hospital, Beijing (China); He, Huiguang [Chinese Academy of Sciences, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Beijing (China); Chinese Academy of Sciences, Research Center for Brain-Inspired Intelligence, Institute of Automation, Beijing (China)

2016-11-15

Most previous glaucoma studies with resting-state fMRI have focused on the neuronal activity in the individual structure of the brain, yet ignored the functional communication of anatomically separated structures. The purpose of this study is to investigate the efficiency of the functional communication change or not in glaucoma patients. We applied the resting-state fMRI data to construct the connectivity network of 25 normal controls and 25 age-gender-matched primary open angle glaucoma patients. Graph theoretical analysis was performed to assess brain network pattern differences between the two groups. No significant differences of the global network measures were found between the two groups. However, the local measures were radically reorganized in glaucoma patients. Comparing with the hub regions in normal controls' network, we found that six hub regions disappeared and nine hub regions appeared in the network of patients. In addition, the betweenness centralities of two altered hub regions, right fusiform gyrus and right lingual gyrus, were significantly correlated with the visual field mean deviation. Although the efficiency of functional communication is preserved in the brain network of the glaucoma at the global level, the efficiency of functional communication is altered in some specialized regions of the glaucoma. (orig.)

Advancing Health Professions Education Research by Creating a Network of Networks.

Science.gov (United States)

Carney, Patricia A; Brandt, Barbara; Dekhtyar, Michael; Holmboe, Eric S

2018-02-27

Producing the best evidence to show educational outcomes, such as competency achievement and credentialing effectiveness, across the health professions education continuum will require large multisite research projects and longitudinal studies. Current limitations that must be overcome to reach this goal include the prevalence of single-institution study designs, assessments of a single curricular component, and cross-sectional study designs that provide only a snapshot in time of a program or initiative rather than a longitudinal perspective.One solution to overcoming these limitations is to develop a network of networks that collaborates, using longitudinal approaches, across health professions and regions of the United States. Currently, individual networks are advancing educational innovation toward understanding the effectiveness of educational and credentialing programs. Examples of such networks include: (1) the American Medical Association's Accelerating Change in Medical Education initiative, (2) the National Center for Interprofessional Practice and Education, and (3) the Accreditation Council for Graduate Medical Education's Accreditation System. In this Invited Commentary, the authors briefly profile these existing networks, identify their progress and the challenges they have encountered, and propose a vigorous way forward toward creating a national network of networks designed to determine the effectiveness of health professions education and credentialing.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Science.gov (United States)

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Directory of Open Access Journals (Sweden)

S M Hadi Hosseini

Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

Theoretical Computer Science

DEFF Research Database (Denmark)

2002-01-01

The proceedings contains 8 papers from the Conference on Theoretical Computer Science. Topics discussed include: query by committee, linear separation and random walks; hardness results for neural network approximation problems; a geometric approach to leveraging weak learners; mind change...

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

Science.gov (United States)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

Public management and policy networks: foundations of a network approach to governance

NARCIS (Netherlands)

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

2006-01-01

markdownabstract__Abstract__ In this article we address the elaboratlon of the central concepts of a theory of networks and of network management. We suggest that the network approach builds on several theoretical traditions After this we clarify the theoretical concepts and axioms of the policy

Can Social Capital Networks Assist Re-entry Felons to Overcome Barriers to Re-entry and Reduce Recidivism?

Directory of Open Access Journals (Sweden)

Earl Smith

2011-05-01

Full Text Available Based on interviews with 25 reentry felons, this article examines the impact that social capital plays in successful reentry; specifically with securing stable housing and employment. We found that access to social capital allowed those with the lowest probability for success—African American men with felony convictions—to secure both stable employment and housing and thus avoid engaging in illegitimate behavior that leads to recidivism. The findings suggest that even for those individuals reentering society with the most strikes against them (as noted by researchers such as Pager and Travis, access to the resource rich social capital networks provided by reentry programs can allow these individuals to overcome the barriers to reentry and find stable jobs and secure housing. Our findings suggest that more research be done on the impact of social capital embedded in reentry programs and that referrals be made to these types of programs and funding be provided for those that demonstrate the ability to significantly reduce recidivism. As Putman has noted, "Just as a screwdriver (physical capital or a college education (human capital can increase productivity (both individual and collective, so do social contacts affect the productivity of individuals and groups."

Towards a theoretical framework for analysing organisational processes

DEFF Research Database (Denmark)

Rocha, Robson Silva

2003-01-01

In this paper, I discuss how a theoretical framework can be build to analyse socialprocesses of transformation, making the link between macro and micro processes, inwhich this dichotomy can be overcome. The aim of this theoretical framework is toaccount for the transformation in societal...... characteristics and changes in actors' strategiesat micro level, in a way that links macro changes and micro processes - the cognitivestructures of the individual and social structures of the society. In order to build this framework, I draw from the figuration sociology of Norbert Elias, the praxeologia of...

Secure Chaotic Map Based Block Cryptosystem with Application to Camera Sensor Networks

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Muhammad Khurram Khan

2011-01-01

Full Text Available Recently, Wang et al. presented an efficient logistic map based block encryption system. The encryption system employs feedback ciphertext to achieve plaintext dependence of sub-keys. Unfortunately, we discovered that their scheme is unable to withstand key stream attack. To improve its security, this paper proposes a novel chaotic map based block cryptosystem. At the same time, a secure architecture for camera sensor network is constructed. The network comprises a set of inexpensive camera sensors to capture the images, a sink node equipped with sufficient computation and storage capabilities and a data processing server. The transmission security between the sink node and the server is gained by utilizing the improved cipher. Both theoretical analysis and simulation results indicate that the improved algorithm can overcome the flaws and maintain all the merits of the original cryptosystem. In addition, computational costs and efficiency of the proposed scheme are encouraging for the practical implementation in the real environment as well as camera sensor network.

Abnormalities of functional brain networks in pathological gambling: a graph-theoretical approach

Science.gov (United States)

Tschernegg, Melanie; Crone, Julia S.; Eigenberger, Tina; Schwartenbeck, Philipp; Fauth-Bühler, Mira; Lemènager, Tagrid; Mann, Karl; Thon, Natasha; Wurst, Friedrich M.; Kronbichler, Martin

2013-01-01

Functional neuroimaging studies of pathological gambling (PG) demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in PG. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional magnetic resonance imaging data in PG. We compared 19 patients with PG to 19 healthy controls (HCs) using the Graph Analysis Toolbox (GAT). None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (supplementary motor area, SMA), reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients. These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that PG is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in PG cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders. PMID:24098282

Abnormalities of Functional Brain Networks in Pathological Gambling: A Graph-Theoretical Approach

Directory of Open Access Journals (Sweden)

Melanie eTschernegg

2013-09-01

Full Text Available Functional neuroimaging studies of pathological gambling demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in pathological gambling. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional MRI data in pathological gambling. We compared 19 patients with pathological gambling to 19 healthy controls using the Graph Analysis Toolbox (GAT. None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (SMA, reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients.These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that pathological gambling is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in pathological gambling cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

International Nuclear Information System (INIS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-01-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug–target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

Science.gov (United States)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively

Game-theoretic strategies for asymmetric networked systems

Energy Technology Data Exchange (ETDEWEB)

Rao, Nageswara S. [ORNL; Ma, Chris Y. T. [Hang Seng Management College, Hon Kong; Hausken, Kjell [University of Stavanger, Norway; He, Fei [Texas A& M University, Kingsville, TX, USA; Yau, David K. Y. [Singapore University of Technology and Design; Zhuang, Jun [University at Buffalo (SUNY)

2017-07-01

Abstract—We consider an infrastructure consisting of a network of systems each composed of discrete components that can be reinforced at a certain cost to guard against attacks. The network provides the vital connectivity between systems, and hence plays a critical, asymmetric role in the infrastructure operations. We characterize the system-level correlations using the aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual system or network. The survival probabilities of systems and network satisfy first-order differential conditions that capture the component-level correlations. We formulate the problem of ensuring the infrastructure survival as a game between anattacker and a provider, using the sum-form and product-form utility functions, each composed of a survival probability term and a cost term. We derive Nash Equilibrium conditions which provide expressions for individual system survival probabilities, and also the expected capacity specified by the total number of operational components. These expressions differ only in a single term for the sum-form and product-form utilities, despite their significant differences.We apply these results to simplified models of distributed cloud computing infrastructures.

Multifractal analysis of complex networks

International Nuclear Information System (INIS)

Wang Dan-Ling; Yu Zu-Guo; Anh V

2012-01-01

Complex networks have recently attracted much attention in diverse areas of science and technology. Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions. Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new box-covering algorithm for multifractal analysis of complex networks. This algorithm is used to calculate the generalized fractal dimensions D q of some theoretical networks, namely scale-free networks, small world networks, and random networks, and one kind of real network, namely protein—protein interaction networks of different species. Our numerical results indicate the existence of multifractality in scale-free networks and protein—protein interaction networks, while the multifractal behavior is not clear-cut for small world networks and random networks. The possible variation of D q due to changes in the parameters of the theoretical network models is also discussed. (general)

Network coding at different layers in wireless networks

CERN Document Server

2016-01-01

This book focuses on how to apply network coding at different layers in wireless networks – including MAC, routing, and TCP – with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, and redundant information ration) in order to be suitable for the varying wireless environments. The book explores how to deploy network coding in MAC to improve network performance and examines joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the text considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

Brain network of semantic integration in sentence reading: insights from independent component analysis and graph theoretical analysis.

Science.gov (United States)

Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F

2014-02-01

A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.

Competitive game theoretic optimal routing in optical networks

Science.gov (United States)

Yassine, Abdulsalam; Kabranov, Ognian; Makrakis, Dimitrios

2002-09-01

Optical transport service providers need control and optimization strategies for wavelength management, network provisioning, restoration and protection, allowing them to define and deploy new services and maintain competitiveness. In this paper, we investigate a game theory based model for wavelength and flow assignment in multi wavelength optical networks, consisting of several backbone long-haul optical network transport service providers (TSPs) who are offering their services -in terms of bandwidth- to Internet service providers (ISPs). The ISPs act as brokers or agents between the TSP and end user. The agent (ISP) buys services (bandwidth) from the TSP. The TSPs compete among themselves to sell their services and maintain profitability. We present a case study, demonstrating the impact of different bandwidth broker demands on the supplier's profit and the price paid by the network broker.

Linear approximation model network and its formation via ...

Indian Academy of Sciences (India)

To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

Disposition of overcoming students for critical reading

Directory of Open Access Journals (Sweden)

Rosangela Miola Galvão

2018-03-01

Full Text Available This article aims to present the possibilities of an educational practice that focuses on the formation of Basic Education students in critical readers. For this, understand the concepts of alienation and language from the point of view of Historical and Dialectical Materialism and Historical-Cultural Theory was essential to understand how the students of the 7th year are able to overcome this paradigm that contributes to the naive reading of texts worked in the classroom. It was a qualitative study of bibliographic revision in union with the dialectical practice with students in a public school located in the north of the State of Paraná. As methodology, was developed twelve classes with diversified material in which the teacher's mediation sought to contemplate form and content in the way that occurred the deconstruction of the fictitious hero concept represented at the end by the art of the haicai poem. The use of the cell phone instrument and Whatsapp were important for the development of the poetic sense. It seeks, therefore, to demonstrate the contributions of historical and dialectical materialism to teaching practice and human development. The theorists considerations allow us to note that language contributes to the development of higher psychic functions in man and the alienation of subjects in today's society considerably affects the students interpretation and, consequently, formation for critical reading, which can be overcome with the use of a conscious theoretical current.

Overcoming challenges

Medline Plus

Full Text Available ... facts about babies, breastmilk, and breastfeeding Overcoming challenges Common questions about breastfeeding and pain Breastfeeding checklist: How to get a good latch Finding support It takes a village: Building ...

Resource Allocation for Multicell Device-to-Device Communications in Cellular Network: A Game Theoretic Approach

Directory of Open Access Journals (Sweden)

Jun Huang

2015-08-01

Full Text Available Device-to-Device (D2D communication has recently emerged as a promising technology to improve the capacity and coverage of cellular systems. To successfully implement D2D communications underlaying a cellular network, resource allocation for D2D links plays a critical role. While most of prior resource allocation mechanisms for D2D communications have focused on interference within a single-cell system, this paper investigates the resource allocation problem for a multicell cellular network in which a D2D link reuses available spectrum resources of multiple cells. A repeated game theoretic approach is proposed to address the problem. In this game, the base stations (BSs act as players that compete for resource supply of D2D, and the utility of each player is formulated as revenue collected from both cellular and D2D users using resources. Extensive simulations are conducted to verify the proposed approach and the results show that it can considerably enhance the system performance in terms of sum rate and sum rate gain.

A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology

Science.gov (United States)

Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing

2018-03-01

Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.

Peer influence in network markets: a theoretical and empirical analysis

NARCIS (Netherlands)

J. Henkel (Joachim); J.H. Block (Jörn)

2013-01-01

textabstractNetwork externalities spur the growth of networks and the adoption of network goods in two ways. First, they make it more attractive to join a network the larger its installed base. Second, they create incentives for network members to actively recruit new members. Despite indications

Finding quasi-optimal network topologies for information transmission in active networks.

Science.gov (United States)

Baptista, Murilo S; de Carvalho, Josué X; Hussein, Mahir S

2008-01-01

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Finding quasi-optimal network topologies for information transmission in active networks.

Directory of Open Access Journals (Sweden)

Murilo S Baptista

Full Text Available This work clarifies the relation between network circuit (topology and behaviour (information transmission and synchronization in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Overcoming barriers to scheduling embedded generation to support distribution networks

Energy Technology Data Exchange (ETDEWEB)

Wright, A.J.; Formby, J.R.

2000-07-01

Current scheduling of embedded generation for distribution in the UK is limited and patchy. Some DNOs actively schedule while others do none. The literature on the subject is mainly about accommodating volatile wind output, and optimising island systems, for both cost of supply and network stability. The forthcoming NETA will lower prices, expose unpredictable generation to imbalance markets and could introduce punitive constraint payments on DNOs, but at the same time create a dynamic market for both power and ancillary services from embedded generators. Most renewable generators either run as base load (e.g. waste ) or according to the vagaries of the weather (e.g. wind, hydro), so offer little scope for scheduling other than 'off'. CHP plant is normally heat- led for industrial processes or building needs, but supplementary firing or thermal storage often allow considerable scope for scheduling. Micro-CHP with thermal storage could provide short-term scheduling, but tends to be running anyway during the evening peak. Standby generation appears to be ideal for scheduling, but in practice operators may be unwilling to run parallel with the network, and noise and pollution problems may preclude frequent operation. Statistical analysis can be applied to calculate the reliability of several generators compared to one; with a large number of generators such as micro-CHP reliability of a proportion of load is close to unity. The type of communication for generation used will depend on requirements for bandwidth, cost, reliability and whether it is bundled with other services. With high levels of deeply embedded, small-scale generation using induction machines, voltage control and black start capability will become important concerns on 11 kV and LV networks. This will require increased generation monitoring and remote control of switchgear. Examples of cost benefits from scheduling are given, including deferred reinforcement, increased exports on non

Towards understanding international migration determinants today: Theoretical perspective

Directory of Open Access Journals (Sweden)

Predojević-Despić Jelena

2010-01-01

significantly different from those which lead to their stabilization in time and space. Although differences in the income height, risks, employment possibilities, market expansion can all influence the continuation of spatial movement of population, new conditions which arise during migration begin to act as independent factors: development of migratory networks, institutionalized support to the development of trans-national activities, as well as changing the social context of work in countries of destination. Therefore, in the analysis of contemporary international migrations the necessity arises for a systematic approach, namely dynamic perspective of research - from recognition to a detailed insight in changeable trends and forms of contemporary migratory movements in the world. In addition, at the same time with the development of new markets, regional economies and technology centers, there has been a 'trans-national turnabout' in the last fifteen years or so in researching migrations, namely a significant development in the approach which stresses the relations which migrants maintain with their families, communities and cultures which are out of the country in which they migrated in. The final part of the paper calls for the requirement of the following: coordination of theoretical concepts with new social conditions, post-industrial world and global processes of transformations in which migrations have an important role; overcoming inadequate coordination and isolation in studying migrations within special scientific disciplines, as well as poor connections of certain aspects of migration study; research of the causes and consequences of migrations as an inseparable part of the general process of social development. .

Overcoming challenges

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Full Text Available ... and mission Leadership Programs and activities In your community Funding opportunities Internships and jobs View all pages ... breastfeeding myths Breastfeeding myths in the African-American community Incredible facts about babies, breastmilk, and breastfeeding Overcoming ...

Overcoming challenges

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Full Text Available ... menu It's Only Natural Planning ahead Breastfeeding and baby basics Making breastfeeding work for you Addressing breastfeeding ... in the African-American community Incredible facts about babies, breastmilk, and breastfeeding Overcoming challenges Common questions about ...

Overcoming challenges

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Full Text Available ... Disease and Stroke HIV and AIDS Mental Health Pain Pregnancy Reproductive Health Sexual Health Sexually Transmitted Infections ... breastfeeding Overcoming challenges Common questions about breastfeeding and pain Breastfeeding checklist: How to get a good latch ...

Overcoming challenges

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Full Text Available ... into your life Breastfeeding in daily life: At home and in public Laws that support breastfeeding 10 ... and jobs View all pages in this section Home It's Only Natural Overcoming challenges It's Only Natural ...

HIGH: A Hexagon-based Intelligent Grouping Approach in Wireless Sensor Networks

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FAN, C.-S.

2016-02-01

Full Text Available In a random deployment or uniform deployment strategy, sensor nodes are scattered randomly or uniformly in the sensing field, respectively. Hence, the coverage ratio cannot be guaranteed. The coverage ratio of uniform deployment, in general, is larger than that of the random deployment strategy. However, a random deployment or uniform deployment strategy may cause unbalanced traffic pattern in wireless sensor networks (WSNs. Therefore, cluster heads (CHs around the sink have larger loads than those farther away from the sink. That is, CHs close to the sink exhaust their energy earlier. In order to overcome the above problem, we propose a Hexagon-based Intelligent Grouping approacH in WSNs (called HIGH. The coverage, energy consumption and data routing issues are well investigated and taken into consideration in the proposed HIGH scheme. The simulation results validate our theoretical analysis and show that the proposed HIGH scheme achieves a satisfactory coverage ratio, balances the energy consumption among sensor nodes, and extends network lifetime significantly.

Temperature- and supply voltage-independent time references for wireless sensor networks

CERN Document Server

De Smedt, Valentijn; Dehaene, Wim

2015-01-01

This book investigates the possible circuit solutions to overcome the temperature- and supply voltage-sensitivity of fully-integrated time references for ultra-low-power communication in wireless sensor networks. The authors provide an elaborate theoretical introduction and literature study to enable full understanding of the design challenges and shortcomings of current oscillator implementations.  Furthermore, a closer look to the short-term as well as the long-term frequency stability of integrated oscillators is taken. Next, a design strategy is developed and applied to 5 different oscillator topologies and 1 sensor interface.All 6 implementations are subject to an elaborate study of frequency stability, phase noise, and power consumption. In the final chapter all blocks are compared to the state of the art. The main goals of this book are: • to provide a comprehensive overview of timing issues and solutions in wireless sensor networks; • to gain understanding of all underlying mechanisms by starti...

A Bayesian network model for predicting aquatic toxicity mode of action using two dimensional theoretical molecular descriptors

Energy Technology Data Exchange (ETDEWEB)

Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)

2016-11-15

Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by

The US Fire Learning Network: Springing a Rigidity Trap through Multiscalar Collaborative Networks

Directory of Open Access Journals (Sweden)

William Hale. Butler

2010-09-01

Full Text Available Wildland fire management in the United States is caught in a rigidity trap, an inability to apply novelty and innovation in the midst of crisis. Despite wide recognition that public agencies should engage in ecological fire restoration, fire suppression still dominates planning and management, and restoration has failed to gain traction. The U.S. Fire Learning Network (FLN, a multiscalar collaborative endeavor established in 2002 by federal land management agencies and The Nature Conservancy, offers the potential to overcome barriers that inhibit restoration planning and management. By circulating people, planning products, and information among landscape- and regional-scale collaboratives, this network has facilitated the development and dissemination of innovative approaches to ecological fire restoration. Through experimentation and innovation generated in the network, the FLN has fostered change by influencing fire and land management plans as well as federal policy. We suggest that multiscalar collaborative planning networks such as the FLN can facilitate overcoming the rigidity traps that prevent resource management agencies from responding to complex cross-scalar problems.

Developing a theoretical framework for complex community-based interventions.

Science.gov (United States)

Angeles, Ricardo N; Dolovich, Lisa; Kaczorowski, Janusz; Thabane, Lehana

2014-01-01

Applying existing theories to research, in the form of a theoretical framework, is necessary to advance knowledge from what is already known toward the next steps to be taken. This article proposes a guide on how to develop a theoretical framework for complex community-based interventions using the Cardiovascular Health Awareness Program as an example. Developing a theoretical framework starts with identifying the intervention's essential elements. Subsequent steps include the following: (a) identifying and defining the different variables (independent, dependent, mediating/intervening, moderating, and control); (b) postulating mechanisms how the independent variables will lead to the dependent variables; (c) identifying existing theoretical models supporting the theoretical framework under development; (d) scripting the theoretical framework into a figure or sets of statements as a series of hypotheses, if/then logic statements, or a visual model; (e) content and face validation of the theoretical framework; and (f) revising the theoretical framework. In our example, we combined the "diffusion of innovation theory" and the "health belief model" to develop our framework. Using the Cardiovascular Health Awareness Program as the model, we demonstrated a stepwise process of developing a theoretical framework. The challenges encountered are described, and an overview of the strategies employed to overcome these challenges is presented.

Overcoming challenges

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Full Text Available ... breastfeeding means to them. Subscribe To receive Breastfeeding email updates Enter email Submit Overcoming challenges Breastfeeding has a long list ... breastfeeding means to them. Subscribe To receive Breastfeeding email updates Enter email Submit All material contained on ...

Overcoming selfishness: reciprocity, inhibition, and cardiac-autonomic control in the ultimatum game.

Science.gov (United States)

Sütterlin, Stefan; Herbert, Cornelia; Schmitt, Michael; Kübler, Andrea; Vögele, Claus

2011-01-01

The processes underlying decision-making in response to unfair offers in the ultimatum game (UG) have recently been discussed in light of models of reciprocity and fairness-related behavior. It has been suggested that behavior following norm-oriented, internalized expectations of reciprocity requires overcoming economic self-interest. In this study we investigated both, behavioral and peripheral-physiological indicators of inhibitory capacity related to neuronal networks that are likely to be involved in the behavioral response to unfair offers. Both heart-rate variability as an index of inhibitory capacity, and performance in a motor response inhibition task predicted rejection of unfair offers in an UG, suggesting an important role of inhibitory processes in overcoming economic temptations and regulating behavior conforming to social norms of reciprocity and fairness. The role of parasympathetic activity as a physiological trait-marker predicting inter-individual differences in the rejection of unfair offers is discussed.

Conceptual and methodological biases in network models.

Science.gov (United States)

Lamm, Ehud

2009-10-01

Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between "program" and "data." The evolutionary significance of the dynamics of trans-generational and interorganism regulatory networks is explored and implications are presented for understanding the evolution of the biological categories development-heredity, plasticity-evolvability, and epigenetic-genetic.

Overcoming challenges

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Full Text Available ... Contact Us Blog Popular topics Vision and mission Leadership Programs and activities In your community Funding opportunities Internships and jobs View all pages in this section Home It's Only Natural Overcoming challenges It's Only Natural Planning ahead Addressing breastfeeding myths ...

Utilising artificial intelligence in software defined wireless sensor network

CSIR Research Space (South Africa)

Matlou, OG

2017-10-01

Full Text Available Software Defined Wireless Sensor Network (SDWSN) is realised by infusing Software Defined Network (SDN) model in Wireless Sensor Network (WSN), Reason for that is to overcome the challenges of WSN. Artificial Intelligence (AI) and machine learning...

Urban Green Network Design: Defining green network from an urban planning perspective

OpenAIRE

Andrea Tulisi

2017-01-01

From the theoretical context of Smart City various studies have emerged that adopt an analytical approach and description of urban phenomena based on the principles of “network design”; this line of research uses the network systems theory to define the principles that regulate the relationships among the various elements of urban sub-systems in order to optimize their functionality. From the same theoretical basis, urban greenspaces have also been studied as networks, by means of the creatio...

Overcoming challenges

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Full Text Available ... we are What we do Programs and activities Work with us Contact Us Blog Popular topics Vision and mission Leadership Programs and activities In your community Funding opportunities Internships and jobs View all pages in this section Home It's Only Natural Overcoming challenges It's Only Natural ...

Overcoming selfishness: reciprocity, inhibition, and cardiac autonomic control in the ultimatum game

Directory of Open Access Journals (Sweden)

Stefan eSütterlin

2011-07-01

Full Text Available The processes underlying decision-making in response to unfair offers in the ultimatum game (UG have recently been discussed in light of models of reciprocity and fairness-related behavior. It has been suggested that behavior following norm-oriented, internalized expectations of reciprocity requires overcoming economic self-interest. In this study we investigated both, behavioral and peripheral-physiological indicators of inhibitory capacity related to neuronal networks that are likely to be involved in the behavioral response to unfair offers. Both heart-rate variability as an index of inhibitory capacity, and performance in a motor response inhibition task predicted rejection of unfair offers in an ultimatum game, suggesting an important role of inhibitory processes in overcoming economic temptations and regulating behavior conforming to social norms of reciprocity and fairness. The role of parasympathetic activity as a physiological trait-marker predicting inter-individual differences in the rejection of unfair offers is discussed.

Smart Companies, Inspiring the Future: A Theoretical Review

OpenAIRE

Echazarreta Soler, Carmen; Costa Marcé, Albert

2017-01-01

The economic and financial global crises have accelerated the search for alternative business models. The aim of this article is to describe the main characteristics of smart companies capable of overcoming the shortcomings of the current economic system. After conducting a theoretical review of the main studies related to this area, we conclude that there is a need for smart companies championed by leaders who promote the use of information technologies and communication as means...

Game-theoretic interference coordination approaches for dynamic spectrum access

CERN Document Server

Xu, Yuhua

2016-01-01

Written by experts in the field, this book is based on recent research findings in dynamic spectrum access for cognitive radio networks. It establishes a game-theoretic framework and presents cutting-edge technologies for distributed interference coordination. With game-theoretic formulation and the designed distributed learning algorithms, it provides insights into the interactions between multiple decision-makers and the converging stable states. Researchers, scientists and engineers in the field of cognitive radio networks will benefit from the book, which provides valuable information, useful methods and practical algorithms for use in emerging 5G wireless communication.

Team Resilience as a Second-Order Emergent State: A Theoretical Model and Research Directions

Directory of Open Access Journals (Sweden)

Clint Bowers

2017-08-01

Full Text Available Resilience has been recognized as an important phenomenon for understanding how individuals overcome difficult situations. However, it is not only individuals who face difficulties; it is not uncommon for teams to experience adversity. When they do, they must be able to overcome these challenges without performance decrements.This manuscript represents a theoretical model that might be helpful in conceptualizing this important construct. Specifically, it describes team resilience as a second-order emergent state. We also include research propositions that follow from the model.

Marketing communications model for innovation networks

Directory of Open Access Journals (Sweden)

Tiago João Freitas Correia

2015-10-01

Full Text Available Innovation is an increasingly relevant concept for the success of any organization, but it also represents a set of internal and external considerations, barriers and challenges to overcome. Along the concept of innovation, new paradigms emerge such as open innovation and co-creation that are simultaneously innovation modifiers and intensifiers in organizations, promoting organizational openness and stakeholder integration within the value creation process. Innovation networks composed by a multiplicity of agents in co-creative work perform as innovation mechanisms to face the increasingly complexity of products, services and markets. Technology, especially the Internet, is an enabler of all process among organizations supported by co-creative platforms for innovation. The definition of marketing communication strategies that promote motivation and involvement of all stakeholders in synergic creation and external promotion is the central aspect of this research. The implementation of the projects is performed by participative workshops with stakeholders from Madan Parque through IDEAS(REVOLUTION methodology and the operational model LinkUp parameterized for the project. The project is divided into the first part, the theoretical framework, and the second part where a model is developed for the marketing communication strategies that appeal to the Madan Parque case study. Keywords: Marketing Communication; Open Innovation, Technology; Innovation Networks; Incubator; Co-Creation.

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).

The model of social crypto-network

Directory of Open Access Journals (Sweden)

Марк Миколайович Орел

2015-06-01

Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

Deep neural networks for texture classification-A theoretical analysis.

Science.gov (United States)

Basu, Saikat; Mukhopadhyay, Supratik; Karki, Manohar; DiBiano, Robert; Ganguly, Sangram; Nemani, Ramakrishna; Gayaka, Shreekant

2018-01-01

We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate. As a corollary to this analysis, we derive for the first time upper bounds on the VC dimension of Convolutional Neural Network as well as Dropout and Dropconnect networks and the relation between excess error rate of Dropout and Dropconnect networks. The concept of intrinsic dimension is used to validate the intuition that texture-based datasets are inherently higher dimensional as compared to handwritten digits or other object recognition datasets and hence more difficult to be shattered by neural networks. We then derive the mean distance from the centroid to the nearest and farthest sampling points in an n-dimensional manifold and show that the Relative Contrast of the sample data vanishes as dimensionality of the underlying vector space tends to infinity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Trimming of mammalian transcriptional networks using network component analysis

Directory of Open Access Journals (Sweden)

Liao James C

2010-10-01

Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm

Formation of multiple networks

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2013-01-01

we introduce the first network formation model for multiple networks. Network formation models are among the most popular tools in traditional network studies, because of both their practical and theoretical impact. However, existing models are not sufficient to describe the generation of multiple...

Barriers to women engaging in collective action to overcome sexism.

Science.gov (United States)

Radke, Helena R M; Hornsey, Matthew J; Barlow, Fiona Kate

2016-12-01

Over centuries women have fought hard to obtain increasing gender equality, but despite these successes absolute equality remains an elusive goal. Theoretically, women's numerical strength makes them well-placed to take effective collective action, and millions of women engage in feminist collective action every day. In this article, however, we argue that women also face barriers to engaging in feminist collective action; barriers that are associated with the social construction and experience of what it means to be a woman. Our review synthesizes sexism research under a contemporary collective action framework to clarify our current understanding of the literature and to offer novel theoretical explanations for why women might be discouraged from engaging in feminist collective action. Using the antecedents of collective action identified by van Zomeren, Postmes, and Spears' (2008) meta-analysis, we critically review the sexism literature to argue that women face challenges when it comes to (a) identifying with other women and feminists, (b) perceiving sexism and expressing group-based anger, and (c) recognizing the efficacy of collective action. We then outline a research agenda with a view to investigating ways of overcoming these barriers. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Epidemics spreading in interconnected complex networks

International Nuclear Information System (INIS)

Wang, Y.; Xiao, G.

2012-01-01

We study epidemic spreading in two interconnected complex networks. It is found that in our model the epidemic threshold of the interconnected network is always lower than that in any of the two component networks. Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. Theoretical analysis and simulation results show that, generally speaking, the epidemic size is not significantly affected by the inter-network correlation. In interdependent networks which can be viewed as a special case of interconnected networks, however, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant. -- Highlights: ► We study epidemic spreading in two interconnected complex networks. ► The epidemic threshold is lower than that in any of the two networks. And Interconnection correlation has impacts on threshold and average outbreak size. ► Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. ► We demonstrated and proved that Interconnection correlation does not affect epidemic size significantly. ► In interdependent networks, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant.

Epidemics spreading in interconnected complex networks

Energy Technology Data Exchange (ETDEWEB)

Wang, Y. [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore); Institute of High Performance Computing, Agency for Science, Technology and Research (A-STAR), Singapore 138632 (Singapore); Xiao, G., E-mail: egxxiao@ntu.edu.sg [School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (Singapore)

2012-09-03

We study epidemic spreading in two interconnected complex networks. It is found that in our model the epidemic threshold of the interconnected network is always lower than that in any of the two component networks. Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. Theoretical analysis and simulation results show that, generally speaking, the epidemic size is not significantly affected by the inter-network correlation. In interdependent networks which can be viewed as a special case of interconnected networks, however, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant. -- Highlights: ► We study epidemic spreading in two interconnected complex networks. ► The epidemic threshold is lower than that in any of the two networks. And Interconnection correlation has impacts on threshold and average outbreak size. ► Detailed theoretical analysis is proposed which allows quick and accurate calculations of epidemic threshold and average outbreak/epidemic size. ► We demonstrated and proved that Interconnection correlation does not affect epidemic size significantly. ► In interdependent networks, impacts of inter-network correlation on the epidemic threshold and outbreak size are more significant.

Overcoming job stress

Science.gov (United States)

... medlineplus.gov/ency/patientinstructions/000884.htm Overcoming job stress To use the sharing features on this page, ... stay healthy and feel better. Causes of Job Stress Although the cause of job stress is different ...

Tourism-planning network knowledge dynamics

DEFF Research Database (Denmark)

Dredge, Dianne

2014-01-01

This chapter explores the characteristics and functions of tourism networks as a first step in understanding how networks facilitate and reproduce knowledge. A framework to progress understandings of knowledge dynamics in tourism networks is presented that includes four key dimensions: context......, network agents, network boundaries and network resources. A case study of the development of the Next Generation Tourism Handbook (Queensland, Australia), a policy initiative that sought to bring tourism and land use planning knowledge closer together is presented. The case study illustrates...... that the tourism policy and land use planning networks operate in very different spheres and that context, network agents, network boundaries and network resources have a significant influence not only on knowledge dynamics but also on the capacity of network agents to overcome barriers to learning and to innovate....

A theoretical framework for the associations between identity and psychopathology.

Science.gov (United States)

Klimstra, Theo A; Denissen, Jaap J A

2017-11-01

Identity research largely emerged from clinical observations. Decades of empirical work advanced the field in refining existing approaches and adding new approaches. Furthermore, the existence of linkages of identity with psychopathology is now well established. Unfortunately, both the directionality of effects between identity aspects and psychopathology symptoms, and the mechanisms underlying associations are unclear. In the present paper, we present a new framework to inspire hypothesis-driven empirical research to overcome this limitation. The framework has a basic resemblance to theoretical models for the study of personality and psychopathology, so we provide examples of how these might apply to the study of identity. Next, we explain that unique features of identity may come into play in individuals suffering from psychopathology that are mostly related to the content of one's identity. These include pros and cons of identifying with one's diagnostic label. Finally, inspired by Hermans' dialogical self theory and principles derived from Piaget's, Swann's and Kelly's work, we delineate a framework with identity at the core of an individual multidimensional space. In this space, psychopathology symptoms have a known distance (representing relevance) to one's identity, and individual multidimensional spaces are connected to those of other individuals in one's social network. We discuss methodological (quantitative and qualitative, idiographic and nomothetic) and statistical procedures (multilevel models and network models) to test the framework. Resulting evidence can boost the field of identity research in demonstrating its high practical relevance for the emergence and conservation of psychopathology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Game Theoretical Approaches for Transport-Aware Channel Selection in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Chen Shih-Ho

2010-01-01

Full Text Available Effectively sharing channels among secondary users (SUs is one of the greatest challenges in cognitive radio network (CRN. In the past, many studies have proposed channel selection schemes at the physical or the MAC layer that allow SUs swiftly respond to the spectrum states. However, they may not lead to enhance performance due to slow response of the transport layer flow control mechanism. This paper presents a cross-layer design framework called Transport Aware Channel Selection (TACS scheme to optimize the transport throughput based on states, such as RTT and congestion window size, of TCP flow control mechanism. We formulate the TACS problem as two different game theoretic approaches: Selfish Spectrum Sharing Game (SSSG and Cooperative Spectrum Sharing Game (CSSG and present novel distributed heuristic algorithms to optimize TCP throughput. Computer simulations show that SSSG and CSSG could double the SUs throughput of current MAC-based scheme when primary users (PUs use their channel infrequently, and with up to 12% to 100% throughput increase when PUs are more active. The simulation results also illustrated that CSSG performs up to 20% better than SSSG in terms of the throughput.

Bio-inspired networking

CERN Document Server

Câmara, Daniel

2015-01-01

Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore how bio-inspired methods can solve different problems linked to computer networks. Future networks are expected to be autonomous, scalable and adaptive. During millions of years of evolution, nature has developed a number of different systems that present these and other characteristics required for the next generation networks. Indeed, a series of bio-inspired methods have been successfully used to solve the most diverse problems linked to computer networks. This book presents some of these techniques from a theoretical and practical point of view. Discusses the key concepts of bio-inspired networking to aid you in finding efficient networking solutions Delivers examples of techniques both in theoretical concepts and practical applications Helps you apply nature's dynamic resource and task management to your co...

Collaborative networks: Reference modeling

NARCIS (Netherlands)

Camarinha-Matos, L.M.; Afsarmanesh, H.

2008-01-01

Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

Balancing act: Government roles in an energy conservation network

NARCIS (Netherlands)

Peterman, A.; Kourula, A.; Levitt, R.

2014-01-01

Government-led interorganizational alliance networks present a sensible opportunity to overcome many societal challenges through collaborative governance. In particular, few researchers have studied alliance networks in the field of energy conservation in commercial buildings—a sector with unique

EAP-Based Authentication for Ad Hoc Network

OpenAIRE

Bhakti, Muhammad Agni Catur; Abdullah, Azween; Jung, Low Tan

2007-01-01

Wireless network has been deployed worldwide, but some security issues in wireless network might haveprevented its further acceptance. One of the solutions to overcome the limitation of wireless network security isthe IEEE 802.1X specification, a mechanism for port-based network access control, which is based onExtensible Authentication Protocol (EAP). It is an authentication framework that can support multipleauthentication methods. EAP can run over many types of data-link layer and it is fl...

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

Dynamics of the Drosophila circadian clock: theoretical anti-jitter network and controlled chaos.

Directory of Open Access Journals (Sweden)

Hassan M Fathallah-Shaykh

Full Text Available BACKGROUND: Electronic clocks exhibit undesirable jitter or time variations in periodic signals. The circadian clocks of humans, some animals, and plants consist of oscillating molecular networks with peak-to-peak time of approximately 24 hours. Clockwork orange (CWO is a transcriptional repressor of Drosophila direct target genes. METHODOLOGY/PRINCIPAL FINDINGS: Theory and data from a model of the Drosophila circadian clock support the idea that CWO controls anti-jitter negative circuits that stabilize peak-to-peak time in light-dark cycles (LD. The orbit is confined to chaotic attractors in both LD and dark cycles and is almost periodic in LD; furthermore, CWO diminishes the Euclidean dimension of the chaotic attractor in LD. Light resets the clock each day by restricting each molecular peak to the proximity of a prescribed time. CONCLUSIONS/SIGNIFICANCE: The theoretical results suggest that chaos plays a central role in the dynamics of the Drosophila circadian clock and that a single molecule, CWO, may sense jitter and repress it by its negative loops.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

Science.gov (United States)

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Breakdown of interdependent directed networks.

Science.gov (United States)

Liu, Xueming; Stanley, H Eugene; Gao, Jianxi

2016-02-02

Increasing evidence shows that real-world systems interact with one another via dependency connectivities. Failing connectivities are the mechanism behind the breakdown of interacting complex systems, e.g., blackouts caused by the interdependence of power grids and communication networks. Previous research analyzing the robustness of interdependent networks has been limited to undirected networks. However, most real-world networks are directed, their in-degrees and out-degrees may be correlated, and they are often coupled to one another as interdependent directed networks. To understand the breakdown and robustness of interdependent directed networks, we develop a theoretical framework based on generating functions and percolation theory. We find that for interdependent Erdős-Rényi networks the directionality within each network increases their vulnerability and exhibits hybrid phase transitions. We also find that the percolation behavior of interdependent directed scale-free networks with and without degree correlations is so complex that two criteria are needed to quantify and compare their robustness: the percolation threshold and the integrated size of the giant component during an entire attack process. Interestingly, we find that the in-degree and out-degree correlations in each network layer increase the robustness of interdependent degree heterogeneous networks that most real networks are, but decrease the robustness of interdependent networks with homogeneous degree distribution and with strong coupling strengths. Moreover, by applying our theoretical analysis to real interdependent international trade networks, we find that the robustness of these real-world systems increases with the in-degree and out-degree correlations, confirming our theoretical analysis.

Overcoming barriers to development of cooperative medical decision support models.

Science.gov (United States)

Hudson, Donna L; Cohen, Maurice E

2012-01-01

Attempts to automate the medical decision making process have been underway for the at least fifty years, beginning with data-based approaches that relied chiefly on statistically-based methods. Approaches expanded to include knowledge-based systems, both linear and non-linear neural networks, agent-based systems, and hybrid methods. While some of these models produced excellent results none have been used extensively in medical practice. In order to move these methods forward into practical use, a number of obstacles must be overcome, including validation of existing systems on large data sets, development of methods for including new knowledge as it becomes available, construction of a broad range of decision models, and development of non-intrusive methods that allow the physician to use these decision aids in conjunction with, not instead of, his or her own medical knowledge. None of these four requirements will come easily. A cooperative effort among researchers, including practicing MDs, is vital, particularly as more information on diseases and their contributing factors continues to expand resulting in more parameters than the human decision maker can process effectively. In this article some of the basic structures that are necessary to facilitate the use of an automated decision support system are discussed, along with potential methods for overcoming existing barriers.

Paul Karl Feyerabend: The Projections of Theoretical Proliferation in the Relation Science-Metaphysics

Directory of Open Access Journals (Sweden)

María Teresa Gargiulo de Vázquez

2015-05-01

Full Text Available The Paul Karl Feyerabend’s doctrine of theoretical proliferation has been interpreted by his experts as an attempt to preserve the ideal of scientific progress. This hermeneutics describes, in part, the intention of our philosopher. However, this reading does not explain the fundamental criticism that theoretical pluralism supposes for Feyerabend. The theoretical proliferation is itself a reductio ad absurdum of the attempts of logical positivism and critical rationalism to define science at the expense of the metaphysical. This article presents the theoretical proliferation as a vindication of the positive role that the metaphysical plays in scientific practice. We expose the Feyerabend’s defense of metaphysics inasmuch as it is constitute the possibility to overcome the conceptual conservatism, to increase empirical content of science and to recover the descriptive value of scientific theories.

Game Theoretic Solutions to Cyber Attack and Network Defense Problems

National Research Council Canada - National Science Library

Shen, Dan; Chen, Genshe; Cruz, Jr., , Jose B; Blasch, Erik; Kruger, Martin

2007-01-01

.... The protection and defense against cyber attacks to computer network is becoming inadequate as the hacker knowledge sophisticates and as the network and each computer system become more complex...

Stages of neuronal network formation

International Nuclear Information System (INIS)

Woiterski, Lydia; Käs, Josef A; Claudepierre, Thomas; Luxenhofer, Robert; Jordan, Rainer

2013-01-01

Graph theoretical approaches have become a powerful tool for investigating the architecture and dynamics of complex networks. The topology of network graphs revealed small-world properties for very different real systems among these neuronal networks. In this study, we observed the early development of mouse retinal ganglion cell (RGC) networks in vitro using time-lapse video microscopy. By means of a time-resolved graph theoretical analysis of the connectivity, shortest path length and the edge length, we were able to discover the different stages during the network formation. Starting from single cells, at the first stage neurons connected to each other ending up in a network with maximum complexity. In the further course, we observed a simplification of the network which manifested in a change of relevant network parameters such as the minimization of the path length. Moreover, we found that RGC networks self-organized as small-world networks at both stages; however, the optimization occurred only in the second stage. (paper)

The theoretical strength of rubber: numerical simulations of polyisoprene networks at high tensile strains evidence the role of average chain tortuosity

International Nuclear Information System (INIS)

Hanson, David E; Barber, John L

2013-01-01

The ultimate stress and strain of polyisoprene rubber were studied by numerical simulations of three-dimensional random networks, subjected to tensile strains high enough to cause chain rupture. Previously published molecular chain force extension models and a numerical network construction procedure were used to perform the simulations for network crosslink densities between 2 × 10 19 and 1 × 10 20 cm −3 , corresponding to experimental dicumyl-peroxide concentrations of 1–5 parts per hundred. At tensile failure (defined as the point of maximum stress), we find that the fraction of network chains ruptured is between 0.1% and 1%, depending on the crosslink density. The fraction of network chains that are taut, i.e. their end-to-end distance is greater than their unstretched contour length, ranges between 10% and 15% at failure. Our model predicts that the theoretical (defect-free) failure stress should be about twice the highest experimental value reported. For extensions approaching failure, tensile stress is dominated by the network morphology and purely enthalpic bond distortion forces and, in this regime, the model has essentially no free parameters. The average initial chain tortuosity (τ) appears to be an important statistical property of rubber networks; if the stress is scaled by τ and the tensile strain is scaled by τ −1 , we obtain a master curve for stress versus strain, valid for all crosslink densities. We derive an analytic expression for the average tortuosity, which is in agreement with values calculated in the simulations. (paper)

Sensor and ad-hoc networks theoretical and algorithmic aspects

CERN Document Server

Makki, S Kami; Pissinou, Niki; Makki, Shamila; Karimi, Masoumeh; Makki, Kia

2008-01-01

This book brings together leading researchers and developers in the field of wireless sensor networks to explain the special problems and challenges of the algorithmic aspects of sensor and ad-hoc networks. The book also fosters communication not only between the different sensor and ad-hoc communities, but also between those communities and the distributed systems and information systems communities. The topics addressed pertain to the sensors and mobile environment.

Department of Theoretical Physics - Overview

International Nuclear Information System (INIS)

Kwiecinski, J.

2002-01-01

Full text: Research activity of the Department of Theoretical Physics concerns theoretical high energy and elementary particle physics, intermediate energy particle physics, theoretical nuclear physics, theory of nuclear matter, theory of quark-gluon plasma and of relativistic heavy ion collisions, theoretical astrophysics and general physics. There is some emphasis on the phenomenological applications of the theoretical research yet the more formal problems are also considered. The detailed summary of the research projects and of the results obtained in various fields is given in the abstracts. Our Department successfully collaborates with other Departments of the Institute as well as with several scientific institutions both in Poland and abroad. In particular, members of our Department participate in the EC network which allows for the mobility of researchers. Several members of our Department have also participated in the research projects funded by the State Committee for Scientific Research. Besides pure research, members of our Department are also involved in graduate and undergraduate teaching activity both at our Institute and at other academic institutions in Cracow. At present, eight students are working towards their Ph.D. degrees under the supervision of senior members of the Department. (author)

Department of Theoretical Physics - Overview

International Nuclear Information System (INIS)

Kwiecinski, J.

2001-01-01

Full text: Research activity of the Department of Theoretical Physics concerns theoretical high-energy and elementary particle physics, intermediate energy particle physics, theoretical nuclear physics, theory of nuclear matter, theory of quark-gluon plasma and relativistic heavy-ion collisions, theoretical astrophysics and general physics. There is some emphasis on the phenomenological applications of the theoretical research yet more formal problems are also considered. A detailed summary of the research projects and of the results obtained in various field is given in the abstracts. Our Department actively collaborates with other Departments of the Institute as well as with several scientific institutions both in Poland and abroad. In particular, members of our Department participate in the EC network, which stimulates the mobility of researchers. Several members of our Department also participated in the research projects funded by the Polish Committee for Scientific Research (KBN). Besides pure research, members of our Department are also involved in graduate and up graduate teaching activity at our Institute as well as at other academic institution in Cracow. At present nine students are working on their Ph.D. degrees under the supervision of senior members of the Department. (author)

Multi-equilibrium property of metabolic networks: SSI module

Directory of Open Access Journals (Sweden)

Chen Luonan

2011-06-01

Full Text Available Abstract Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Networks and network analysis for defence and security

CERN Document Server

Masys, Anthony J

2014-01-01

Networks and Network Analysis for Defence and Security discusses relevant theoretical frameworks and applications of network analysis in support of the defence and security domains. This book details real world applications of network analysis to support defence and security. Shocks to regional, national and global systems stemming from natural hazards, acts of armed violence, terrorism and serious and organized crime have significant defence and security implications. Today, nations face an uncertain and complex security landscape in which threats impact/target the physical, social, economic

Game-theoretic pricing for video streaming in mobile networks.

Science.gov (United States)

Lin, W Sabrina; Liu, K J Ray

2012-05-01

Mobile phones are among the most popular consumer devices, and the recent developments of 3G networks and smart phones enable users to watch video programs by subscribing data plans from service providers. Due to the ubiquity of mobile phones and phone-to-phone communication technologies, data-plan subscribers can redistribute the video content to nonsubscribers. Such a redistribution mechanism is a potential competitor for the mobile service provider and is very difficult to trace given users' high mobility. The service provider has to set a reasonable price for the data plan to prevent such unauthorized redistribution behavior to protect or maximize his/her own profit. In this paper, we analyze the optimal price setting for the service provider by investigating the equilibrium between the subscribers and the secondary buyers in the content-redistribution network. We model the behavior between the subscribers and the secondary buyers as a noncooperative game and find the optimal price and quantity for both groups of users. Based on the behavior of users in the redistribution network, we investigate the evolutionarily stable ratio of mobile users who decide to subscribe to the data plan. Such an analysis can help the service provider preserve his/her profit under the threat of the redistribution networks and can improve the quality of service for end users.

Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool

Science.gov (United States)

Ruiz-Martinez, A.; Pereniguez-Garcia, F.; Marin-Lopez, R.; Ruiz-Martinez, P. M.; Skarmeta-Gomez, A. F.

2013-01-01

In the teaching of computer networks the main problem that arises is the high price and limited number of network devices the students can work with in the laboratories. Nowadays, with virtualization we can overcome this limitation. In this paper, we present a methodology that allows students to learn advanced computer network concepts through…

Online Social Networks: Essays on Membership, Privacy, and Structure

NARCIS (Netherlands)

Hofstra, B.

2017-01-01

The structure of social networks is crucial for obtaining social support, for meaningful connections to unknown social groups, and to overcome prejudice. Yet, we know little about the structure of social networks beyond those contacts that stand closest to us. This lack of knowledge results from a

vhv supply networks, problems of network structure

Energy Technology Data Exchange (ETDEWEB)

Raimbault, J

1966-04-01

The present and future power requirements of the Paris area and the structure of the existing networks are discussed. The various limitations that will have to be allowed for to lay down the structure of a regional transmission network leading in the power of the large national transmission network to within the Paris built up area are described. The theoretical solution that has been adopted, and the features of its final achievement, which is planned for about the year 2000, and the intermediate stages are given. The problem of the structure of the National Power Transmission network which is to supply the regional network was studied. To solve this problem, a 730 kV voltage network will have to be introduced.

The democratizing impact of governance networks

DEFF Research Database (Denmark)

Sørensen, Eva; Torfing, Jacob

2018-01-01

impact of governance networks. It claims that the initial celebration of the pluralization of public governance and the subsequent call for a democratic anchorage of governance networks should give way to a new concern for how governance networks can strengthen and democratize political leadership. Tying......Initially, governance networks were intended as tools for making public governance more effective. Yet, scholars have argued that governance networks also have the potential to democratize public governance. This article provides an overview of theoretical arguments pertaining to the democratizing...... political leadership to networked processes of collaborative governance fosters ‘interactive political leadership’. The article presents theoretical arguments in support of interactive political leadership, and provides an illustrative case study of a recent attempt to strengthen political leadership...

Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks

Directory of Open Access Journals (Sweden)

Lan Liu

2017-01-01

Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when qnetwork malware and provide a theoretical basis to reduce and prevent network security incidents.

Estimating the Theoretical Value for LAN Network Throughput Based Power Line Communications Technology Under the Homeplug 1.0 Standard

Directory of Open Access Journals (Sweden)

Martha Fabiola Contreras Higuera

2013-06-01

transmission of information using the grid as a physical means of transmission. The analysis considers the influence of the size of the packages, number of stations, mechanisms of access to the medium, the window size of initial containment, among other important aspects; in order to analyze the behavior of the Throughput on LAN networks, making use of PLC technology for their implementation at the theoretical level.

Graph Theoretical Analysis of Developmental Patterns of the White Matter Network

Directory of Open Access Journals (Sweden)

Zhang eChen

2013-11-01

Full Text Available Understanding the development of human brain organization is critical for gaining insight into how the enhancement of cognitive processes is related to the fine-tuning of the brain network. However, the developmental trajectory of the large-scale white matter (WM network is not fully understood. Here, using graph theory, we examine developmental changes in the organization of WM networks in 180 typically-developing participants. WM networks were constructed using whole brain tractography and 78 cortical regions of interest were extracted from each participant. The subjects were first divided into 5 equal sample size (n=36 groups (early childhood: 6.0-9.7 years; late childhood: 9.8-12.7 years; adolescence: 12.9-17.5 years; young adult: 17.6-21.8 years; adult: 21.9-29.6 years. Most prominent changes in the topological properties of developing brain networks occur at late childhood and adolescence. During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration. However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages. In addition, several pivotal hubs were identified that are vital for the global coordination of information flow over the whole brain network across all age groups. Significant increases of nodal efficiency were present in several regions such as precuneus at late childhood. Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network. This study used network analysis to elucidate the topological changes in brain maturation, paving the way for developing novel methods for analyzing disrupted brain connectivity in

Resource aware sensor nodes in wireless sensor networks

International Nuclear Information System (INIS)

Merrett, G V; Al-Hashimi, B M; White, N M; Harris, N R

2005-01-01

Wireless sensor networks are continuing to receive considerable research interest due, in part, to the range of possible applications. One of the greatest challenges facing researchers is in overcoming the limited network lifetime inherent in the small locally powered sensor nodes. In this paper, we propose IDEALS, a system to manage a wireless sensor network using a combination of information management, energy harvesting and energy monitoring, which we label resource awareness. Through this, IDEALS is able to extend the network lifetime for important messages, by controlling the degradation of the network to maximise information throughput

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

Advanced network programming principles and techniques : network application programming with Java

CERN Document Server

Ciubotaru, Bogdan

2013-01-01

Answering the need for an accessible overview of the field, this text/reference presents a manageable introduction to both the theoretical and practical aspects of computer networks and network programming. Clearly structured and easy to follow, the book describes cutting-edge developments in network architectures, communication protocols, and programming techniques and models, supported by code examples for hands-on practice with creating network-based applications. Features: presents detailed coverage of network architectures; gently introduces the reader to the basic ideas underpinning comp

The application of graph theoretical analysis to complex networks in the brain.

Science.gov (United States)

Reijneveld, Jaap C; Ponten, Sophie C; Berendse, Henk W; Stam, Cornelis J

2007-11-01

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks

CERN Document Server

Santi, Paolo

2012-01-01

Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and

Negative Attitudes, Networks and Education

DEFF Research Database (Denmark)

Bennett, Patrick; la Cour, Lisbeth; Larsen, Birthe

This paper theoretically and empirically assesses the potential explanations behind the educational gap between young natives and immigrants using two measures, negative attitudes towards immigrants and networking. The paper considers that two these parameters may influence high and uneducated...... workers as well as immigrants and natives differently, creating different incentives to acquire education for the two groups. Using rich Danish administrative data, this paper finds suggestive evidence rejecting the theoretical case where negative attitudes decrease 1st generation immigrant education...... and indications that quality of networks seems to matter more for immigrants than the quantity of individuals in a potential network....

MIMO Communication for Cellular Networks

CERN Document Server

Huang, Howard; Venkatesan, Sivarama

2012-01-01

As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

An Optimal Path Computation Architecture for the Cloud-Network on Software-Defined Networking

Directory of Open Access Journals (Sweden)

Hyunhun Cho

2015-05-01

Full Text Available Legacy networks do not open the precise information of the network domain because of scalability, management and commercial reasons, and it is very hard to compute an optimal path to the destination. According to today’s ICT environment change, in order to meet the new network requirements, the concept of software-defined networking (SDN has been developed as a technological alternative to overcome the limitations of the legacy network structure and to introduce innovative concepts. The purpose of this paper is to propose the application that calculates the optimal paths for general data transmission and real-time audio/video transmission, which consist of the major services of the National Research & Education Network (NREN in the SDN environment. The proposed SDN routing computation (SRC application is designed and applied in a multi-domain network for the efficient use of resources, selection of the optimal path between the multi-domains and optimal establishment of end-to-end connections.

Neural Network for Sparse Reconstruction

Directory of Open Access Journals (Sweden)

Qingfa Li

2014-01-01

Full Text Available We construct a neural network based on smoothing approximation techniques and projected gradient method to solve a kind of sparse reconstruction problems. Neural network can be implemented by circuits and can be seen as an important method for solving optimization problems, especially large scale problems. Smoothing approximation is an efficient technique for solving nonsmooth optimization problems. We combine these two techniques to overcome the difficulties of the choices of the step size in discrete algorithms and the item in the set-valued map of differential inclusion. In theory, the proposed network can converge to the optimal solution set of the given problem. Furthermore, some numerical experiments show the effectiveness of the proposed network in this paper.

Adaptation in Food Networks: Theoretical Framework and Empirical Evidences

Directory of Open Access Journals (Sweden)

Gaetano Martino

2013-03-01

Full Text Available The paper concerns the integration in food networks under a governance point of view. We conceptualize the integration processes in terms of the adaptation theory and focus the issues related under a transaction cost economics perspective. We conjecture that the allocation of decisions rights between the parties to a transaction is a key instrument in order to cope with the sources of basic uncertainty in food networks: technological innovation, sustainability strategies, quality and safety objectives. Six case studies are proposed which contribute to corroborate our conjecture. Managerial patters based on a joint decision approach also are documented

Networked Identities

DEFF Research Database (Denmark)

Ryberg, Thomas; Larsen, Malene Charlotte

2008-01-01

of CoPs we shall argue that the metaphor or theory of networked learning is itself confronted with some central tensions and challenges that need to be addressed. We then explore these theoretical and analytic challenges to the network metaphor, through an analysis of a Danish social networking site. We......In this article we take up a critique of the concept of Communities of Practice (CoP) voiced by several authors, who suggest that networks may provide a better metaphor to understand social forms of organisation and learning. Through a discussion of the notion of networked learning and the critique...... argue that understanding meaning-making and ‘networked identities’ may be relevant analytic entry points in navigating the challenges....

Graph Theoretical Analysis of Network Centric Operations Using Multi-Layer Models

National Research Council Canada - National Science Library

Wong-Jiru, Ann

2006-01-01

.... The research incorporates the importance of understanding network topology for evaluating an environment for net-centricity and using network characteristics to help commanders assess the effects...

The management of complex system innovations. A theoretic approach to network formation and critical success factor identification using the case of fuel cell vehicles

Energy Technology Data Exchange (ETDEWEB)

Venghaus, Sandra

2011-07-01

Given the economic, ecological and social importance of automotive transportation, the development of alternative fueling and propulsion technologies requires a wise and sustainable political course of action. Not least the public debate on the impact of transport emissions on climate change and the call for limits to automotive CO-2-emissions reflect the relevance of the topic. In the search for innovative alternatives to the conventional gasoline or diesel propulsion technology, electromobility and hydrogen-based fuel cell vehicles constitute the two most widely discussed long-term options. The market introduction of fuel cell vehicles serves as an expedient example of a highly complex system innovation (CSI), which requires the cooperation of a variety of actors from formerly independent economic sectors in order to overcome the significant barriers to market entry. As will be discussed, such CSI can only be successfully implemented in an environment, within which the complexity-induced knowledge gap is reduced by a systematic exchange of information with respect to both the critical success factors identified by each of the involved stakeholders as well as their cooperation needs and expectations. Given this challenge, a framework is developed, which serves as the basis for a structured dialogue among the multiple stakeholders involved in the development process of a complex system innovation. The framework can thus best be classified as a corporate moderation and decision-support tool to achieve transparency in and impose structure on complex contexts. Methodically, the presented thesis addresses the development of a holistic approach to the management of complex system innovations from two perspectives: (1) a theoretical perspective of analyzing underlying structures and processes of CSI management (i.e., the CSI Management Framework), as well as (2) the development of a strategic approach for the practical implementation of CSI management in complex networks

Enhancing social networks: a qualitative study of health and social care practice in UK mental health services.

Science.gov (United States)

Webber, Martin; Reidy, Hannah; Ansari, David; Stevens, Martin; Morris, David

2015-03-01

People with severe mental health problems such as psychosis have access to less social capital, defined as resources within social networks, than members of the general population. However, a lack of theoretically and empirically informed models hampers the development of social interventions which seek to enhance an individual's social networks. This paper reports the findings of a qualitative study, which used ethnographic field methods in six sites in England to investigate how workers helped people recovering from psychosis to enhance their social networks. This study drew upon practice wisdom and lived experience to provide data for intervention modelling. Data were collected from 73 practitioners and 51 people who used their services in two phases. Data were selected and coded using a grounded theory approach to depict the key themes that appeared to underpin the generation of social capital within networks. Findings are presented in four over-arching themes - worker skills, attitudes and roles; connecting people processes; role of the agency; and barriers to network development. The sub-themes which were identified included worker attitudes; person-centred approach; equality of worker-individual relationship; goal setting; creating new networks and relationships; engagement through activities; practical support; existing relationships; the individual taking responsibility; identifying and overcoming barriers; and moving on. Themes were consistent with recovery models used within mental health services and will provide the basis for the development of an intervention model to enhance individuals' access to social capital within networks. © 2014 John Wiley & Sons Ltd.

Bioethics networks and reproduction technologies: theoretical and methodological controversies - DOI: 10.3395/reciis.v1i2.87en

Directory of Open Access Journals (Sweden)

Rosa Maria Leite Pedro

2007-12-01

Full Text Available The object of this paper is to discuss some of the theoretical and methodological controversies surrounding the emerging field of bioethics, especially focusing on reproduction biotechnologies, attempting to give some examples of its implications as a network of controversies. Initially, it presents the new reproduction biotechnologies in terms of the effect which they are producing on our understanding about human nature and life, as well as the context of the emergence of bioethics, traditionally conceived of as a critical and analytical example of the relationship between technology and humanity. As an alternative way of explaining these relationships, it outlines the aspect of bioethics as a network effect, in which the technology-society hybrid is shown both in the building of bioethical norms and in the instabilities which challenge these norms. As a way of understanding this heterogeneous and complex network, Controversy Analysis is proposed as a methodological tool. In order to illustrate the richness of such perspective, a brief empirical study is presented, in which an attempt is made to track controversies articulated around the relations between bioethics and reproduction biotechnologies, with a specific focus on stem cell research, as published by the on-line media from January of 2004 until July of 2006, raising questions about subjects such as: life, humanity, artifice and autonomy.

Network public goods with asymmetric information about cooperation preferences and network degree

NARCIS (Netherlands)

Dijkstra, Jacob; van Assen, Marcus

2013-01-01

We propose a game theoretical model of one-shot network public goods formalizing the 'closure argument' that cooperation is more frequent in denser groups or networks. Equilibrium analyses show that (i) an 'inefficiency problem' exists: players all preferring mutual cooperation need not all

Predictive minimum description length principle approach to inferring gene regulatory networks.

Science.gov (United States)

Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

2011-01-01

Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

Implementation of the Brazilian radiation metrology network

International Nuclear Information System (INIS)

Ramos, Manoel M.O.; Araujo, Margareth M. de

1998-01-01

The ever increasing need for calibration of survey, personal, and contamination meters in Brazil are not completely satisfied by the two operating laboratories. To overcome this deficiency a radiation metrology network is being implemented with the support of IAEA. In a near future this network will count other three calibration laboratories which are being installed in different regions of the country, and accredited through INMETRO. (author)

Social exchange : Relations and networks

NARCIS (Netherlands)

Dijkstra, Jacob

2015-01-01

In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network

Exploring continuous organisational transformation as a form of network interdependence

OpenAIRE

Stebbings, H; Braganza, A

2008-01-01

In this paper we examine the problematic area of continuous transformation. We conduct our analysis from three theoretical perspectives: the resource based view, social network theory, and stakeholder theory. We found that the continuous transformation can be explained through the concept of Network Interdependence. This paper describes Network Interdependence and develops theoretical propositions from a synthesis of the three theories. Our contribution of Network Interdependence offers f...

The Photograph as Network

DEFF Research Database (Denmark)

Wiegand, Frauke Katharina

2017-01-01

Inspired by actor-network theory (ANT), this article develops a theoretical framework to grasp the dynamic visual work of memory. It introduces three sensitizing concepts of actor-network methodology, namely entanglement, relationality and traceability, and operationalizes them in a methodological...

The Role of Trust in Costly Network Formation

NARCIS (Netherlands)

Gilles, R.P.; Sarangi, S.

2003-01-01

We consider game theoretic models of social network formation.In this paper we limit our investigation to game theoretic models of network formation that are based on individual actions only.Our approach is based on three simple and realistic principles: (1) Link formation is a binary process of

Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank

OpenAIRE

Zhao, Liang; Liao, Siyu; Wang, Yanzhi; Li, Zhe; Tang, Jian; Pan, Victor; Yuan, Bo

2017-01-01

Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks. Empirical results have shown that neural networks with weight matrices of LDR matrices, referred as LDR neural networks, can achieve significant reduction in space and computational complexity while retaining high accuracy. We formally study LDR matrices in deep learning. First, we prove the universal approximation property of LDR neural networks with a ...

Novel Holistic Approaches for Overcoming Therapy Resistance in Pancreatic and Colon Cancers.

Science.gov (United States)

Sarkar, Fazlul H

2016-01-01

Gastrointestinal (GI) cancers, such as of the colon and pancreas, are highly resistant to both standard and targeted therapeutics. Therapy-resistant and heterogeneous GI cancers harbor highly complex signaling networks (the resistome) that resist apoptotic programming. Commonly used gemcitabine or platinum-based regimens fail to induce meaningful (i.e. disease-reversing) perturbations in the resistome, resulting in high rates of treatment failure. The GI cancer resistance networks are, in part, due to interactions between parallel signaling and aberrantly expressed microRNAs (miRNAs) that collectively promote the development and survival of drug-resistant cancer stem cells with epithelial-to-mesenchymal transition (EMT) characteristics. The lack of understanding of the resistance networks associated with this subpopulation of cells as well as reductionist, single protein-/pathway-targeted approaches have made 'effective drug design' a difficult task. We propose that the successful design of novel therapeutic regimens to target drug-resistant GI tumors is only possible if network-based drug avenues and agents, in particular 'natural agents' with no known toxicity, are correctly identified. Natural agents (dietary agents or their synthetic derivatives) can individually alter miRNA profiles, suppress EMT pathways and eliminate cancer stem-like cells that derive from pancreatic cancer and colon cancer, by partially targeting multiple yet meaningful networks within the GI cancer resistome. However, the efficacy of these agents as combinations (e.g. consumed in the diet) against this resistome has never been studied. This short review article provides an overview of the different challenges involved in the understanding of the GI resistome, and how novel computational biology can help in the design of effective therapies to overcome resistance. © 2015 S. Karger AG, Basel.

Towards overcoming poor readership and building reading culture ...

African Journals Online (AJOL)

Towards overcoming poor readership and building reading culture of in schools. ... of this paper is to find strategies that can overcome poor readership in schools. ... Keywords: English First Additional Language, Writing Skills, Spelling Errors, ...

Network Formation under the Threat of Disruption

NARCIS (Netherlands)

Hoyer, B.

2013-01-01

The studies in this thesis are focused on the impact the presence of a network disruptor has on network formation models. In particular, we build two theoretical models to study the effect of network disruption on network formation and test the effect network disruption has on equilibrium selection

Replicability and generalizability of PTSD networks

DEFF Research Database (Denmark)

Eiko I., Fried; Eidhof, Marloes B.; Palic, Sabina

2018-01-01

The growing literature conceptualizing mental disorders like Posttraumatic Stress Disorder (PTSD) as networks of interacting symptoms faces three key challenges. Prior studies predominantly used (a) small samples with low power for precise estimation, (b) non-clinical samples, and (c) single...... samples. This renders network structures in clinical data, and the extent to which networks replicate across datasets, unknown. To overcome these limitations, the present cross-cultural multisite study estimated regularized partial correlation networks of 16 PTSD symptoms across four datasets...... of traumatized patients receiving treatment for PTSD (total N=2,782). Despite differences in culture, trauma-type and severity of the samples, considerable similarities emerged, with moderate to high correlations between symptom profiles (0.43-0.82), network structures (0.62-0.74), and centrality estimates (0...

Optimization in a Networked Economy

Directory of Open Access Journals (Sweden)

Ahmet Sekreter

2017-10-01

Full Text Available An age of network has been living for the last decades. The information technologies have been used by hundreds of millions of users. These technologies are enabling to connect businesses and economic activities. One of the characteristics of the networked economy is the amount of data that produced due to the interlinking of firms, individuals, processes by businesses, and economic activities. Another issue with the networked economy is the complexity of the data. Extraction of the knowledge from the networked economy has challenges by the traditional approach since data is large scale, second decentralized, and third they connect many heterogeneous agents. The challenges can be overcome by the new optimization methods including human element or the social interactions with technological infrastructure.

Vulnerability of network of networks

Science.gov (United States)

Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.

2014-10-01

Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.

Convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks

Science.gov (United States)

Long, Yin; Zhang, Xiao-Jun; Wang, Kui

2018-05-01

In this paper, convergence and approximate calculation of average degree under different network sizes for decreasing random birth-and-death networks (RBDNs) are studied. First, we find and demonstrate that the average degree is convergent in the form of power law. Meanwhile, we discover that the ratios of the back items to front items of convergent reminder are independent of network link number for large network size, and we theoretically prove that the limit of the ratio is a constant. Moreover, since it is difficult to calculate the analytical solution of the average degree for large network sizes, we adopt numerical method to obtain approximate expression of the average degree to approximate its analytical solution. Finally, simulations are presented to verify our theoretical results.

Replicability and Generalizability of Posttraumatic Stress Disorder (PTSD) Networks

DEFF Research Database (Denmark)

Fried, Eiko I.; Eidhof, Marloes B.; Palic, Sabina

2018-01-01

. This renders network structures in clinical data, and the extent to which networks replicate across data sets, unknown. To overcome these limitations, the present cross-cultural multisite study estimated regularized partial correlation networks of 16 PTSD symptoms across four data sets of traumatized patients...... discuss the importance of future replicability efforts to improve clinical psychological science and provide code, model output, and correlation matrices to make the results of this article fully reproducible....

Cloud-based Networked Visual Servo Control

OpenAIRE

Wu, Haiyan; Lu, Lei; Chen, Chih-Chung; Hirche, Sandra; Kühnlenz, Kolja

2013-01-01

The performance of vision-based control systems, in particular of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitti...

Epidemiologic Considerations in Network Modeling of Theoretical Disease Events

National Research Council Canada - National Science Library

Lem, Marcus

2006-01-01

.... Network analysis has shown utility in the study of a range of communicable disease outbreaks affecting both health and commerce, including SARS, tuberculosis, syphilis and foot-and mouth-disease...

The Deep Structure of Organizational Online Networking

DEFF Research Database (Denmark)

Trier, Matthias; Richter, Alexander

2015-01-01

While research on organizational online networking recently increased significantly, most studies adopt quantitative research designs with a focus on the consequences of social network configurations. Very limited attention is paid to comprehensive theoretical conceptions of the complex phenomenon...... of organizational online networking. We address this gap by adopting a theoretical framework of the deep structure of organizational online networking with a focus on their emerging meaning for the employees. We apply and assess the framework in a qualitative case study of a large-scale implementation...... of a corporate social network site (SNS) in a global organization. We reveal organizational online networking as a multi-dimensional phenomenon with multiplex relationships that are unbalanced, primarily consist of weak ties and are subject to temporal change. Further, we identify discourse drivers...

Cognitive wireless networks

CERN Document Server

Feng, Zhiyong; Zhang, Ping

2015-01-01

This brief examines the current research in cognitive wireless networks (CWNs). Along with a review of challenges in CWNs, this brief presents novel theoretical studies and architecture models for CWNs, advances in the cognitive information awareness and delivery, and intelligent resource management technologies. The brief presents the motivations and concepts of CWNs, including theoretical studies of temporal and geographic distribution entropy as well as cognitive information metrics. A new architecture model of CWNs is proposed with theoretical, functional and deployment architectures suppo

Overcoming Absence

DEFF Research Database (Denmark)

Paldam, Camilla Skovbjerg

2017-01-01

In this chapter, I address the rhetoric of modern love correspondence – its various purposes, modes of communication, and meta-reflections on writing and media – from the beginning of the 20th century till today. I analyze how love and the beloved are mediated in the articulated desire and longing...... of love letters, and how love letters are used as a medium to overcome absence. I also reflect on the material status of love letters in relation to the technological development and subsequently the replacement of traditional letters by their digital counterparts such as email, text messages and real...

Challenges of Integrating NASA's Space Communications Networks

Science.gov (United States)

Reinert, Jessica; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Challenges of Integrating NASAs Space Communication Networks

Science.gov (United States)

Reinert, Jessica M.; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Psychotherapy Integration via Theoretical Unification

Directory of Open Access Journals (Sweden)

Warren W. Tryon

2017-01-01

Full Text Available Meaningful psychotherapy integration requires theoretical unification because psychotherapists can only be expected to treat patients with the same diagnoses similarly if they understand these disorders similarly and if they agree on the mechanisms by which effective treatments work. Tryon (in press has proposed a transtheoretic transdiagnostic psychotherapy based on an Applied Psychological Science (APS clinical orientation, founded on a BioPsychology Network explanatory system that provides sufficient theoretical unification to support meaningful psychotherapy integration. That proposal focused mainly on making a neuroscience argument. This article makes a different argument for theoretical unification and consequently psychotherapy integration. The strength of theories of psychotherapy, like all theory, is to focus on certain topics, goals, and methods. But this strength is also a weakness because it can blind one to alternative perspectives and thereby promote unnecessary competition among therapies. This article provides a broader perspective based on learning and memory that is consistent with the behavioral, cognitive, cognitive-behavioral, psychodynamic, pharmacologic, and Existential/Humanistic/Experiential clinical orientations. It thereby provides a basis for meaningful psychotherapy integration.

A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks

Science.gov (United States)

Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie

2014-01-01

The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171

A distribution network review

International Nuclear Information System (INIS)

Fairbairn, R.J.; Maunder, D.; Kenyon, P.

1999-01-01

This report summarises the findings of a study reviewing the distribution network in England, Scotland and Wales to evaluate its ability to accommodate more embedded generation from both fossil fuel and renewable energy sources. The background to the study is traced, and descriptions of the existing electricity supply system, the licence conditions relating to embedded generation, and the effects of the Review of Electricity Trading Arrangements are given. The ability of the UK distribution networks to accept embedded generation is examined, and technical benefits/drawbacks arising from embedded generation, and the potential for uptake of embedded generation technologies are considered. The distribution network capacity and the potential uptake of embedded generation are compared, and possible solutions to overcome obstacles are suggested. (UK)

A distribution network review

Energy Technology Data Exchange (ETDEWEB)

Fairbairn, R.J.; Maunder, D.; Kenyon, P.

1999-07-01

This report summarises the findings of a study reviewing the distribution network in England, Scotland and Wales to evaluate its ability to accommodate more embedded generation from both fossil fuel and renewable energy sources. The background to the study is traced, and descriptions of the existing electricity supply system, the licence conditions relating to embedded generation, and the effects of the Review of Electricity Trading Arrangements are given. The ability of the UK distribution networks to accept embedded generation is examined, and technical benefits/drawbacks arising from embedded generation, and the potential for uptake of embedded generation technologies are considered. The distribution network capacity and the potential uptake of embedded generation are compared, and possible solutions to overcome obstacles are suggested. (UK)

A probabilistic approach to identify putative drug targets in biochemical networks.

NARCIS (Netherlands)

Murabito, E.; Smalbone, K.; Swinton, J.; Westerhoff, H.V.; Steuer, R.

2011-01-01

Network-based drug design holds great promise in clinical research as a way to overcome the limitations of traditional approaches in the development of drugs with high efficacy and low toxicity. This novel strategy aims to study how a biochemical network as a whole, rather than its individual

Adaptive control using neural networks and approximate models.

Science.gov (United States)

Narendra, K S; Mukhopadhyay, S

1997-01-01

The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods are used for realizing the neural controllers to overcome computational complexity. In this paper, we introduce two classes of models which are approximations to the NARMA model, and which are linear in the control input. The latter fact substantially simplifies both the theoretical analysis as well as the practical implementation of the controller. Extensive simulation studies have shown that the neural controllers designed using the proposed approximate models perform very well, and in many cases even better than an approximate controller designed using the exact NARMA model. In view of their mathematical tractability as well as their success in simulation studies, a case is made in this paper that such approximate input-output models warrant a detailed study in their own right.

On the Need of Novel Medium Access Control Schemes for Network Coding enabled Wireless Mesh Networks

DEFF Research Database (Denmark)

Paramanathan, Achuthan; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani

2013-01-01

that network coding will improve the throughput in such systems, but our novel medium access scheme improves the performance in the cross topology by another 66 % for network coding and 150 % for classical forwarding in theory. These gains translate in a theoretical gain of 33 % of network coding over...

Modelling the phonotactic structure of natural language words with simple recurrent networks

NARCIS (Netherlands)

Stoianov, [No Value; Nerbonne, J; Bouma, H; Coppen, PA; vanHalteren, H; Teunissen, L

1998-01-01

Simple Recurrent Networks (SRN) are Neural Network (connectionist) models able to process natural language. Phonotactics concerns the order of symbols in words. We continued an earlier unsuccessful trial to model the phonotactics of Dutch words with SRNs. In order to overcome the previously reported

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

Science.gov (United States)

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

Remote but Not Removed: Professional Networks That Support Rural Educators

Science.gov (United States)

Parsley, Danette

2018-01-01

The Northwest Rural Innovation and Student Engagement (NW RISE) Network connects rural educators in the Pacific Northwest to help them succeed in the profession and overcome the challenges caused by teacher isolation. In this article, the author takes stock of what was learned in the four years since the network was established. She also shares…

Department of Theoretical Physics - Overview

International Nuclear Information System (INIS)

Kwiecinski, J.

2000-01-01

Full text: Research activity of the Department of Theoretical Physics concerns theoretical high-energy and elementary particle physics, intermediate energy particle physics, theoretical nuclear physics, theory of nuclear matter, theory of quark-gluon plasma and of relativistic heavy-ion collisions, theoretical astrophysics and general physics. There is some emphasis on the phenomenological applications of the theoretical research, yet the more formal problems are also considered. The detailed summary of the research projects and of the results obtained in various fields is given in the abstracts. Our Department actively collaborates with other Departments of the Institute as well as with several scientific institutions both in Poland and abroad. In particular members of our Department participate in the EC network which allows mobility of researchers. Several members of our Department have also participated in the research projects funded by the Polish Committee for Scientific Research (KBN). The complete list of grants is listed separately. Besides pure research, members of our Department are also involved in graduate and undergraduate teaching activity both at our Institute as well as at other academic institutions in Cracow. At present five students are working for their Ph.D. or MSc degrees under supervision of the senior members from the Department. We continue our participation at the EC SOCRATES-ERASMUS educational programme which allows exchange of graduate students between our Department and the Department of Physics of the University of Durham in the UK. (author)

Rational function systems and electrical networks with multiparameters

CERN Document Server

Lu, KaiSheng

2012-01-01

To overcome the problems of system theory and network theory over real field, this book uses matrices over the field F(z) of rational functions in multiparameters describing coefficient matrices of systems and networks and makes systems and network description over F(z) and researches their structural properties: reducible condition of a class of matrices over F(z) and their characteristic polynomial; type1 matrix and two basic properties; variable replacement conditions for independent parameters; structural controllability and observability of linear systems over F(z); separability, reducibi

A THEORETICAL MODEL OF SUPPORTING OPEN SOURCE FRONT END INNOVATION THROUGH IDEA MANAGEMENT

DEFF Research Database (Denmark)

Aagaard, Annabeth

2013-01-01

to overcome these various challenges companies are looking for new models to support FEI. This theoretical paper explores in what way idea management may be applied as a tool in facilitation of front end innovation and how this facilitation may be captured in a conceptual model. First, I show through...... a literature study, how idea management and front end innovation are related and how they may support each other. Secondly, I present a theoretical model of how idea management may be applied in support of the open source front end of new product innovations. Thirdly, I present different venues of further...... exploration of active facilitation of open source front end innovation through idea management....

Evaluation and Simulation of Common Video Conference Traffics in Communication Networks

Directory of Open Access Journals (Sweden)

Farhad faghani

2014-01-01

Full Text Available Multimedia traffics are the basic traffics in data communication networks. Especially Video conferences are the most desirable traffics in huge networks(wired, wireless, …. Traffic modeling can help us to evaluate the real networks. So, in order to have good services in data communication networks which provide multimedia services, QoS will be very important .In this research we tried to have an exact traffic model design and simulation to overcome QoS challenges. Also, we predict bandwidth by Kalman filter in Ethernet networks.

Networks, Micro Small Enterprises (MSE'S) and Performance: the ...

African Journals Online (AJOL)

Networks, Micro Small Enterprises (MSE'S) and Performance: the Case of Kenya. ... It adopts the network perspective theoretical approach. Empirically, the ... entrepreneurial personal network as a copying strategy in the process of global

Towards integrating control and information theories from information-theoretic measures to control performance limitations

CERN Document Server

Fang, Song; Ishii, Hideaki

2017-01-01

This book investigates the performance limitation issues in networked feedback systems. The fact that networked feedback systems consist of control and communication devices and systems calls for the integration of control theory and information theory. The primary contributions of this book lie in two aspects: the newly-proposed information-theoretic measures and the newly-discovered control performance limitations. We first propose a number of information notions to facilitate the analysis. Using those notions, classes of performance limitations of networked feedback systems, as well as state estimation systems, are then investigated. In general, the book presents a unique, cohesive treatment of performance limitation issues of networked feedback systems via an information-theoretic approach. This book is believed to be the first to treat the aforementioned subjects systematically and in a unified manner, offering a unique perspective differing from existing books.

A sign-theoretic approach to biotechnology

DEFF Research Database (Denmark)

Bruni, Luis Emilio

” semiotic networks across hierarchical levels and for relating the different emergent codes in living systems. I consider this an important part of the work because there I define some of the main concepts that will help me to analyse different codes and semiotic processes in living systems in order...... to exemplify what is the relevance of a sign-theoretic approach to biotechnology. In particular, I introduce the notion of digital-analogical consensus as a semiotic pattern for the creation of complex logical products that constitute specific signs. The chapter ends with some examples of conspicuous semiotic...... to exemplify how a semiotic approach can be of help when organising the knowledge that can lead us to understanding the relevance, the role and the position of signal transduction networks in relation to the larger semiotic networks in which they function, i.e.: in the hierarchical formal processes of mapping...

Network Experiences Lead to the Adaption of a Firm’s Network Competence

Directory of Open Access Journals (Sweden)

Bianka Kühne

2011-12-01

Full Text Available Networks become increasingly important as external sources of innovation for firms. Through networks firms get incontact with different actors with whom they can exchange information and collaborate. A firm’s ability to be asuccessful network actor depends on its network competence. This term can be defined as having the necessaryknowledge, skills and qualifications for networking as well as using them effectively. In this paper we investigate thelink between a firm’s network competence and the benefits resulting from it in a two‐way direction. First, thenetwork competence of the firm facilitates the adoption of information from other network actors which may leadto innovation success. Second the perceived network benefits shall in their turn influence the network competenceof the firm. Consequently, firms will adapt their network strategy corresponding their experiences. The objective ofthis paper is to investigate the dynamics of networking and its influence on the firm’s network competence. For thisexploratory research 3 Belgian networks are examined. In‐depth interviews are used in combination with semistructuredinterview guides to conduct the research. Our results indicate that some firms perceive benefits fromtheir network efforts, for others it is more a burden. Furthermore, in some of our cases we found that positiveexperiences with clear benefits motivate the firm to enhance its network competence. This is illustrated by the factthat collaborations are more frequently initiated, trust is more easily build, firms are more open to communicateinformation and the confidentiality threshold is overcome.

Why Mondragon? Analyzing What Works in Overcoming Inequalities

Science.gov (United States)

Redondo, Gisela; Santa Cruz, Ignacio; Rotger, Josep Maria

2011-01-01

Research using the critical communicative methodology (CCM) aims to identify the elements that help overcome inequalities. Drawing on research on the Basque Mondragon Corporation (MC), the authors focus on two major elements such as, selecting research cases that have been shown to succeed in overcoming inequalities, and communicative data…

Computer Network Attack Versus Operational Maneuver from the Sea

National Research Council Canada - National Science Library

Herdegen, Dale

2000-01-01

...) vulnerable to computer network attack (CNA). Mission command and control can reduce the impact of the loss of command and control, but it can not overcome the vast and complex array of threats...

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

Directory of Open Access Journals (Sweden)

Kim Man-Sun

2012-05-01

Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

A theoretical design for learning model addressing the networked society

DEFF Research Database (Denmark)

Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm

2010-01-01

The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...

TMAC: Timestamp-Ordered MAC Protocol for Wireless Mesh Networks

KAUST Repository

Nawab, Faisal

2011-05-01

Wireless Mesh Networks (WMNs) have emerged to meet a need for a self-organized and self-configured multi-hop wireless network infrastructure. Low cost infrastructure and ease of deployment have made WMNs an attractive technology for last mile access. However, 802.11 based WMNs are subject to serious fairness issues. With backlogged TCP traffic, nodes which are two or more hops away from the gateway are subject to starvation, while the one-hop away node saturates the channel with its own local traffic. We study the interactions of TCP and IEEE 802.11 MAC in WMNs to aid us in understanding and overcoming the unfairness problem. We propose a Markov chain to capture the behavior of TCP sessions, particularly the impact on network throughput performance due to the effect of queue utilization and packet relaying. A closed form solution is derived to numerically derive the throughput. Based on the developed model, we propose a distributed MAC protocol called Timestamp-ordered MAC (TMAC), aiming to alleviate the unfairness problem in WMNs via a manipulative per-node scheduling mechanism which takes advantage of the age of each packet as a priority metric. Simulation is conducted to validate our model and to illustrate the fairness characteristics of TMAC. Our results show that TMAC achieves excellent resource allocation fairness while maintaining above 90% of maximum link capacity in parking lot and large grid topologies. Our work illuminates the factors affecting TCP fairness in WMNs. Our theoretical and empirical findings can be used in future research to develop more fairness-aware protocols for WMNs.

Overcoming weak intrinsic depolarizing resonances with energy-jump

International Nuclear Information System (INIS)

Huang, H.; Ahrens, L.; Alessi, J.G.

1997-01-01

In the recent polarized proton runs in the AGS, a 5% partial snake was used successfully to overcome the imperfection depolarizing resonances. Polarized proton beam was accelerated up to the required RHIC injection energy of 25 GeV. However, significant amount of polarization was lost at 0+ν y , 12+ν y and 36+ν y , which is believed to be partially due to the coupling resonances. To overcome the coupling resonance, an energy-jump was generated by rapidly changing the beam circumference using the powerful AGS rf system. It clearly demonstrates that the novel energy-jump method can successfully overcome coupling resonances and weak intrinsic resonances

Immunization of Epidemics in Multiplex Networks

Science.gov (United States)

Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo

2014-01-01

Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks. PMID:25401755

Immunization of epidemics in multiplex networks.

Science.gov (United States)

Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo

2014-01-01

Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.

Wireless mesh networks.

Science.gov (United States)

Wang, Xinheng

2008-01-01

Wireless telemedicine using GSM and GPRS technologies can only provide low bandwidth connections, which makes it difficult to transmit images and video. Satellite or 3G wireless transmission provides greater bandwidth, but the running costs are high. Wireless networks (WLANs) appear promising, since they can supply high bandwidth at low cost. However, the WLAN technology has limitations, such as coverage. A new wireless networking technology named the wireless mesh network (WMN) overcomes some of the limitations of the WLAN. A WMN combines the characteristics of both a WLAN and ad hoc networks, thus forming an intelligent, large scale and broadband wireless network. These features are attractive for telemedicine and telecare because of the ability to provide data, voice and video communications over a large area. One successful wireless telemedicine project which uses wireless mesh technology is the Emergency Room Link (ER-LINK) in Tucson, Arizona, USA. There are three key characteristics of a WMN: self-organization, including self-management and self-healing; dynamic changes in network topology; and scalability. What we may now see is a shift from mobile communication and satellite systems for wireless telemedicine to the use of wireless networks based on mesh technology, since the latter are very attractive in terms of cost, reliability and speed.

Coping strategy and its theoretical foundations to promote physical education in preschool education in the Day Care Center

Directory of Open Access Journals (Sweden)

Rasciel de la Caridad Zayas Acosta

2010-12-01

Full Text Available With the present work is intended to address the difficulties of management of child circle that finds its causes in the limitations that exist in the theoretical order as in the methodological and practical, due to deficiencies in their training and the inadequacies of its improvement to the development of Physical Education in Early Childhood Education. For this purpose was deemed necessary to determine the theoretical foundations necessary to incorporate in overcoming managers to guide their teachers in achieving their development are.

Social exchange: Relations and networks

OpenAIRE

Dijkstra, Jacob

2015-01-01

In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network research. The paper provides an accessible entry into the literature on social exchange.

Preventing Wormhole Attacks on Wireless Ad Hoc Networks: A Graph Theoretic Approach

National Research Council Canada - National Science Library

Lazos, L; Poovendran, Radha; Meadows, C; Syverson, P; Chang, L. W

2005-01-01

We study the problem of characterizing the wormhole attack, an attack that can be mounted on a wide range of wireless network protocols without compromising any cryptographic quantity or network node...

A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.

Science.gov (United States)

Sillin, Henry O; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K

2013-09-27

Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.

Scalable High-Performance Parallel Design for Network Intrusion Detection Systems on Many-Core Processors

OpenAIRE

Jiang, Hayang; Xie, Gaogang; Salamatian, Kavé; Mathy, Laurent

2013-01-01

Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. Both hardware accelerated and parallel software-based NIDS solutions, based on commodity multi-core and GPU processors, have been proposed to overcome these challenges. Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. ...

Bidirectional selection between two classes in complex social networks.

Science.gov (United States)

Zhou, Bin; He, Zhe; Jiang, Luo-Luo; Wang, Nian-Xin; Wang, Bing-Hong

2014-12-19

The bidirectional selection between two classes widely emerges in various social lives, such as commercial trading and mate choosing. Until now, the discussions on bidirectional selection in structured human society are quite limited. We demonstrated theoretically that the rate of successfully matching is affected greatly by individuals' neighborhoods in social networks, regardless of the type of networks. Furthermore, it is found that the high average degree of networks contributes to increasing rates of successful matches. The matching performance in different types of networks has been quantitatively investigated, revealing that the small-world networks reinforces the matching rate more than scale-free networks at given average degree. In addition, our analysis is consistent with the modeling result, which provides the theoretical understanding of underlying mechanisms of matching in complex networks.

TYPICAL BANKING CRISES INTERNATIONAL BUSINESS ENVIRONMENT AND WAYS TO OVERCOME THEM

Directory of Open Access Journals (Sweden)

Ion Gr. IONESCU

2014-06-01

Full Text Available International financial environment is characterized as consisting of free trade and especially from the free movement of the capital on the financial markets, so very favourable, which also led to the rapid development of global financial markets. We lack the ability to keep the peace (silence for to counter the excesses of the financial markets. Without this ability, the global economy is exposed to the collapse. Financial capital enjoys a privileged position. He is more mobile than other factors of production and even more mobile than direct investment. Yet crises must be overcome. To support the arguments of this paper, we use a flexible methodology, starting from simple to complex, from theoretical to practical, from principle, to particularly, adding, specialty practice examples, from the international sphere, convinced that work-international banking must be healthy, able to generate profitable and dynamic business environments, safe for entrepreneurs and bankers, but also ordinary people.

SEMANTIC NETWORKS: THEORETICAL, TECHNICAL, METHODOLOGIC AND ANALYTICAL ASPECTS

Directory of Open Access Journals (Sweden)

José Ángel Vera Noriega

2005-09-01

Full Text Available This work is a review of the methodological procedures and cares for the measurement of the connotative meanings which will be used in the elaboration of instruments with ethnic validity. Beginning from the techniques originally proposed by Figueroa et al. (1981 and later described by Lagunes (1993, the intention is to offer a didactic panorama to carry out the measurement by semantic networks introducing some recommendations derived from the studies performed with this method.

International network competition

OpenAIRE

Tangerås, Thomas P.; Tåg, Joacim

2014-01-01

We analyse network competition in a market with international calls. National regulatory agencies (NRAs) have incentives to set regulated termination rates above marginal cost to extract rent from international call termination. International network ownership and deregulation are alternatives to combat the incentives of NRAs to distort termination rates. We provide conditions under which each of these policies increase efficiency and aggregate welfare. Our findings provide theoretical suppor...

Immunization of epidemics in multiplex networks.

Directory of Open Access Journals (Sweden)

Dawei Zhao

Full Text Available Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted immunization and layer node-based random (targeted immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF networks.

Solidarity Networks: What Are They? And Why Should We Care?

Science.gov (United States)

Smith, Janel

2009-01-01

Purpose: The purpose of this paper is to investigate the theoretical foundations of the solidarity network concept and its perceived utility as an enabling force for social organizations to influence change. The theoretical framework presented is intended to stimulate dialogue, interest and investigation on the subject of solidarity networks.…

Statistical mechanics of complex networks

CERN Document Server

Rubi, Miguel; Diaz-Guilera, Albert

2003-01-01

Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

Overcoming barriers in care for the dying: Theoretical analysis of an innovative program model.

Science.gov (United States)

Wallace, Cara L

2016-08-01

This article explores barriers to end-of-life (EOL) care (including development of a death denying culture, ongoing perceptions about EOL care, poor communication, delayed access, and benefit restrictions) through the theoretical lens of symbolic interactionism (SI), and applies general systems theory (GST) to a promising practice model appropriate for addressing these barriers. The Compassionate Care program is a practice model designed to bridge gaps in care for the dying and is one example of a program offering concurrent care, a recent focus of evaluation though the Affordable Care Act. Concurrent care involves offering curative care alongside palliative or hospice care. Additionally, the program offers comprehensive case management and online resources to enrollees in a national health plan (Spettell et al., 2009).SI and GST are compatible and interrelated theories that provide a relevant picture of barriers to end-of-life care and a practice model that might evoke change among multiple levels of systems. These theories promote insight into current challenges in EOL care, as well as point to areas of needed research and interventions to address them. The article concludes with implications for policy and practice, and discusses the important role of social work in impacting change within EOL care.

High speed all-optical networks

Science.gov (United States)

Chlamtac, Imrich

1993-01-01

An inherent problem of conventional point-to-point WAN architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. This report presents the first solution to WDM based WAN networks that overcomes this limitation. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs.

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness

Science.gov (United States)

Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-01-01

the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a “social networking condition” in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. Conclusions More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks. PMID:26068087

The Role of Social Network Technologies in Online Health Promotion: A Narrative Review of Theoretical and Empirical Factors Influencing Intervention Effectiveness.

Science.gov (United States)

Balatsoukas, Panos; Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John

2015-06-11

networking within health promotion interventions. Most of the trials investigated the value of a "social networking condition" in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks.

Toward Measuring Network Aesthetics Based on Symmetry

Directory of Open Access Journals (Sweden)

Zengqiang Chen

2017-05-01

Full Text Available In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

Network science, nonlinear science and infrastructure systems

CERN Document Server

2007-01-01

Network Science, Nonlinear Science and Infrastructure Systems has been written by leading scholars in these areas. Its express purpose is to develop common theoretical underpinnings to better solve modern infrastructural problems. It is felt by many who work in these fields that many modern communication problems, ranging from transportation networks to telecommunications, Internet, supply chains, etc., are fundamentally infrastructure problems. Moreover, these infrastructure problems would benefit greatly from a confluence of theoretical and methodological work done with the areas of Network Science, Dynamical Systems and Nonlinear Science. This book is dedicated to the formulation of infrastructural tools that will better solve these types of infrastructural problems. .

Machine learning a theoretical approach

CERN Document Server

Natarajan, Balas K

2014-01-01

This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation

Interconnection policy: a theoretical survey

Directory of Open Access Journals (Sweden)

César Mattos

2003-01-01

Full Text Available This article surveys the theoretical foundations of interconnection policy. The requirement of an interconnection policy should not be taken for granted in all circumstances, even considering the issue of network externalities. On the other hand, when it is required, an encompassing interconnection policy is usually justified. We provide an overview of the theory on interconnection pricing that results in several different prescriptions depending on which problem the regulator aims to address. We also present a survey on the literature on two-way interconnection.

Content Propagation in Online Social Networks

NARCIS (Netherlands)

Blenn, N.

2014-01-01

This thesis presents methods and techniques to analyze content propagation within online social networks (OSNs) using a graph theoretical approach. Important factors and different techniques to analyze and describe content propagation, starting from the smallest entity in a network, representing a

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....

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....

Synchronization of Switched Interval Networks and Applications to Chaotic Neural Networks

Directory of Open Access Journals (Sweden)

Jinde Cao

2013-01-01

Full Text Available This paper investigates synchronization problem of switched delay networks with interval parameters uncertainty, based on the theories of the switched systems and drive-response technique, a mathematical model of the switched interval drive-response error system is established. Without constructing Lyapunov-Krasovskii functions, introducing matrix measure method for the first time to switched time-varying delay networks, combining Halanay inequality technique, synchronization criteria are derived for switched interval networks under the arbitrary switching rule, which are easy to verify in practice. Moreover, as an application, the proposed scheme is then applied to chaotic neural networks. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Network connectivity value.

Science.gov (United States)

Dragicevic, Arnaud; Boulanger, Vincent; Bruciamacchie, Max; Chauchard, Sandrine; Dupouey, Jean-Luc; Stenger, Anne

2017-04-21

In order to unveil the value of network connectivity, we formalize the construction of ecological networks in forest environments as an optimal control dynamic graph-theoretic problem. The network is based on a set of bioreserves and patches linked by ecological corridors. The node dynamics, built upon the consensus protocol, form a time evolutive Mahalanobis distance weighted by the opportunity costs of timber production. We consider a case of complete graph, where the ecological network is fully connected, and a case of incomplete graph, where the ecological network is partially connected. The results show that the network equilibrium depends on the size of the reception zone, while the network connectivity depends on the environmental compatibility between the ecological areas. Through shadow prices, we find that securing connectivity in partially connected networks is more expensive than in fully connected networks, but should be undertaken when the opportunity costs are significant. Copyright © 2017 Elsevier Ltd. All rights reserved.

Factors for Successful Use of Social Networking Sites in Higher Education

Directory of Open Access Journals (Sweden)

L Schlenkrich

2012-09-01

Full Text Available Social networking sites are extremely popular online destinations that offer users easy ways to build and maintain relationships with each other, and to disseminate information in an activity referred to as social networking. Students, lecturers, teachers, parents and businesses, in increasing numbers, use tools available on social networking sites to communicate with each other in a fast and cost-effective manner. The use of social networking sites to support educational initiatives has received much attention. However, the full potential of social network sites has yet to be achieved as users continue to strive for optimal ways of using these sites, as well as battle to overcome the negative characteristics (for example, privacy, security, governance, user behaviour, information quality of these sites. This paper proposes factors for successful use of social networking sites in higher educational institutions. These success factors need to be adopted by users in order to develop the positive aspects of social networking, while at the same time mitigating the negative characteristics. An initial set of factors for successful use of social networking sites, as well as measures to test successful use of social networking sites were derived from the literature. These factors were tested by means of an online survey of students at a university, the results of which informed the final factors for successful use of social networking sites. The factors enable users to overcome the negative characteristics associated with social networking sites. If used successfully, social networking sites can offer lecturers and students a useful tool with which to develop their relationship and contribute to their learning experience.

Protection of electricity distribution networks

CERN Document Server

Gers, Juan M

2004-01-01

Written by two practicing electrical engineers, this second edition of the bestselling Protection of Electricity Distribution Networks offers both practical and theoretical coverage of the technologies, from the classical electromechanical relays to the new numerical types, which protect equipment on networks and in electrical plants. A properly coordinated protection system is vital to ensure that an electricity distribution network can operate within preset requirements for safety for individual items of equipment, staff and public, and the network overall. Suitable and reliable equipment sh

Learning communities and overcoming poverty in Brazil

Directory of Open Access Journals (Sweden)

Tatiana Santos Pitanga

2015-09-01

Full Text Available Object: Brazil has implemented social programs to meet the Millennium Development Goals of reducing poverty and inequality. Despite the good results still there are ghettos and educational and social inequalities. Moreover Learning Communities are responding to these needs by promoting education based on successful actions scientifically proven of which promote educational change and social inclusion. The aim of this article is to highlight the characteristics of Learning Communities that allow overcoming poverty, and in this perspective, explain the implementation of the Learning Communities in Brazil and how, in this way, it is creating the conditions for effective overcoming give poverty and inequality in this country.Design / methodology: This article is based on documentary analysis of reports of the INCLUD-ED - the project on school education more scientific resources has been funded by the European Union, United Nations / ECLAC, Brazilian public agencies and websites of official institutions that promote Learning Communities in Brazil. Brazilian Institute of Geography and Statistics are also collected.Contributions and results: It highlights successful actions that contribute to overcoming poverty and social exclusion. Such actions are based on dialogic learning, democratic management and the formation of heterogeneous groups. It is observed that in Brazil are carrying out such actions and the ongoing expansion of the project in the country is creating the conditions for effective poverty reduction.Added value: This article reveals specific elements of overcoming poverty through education.

GENERAL: Epidemic spreading on networks with vaccination

Science.gov (United States)

Shi, Hong-Jing; Duan, Zhi-Sheng; Chen, Guan-Rong; Li, Rong

2009-08-01

In this paper, a new susceptible-infected-susceptible (SIS) model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns (the recovered individuals have or have not immunity) on scale-free networks are discussed. Both theoretical and numerical analyses are presented. The epidemic thresholds related to the vaccination rate, the vaccination-invalid rate and the vaccination success rate on scale-free networks are demonstrated, showing different results from the reported observations. This reveals that whether or not the epidemic can spread over a network under vaccination control is determined not only by the network structure but also by the medicine's effective duration. Moreover, for a given infective rate, the proportion of individuals to vaccinate can be calculated theoretically for the case that the recovered nodes have immunity. Finally, simulated results are presented to show how to control the disease prevalence.

A distributed framework for inter-domain virtual network embedding

Science.gov (United States)

Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

2013-03-01

Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

Reverse engineering large-scale genetic networks: synthetic versus

Indian Academy of Sciences (India)

Development of microarray technology has resulted in an exponential rise in gene expression data. Linear computational methods are of great assistance in identifying molecular interactions, and elucidating the functional properties of gene networks. It overcomes the weaknesses of in vivo experiments including high cost, ...

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks.

Science.gov (United States)

Pyle, Ryan; Rosenbaum, Robert

2017-01-06

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Dynamic behaviors in directed networks

International Nuclear Information System (INIS)

Park, Sung Min; Kim, Beom Jun

2006-01-01

Motivated by the abundance of directed synaptic couplings in a real biological neuronal network, we investigate the synchronization behavior of the Hodgkin-Huxley model in a directed network. We start from the standard model of the Watts-Strogatz undirected network and then change undirected edges to directed arcs with a given probability, still preserving the connectivity of the network. A generalized clustering coefficient for directed networks is defined and used to investigate the interplay between the synchronization behavior and underlying structural properties of directed networks. We observe that the directedness of complex networks plays an important role in emerging dynamical behaviors, which is also confirmed by a numerical study of the sociological game theoretic voter model on directed networks

Three-dimensional attached viscous flow basic principles and theoretical foundations

CERN Document Server

Hirschel, Ernst Heinrich; Kordulla, Wilhelm

2014-01-01

Viscous flow is usually treated in the frame of boundary-layer theory and as a two-dimensional flow. At best, books on boundary layers provide the describing equations for three-dimensional boundary layers, and solutions only for certain special cases.   This book presents the basic principles and theoretical foundations of three-dimensional attached viscous flows as they apply to aircraft of all kinds. Though the primary flight speed range is that of civil air transport vehicles, flows past other flying vehicles up to hypersonic speeds are also considered. Emphasis is put on general three-dimensional attached viscous flows and not on three-dimensional boundary layers, as this wider scope is necessary in view of the theoretical and practical problems that have to be overcome in practice.   The specific topics covered include weak, strong, and global interaction; the locality principle; properties of three-dimensional viscous flows; thermal surface effects; characteristic properties; wall compatibility con...

Networks as a Type of Social Entrepreneurship to Advance Population Health

OpenAIRE

Wei-Skillern, Jane

2010-01-01

A detailed case study from the field of social entrepreneurship is used to illustrate the network approach, which does not require more resources but rather makes better use of existing resources. Leaders in public health can use networks to overcome some of the barriers that inhibit the widespread adoption of a population health approach to community health. Public health leaders who embrace social entrepreneurship may be better able to accomplish their missions by building their networks ra...

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks.

Science.gov (United States)

Shah, Shashi; Kittipiyakul, Somsak; Lim, Yuto; Tan, Yasuo

2018-05-10

The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs) analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR) dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE), cannot be guaranteed. Potential games (PGs) ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC) as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR) algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Marginal Contribution-Based Distributed Subchannel Allocation in Small Cell Networks

Directory of Open Access Journals (Sweden)

Shashi Shah

2018-05-01

Full Text Available The paper presents a game theoretic solution for distributed subchannel allocation problem in small cell networks (SCNs analyzed under the physical interference model. The objective is to find a distributed solution that maximizes the welfare of the SCNs, defined as the total system capacity. Although the problem can be addressed through best-response (BR dynamics, the existence of a steady-state solution, i.e., a pure strategy Nash equilibrium (NE, cannot be guaranteed. Potential games (PGs ensure convergence to a pure strategy NE when players rationally play according to some specified learning rules. However, such a performance guarantee comes at the expense of complete knowledge of the SCNs. To overcome such requirements, properties of PGs are exploited for scalable implementations, where we utilize the concept of marginal contribution (MC as a tool to design learning rules of players’ utility and propose the marginal contribution-based best-response (MCBR algorithm of low computational complexity for the distributed subchannel allocation problem. Finally, we validate and evaluate the proposed scheme through simulations for various performance metrics.

Fear of Public Speaking: How Can I Overcome It?

Science.gov (United States)

... I overcome it? How can I overcome my fear of public speaking? Answers from Craig N. Sawchuk, Ph.D., L.P. Fear of public speaking is a common form of ... It can range from slight nervousness to paralyzing fear and panic. Many people with this fear avoid ...

Modeling the propagation of mobile malware on complex networks

Science.gov (United States)

Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue

2016-08-01

In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.

Department of Theoretical Physics - Overview

International Nuclear Information System (INIS)

Kwiecinski, J.

1999-01-01

Full text: Research activity of the Department of Theoretical Physics concerns theoretical high-energy and elementary particle physics, intermediate energy particle physics, theoretical nuclear physics, theory of nuclear matter, theory of quark-gluon plasma and of relativistic heavy-ion collisions, theoretical astrophysics and general physics. There is some emphasis on the phenomenological applications of the theoretical research yet the more formal problems are also considered. The detailed summary of the research projects and of the results obtained in various fields is given in the abstracts. Our Department actively collaborates with other Departments of the Institute as well as with several scientific institutions both in Poland and abroad. In particular members of our Department participate in the EC network which allows mobility of researchers. Several members of our Department have also participated in the research projects funded by the Polish Committee for Scientific Research (KBN). The complete list of grants is listed separately. Besides pure research, members of our Department are also involved in graduate and undergraduate teaching activity both at our Institute as well as at other academic institutions in Cracow. At present five PhD students are working for their degree under supervision of the senior members from the Department. In the last year we have completed our active participation in the educational TEMPUS programme funded by the European Communities. This programme has in particular allowed exchange of students between our Department and the Department of Physics of the University of Durham in the United Kingdom. In 1998 we joined the SOCRATES - ERASMUS project which will make it possible to continue this exchange. (author)

The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.

Directory of Open Access Journals (Sweden)

Ross S Williamson

2015-04-01

Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.

Towards Device-Independent Information Processing on General Quantum Networks

Science.gov (United States)

Lee, Ciarán M.; Hoban, Matty J.

2018-01-01

The violation of certain Bell inequalities allows for device-independent information processing secure against nonsignaling eavesdroppers. However, this only holds for the Bell network, in which two or more agents perform local measurements on a single shared source of entanglement. To overcome the practical constraints that entangled systems can only be transmitted over relatively short distances, large-scale multisource networks have been employed. Do there exist analogs of Bell inequalities for such networks, whose violation is a resource for device independence? In this Letter, the violation of recently derived polynomial Bell inequalities will be shown to allow for device independence on multisource networks, secure against nonsignaling eavesdroppers.

Entropy Characterization of Random Network Models

Directory of Open Access Journals (Sweden)

Pedro J. Zufiria

2017-06-01

Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

Scaling Laws for Heterogeneous Wireless Networks

Science.gov (United States)

2009-09-01

planned and the size of communication networks that are fundamentally understood. On the one hand, wireline networks (like the Internet) have grown from...Franceschetti, Marco D. Migliore, and Paolo Minero . The capacity of wireless networks: Information-theoretic and physical limits. In Proceedings of the...Allerton Conference on Communication, Control, and Computing, September 2007. [12] Massimo Franceschetti, Marco D. Migliore, and Paolo Minero . The

Flory-Stockmayer analysis on reprocessable polymer networks

Science.gov (United States)

Li, Lingqiao; Chen, Xi; Jin, Kailong; Torkelson, John

Reprocessable polymer networks can undergo structure rearrangement through dynamic chemistries under proper conditions, making them a promising candidate for recyclable crosslinked materials, e.g. tires. This research field has been focusing on various chemistries. However, there has been lacking of an essential physical theory explaining the relationship between abundancy of dynamic linkages and reprocessability. Based on the classical Flory-Stockmayer analysis on network gelation, we developed a similar analysis on reprocessable polymer networks to quantitatively predict the critical condition for reprocessability. Our theory indicates that it is unnecessary for all bonds to be dynamic to make the resulting network reprocessable. As long as there is no percolated permanent network in the system, the material can fully rearrange. To experimentally validate our theory, we used a thiol-epoxy network model system with various dynamic linkage compositions. The stress relaxation behavior of resulting materials supports our theoretical prediction: only 50 % of linkages between crosslinks need to be dynamic for a tri-arm network to be reprocessable. Therefore, this analysis provides the first fundamental theoretical platform for designing and evaluating reprocessable polymer networks. We thank McCormick Research Catalyst Award Fund and ISEN cluster fellowship (L. L.) for funding support.

Socio-theoretic Accounts of IS

DEFF Research Database (Denmark)

Rose, Jeremy; Jones, Matthew

2005-01-01

A long-standing debate in the IS literature concerns the relationship between technology and organization. Does technology cause effects in organizations, or is it humans that determine how technology is used? Many socio-theoretic accounts of a middle way between the extremes of technological...... confusion. This paper argues that neither structuration theory nor actor network theory offers a particularly convincing account of the interaction of humans and machines, and that their different accounts of agency make them hard to integrate in any meaningful way. Comparing the two theories and their use...

Overcoming the Photovoltage Plateau in Large Bandgap Perovskite Photovoltaics.

Science.gov (United States)

Rajagopal, Adharsh; Stoddard, Ryan J; Jo, Sae Byeok; Hillhouse, Hugh W; Jen, Alex K-Y

2018-05-09

Development of large bandgap (1.80-1.85 eV E g ) perovskite is crucial for perovskite-perovskite tandem solar cells. However, the performance of 1.80-1.85 eV E g perovskite solar cells (PVKSCs) are significantly lagging their counterparts in the 1.60-1.75 eV E g range. This is because the photovoltage ( V oc ) does not proportionally increase with E g due to lower optoelectronic quality of conventional (MA,FA,Cs)Pb(I,Br) 3 and results in a photovoltage plateau ( V oc limited to 80% of the theoretical limit for ∼1.8 eV E g ). Here, we incorporate phenylethylammonium (PEA) in a mixed-halide perovskite composition to solve the inherent material-level challenges in 1.80-1.85 eV E g perovskites. The amount of PEA incorporation governs the topography and optoelectronic properties of resultant films. Detailed structural and spectroscopic characterization reveal the characteristic trends in crystalline size, orientation, and charge carrier recombination dynamics and rationalize the origin of improved material quality with higher luminescence. With careful interface optimization, the improved material characteristics were translated to devices and V oc values of 1.30-1.35 V were achieved, which correspond to 85-87% of the theoretical limit. Using an optimal amount of PEA incorporation to balance the increase in V oc and the decrease in charge collection, a highest power conversion efficiency of 12.2% was realized. Our results clearly overcome the photovoltage plateau in the 1.80-1.85 eV E g range and represent the highest V oc achieved for mixed-halide PVKSCs. This study provides widely translatable insights, an important breakthrough, and a promising platform for next-generation perovskite tandems.

Connectivity, cycles, and persistence thresholds in metapopulation networks.

Directory of Open Access Journals (Sweden)

Yael Artzy-Randrup

2010-08-01

Full Text Available Synthesising the relationships between complexity, connectivity, and the stability of large biological systems has been a longstanding fundamental quest in theoretical biology and ecology. With the many exciting developments in modern network theory, interest in these issues has recently come to the forefront in a range of multidisciplinary areas. Here we outline a new theoretical analysis specifically relevant for the study of ecological metapopulations focusing primarily on marine systems, where subpopulations are generally connected via larval dispersal. Our work determines the qualitative and quantitative conditions by which dispersal and network structure control the persistence of a set of age-structured patch populations. Mathematical modelling combined with a graph theoretic analysis demonstrates that persistence depends crucially on the topology of cycles in the dispersal network which tend to enhance the effect of larvae "returning home." Our method clarifies the impact directly due to network structure, but this almost by definition can only be achieved by examining the simplified case in which patches are identical; an assumption that we later relax. The methodology identifies critical migration routes, whose presence are vital to overall stability, and therefore should have high conservation priority. In contrast, "lonely links," or links in the network that do not participate in a cyclical component, have no impact on persistence and thus have low conservation priority. A number of other intriguing criteria for persistence are derived. Our modelling framework reveals new insights regarding the determinants of persistence, stability, and thresholds in complex metapopulations. In particular, while theoretical arguments have, in the past, suggested that increasing connectivity is a destabilizing feature in complex systems, this is not evident in metapopulation networks where connectivity, cycles, coherency, and heterogeneity all tend

The theoretical ultimate magnetoelectric coefficients of magnetoelectric composites by optimization design

International Nuclear Information System (INIS)

Wang, H.-L.; Liu, B.

2014-01-01

This paper investigates what is the largest magnetoelectric (ME) coefficient of ME composites, and how to realize it. From the standpoint of energy conservation, a theoretical analysis is carried out on an imaginary lever structure consisting of a magnetostrictive phase, a piezoelectric phase, and a rigid lever. This structure is a generalization of various composite layouts for optimization on ME effect. The predicted theoretical ultimate ME coefficient plays a similar role as the efficiency of ideal heat engine in thermodynamics, and is used to evaluate the existing typical ME layouts, such as the parallel sandwiched layout and the serial layout. These two typical layouts exhibit ME coefficient much lower than the theoretical largest values, because in the general analysis the stress amplification ratio and the volume ratio can be optimized independently and freely, but in typical layouts they are dependent or fixed. To overcome this shortcoming and achieve the theoretical largest ME coefficient, a new design is presented. In addition, it is found that the most commonly used electric field ME coefficient can be designed to be infinitely large. We doubt the validity of this coefficient as a reasonable ME effect index and consider three more ME coefficients, namely the electric charge ME coefficient, the voltage ME coefficient, and the static electric energy ME coefficient. We note that the theoretical ultimate value of the static electric energy ME coefficient is finite and might be a more proper measure of ME effect

Border detection in complex networks

International Nuclear Information System (INIS)

Travencolo, Bruno A N; Viana, Matheus Palhares; Costa, Luciano da Fontoura

2009-01-01

One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

Science.gov (United States)

Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S

2013-08-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures. Copyright © 2013 Elsevier B.V. All rights reserved.

Chromosomocentric approach to overcoming difficulties in implementation of international project Human Proteome

Directory of Open Access Journals (Sweden)

A. I. Archakov

2013-12-01

Full Text Available The international project Human Proteome (PHP, being a logical continuation of the project Human Genome, was started on September 23, 2010. In correspondence with the genocentric approach, the PHP aim is to prepare a catalogue of all human proteins and to decipher a network of their interactions. The PHP implementation difficulties arise because the research subject itself – proteome – is much more complicated than genome. The major problem is the insufficient sensitivity of proteome methods that does not allow detecting low- and ultralow-copy proteins. Bad reproducibility of proteome methods and the lack of so-called “gold standard” is the second major complicacy in PHP implementation. The third problem is the dynamic character of proteome, its instabili­ty in time. The paper deals with possible variants of overcoming these complicacies, preventing from successful implementation of PHP.

Rescuing policy in tourism network research

DEFF Research Database (Denmark)

Dredge, Dianne

2018-01-01

Networks provide a powerful lens to understand complex relational entanglements that are transforming social, economic and political life. Through a discussion of the various streams of network research in tourism, this paper argues that policy matters run across and throughout these strands....... Rather than arguing for increased interest in tourism policy network research as a separate subfield, the paper argues for deeper theoretical engagement with the policy dimension in tourism network research. Researchers adopting a network ontology could gain considerable insights and open up new lines...

Bayesian Network Models in Cyber Security: A Systematic Review

NARCIS (Netherlands)

Chockalingam, S.; Pieters, W.; Herdeiro Teixeira, A.M.; van Gelder, P.H.A.J.M.; Lipmaa, Helger; Mitrokotsa, Aikaterini; Matulevicius, Raimundas

2017-01-01

Bayesian Networks (BNs) are an increasingly popular modelling technique in cyber security especially due to their capability to overcome data limitations. This is also instantiated by the growth of BN models development in cyber security. However, a comprehensive comparison and analysis of these

Networks as a type of social entrepreneurship to advance population health.

Science.gov (United States)

Wei-Skillern, Jane

2010-11-01

A detailed case study from the field of social entrepreneurship is used to illustrate the network approach, which does not require more resources but rather makes better use of existing resources. Leaders in public health can use networks to overcome some of the barriers that inhibit the widespread adoption of a population health approach to community health. Public health leaders who embrace social entrepreneurship may be better able to accomplish their missions by building their networks rather than just their organizations.

Network Survivability

DEFF Research Database (Denmark)

Marzo, José L.; Stidsen, Thomas Riis; Ruepp, Sarah Renée

2010-01-01

– are vital to modern services such as mobile telephony, online banking and VoIP. This book examines communication networking from a mathematical viewpoint. The contributing authors took part in the European COST action 293 – a four-year program of multidisciplinary research on this subject. In this book...... they offer introductory overviews and state-of-the-art assessments of current and future research in the fields of broadband, optical, wireless and ad hoc networks. Particular topics of interest are design, optimization, robustness and energy consumption. The book will be of interest to graduate students......, researchers and practitioners in the areas of networking, theoretical computer science, operations research, distributed computing and mathematics....

Culture, agency and power: Theoretical reflections on informal economic networks and political process

OpenAIRE

Meagher, Kate

2009-01-01

Do network theory really offer a suitable concept for the theorization of informal processes of economic regulation and institutional change? This working paper challenges both essentialist and skeptical attitudes to networks through an examination of the positive and negative effects of network governance in contemporary societies in a range of regional contexts. The analysis focuses on three broad principles of non-state organization - culture, agency and power - and their role in shaping p...

Geometrical methods for power network analysis

Energy Technology Data Exchange (ETDEWEB)

Bellucci, Stefano; Tiwari, Bhupendra Nath [Istituto Nazioneale di Fisica Nucleare, Frascati, Rome (Italy). Lab. Nazionali di Frascati; Gupta, Neeraj [Indian Institute of Technology, Kanpur (India). Dept. of Electrical Engineering

2013-02-01

Uses advanced geometrical methods to analyse power networks. Provides a self-contained and tutorial introduction. Includes a fully worked-out example for the IEEE 5 bus system. This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds. The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system. This work addresses applied mathematicians, theoretical physicists and power engineers interested in novel mathematical approaches to power network theory.

Control Theoretical Expression of Quantum Systems And Lower Bound of Finite Horizon Quantum Algorithms

OpenAIRE

Yanagisawa, Masahiro

2007-01-01

We provide a control theoretical method for a computational lower bound of quantum algorithms based on quantum walks of a finite time horizon. It is shown that given a quantum network, there exists a control theoretical expression of the quantum system and the transition probability of the quantum walk is related to a norm of the associated transfer function.

HOLA: Human-like Orthogonal Network Layout.

Science.gov (United States)

Kieffer, Steve; Dwyer, Tim; Marriott, Kim; Wybrow, Michael

2016-01-01

Over the last 50 years a wide variety of automatic network layout algorithms have been developed. Some are fast heuristic techniques suitable for networks with hundreds of thousands of nodes while others are multi-stage frameworks for higher-quality layout of smaller networks. However, despite decades of research currently no algorithm produces layout of comparable quality to that of a human. We give a new "human-centred" methodology for automatic network layout algorithm design that is intended to overcome this deficiency. User studies are first used to identify the aesthetic criteria algorithms should encode, then an algorithm is developed that is informed by these criteria and finally, a follow-up study evaluates the algorithm output. We have used this new methodology to develop an automatic orthogonal network layout method, HOLA, that achieves measurably better (by user study) layout than the best available orthogonal layout algorithm and which produces layouts of comparable quality to those produced by hand.

Extending AAA operational model for profile-based access control in ethernet-based Neutral Access Networks

NARCIS (Netherlands)

Matias, J.; Jacob, E.; Demchenko, Y.; de Laat, C.; Gommans, L.; Macías López, E.M.; Bogliolo, A.; Perry, M.; Ran, M

2010-01-01

Neutral Access Networks (NAN) have appeared as a new model to overcome some restrictions and lack of flexibility that are present currently in broadband access networks. NAN brings new business opportunities by opening this market to new stakeholders. Although the NAN model is accepted, there are

THE NETWORKS IN TOURISM: A THEORETICAL APPROACH

Directory of Open Access Journals (Sweden)

Maria TĂTĂRUȘANU

2016-12-01

Full Text Available The economic world in which tourism companies act today is in a continuous changing process. The most important factor of these changes is the globalization of their environment, both in economic, social, natural and cultural aspects. The tourism companies can benefit from the opportunities brought by globalization, but also could be menaced by the new context. How could react the companies to these changes in order to create and maintain long term competitive advantage for their business? In the present paper we make a literature review of the new tourism companies´ business approach: the networks - a result and/or a reason for exploiting the opportunities or, on the contrary, for keeping their actual position on the market. It’s a qualitative approach and the research methods used are analyses, synthesis, abstraction, which are considered the most appropriate to achieve the objective of the paper.

Distinct enlargement of network size or measurement speed for serial FBG sensor networks utilizing SIK-DS-CDMA

Energy Technology Data Exchange (ETDEWEB)

Abbenseth, S; Lochmann, S I [Hochschule Wismar, Univ. of Technology, Business and Design, Dept. of Electrical Engineering and Informatics, Philipp-Mueller-Strasse, 23952, Wismar (Germany)

2005-01-01

Using the spectral selectivity and adjustable reflectivity FBGs are predestined for serial networking. Presently the addressing is realised by time division multiplex (TDM) or wavelength division multiplex (WDM). But these technologies have big disadvantages regarding the effective use of the prevailing resources time and wavelength, respectively. In this paper a new scheme capable of addressing a large number of FBGs in a single serial network is proposed and compared to TDM and WDM. Using all optical sequence inversion keyed (SIK) direct sequence (DS) code division multiplex (CDM) it overcomes the restrictions handling the resources time and wavelength without losing accuracy.

Distinct enlargement of network size or measurement speed for serial FBG sensor networks utilizing SIK-DS-CDMA

International Nuclear Information System (INIS)

Abbenseth, S; Lochmann, S I

2005-01-01

Using the spectral selectivity and adjustable reflectivity FBGs are predestined for serial networking. Presently the addressing is realised by time division multiplex (TDM) or wavelength division multiplex (WDM). But these technologies have big disadvantages regarding the effective use of the prevailing resources time and wavelength, respectively. In this paper a new scheme capable of addressing a large number of FBGs in a single serial network is proposed and compared to TDM and WDM. Using all optical sequence inversion keyed (SIK) direct sequence (DS) code division multiplex (CDM) it overcomes the restrictions handling the resources time and wavelength without losing accuracy

Percolation-theoretic bounds on the cache size of nodes in mobile opportunistic networks.

Science.gov (United States)

Yuan, Peiyan; Wu, Honghai; Zhao, Xiaoyan; Dong, Zhengnan

2017-07-18

The node buffer size has a large influence on the performance of Mobile Opportunistic Networks (MONs). This is mainly because each node should temporarily cache packets to deal with the intermittently connected links. In this paper, we study fundamental bounds on node buffer size below which the network system can not achieve the expected performance such as the transmission delay and packet delivery ratio. Given the condition that each link has the same probability p to be active in the next time slot when the link is inactive and q to be inactive when the link is active, there exists a critical value p c from a percolation perspective. If p > p c , the network is in the supercritical case, where we found that there is an achievable upper bound on the buffer size of nodes, independent of the inactive probability q. When p network is in the subcritical case, and there exists a closed-form solution for buffer occupation, which is independent of the size of the network.

Node design in optical packet switched networks

DEFF Research Database (Denmark)

Nord, Martin

2006-01-01

The thesis discusses motivation, realisation and performance of the Optical Packet Switching (OPS) network paradigm. The work includes proposals for designs and methods to efficiently use both the wavelength- and time domain for contention resolution in asynchronous operation. The project has also......S parameter. Finally, the thesis includes a proposal for a node design and associated MAC protocol for an OPS ring topology metropolitan area network with high throughput and fairness, also for unbalanced traffic....... proposed parallel designs to overcome scalability constraints and to support migration scenarios. Furthermore, it has proposed and demonstrated optical input processing schemes for hybrids networks to simultaneously support OPS and Optical Circuit Switching. Quality of Service (QoS) differentiation enables...

A child abuse research network: Now what?

Science.gov (United States)

Lindberg, Daniel M; Scribano, Philip V

2017-08-01

As foundational work in preparation for a sustainable, multi-center network devoted to child abuse medical research, we recently used a combination of survey and modified Delphi methodologies to determine research priorities for future multi-center studies. Avoiding missed diagnoses, and improving selected/indicated prevention were the topics rated most highly in terms of research priority. Several constructive commentaries in this issue identify the key challenges which must be overcome to ensure a successful network. Indeed, as with the clinical work of child abuse pediatrics, a scientific network will also require constant collaboration within and outside the community of child abuse pediatricians, the wider medical community, and even non-medical professions. Copyright © 2017 Elsevier Ltd. All rights reserved.

The future of network governance research

DEFF Research Database (Denmark)

Lewis, Jenny

2011-01-01

that comprises it. The main theoretical and empirical approaches that have been used to guide it to date are then briefly described, emphasizing recent debates about interpretivism and decentring. Next, it suggests that a robust and interesting future for network governance requires diversity, rather than...... adherence to a single approach. It is argued that more sophisticated approaches for examining network governance are fashioned through a synthesis of ideas and methods to create an analysis of networks as networks. This is especially the case where some formal analysis of network structure is used...

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Overcoming Challenges of Real-World Implementation

Science.gov (United States)

Shuldiner, AR; Relling, MV; Peterson, JF; Hicks, JK; Freimuth, RR; Sadee, W; Pereira, NL; Roden, DM; Johnson, JA; Klein, TE

2013-01-01

The pace of discovery of potentially actionable pharmacogenetic variants has increased dramatically in recent years. However, the implementation of this new knowledge for individualized patient care has been slow. The Pharmacogenomics Research Network (PGRN) Translational Pharmacogenetics Program seeks to identify barriers and develop real-world solutions to implementation of evidence-based pharmacogenetic tests in diverse health-care settings. Dissemination of the resulting toolbox of “implementation best practices” will prove useful to a broad audience. PMID:23588301

Visual summation in night-flying sweat bees: a theoretical study.

Science.gov (United States)

Theobald, Jamie Carroll; Greiner, Birgit; Wcislo, William T; Warrant, Eric J

2006-07-01

Bees are predominantly diurnal; only a few groups fly at night. An evolutionary limitation that bees must overcome to inhabit dim environments is their eye type: bees possess apposition compound eyes, which are poorly suited to vision in dim light. Here, we theoretically examine how nocturnal bees Megalopta genalis fly at light levels usually reserved for insects bearing more sensitive superposition eyes. We find that neural summation should greatly increase M. genalis's visual reliability. Predicted spatial summation closely matches the morphology of laminal neurons believed to mediate such summation. Improved reliability costs acuity, but dark adapted bees already suffer optical blurring, and summation further degrades vision only slightly.

Error-backpropagation in temporally encoded networks of spiking neurons

NARCIS (Netherlands)

S.M. Bohte (Sander); J.A. La Poutré (Han); J.N. Kok (Joost)

2000-01-01

textabstractFor a network of spiking neurons that encodes information in the timing of individual spike-times, we derive a supervised learning rule, emph{SpikeProp, akin to traditional error-backpropagation and show how to overcome the discontinuities introduced by thresholding. With this algorithm,

Hybrid Multicast-Unicast Video Streaming over Heterogeneous Cellular Networks

OpenAIRE

Almowuena, Saleh Abdullah

2016-01-01

The demand for multimedia streaming over mobile networks has been steadily increasing in the past several years. For instance, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go. Unfortunately, this growth in demand has strained the wireless networks despite the significant increase in their capacities with recent generations. It has also caused a significant increase in the energy consumption at mobile terminals. To overcome these chal...

Overcoming Barriers to Public Engagement through a Multi-Institution Consortium

Science.gov (United States)

Lambert, K. F.; Weiss, M.; Garlick, S.

2016-12-01

A growing body of evidence suggests that public engagement with science (PES) can enhance the relevance and impact of science on society. At the same time, advances in our understanding of public engagement suggest that greater skills, resources, and time horizons are often required to create effective programs. Consequently, despite a proliferation of training programs, many scientists still face the challenge of balancing the demands of public engagement with the requirements of their disciplinary research. Novel institutions are emerging that bring together interdisciplinary networks of principle investigators with PES practitioners to overcome barriers to effective and sustained public engagement in the environmental sciences. We will use the Science Policy Exchange (SPE), a consortium housed at the Harvard Forest, Harvard University, to illustrate how PIs and PES practitioners can collaborate to design public engagement processes, conduct policy-relevant scientific syntheses, and implement science communication strategies. Results from two SPE case studies demonstrate how multi-institutional consortia can help scientists overcome barriers such as lack of knowledge of evidence-based PES approaches, limits on time and funding to implement PES projects, and the need to integrate PES activities with research. The case studies also show how SPE strives to achieve credibility, saliency, and legitimacy in different public policy contexts: (1) engagement between scientists and local stakeholders to develop scenarios of landscape change; and (2) engagement between scientists and policy makers to understand the relationship between power plant emission standards, and air quality, human health and ecosystem function. The presentation will conclude with examples of how SPE programs have led to institutional change (staffing and budget), cultural change (attitudes and expectations of senior leaders), and research change (development of research questions, funding proposals

General-Purpose Computation with Neural Networks: A Survey of Complexity Theoretic Results

Czech Academy of Sciences Publication Activity Database

Šíma, Jiří; Orponen, P.

2003-01-01

Roč. 15, č. 12 (2003), s. 2727-2778 ISSN 0899-7667 R&D Projects: GA AV ČR IAB2030007; GA ČR GA201/02/1456 Institutional research plan: AV0Z1030915 Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * feedforward networks * reccurent networks * probabilistic computation * analog computation Subject RIV: BA - General Mathematics Impact factor: 2.747, year: 2003

A study on Optical Labelling Techniques for All-Optical Networks

DEFF Research Database (Denmark)

Holm-Nielsen, Pablo Villanueva

2005-01-01

Optical switching has been proposed as an effective solution to overcoming the potential electronic bottleneck in all-optical network nodes carrying IP over WDM. The solution builds on the use of optical labelling as a mean to route packets or bursts of packets through the network. In addition...... of an intermediate wavelength between label erasure and label insertion. The above mentioned functionalities are assembled in whole network systems experiments that validates the different labelling schemes with respect to transmission, wavelength conversion, label swapping and retransmission. Optical labelling...... and specially the orthogonal schemes for optical labelling, are thus shown to be an effective solution to all-optical networks....

A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

Science.gov (United States)

Goekoop, Rutger; Goekoop, Jaap G

2014-01-01

The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. To examine the ability of network community detection (NCD) to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS). Principal component analysis (PCA) was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS). An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS) was optimized using a previously published technique. In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "Depression", "Mania", "Anxiety", "Psychosis", "Retardation", and "Behavioral Disorganization". Network metrics were used to quantify the continuities between the elementary syndromes. We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a 'Psychopathology Web'. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.

Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

Directory of Open Access Journals (Sweden)

Joseph A. Wayman

2015-03-01

Full Text Available Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge

The Design of a Large Scale Airline Network

NARCIS (Netherlands)

Carmona Benitez, R.B.

2012-01-01

Airlines invest a lot of money before opening new pax transportation services, for this reason, airlines have to analyze if their profits will overcome the amount of money they have to invest to open new services. The design and analysis of the feasibility of airlines networks can be done by using

High speed all optical networks

Science.gov (United States)

Chlamtac, Imrich; Ganz, Aura

1990-01-01

An inherent problem of conventional point-to-point wide area network (WAN) architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. The first solution to wavelength division multiplexing (WDM) based WAN networks that overcomes this limitation is presented. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs. The principle of the Lightnet architecture is the construction and use of virtual topology networks, embedded in the original network in the wavelength domain. For this construction Lightnets utilize the new concept of lightpaths which constitute the links of the virtual topology. Lightpaths are all-optical, multihop, paths in the network that allow data to be switched through intermediate nodes using high throughput passive optical switches. The use of the virtual topologies and the associated switching design introduce a number of new ideas, which are discussed in detail.

OVERCOMING THE CULTURAL DIFFERENCES: PARABLE AS A MEANS OF INTERCULTURAL DIALOGUE

Directory of Open Access Journals (Sweden)

Tetyana V. Danylova

2013-09-01

Full Text Available Purpose. This article attempts to investigate the ways to overcome negative after-effects of intercultural communication. Methodology and theoretical results: To avoid the negative after-effects of intercultural communication caused by the clash of different reality tunnels, it is necessary to go beyond the framework of the specific symbolical territory, which is seen as the only true reality. Expanding the horizons of life, going beyond the boundaries of a personal reality tunnel can be achieved, in particular, by using parables. Acquaintance with parables helps to extend the set of the world perception models and to change the positions of the communication process participants. Parables act as intermediaries between people of different cultures and mentalities. Owing to its archetypical form, parable becomes one of the most popular narratives illustrating deep and multi-faceted truths that sometimes cannot be expressed by any other way. Parable serves as an open and flexible model of the world and a model of an individual "I self". This model helps people to constitute themselves as a part of their world. Parable requires to reject its interpretation in the oppositions inherent in a given culture and to reconsider the very way of understanding. Rejection of the oppositions provides the possibility of perceiving the world as integrity, unity in diversity, helps to overcome one-sided picture of the inner world of a man and his life in society. Understanding of a parable works towards changing personal position, and human creative nature is actualized. Conclusion: Parables uniquely reflect the real world and contribute to personal understanding of reality. Parables are successfully transplanted into different cultures operating as heritage of a culture-recipient and as a connecting link, which optimizes an intercultural dialogue.

Graph theoretic analysis of protein interaction networks of eukaryotes

Science.gov (United States)

Goh, K.-I.; Kahng, B.; Kim, D.

2005-11-01

Owing to the recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high-throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are conserved across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interologs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interolog additions, for which we present a possible scenario through an in silico modeling.

Epidemics in partially overlapped multiplex networks.

Directory of Open Access Journals (Sweden)

Camila Buono

Full Text Available Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction [Formula: see text] of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted [Formula: see text]. We also theoretically determine the dependence of the epidemic threshold on the fraction [Formula: see text] of shared nodes in a system composed of two layers. We find that in the limit of [Formula: see text] the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.

An Information Theoretic Investigation Of Complex Adaptive Supply Networks With Organizational Topologies

Science.gov (United States)

2016-12-22

for the global pattern. A network view has proven useful in modeling a supply - chain for patterns of interaction. Queuing theory can be used to...phenomena. Second, operations management and supply - chain management lack metrics for evolution and dynamism in supply networks. Third, developing...robust theories in the presence of 14 adaptation is a formidable task. Supply - chain management theory can be built by identifying CAS phenomena and

Perspectives on next-generation technology for environmental sensor networks

Science.gov (United States)

Barbara J. Benson; Barbara J. Bond; Michael P. Hamilton; Russell K. Monson; Richard Han

2009-01-01

Sensor networks promise to transform and expand environmental science. However, many technological difficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization...

Urban Green Network Design: Defining green network from an urban planning perspective

Directory of Open Access Journals (Sweden)

Andrea Tulisi

2017-08-01

Full Text Available From the theoretical context of Smart City various studies have emerged that adopt an analytical approach and description of urban phenomena based on the principles of “network design”; this line of research uses the network systems theory to define the principles that regulate the relationships among the various elements of urban sub-systems in order to optimize their functionality. From the same theoretical basis, urban greenspaces have also been studied as networks, by means of the creation of models capable of measuring the performance of the system in its entirety, posing the basis of a new multy-disciplinary research field called green network. This paper presents the results of research aimed at clarifying the meaning of green network from an urban planning perspective through a lexical analysis applied to a textual corpus of more than 300 abstracts of research papers that have dealt with this topic over the last twenty years. The results show that the concept of green network appears still fuzzy and unclear, due to the different meaning given to the term “green” and to an incorrect use of the term “network”, often referred to as a generic set of natural areas present in a city, without any reference to the network system theory or to the basic rules linking these elements together. For this reason, the paper proposes a unique definition of green network from an urban planning perspective that takes into account the contribution of other research areas to effective green infrastructure planning. This is the concept of “urban green network design” defined as “an urban planning practice, supported by decision support tools able to model green infrastructure as network, composed by natural and semi-natural areas, whose connections are modelled according to specific variables, in order to deliver an equal distribution of public services for enhancing the quality of life as well as a wide range of ecosystem services”.

Silicon nanophotonics for scalable quantum coherent feedback networks

International Nuclear Information System (INIS)

Sarovar, Mohan; Brif, Constantin; Soh, Daniel B.S.; Cox, Jonathan; DeRose, Christopher T.; Camacho, Ryan; Davids, Paul

2016-01-01

The emergence of coherent quantum feedback control (CQFC) as a new paradigm for precise manipulation of dynamics of complex quantum systems has led to the development of efficient theoretical modeling and simulation tools and opened avenues for new practical implementations. This work explores the applicability of the integrated silicon photonics platform for implementing scalable CQFC networks. If proven successful, on-chip implementations of these networks would provide scalable and efficient nanophotonic components for autonomous quantum information processing devices and ultra-low-power optical processing systems at telecommunications wavelengths. We analyze the strengths of the silicon photonics platform for CQFC applications and identify the key challenges to both the theoretical formalism and experimental implementations. In particular, we determine specific extensions to the theoretical CQFC framework (which was originally developed with bulk-optics implementations in mind), required to make it fully applicable to modeling of linear and nonlinear integrated optics networks. We also report the results of a preliminary experiment that studied the performance of an in situ controllable silicon nanophotonic network of two coupled cavities and analyze the properties of this device using the CQFC formalism. (orig.)

Silicon nanophotonics for scalable quantum coherent feedback networks

Energy Technology Data Exchange (ETDEWEB)

Sarovar, Mohan; Brif, Constantin [Sandia National Laboratories, Livermore, CA (United States); Soh, Daniel B.S. [Sandia National Laboratories, Livermore, CA (United States); Stanford University, Edward L. Ginzton Laboratory, Stanford, CA (United States); Cox, Jonathan; DeRose, Christopher T.; Camacho, Ryan; Davids, Paul [Sandia National Laboratories, Albuquerque, NM (United States)

2016-12-15

The emergence of coherent quantum feedback control (CQFC) as a new paradigm for precise manipulation of dynamics of complex quantum systems has led to the development of efficient theoretical modeling and simulation tools and opened avenues for new practical implementations. This work explores the applicability of the integrated silicon photonics platform for implementing scalable CQFC networks. If proven successful, on-chip implementations of these networks would provide scalable and efficient nanophotonic components for autonomous quantum information processing devices and ultra-low-power optical processing systems at telecommunications wavelengths. We analyze the strengths of the silicon photonics platform for CQFC applications and identify the key challenges to both the theoretical formalism and experimental implementations. In particular, we determine specific extensions to the theoretical CQFC framework (which was originally developed with bulk-optics implementations in mind), required to make it fully applicable to modeling of linear and nonlinear integrated optics networks. We also report the results of a preliminary experiment that studied the performance of an in situ controllable silicon nanophotonic network of two coupled cavities and analyze the properties of this device using the CQFC formalism. (orig.)

Studying Pensions Funds Through an Infinite Servers Nodes Network: A Theoretical Problem

International Nuclear Information System (INIS)

Ferreira, M A M; Andrade, M; Filipe, J A

2012-01-01

This study intends to present a representation of a pensions fund through a stochastic network with two infinite servers nodes. With this representation it is allowed to deduce an equilibrium condition of the system with basis on the identity of the random rates expected values, for which the contributions arrive to the fund and the pensions are paid by the fund. In our study a stochastic network is constructed where traffic is represented. This network allows to study the equilibrium in the system and it is admissible to get a balance to a pensions fund. A specific case is studied. When the arrivals from outside at nodes A and B are according to a Poisson process, with rates λ A and λ B , respectively, the system may be seen as a two nodes network where the first node is a M/G/∞ queue and second a M t /G/∞ queue. For this case in the long term the conditions of equilibrium are as follows: m A λ A α A = m B (ρλ A + λ B )α B . In this formula it is established a relationship among the two nodes. Several examples are given in the study.

Tinnitus: Network pathophysiology-network pharmacology

Directory of Open Access Journals (Sweden)

Ana Belen eElgoyhen

2012-01-01

Full Text Available Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for 1 in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single FDA-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in central nervous system pathologies is changing from that of magic bullets that target individual chemoreceptors or disease-causing genes into that of magic shotguns, promiscuous or dirty drugs that target disease-causing networks, also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy.

Tinnitus: network pathophysiology-network pharmacology.

Science.gov (United States)

Elgoyhen, Ana B; Langguth, Berthold; Vanneste, Sven; De Ridder, Dirk

2012-01-01

Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for one in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single Food and Drug Administration (FDA)-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system (CNS) disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in CNS pathologies is changing from that of "magic bullets" that target individual chemoreceptors or "disease-causing genes" into that of "magic shotguns," "promiscuous" or "dirty drugs" that target "disease-causing networks," also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy.

Public Management and Educational Performance: The impact of Managerial Networking

NARCIS (Netherlands)

O'Toole, Laurence J.; Meier, Kenneth J.

2003-01-01

Policies are implemented in complex networks of organizations and target populations. Effective action often requires managers to deal with an array of actors to procure resources, build support, coproduce results, and overcome obstacles to implementation. Few large-n studies have examined the

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

Science.gov (United States)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network

Directory of Open Access Journals (Sweden)

Jundong Chen

2014-05-01

Full Text Available Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the privacy strategies of these users, very little work has been done in analyzing how these factors influence each other and collectively contribute towards the users’ privacy strategies. In this paper, we analyze the influence of attribute importance, benefit, risk and network topology on the users’ attribute disclosure behavior by introducing a weighted evolutionary game model. Results show that: irrespective of risk, users aremore likely to reveal theirmost important attributes than their least important attributes; when the users’ range of influence is increased, the risk factor plays a smaller role in attribute disclosure; the network topology exhibits a considerable effect on the privacy in an environment with risk.

Thin Watts-Strogatz networks.

Science.gov (United States)

de Moura, Alessandro P S

2006-01-01

A modified version of the Watts-Strogatz (WS) network model is proposed, in which the number of shortcuts scales with the network size N as Nalpha, with alpha infinity, whereas in the original WS model, this ratio is constant. We call such networks "thin Watts-Strogatz networks." We show that even though the fraction of shortcuts becomes vanishingly small for large networks, they still cause a kind of small-world effect, in the sense that the length L of the network increases sublinearly with the size. We develop a mean-field theory for these networks, which predicts that the length scales as N1-alpha ln N for large N. We also study how a search using only local information works in thin WS networks. We find that the search performance is enhanced compared to the regular network, and we predict that the search time tau scales as N1-alpha/2. These theoretical results are tested using numerical simulations. We comment on the possible relevance of thin WS networks for the design of high-performance low-cost communication networks.

Value Creation in Cryptocurrency Networks

DEFF Research Database (Denmark)

Kazan, Erol; Tan, Chee-Wee; Lim, Eric T. K.

2015-01-01

Cryptocurrency networks have given birth to a diversity of start-ups and attracted a huge influx of venture capital to invest in these start-ups for creating and capturing value within and between such networks. Synthesizing strategic management and information systems (IS) literature, this study...... advances a unified theoretical framework for identifying and investigating how cryptocurrency companies configure value through digital business models. This framework is then employed, via multiple case studies, to examine digital business models of companies within the bitcoin network. Findings suggest...... on value configurations and digital businesses models within the emerging and increasingly pervasive domain of cryptocurrency networks....

Co-operation between Large Enterprises (LE’s and SME’s: an Approach to Overcome the Stage Internationalization Process

Directory of Open Access Journals (Sweden)

Eurico Brilhante Dias

2014-12-01

Full Text Available Many companies are using their networks in order to overcome psychic distance – liability of foreignness – and liability of outsidership; and networks at domestic markets can be a base in which SMEs can find a lever to get a rapid internationalization process. Regarding this topic has been developed a case study in the Polish market, where a local retailer (“Biedronka” owned by a Portuguese group (“Jerónimo Martins” is offering Portuguese products. In order to apply a constructivist methodology, using the case study method, five SMEs where selected in order to understand if co-operation between these companies and a LE (Large Enterprise would be a way in order to overcome the liability of foreignness and the liability of outsidership. It was also our purpose the understanding of which are the main issues that promote insidership and also the promotion of a rapid internationalization. Our conclusions have shown a LE as a source of institutional and market-specific knowledge, and regarding this last type of knowledge, as source of opportunities, and also how a SME with internationalization knowledge, an international focus and adaptation skills (in order to adapt products and prices can introduce in a co-operative international venture, in far psychic markets, the ingredients needed to get a successful and rapid entry in a foreign market. Trust as a resource, accumulated during lasting relationships in the domestic market, has been shown as a basic requirement to develop these co-operative approaches in international markets.

Quantum state transfer and network engineering

International Nuclear Information System (INIS)

Nikolopoulos, Georgios M.; Jex, Igor

2014-01-01

Presents the basics of large-scale quantum information processing and networking. Covers most aspects of the problems of state transfer and quantum network engineering. Reflects the interdisciplinary nature of the field. Presents various theoretical approaches as well as possible implementations and related experiments. Faithful communication is a necessary precondition for large-scale quantum information processing and networking, irrespective of the physical platform. Thus, the problems of quantum-state transfer and quantum-network engineering have attracted enormous interest over the last years, and constitute one of the most active areas of research in quantum information processing. The present volume introduces the reader to fundamental concepts and various aspects of this exciting research area, including links to other related areas and problems. The implementation of state-transfer schemes and the engineering of quantum networks are discussed in the framework of various quantum optical and condensed matter systems, emphasizing the interdisciplinary character of the research area. Each chapter is a review of theoretical or experimental achievements on a particular topic, written by leading scientists in the field. The volume aims at both newcomers as well as experienced researchers.

The QKD network: model and routing scheme

Science.gov (United States)

Yang, Chao; Zhang, Hongqi; Su, Jinhai

2017-11-01

Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.

Location-aware network operation for cloud radio access network

KAUST Repository

Wang, Fanggang

2017-06-20

One of the major challenges in effectively operating a cloud radio access network (C-RAN) is the excessive overhead signaling and computation load that scale rapidly with the size of the network. In this paper, the exploitation of location information of the mobile devices is proposed to address this challenge. We consider an approach in which location-assisted channel state information (CSI) acquisition methods are introduced to complement conventional pilot-based CSI acquisition methods and avoid excessive overhead signaling. A low-complexity algorithm is designed to maximize the sum rate. An adaptive algorithm is also proposed to address the uncertainty issue in CSI acquisition. Both theoretical and numerical analyses show that location information provides a new dimension to improve throughput for next-generation massive cooperative networks.

Information-theoretic metamodel of organizational evolution

Science.gov (United States)

Sepulveda, Alfredo

2011-12-01

Social organizations are abstractly modeled by holarchies---self-similar connected networks---and intelligent complex adaptive multiagent systems---large networks of autonomous reasoning agents interacting via scaled processes. However, little is known of how information shapes evolution in such organizations, a gap that can lead to misleading analytics. The research problem addressed in this study was the ineffective manner in which classical model-predict-control methods used in business analytics attempt to define organization evolution. The purpose of the study was to construct an effective metamodel for organization evolution based on a proposed complex adaptive structure---the info-holarchy. Theoretical foundations of this study were holarchies, complex adaptive systems, evolutionary theory, and quantum mechanics, among other recently developed physical and information theories. Research questions addressed how information evolution patterns gleamed from the study's inductive metamodel more aptly explained volatility in organization. In this study, a hybrid grounded theory based on abstract inductive extensions of information theories was utilized as the research methodology. An overarching heuristic metamodel was framed from the theoretical analysis of the properties of these extension theories and applied to business, neural, and computational entities. This metamodel resulted in the synthesis of a metaphor for, and generalization of organization evolution, serving as the recommended and appropriate analytical tool to view business dynamics for future applications. This study may manifest positive social change through a fundamental understanding of complexity in business from general information theories, resulting in more effective management.

Additive Feed Forward Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1999-01-01

This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

Topological Vulnerability Evaluation Model Based on Fractal Dimension of Complex Networks.

Directory of Open Access Journals (Sweden)

Li Gou

Full Text Available With an increasing emphasis on network security, much more attentions have been attracted to the vulnerability of complex networks. In this paper, the fractal dimension, which can reflect space-filling capacity of networks, is redefined as the origin moment of the edge betweenness to obtain a more reasonable evaluation of vulnerability. The proposed model combining multiple evaluation indexes not only overcomes the shortage of average edge betweenness's failing to evaluate vulnerability of some special networks, but also characterizes the topological structure and highlights the space-filling capacity of networks. The applications to six US airline networks illustrate the practicality and effectiveness of our proposed method, and the comparisons with three other commonly used methods further validate the superiority of our proposed method.

Neural electrical activity and neural network growth.

Science.gov (United States)

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

International Nuclear Information System (INIS)

Ortiz R, J. M.; Martinez B, M. R.; Vega C, H. R.; Gallego D, E.; Lorente F, A.; Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E.

2011-01-01

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

Parameter learning in MTE networks using incomplete data

DEFF Research Database (Denmark)

Fernández, Antonio; Langseth, Helge; Nielsen, Thomas Dyhre

a considerable computational burden as well as the inability to handle missing values in the training data. In this paper we describe an EM-based algorithm for learning the maximum likelihood parameters of an MTE network when confronted with incomplete data. In order to overcome the computational difficulties we......Bayesian networks with mixtures of truncated exponentials (MTEs) are gaining popularity as a flexible modelling framework for hybrid domains. MTEs support efficient and exact inference algorithms, but estimating an MTE from data has turned out to be a difficult task. Current methods suffer from...

A Game Theoretic Framework for Bandwidth Allocation and Pricing in Federated Wireless Networks

Science.gov (United States)

Gu, Bo; Yamori, Kyoko; Xu, Sugang; Tanaka, Yoshiaki

With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.

Mapping social networks in software process improvement

DEFF Research Database (Denmark)

Tjørnehøj, Gitte; Nielsen, Peter Axel

2005-01-01

Software process improvement in small, agile organizations is often problematic. Model-based approaches seem to overlook problems. We have been seeking an alternative approach to overcome this through action research. Here we report on a piece of action research from which we developed an approach...... to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...... software process improvement....

Anticipatory Cognitive Systems: a Theoretical Model

Science.gov (United States)

Terenzi, Graziano

This paper deals with the problem of understanding anticipation in biological and cognitive systems. It is argued that a physical theory can be considered as biologically plausible only if it incorporates the ability to describe systems which exhibit anticipatory behaviors. The paper introduces a cognitive level description of anticipation and provides a simple theoretical characterization of anticipatory systems on this level. Specifically, a simple model of a formal anticipatory neuron and a model (i.e. the τ-mirror architecture) of an anticipatory neural network which is based on the former are introduced and discussed. The basic feature of this architecture is that a part of the network learns to represent the behavior of the other part over time, thus constructing an implicit model of its own functioning. As a consequence, the network is capable of self-representation; anticipation, on a oscopic level, is nothing but a consequence of anticipation on a microscopic level. Some learning algorithms are also discussed together with related experimental tasks and possible integrations. The outcome of the paper is a formal characterization of anticipation in cognitive systems which aims at being incorporated in a comprehensive and more general physical theory.

Diagnostic Neural Network Systems for the Electronic Circuits

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Neural Networks is one of the most important artificial intelligent approaches for solving the diagnostic processes. This research concerns with uses the neural networks for diagnosis of the electronic circuits. Modern electronic systems contain both the analog and digital circuits. But, diagnosis of the analog circuits suffers from great complexity due to their nonlinearity. To overcome this problem, the proposed system introduces a diagnostic system that uses the neural network to diagnose both the digital and analog circuits. So, it can face the new requirements for the modern electronic systems. A fault dictionary method was implemented in the system. Experimental results are presented on three electronic systems. They are: artificial kidney, wireless network and personal computer systems. The proposed system has improved the performance of the diagnostic systems when applied for these practical cases

Governance and strategy of entrepreneurial networks: an introduction

NARCIS (Netherlands)

J. Windsperger (Josef); G.W.J. Hendrikse (George); G. Cliquet (Gérard); T. Ehrmann (Thomas)

2017-01-01

textabstractThis special issue focuses on empirical and theoretical papers that help us to better understand the strategy and governance of entrepreneurial networks, such as franchise chains, alliances, and cooperative networks. The following central themes are covered: (I) Which formal governance

Rumor propagation with heterogeneous transmission in social networks

Science.gov (United States)

Vega-Oliveros, Didier A.; Costa, Luciano da F.; Rodrigues, Francisco A.

2017-02-01

Rumor models consider that information transmission occurs with the same probability between each pair of nodes. However, this assumption is not observed in social networks, which contain influential spreaders. To overcome this limitation, we assume that central individuals have a higher capacity to convince their neighbors than peripheral subjects. From extensive numerical simulations we find that spreading is improved in scale-free networks when the transmission probability is proportional to the PageRank, degree, and betweenness centrality. In addition, the results suggest that spreading can be controlled by adjusting the transmission probabilities of the most central nodes. Our results provide a conceptual framework for understanding the interplay between rumor propagation and heterogeneous transmission in social networks.

Multi-level deep supervised networks for retinal vessel segmentation.

Science.gov (United States)

Mo, Juan; Zhang, Lei

2017-12-01

Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

THEORETICAL ASPECTS OF INFORMATIONAL SERVICES REGIONAL MARKET EFFECTIVE DEVELOPMENT

Directory of Open Access Journals (Sweden)

I.N. Korabejnikov

2008-12-01

Full Text Available The peculiarities and priorities of the informational services regional market formation as a part of network model of the economic development are described in this article. The authors present the classification of the factors which have an influence on the effectiveness of the informational services regional market development. Theoretical aspects of the informational services regional market effective development are shown.

An evolving network model with community structure

International Nuclear Information System (INIS)

Li Chunguang; Maini, Philip K

2005-01-01

Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

Understanding Event-based Business Networks

OpenAIRE

2008-01-01

Abstract This article deals with the temporality in business networks. Marketing as networks approach stresses interaction processes and interdependence among actors noting that business markets are mainly socially constructed. The approach has increased our understanding of business marketing but further attention for theory development and empirical validation is needed. Theoretical foundations of the approach are conceptually analysed here, taking time and timing into particular...

Artificial neural networks in neutron dosimetry

Energy Technology Data Exchange (ETDEWEB)

Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado, G.A.; Perales M, W.A.; Robles R, J.A. [Unidades Academicas de Estudios Nucleares, UAZ, A.P. 336, 98000 Zacatecas (Mexico); Gallego, E.; Lorente, A. [Depto. de Ingenieria Nuclear, Universidad Politecnica de Madrid, (Spain)

2005-07-01

An artificial neural network has been designed to obtain the neutron doses using only the Bonner spheres spectrometer's count rates. Ambient, personal and effective neutron doses were included. 187 neutron spectra were utilized to calculate the Bonner count rates and the neutron doses. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra, UTA4 response matrix and fluence-to-dose coefficients were used to calculate the count rates in Bonner spheres spectrometer and the doses. Count rates were used as input and the respective doses were used as output during neural network training. Training and testing was carried out in Mat lab environment. The artificial neural network performance was evaluated using the {chi}{sup 2}- test, where the original and calculated doses were compared. The use of Artificial Neural Networks in neutron dosimetry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

Artificial neural networks in neutron dosimetry

International Nuclear Information System (INIS)

Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado, G.A.; Perales M, W.A.; Robles R, J.A.; Gallego, E.; Lorente, A.

2005-01-01

An artificial neural network has been designed to obtain the neutron doses using only the Bonner spheres spectrometer's count rates. Ambient, personal and effective neutron doses were included. 187 neutron spectra were utilized to calculate the Bonner count rates and the neutron doses. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra, UTA4 response matrix and fluence-to-dose coefficients were used to calculate the count rates in Bonner spheres spectrometer and the doses. Count rates were used as input and the respective doses were used as output during neural network training. Training and testing was carried out in Mat lab environment. The artificial neural network performance was evaluated using the χ 2 - test, where the original and calculated doses were compared. The use of Artificial Neural Networks in neutron dosimetry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

Overcoming the Challenges of Co-creation

Science.gov (United States)

Pandya, R.; Udu-gama, N.; Goodwin, M.; Otellini, P.

2016-12-01

There is growing interest in co-creation, especially for community-related issues like climate change, resilience, pollution, and environmental justice. Nevertheless, co-creation is still not mainstream practice in either geosciences or the world of decision-makers. This presents many challenges. On the science side, challenges include a paucity of training opportunities, lack of funding for co-creation, difficulty publishing or otherwise getting credit for the effort, and a perceived lack of prestige compared to theoretical research. On the community side, parallel challenges include a lack of experience working with scientists or thinking about geoscience's relevance to community issues, tight budgets and competing priorities, the need for outputs beyond publications, and the difficulty including science among a range of factors. Additionally, scientists and community leaders often work across public and private sectors and must navigate different approaches to data, privacy, and accountability. We'll use this session to explore opportunities to overcome the challenges of co-creation. Systems thinking suggests a range of approaches: enabling individuals, reducing specific challenges, changing the relationship between the elements of the systems, and changing the goals or mindsets of the systems - each more powerful than the last. For example, mentoring and coaching enables individuals, and pro-bono work eases the challenge of getting professional credit. New modes of output, like plain language abstracts, change the relationship between publications and other outputs. We can work on changing mindsets by publicizing and celebrating individual successes. With more effort and impact, we can build collaborations in the collective impact model, where we bring scientific and community organizations together around a common agenda and shared measurement. Building on these examples, we will use this session to collect strategies and opportunities from all participants.

A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

Directory of Open Access Journals (Sweden)

Rutger Goekoop

Full Text Available INTRODUCTION: The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. AIM: To examine the ability of network community detection (NCD to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. METHODS: 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS. Principal component analysis (PCA was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS. An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS was optimized using a previously published technique. RESULTS: In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "Depression", "Mania", "Anxiety", "Psychosis", "Retardation", and "Behavioral Disorganization". Network metrics were used to quantify the continuities between the elementary syndromes. CONCLUSION: We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a 'Psychopathology Web'. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.

Overcoming challenges

Medline Plus

Full Text Available ... It takes a village: Building your breastfeeding support network How to get your family on board with breastfeeding African-American celebrity moms who ... inquiries Social media About Us Who we are What we ...

Neural Network to Solve Concave Games

OpenAIRE

Liu, Zixin; Wang, Nengfa

2014-01-01

The issue on neural network method to solve concave games is concerned. Combined with variational inequality, Ky Fan inequality, and projection equation, concave games are transformed into a neural network model. On the basis of the Lyapunov stable theory, some stability results are also given. Finally, two classic games’ simulation results are given to illustrate the theoretical results.

Species richness in soil bacterial communities: a proposed approach to overcome sample size bias.

Science.gov (United States)

Youssef, Noha H; Elshahed, Mostafa S

2008-09-01

Estimates of species richness based on 16S rRNA gene clone libraries are increasingly utilized to gauge the level of bacterial diversity within various ecosystems. However, previous studies have indicated that regardless of the utilized approach, species richness estimates obtained are dependent on the size of the analyzed clone libraries. We here propose an approach to overcome sample size bias in species richness estimates in complex microbial communities. Parametric (Maximum likelihood-based and rarefaction curve-based) and non-parametric approaches were used to estimate species richness in a library of 13,001 near full-length 16S rRNA clones derived from soil, as well as in multiple subsets of the original library. Species richness estimates obtained increased with the increase in library size. To obtain a sample size-unbiased estimate of species richness, we calculated the theoretical clone library sizes required to encounter the estimated species richness at various clone library sizes, used curve fitting to determine the theoretical clone library size required to encounter the "true" species richness, and subsequently determined the corresponding sample size-unbiased species richness value. Using this approach, sample size-unbiased estimates of 17,230, 15,571, and 33,912 were obtained for the ML-based, rarefaction curve-based, and ACE-1 estimators, respectively, compared to bias-uncorrected values of 15,009, 11,913, and 20,909.

Overcoming challenges

Medline Plus

Full Text Available ... your breastfeeding support network How to get your family on board with breastfeeding African-American celebrity moms ... health care Get health insurance Get help with family planning Get help with mental health Find girls' ...

Short term memory in echo state networks

OpenAIRE

Jaeger, H.

2001-01-01

The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

Overcoming Barriers in Working with Families

Science.gov (United States)

Heru, Alison M.; Drury, Laura

2006-01-01

Objective: The Accreditation Council for Graduate Medical Education and the Residency Review Committee for psychiatry outline the expected competencies for residents. These competencies include working with families. This article describes barriers that residents face when working with families, and offers ways to overcome these barriers. Method:…

Robustness and Vulnerability of Networks with Dynamical Dependency Groups.

Science.gov (United States)

Bai, Ya-Nan; Huang, Ning; Wang, Lei; Wu, Zhi-Xi

2016-11-28

The dependency property and self-recovery of failure nodes both have great effects on the robustness of networks during the cascading process. Existing investigations focused mainly on the failure mechanism of static dependency groups without considering the time-dependency of interdependent nodes and the recovery mechanism in reality. In this study, we present an evolving network model consisting of failure mechanisms and a recovery mechanism to explore network robustness, where the dependency relations among nodes vary over time. Based on generating function techniques, we provide an analytical framework for random networks with arbitrary degree distribution. In particular, we theoretically find that an abrupt percolation transition exists corresponding to the dynamical dependency groups for a wide range of topologies after initial random removal. Moreover, when the abrupt transition point is above the failure threshold of dependency groups, the evolving network with the larger dependency groups is more vulnerable; when below it, the larger dependency groups make the network more robust. Numerical simulations employing the Erdős-Rényi network and Barabási-Albert scale free network are performed to validate our theoretical results.

Power Laws, Scale-Free Networks and Genome Biology

CERN Document Server

Koonin, Eugene V; Karev, Georgy P

2006-01-01

Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for disco...

Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

Science.gov (United States)

Kiang, Richard K.

1992-01-01

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

A random walk evolution model of wireless sensor networks and virus spreading

International Nuclear Information System (INIS)

Wang Ya-Qi; Yang Xiao-Yuan

2013-01-01

In this paper, considering both cluster heads and sensor nodes, we propose a novel evolving a network model based on a random walk to study the fault tolerance decrease of wireless sensor networks (WSNs) due to node failure, and discuss the spreading dynamic behavior of viruses in the evolution model. A theoretical analysis shows that the WSN generated by such an evolution model not only has a strong fault tolerance, but also can dynamically balance the energy loss of the entire network. It is also found that although the increase of the density of cluster heads in the network reduces the network efficiency, it can effectively inhibit the spread of viruses. In addition, the heterogeneity of the network improves the network efficiency and enhances the virus prevalence. We confirm all the theoretical results with sufficient numerical simulations. (general)

Adolescents' Self-Efficacy to Overcome Barriers to Physical Activity Scale

Science.gov (United States)

Dwyer, John J. M.; Chulak, Tala; Maitland, Scott; Allison, Kenneth R.; Lysy, Daria C.; Faulkner, Guy E. J.; Sheeshka, Judy

2012-01-01

This paper describes a revised measure of self-efficacy to overcome barriers to moderate and vigorous physical activity in a sample of 484 high school students in Toronto, Ontario. The students had a mean age of 15.3 years. Principal axis factoring with oblique rotation yielded five factors: self-efficacy to overcome internal, harassment, physical…

Intelligent neural network diagnostic system

International Nuclear Information System (INIS)

Mohamed, A.H.

2010-01-01

Recently, artificial neural network (ANN) has made a significant mark in the domain of diagnostic applications. Neural networks are used to implement complex non-linear mappings (functions) using simple elementary units interrelated through connections with adaptive weights. The performance of the ANN is mainly depending on their topology structure and weights. Some systems have been developed using genetic algorithm (GA) to optimize the topology of the ANN. But, they suffer from some limitations. They are : (1) The computation time requires for training the ANN several time reaching for the average weight required, (2) Slowness of GA for optimization process and (3) Fitness noise appeared in the optimization of ANN. This research suggests new issues to overcome these limitations for finding optimal neural network architectures to learn particular problems. This proposed methodology is used to develop a diagnostic neural network system. It has been applied for a 600 MW turbo-generator as a case of real complex systems. The proposed system has proved its significant performance compared to two common methods used in the diagnostic applications.

Building functional networks of spiking model neurons.

Science.gov (United States)

Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

2016-03-01

Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

Artificial neural network modelling

CERN Document Server

Samarasinghe, Sandhya

2016-01-01

This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

Advances in network systems architectures, security, and applications

CERN Document Server

Awad, Ali; Furtak, Janusz; Legierski, Jarosław

2017-01-01

This book provides the reader with a comprehensive selection of cutting–edge algorithms, technologies, and applications. The volume offers new insights into a range of fundamentally important topics in network architectures, network security, and network applications. It serves as a reference for researchers and practitioners by featuring research contributions exemplifying research done in the field of network systems. In addition, the book highlights several key topics in both theoretical and practical aspects of networking. These include wireless sensor networks, performance of TCP connections in mobile networks, photonic data transport networks, security policies, credentials management, data encryption for network transmission, risk management, live TV services, and multicore energy harvesting in distributed systems. .

Impulsive generalized function synchronization of complex dynamical networks

International Nuclear Information System (INIS)

Zhang, Qunjiao; Chen, Juan; Wan, Li

2013-01-01

This Letter investigates generalized function synchronization of continuous and discrete complex networks by impulsive control. By constructing the reasonable corresponding impulsively controlled response networks, some criteria and corollaries are derived for the generalized function synchronization between the impulsively controlled complex networks, continuous and discrete networks are both included. Furthermore, the generalized linear synchronization and nonlinear synchronization are respectively illustrated by several examples. All the numerical simulations demonstrate the correctness of the theoretical results

Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

KAUST Repository

Alsibyani, Hassan M.

2018-01-01

. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing

LIFE-LONG EDUCATION AS A RESOURCE TO OVERCOME THE PSYCHOLOGICAL BARRIERS IN THE PROCESS OF PROFESSIONAL DEVELOPMENT OF THE INDIVIDUAL

Directory of Open Access Journals (Sweden)

Elvira E. Symanyuk

2015-01-01

Full Text Available The current situation in Russia is characterized by rapid modernization and development of various spheres of activity. Intense pace of social and economic development of some countries, the processes of globalization, increasing competition due to the open labor market, act as a call to the level of personal and professional specialist development, to its ability for properly planning activities, mobility reconstructed in a rapidly changing professional situation, develop innovative technology and build their professional career. The aim of this paper is a theoretical justification of continuing education as a resource for overcoming the psychological barriers in the process of professional development of the individual. Career stagnation objectively arising in the process of professionalization, the reduction of professional expectations and values mismatch personal and professional characteristics with the requirements of current professional situation are considered by the authors as psychological barriers to the professional development of an individual. Methods. The authors used theoretical methods of research – analysis of the literature on the study, the synthesis of the conceptual issues of the classification. The paper presents an analysis of the Russian and foreign theories on the origin and development of psychological barriers. Results. The terms «psychological barrier» and «overcoming the behavior» are specified. The psychological professional-development barriers of the person are highlighted and classified: professional degradation, deterioration of professional and psychological health of individuals. The resources for overcoming the psychological barriers are defined; the integral role is assigned to continuing education and self-education. As both Russian and international experience shows, adult education is becoming one of the leading forms of social activity having a wide array of technologies, methods and

Facilitating value co-creation in networks

DEFF Research Database (Denmark)

Rasmussen, Mette Apollo

participants in varied ways come to grasp the meaning of networking. The dissertation draws on insights from the Service-Dominant (S-D) Logic to explain how networks can be seen as spheres for value co-creation. Co-creation as a theoretical construct has evolved from varied streams of service marketing...... of networking. The concept of “imaginative value” (Beckert, 2011) is used to explain the oscillating behaviors observed in the two networks. Imaginative value can be defined as symbolic value that actors ascribe to an object, in this case the network. I argue that the group practices in the networks led......The dissertation investigates through two ethnographic case studies how value co-creation takes place in inter-organizational networks that have been facilitated by a municipality. The contribution of the study to business network research is the emphasis on development phases of networks...

The role of guanxi networks in the performance of women-led firms in China

OpenAIRE

Scott, Jonathan; Harrison, Richard; Hussain, Javed; Millman, Cindy

2012-01-01

Purpose – This exploratory study aims to examine how knowledge acquired via guanxi (networks and connections) is enabling women in China to overcome a number of significant barriers and challenges in order to start and grow successful businesses.\\ud \\ud Design/methodology/approach – The authors undertook two in-depth interviews to qualitatively investigate the use of guanxi as a means of overcoming various barriers faced by Chinese women in establishing and growing their businesses.\\ud \\ud Fi...

Overcoming Innocents' Naiveté: Pre-interrogation Decision-making Among Innocent Suspects.

Science.gov (United States)

Scherr, Kyle C; Alberts, Kimberly M; Franks, Andrew S; Hawkins, Ian

2016-07-01

Suspects, especially innocent ones, are highly susceptible to waiving their interrogation rights. This research tested the ability of two strategies to overcome innocent suspects' willingness to waive their rights. One strategy was based on the social influence of scarcity (i.e., not constraining the pre-interrogation time limit). The other strategy focused on disrupting individuals' cognitive fluency during the decision-making process (i.e., violating their induced expectation of offering a waiver). Disrupting innocent individuals' cognitive fluency increased their willingness to invoke their rights and, notably, was not qualified by interactions with any other factors. However, scarcity did not influence individuals' pre-interrogation decision-making. Results also further established the association between innocent individuals' naïve mindset and their willingness to waive their rights - specifically, innocents' willingness to waive their rights increased with the strength of their just world beliefs. The theoretical and applied implications of these findings are discussed. The importance and benefit of reforming pre-interrogation protocols using fair and feasible strategies that would disrupt suspects' cognitive fluency are emphasized. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Social Networking and Academic Performance: A Review

Science.gov (United States)

Doleck, Tenzin; Lajoie, Susanne

2018-01-01

The ubiquitous use of social networking sites by students and the potential impacts of such use on academic performance are of both theoretical and practical importance. Hence, this paper addresses the question: how does the use of social networking sites influence academic performance? The present review synthesizes the empirical findings of the…

Successful Writing: Five Roadblocks to Overcome

Science.gov (United States)

King, Kathleen P.

2013-01-01

This article provides essential strategies to be more successful in one of the major roles in academia: writing. Most academics struggle with roadblocks in their writing process. We are forever battling to complete research articles, manuscripts, grant proposals or other documents. The strategies and perspective shared here help overcome several…

Difference-theoretical Analysis of Aesthetic Media and Forms

Directory of Open Access Journals (Sweden)

Franz Kasper Krönig

2018-04-01

Full Text Available The general medium/form-difference-theory as proposed by Fritz Heider (cf. Heider, 1959 has been seized on by the sociological systems theory as an epistemological and heuristic basis of such a generality that it can be applied to virtually all conceivable fields of research. One could arguably speak of a new paradigm that overcomes traditional differences such as subject/object and cause/effect. This approach has been applied to all types of art, and various research questions in the fields of aesthetics and art theory. This paper proposes a differentiation and categorisation of aesthetic media and forms in order to lay the groundwork for art criticism on a third way between subjective appreciation and objective reasoning. Musical examples demonstrate the applicability of the medium/form-difference-theoretical approach for the aesthetics of music and music criticism.

Virus spreading in wireless sensor networks with a medium access control mechanism

International Nuclear Information System (INIS)

Wang Ya-Qi; Yang Xiao-Yuan

2013-01-01

In this paper, an extended version of standard susceptible-infected (SI) model is proposed to consider the influence of a medium access control mechanism on virus spreading in wireless sensor networks. Theoretical analysis shows that the medium access control mechanism obviously reduces the density of infected nodes in the networks, which has been ignored in previous studies. It is also found that by increasing the network node density or node communication radius greatly increases the number of infected nodes. The theoretical results are confirmed by numerical simulations. (general)

Designing Caregiver-Implemented Shared-Reading Interventions to Overcome Implementation Barriers

Science.gov (United States)

Logan, Jessica R.; Damschroder, Laura

2015-01-01

Purpose This study presents an application of the theoretical domains framework (TDF; Michie et al., 2005), an integrative framework drawing on behavior-change theories, to speech-language pathology. Methods A multistep procedure was used to identify barriers affecting caregivers' implementation of shared-reading interventions with their children with language impairment (LI). The authors examined caregiver-level data corresponding to implementation issues from two randomized controlled trials and mapped these to domains in the TDF as well as empirically validated behavior-change techniques. Results Four barriers to implementation were identified as potentially affecting caregivers' implementation: time pressures, reading difficulties, discomfort with reading, and lack of awareness of benefits. These were mapped to 3 TDF domains: intentions, beliefs about capabilities, and skills. In turn, 4 behavior-change techniques were identified as potential vehicles for affecting these domains: reward, feedback, model, and encourage. An ongoing study is described that is determining the effects of these techniques for improving caregivers' implementation of a shared-reading intervention. Conclusions A description of the steps to identifying barriers to implementation, in conjunction with an ongoing experiment that will explicitly determine whether behavior-change techniques affect these barriers, provides a model for how implementation science can be used to identify and overcome implementation barriers in the treatment of communication disorders. PMID:26262941

Learning in Neural Networks: VLSI Implementation Strategies

Science.gov (United States)

Duong, Tuan Anh

1995-01-01

Fully-parallel hardware neural network implementations may be applied to high-speed recognition, classification, and mapping tasks in areas such as vision, or can be used as low-cost self-contained units for tasks such as error detection in mechanical systems (e.g. autos). Learning is required not only to satisfy application requirements, but also to overcome hardware-imposed limitations such as reduced dynamic range of connections.

Neutron spectrometry with artificial neural networks

International Nuclear Information System (INIS)

Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Rodriguez, J.M.; Mercado S, G.A.; Iniguez de la Torre Bayo, M.P.; Barquero, R.; Arteaga A, T.

2005-01-01

An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using 129 neutron spectra. These include isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra from mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-bin ned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and the respective spectrum was used as output during neural network training. After training the network was tested with the Bonner spheres count rates produced by a set of neutron spectra. This set contains data used during network training as well as data not used. Training and testing was carried out in the Mat lab program. To verify the network unfolding performance the original and unfolded spectra were compared using the χ 2 -test and the total fluence ratios. The use of Artificial Neural Networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

The structural, connectomic and network covariance of the human brain.

Science.gov (United States)

Irimia, Andrei; Van Horn, John D

2013-02-01

Though it is widely appreciated that complex structural, functional and morphological relationships exist between distinct areas of the human cerebral cortex, the extent to which such relationships coincide remains insufficiently appreciated. Here we determine the extent to which correlations between brain regions are modulated by either structural, connectomic or network-theoretic properties using a structural neuroimaging data set of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volumes acquired from N=110 healthy human adults. To identify the linear relationships between all available pairs of regions, we use canonical correlation analysis to test whether a statistically significant correlation exists between each pair of cortical parcels as quantified via structural, connectomic or network-theoretic measures. In addition to this, we investigate (1) how each group of canonical variables (whether structural, connectomic or network-theoretic) contributes to the overall correlation and, additionally, (2) whether each individual variable makes a significant contribution to the test of the omnibus null hypothesis according to which no correlation between regions exists across subjects. We find that, although region-to-region correlations are extensively modulated by structural and connectomic measures, there are appreciable differences in how these two groups of measures drive inter-regional correlation patterns. Additionally, our results indicate that the network-theoretic properties of the cortex are strong modulators of region-to-region covariance. Our findings are useful for understanding the structural and connectomic relationship between various parts of the brain, and can inform theoretical and computational models of cortical information processing. Published by Elsevier Inc.

STRUCTURE AND COOPTATION IN ORGANIZATION NETWORK

Directory of Open Access Journals (Sweden)

Valéria Riscarolli

2007-10-01

Full Text Available Business executive are rethinking business concept, based on horizontalization principles. As so, most organizational functions are outsourced, leading the enterprise to build business through a network of organizations. Here we study the case of Cia Hering’s network of organizations, a leader in knit apparel segment in Latin America (IEMI, 2004, looking at the network’s structure and levels of cooptation. A theoretical model was used using Quinn et al. (2001 “sun ray” network structure as basis to analyze the case study. Main results indicate higher degree of structural conformity, but incipient degree of coopetation in the network.

Congested Link Inference Algorithms in Dynamic Routing IP Network

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Yu Chen

2017-01-01

Full Text Available The performance descending of current congested link inference algorithms is obviously in dynamic routing IP network, such as the most classical algorithm CLINK. To overcome this problem, based on the assumptions of Markov property and time homogeneity, we build a kind of Variable Structure Discrete Dynamic Bayesian (VSDDB network simplified model of dynamic routing IP network. Under the simplified VSDDB model, based on the Bayesian Maximum A Posteriori (BMAP and Rest Bayesian Network Model (RBNM, we proposed an Improved CLINK (ICLINK algorithm. Considering the concurrent phenomenon of multiple link congestion usually happens, we also proposed algorithm CLILRS (Congested Link Inference algorithm based on Lagrangian Relaxation Subgradient to infer the set of congested links. We validated our results by the experiments of analogy, simulation, and actual Internet.

Nonlinear adaptive inverse control via the unified model neural network

Science.gov (United States)

Jeng, Jin-Tsong; Lee, Tsu-Tian

1999-03-01

In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

Information Diffusion in Facebook-Like Social Networks Under Information Overload

Science.gov (United States)

Li, Pei; Xing, Kai; Wang, Dapeng; Zhang, Xin; Wang, Hui

2013-07-01

Research on social networks has received remarkable attention, since many people use social networks to broadcast information and stay connected with their friends. However, due to the information overload in social networks, it becomes increasingly difficult for users to find useful information. This paper takes Facebook-like social networks into account, and models the process of information diffusion under information overload. The term view scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated is proposed to characterize the information diffusion efficiency. Through theoretical analysis, we find that factors such as network structure and view scope number have no impact on the information diffusion efficiency, which is a surprising result. To verify the results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly.

Generalized neurofuzzy network modeling algorithms using Bézier-Bernstein polynomial functions and additive decomposition.

Science.gov (United States)

Hong, X; Harris, C J

2000-01-01

This paper introduces a new neurofuzzy model construction algorithm for nonlinear dynamic systems based upon basis functions that are Bézier-Bernstein polynomial functions. This paper is generalized in that it copes with n-dimensional inputs by utilising an additive decomposition construction to overcome the curse of dimensionality associated with high n. This new construction algorithm also introduces univariate Bézier-Bernstein polynomial functions for the completeness of the generalized procedure. Like the B-spline expansion based neurofuzzy systems, Bézier-Bernstein polynomial function based neurofuzzy networks hold desirable properties such as nonnegativity of the basis functions, unity of support, and interpretability of basis function as fuzzy membership functions, moreover with the additional advantages of structural parsimony and Delaunay input space partition, essentially overcoming the curse of dimensionality associated with conventional fuzzy and RBF networks. This new modeling network is based on additive decomposition approach together with two separate basis function formation approaches for both univariate and bivariate Bézier-Bernstein polynomial functions used in model construction. The overall network weights are then learnt using conventional least squares methods. Numerical examples are included to demonstrate the effectiveness of this new data based modeling approach.

Network dynamics and its relationships to topology and coupling structure in excitable complex networks

International Nuclear Information System (INIS)

Zhang Li-Sheng; Mi Yuan-Yuan; Gu Wei-Feng; Hu Gang

2014-01-01

All dynamic complex networks have two important aspects, pattern dynamics and network topology. Discovering different types of pattern dynamics and exploring how these dynamics depend on network topologies are tasks of both great theoretical importance and broad practical significance. In this paper we study the oscillatory behaviors of excitable complex networks (ECNs) and find some interesting dynamic behaviors of ECNs in oscillatory probability, the multiplicity of oscillatory attractors, period distribution, and different types of oscillatory patterns (e.g., periodic, quasiperiodic, and chaotic). In these aspects, we further explore strikingly sharp differences among network dynamics induced by different topologies (random or scale-free topologies) and different interaction structures (symmetric or asymmetric couplings). The mechanisms behind these differences are explained physically. (interdisciplinary physics and related areas of science and technology)

OVERCOMING THE ANTINOMIES OF HUMAN EXISTENCE: ONTOLOGY OF TRICKSTER

Directory of Open Access Journals (Sweden)

T. V. Danylova

2014-12-01

Full Text Available Purpose. This paper aims to study the ontological status of a trickster character in “Panchatantra” and its receptions. Methodology. The author has used analytical methodology of C. Levi-Strauss, C. Jung’s theory of archetypes, and hermeneutical methodology. Theoretical basis and results. Perception of the world in the form of a narrative is inherent in the very specifics of the human thinking. Among the most famous literary narratives that structured cultural experience of different nations are the framed story “Panchatantra” and its receptions “Kalilah and Dimnah” and “Stefanit and Ihnilat”. The framework of the analyzed text is the story about two jackals Karataka and Damanaka, Lion, and Bull. “Panchatantra” is deeply rooted in the animal epos, which is based on the totemic myth. Myths were created by primitive thinking that sought to systematize the world, to give it order through binary oppositions. Their hard core is “Life – Death” opposition. A myth deals with oppositions and seeks to neutralize them. Thus, a myth serves as the logical tool to overcome the fundamental contradictions. This is carried out by introducing a mediator. Two poles, two extreme points are unambiguous; ambiguity “occurs” at an intermediate stage only. Shift from one point to another is impossible directly – for this we need a mediator. In the given narrative the binary opposition “Life – Death” is replaced by its metaphor – Bull and Lion, herbivore (metaphor for life and carnivore (metaphor for death. These oppositions are mediated by Jackal (Karataka&Damanaka that feeds on carrion and has a dual nature. A mediator, which overcomes or at least mitigates the binary opposition, is seen as a compromise between herbivores and carnivores that embody the antinomy of life and death. This mediator is a trickster – bipolar character (good and evil at the same time. A trickster freely acts in unordered world of Chaos without Life �

Investigating DMOs through the Lens of Social Network Analysis: Theoretical Gaps, Methodological Challenges and Practitioner Perspectives

Directory of Open Access Journals (Sweden)

Dean HRISTOV

2015-06-01

Full Text Available The extant literature on networks in tourism management research has traditionally acknowledged destinations as the primary unit of analysis. This paper takes an alternative perspective and positions Destination Management Organisations (DMOs at the forefront of today’s tourism management research agenda. Whilst providing a relatively structured approach to generating enquiry, network research vis-à-vis Social Network Analysis (SNA in DMOs is often surrounded by serious impediments. Embedded in the network literature, this conceptual article aims to provide a practitioner perspective on addressing the obstacles to undertaking network studies in DMO organisations. A simple, three-step methodological framework for investigating DMOs as interorganisational networks of member organisations is proposed in response to complexities in network research. The rationale behind introducing such framework lies in the opportunity to trigger discussions and encourage further academic contributions embedded in both theory and practice. Academic and practitioner contributions are likely to yield insights into the importance of network methodologies applied to DMO organisations.

Risk measures on networks and expected utility

International Nuclear Information System (INIS)

Cerqueti, Roy; Lupi, Claudio

2016-01-01

In reliability theory projects are usually evaluated in terms of their riskiness, and often decision under risk is intended as the one-shot-type binary choice of accepting or not accepting the risk. In this paper we elaborate on the concept of risk acceptance, and propose a theoretical framework based on network theory. In doing this, we deal with system reliability, where the interconnections among the random quantities involved in the decision process are explicitly taken into account. Furthermore, we explore the conditions to be satisfied for risk-acceptance criteria to be consistent with the axiomatization of standard expected utility theory within the network framework. In accordance with existing literature, we show that a risk evaluation criterion can be meaningful even if it is not consistent with the standard axiomatization of expected utility, once this is suitably reinterpreted in the light of networks. Finally, we provide some illustrative examples. - Highlights: • We discuss risk acceptance and theoretically develop this theme on the basis of network theory. • We propose an original framework for describing the algebraic structure of the set of the networks, when they are viewed as risks. • We introduce the risk measures on networks, which induce total orders on the set of networks. • We state conditions on the risk measures on networks to let the induced risk-acceptance criterion be consistent with a new formulation of the expected utility theory.

Epidemic processes in complex networks

Science.gov (United States)

Pastor-Satorras, Romualdo; Castellano, Claudio; Van Mieghem, Piet; Vespignani, Alessandro

2015-07-01

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.

The minimum spanning tree : An unbiased method for brain network analysis

NARCIS (Netherlands)

Tewarie, P.; van Dellen, E.; Hillebrand, A.; Stam, C. J.

2015-01-01

The brain is increasingly studied with graph theoretical approaches, which can be used to characterize network topology. However, studies on brain networks have reported contradictory findings, and do not easily converge to a clear concept of the structural and functional network organization of the

Effects of network resolution on topological properties of human neocortex

DEFF Research Database (Denmark)

Romero-Garcia, Rafael; Atienza, Mercedes; Clemmensen, Line Katrine Harder

2012-01-01

Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small-world or......Graph theoretical analyses applied to neuroimaging datasets have provided valuable insights into the large-scale anatomical organization of the human neocortex. Most of these studies were performed with different cortical scales leading to cortical networks with different levels of small...

Nonbinary Tree-Based Phylogenetic Networks.

Science.gov (United States)

Jetten, Laura; van Iersel, Leo

2018-01-01

Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.

Fast evaluation of theoretical uncertainties with Sherpa and MCgrid

Energy Technology Data Exchange (ETDEWEB)

Bothmann, Enrico; Schumann, Steffen [II. Physikalisches Institut, Georg-August-Universitaet Goettingen (Germany); Schoenherr, Marek [Physik-Institut, Universitaet Zuerich (Switzerland)

2016-07-01

The determination of theoretical error estimates and PDF/α{sub s}-fits requires fast evaluations of cross sections for varied QCD input parameters. These include PDFs, the strong coupling constant α{sub S} and the renormalization and factorization scales. Beyond leading order QCD, a full dedicated calculation for each set of parameters is often too time-consuming, certainly when performing PDF-fits. In this talk we discuss two methods to overcome this issue for any QCD NLO calculation: The novel event-reweighting feature in Sherpa and the automated generation of interpolations grids using the recently introduced MCgrid interface. For the Sherpa event-reweighting we present the newly added support for the all-order PDF dependencies of parton shower emissions. Building on that we discuss the sensitivity of high precision observables to those dependencies.

Study of a family that overcomes poverty issues: family resilience?

Directory of Open Access Journals (Sweden)

María Ángela Mattar Yunes

2015-09-01

Full Text Available Generally, researches with families focus the difficulties and the negative aspects of family life by bringing up their maladjustments and failures. The interest in family resilience contributes to change this logic by demonstrating the healthy aspects of the family world. Nevertheless, the term resilience presents ideological controversies which are more severe when the discussion is about families and poverty. In order to diminish these contradictions this study adopted a systemic concept of resilience which refers to “those processes that make possible to overcome adversities”. A case study was realized with a low income family who lived in a “very poor” neighborhood in the deep south of Brazil. The methodological strategies to the formal investigation of the family were: life history of the family using the principles of reflexive interview, genograms and data analyses through the approach of the grounded theory. The results showed that the family lived a number of risk experiences such as adoption, privation of basic needs, migration and diseases. Among the indicators of their abilities of “overcoming adversities”, emerged the belief system as the core of the discourses. The family showed that they value the interpersonal relationships through intra and extra familiar interactions based in the patterns of help, learning, affection and solidarity. During the crisis the family gives meaning to the difficulties in order to maintaining the situation controlled through cohesion, open communication, mutual respect and getting support of the extended family/ social network. The pos-adversity period is perceived as benefic and transforming as the family feels stronger and with feelings of solidarity, which is a mark of this family. Their attitude in relation to the neighborhood is active in the sense of promoting the welfare of other families who live in the same social address. Would those above identified processes be adequate to

Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey

OpenAIRE

Luong, Nguyen Cong; Wang, Ping; Niyato, Dusit; Liang, Ying-Chang; Hou, Fen; Han, Zhu

2017-01-01

This paper presents a comprehensive literature review on applications of economic and pricing theory for resource management in the evolving fifth generation (5G) wireless networks. The 5G wireless networks are envisioned to overcome existing limitations of cellular networks in terms of data rate, capacity, latency, energy efficiency, spectrum efficiency, coverage, reliability, and cost per information transfer. To achieve the goals, the 5G systems will adopt emerging technologies such as mas...

Využití Network marketingu ve vybrané firmě

OpenAIRE

SAIKO, Michaela

2009-01-01

In my work I appreciated and considered the particular advantages compared to classical network marketing business. In the theoretical part, I mainly focused on the definition of network marketing, network marketing history, abuse of the principle of NWM, advantages and disadvantages of network marketing, illegal system and calculation of remuneration in network marketing. The analysis was first carried out the characteristics of the selected company, followed by analysis of network marketing...

Auxetic metamaterials from disordered networks

Science.gov (United States)

Reid, Daniel R.; Pashine, Nidhi; Wozniak, Justin M.; Jaeger, Heinrich M.; Liu, Andrea J.; Nagel, Sidney R.; de Pablo, Juan J.

2018-02-01

Recent theoretical work suggests that systematic pruning of disordered networks consisting of nodes connected by springs can lead to materials that exhibit a host of unusual mechanical properties. In particular, global properties such as Poisson’s ratio or local responses related to deformation can be precisely altered. Tunable mechanical responses would be useful in areas ranging from impact mitigation to robotics and, more generally, for creation of metamaterials with engineered properties. However, experimental attempts to create auxetic materials based on pruning-based theoretical ideas have not been successful. Here we introduce a more realistic model of the networks, which incorporates angle-bending forces and the appropriate experimental boundary conditions. A sequential pruning strategy of select bonds in this model is then devised and implemented that enables engineering of specific mechanical behaviors upon deformation, both in the linear and in the nonlinear regimes. In particular, it is shown that Poisson’s ratio can be tuned to arbitrary values. The model and concepts discussed here are validated by preparing physical realizations of the networks designed in this manner, which are produced by laser cutting 2D sheets and are found to behave as predicted. Furthermore, by relying on optimization algorithms, we exploit the networks’ susceptibility to tuning to design networks that possess a distribution of stiffer and more compliant bonds and whose auxetic behavior is even greater than that of homogeneous networks. Taken together, the findings reported here serve to establish that pruned networks represent a promising platform for the creation of unique mechanical metamaterials.

Theoretical Relevance of Neuropsychological Data for Connectionist Modelling

Directory of Open Access Journals (Sweden)

Mauricio Iza

2011-05-01

Full Text Available The symbolic information-processing paradigm in cognitive psychology has met a growing challenge from neural network models over the past two decades. While neuropsychological
evidence has been of great utility to theories concerned with information processing, the real question is, whether the less rigid connectionist models provide valid, or enough, information
concerning complex cognitive structures. In this work, we will discuss the theoretical implications that neuropsychological data posits for modelling cognitive systems.

Dye incorporation in polyphosphate gels: synthesis and theoretical calculations

Directory of Open Access Journals (Sweden)

Jordan Del Nero

2003-06-01

Full Text Available In this work we described theoretical calculations on the electronic structure and optical properties of the dyes crystal violet and malachite green based in semiempirical methods (Parametric Method 3 and Intermediate Neglect of Differential Overlap / Spectroscopic - Configuration Interaction and the synthesis of a new hybrid material based upon the incorporation of these dyes in an aluminum polyphosphate gel network. The samples are nearly transparent, free-standing thick films. The optical properties of the entrapped dyes are sensitive to chemical changes within the matrix caused either by gel aging or external stimulli such as exposition to acidic and basic vapors that can percolate within the matrix. Our theoretical modeling is in good agreement with the experimental results for the dyes.

Addressing and overcoming barriers for energy savings in business

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Kasper

Energy savings are generally viewed as an effective way to cut GHG emissions, as there are huge potentials for improvements because of several barriers and constraining factors for implementing otherwise profitable solutions. Several different polity tools have been applied to overcome these barr......Energy savings are generally viewed as an effective way to cut GHG emissions, as there are huge potentials for improvements because of several barriers and constraining factors for implementing otherwise profitable solutions. Several different polity tools have been applied to overcome...

Group percolation in interdependent networks

Science.gov (United States)

Wang, Zexun; Zhou, Dong; Hu, Yanqing

2018-03-01

In many real network systems, nodes usually cooperate with each other and form groups to enhance their robustness to risks. This motivates us to study an alternative type of percolation, group percolation, in interdependent networks under attack. In this model, nodes belonging to the same group survive or fail together. We develop a theoretical framework for this group percolation and find that the formation of groups can improve the resilience of interdependent networks significantly. However, the percolation transition is always of first order, regardless of the distribution of group sizes. As an application, we map the interdependent networks with intersimilarity structures, which have attracted much attention recently, onto the group percolation and confirm the nonexistence of continuous phase transitions.

A measure theoretic approach to traffic flow optimization on networks

OpenAIRE

Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea

2018-01-01

We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...

The interplay between social networks and culture: theoretically and among whales and dolphins.

Science.gov (United States)

Cantor, Mauricio; Whitehead, Hal

2013-05-19

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour.

1st International Conference on Network Analysis

CERN Document Server

Kalyagin, Valery; Pardalos, Panos

2013-01-01

This volume contains a selection of contributions from the "First International Conference in Network Analysis," held at the University of Florida, Gainesville, on December 14-16, 2011. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of this volume is to overcome this difficulty by collecting the major results found by the participants and combining them in one easily accessible compilation. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the...

The role of neural networks in nuclear power plant safety systems

International Nuclear Information System (INIS)

Boger, Z.

1993-01-01

Neural networks (NN) techniques have been applied in recent years to many systems by researchers in the nuclear power industry, mainly for modeling and sensor validation. Recent results are reviewed, including new directions in applications to control systems, safety analysis, and ''virtual'' instruments. As new fast learning algorithms become available, large systems may be learned effectively, even with few training examples. The nuclear industry hesitates to include NN in safety related systems, but it seems that the obstacles could be overcome with the demonstration of successful applications, even from other industries. Coupling of full-scale reactor simulators, as fault database generators, with neural networks learning should be explored. The integration of Expert System technology with NN should improve the Validation and Verification tasks, and also help overcome psychological barriers. It may prove that the potential of NN to help operators, compared with the existing and proposed alternatives, outweigh the risks. (author). 58 refs, 2 figs

The Innovation Network Scoreboard: Towards key Performance Indicators for the Assessment of Innovation Networks

NARCIS (Netherlands)

Kohl, Holger; Cap, Jan-Patrick; Blaich, Erik; von Raesfeld Meijer, Ariane M.; Dameri, R.P.; Garelli, R.; Resta, M.; Beltrametti, L.

2015-01-01

This work operationalizes a framework for the assessment of innovation networks. While a theoretical framework provides value to scholars, practitioners require concrete methods and indicators that they can apply to their projects. Scholars face the same demand when conducting empirical research.

A Game-Theoretic Approach to Branching Time Abstract-Check-Refine Process

Science.gov (United States)

Wang, Yi; Tamai, Tetsuo

2009-01-01

Since the complexity of software systems continues to grow, most engineers face two serious problems: the state space explosion problem and the problem of how to debug systems. In this paper, we propose a game-theoretic approach to full branching time model checking on three-valued semantics. The three-valued models and logics provide successful abstraction that overcomes the state space explosion problem. The game style model checking that generates counter-examples can guide refinement or identify validated formulas, which solves the system debugging problem. Furthermore, output of our game style method will give significant information to engineers in detecting where errors have occurred and what the causes of the errors are.

Negative Attitudes, Network and Education

DEFF Research Database (Denmark)

Bennett, Patrick; la Cour, Lisbeth; Larsen, Birthe

, the impact of negative attitudes and networking taking into account that these parameters may influence high and uneducated workers as well as immigrants and natives differently, creating different incentives to acquire education for the two ethnic groups. Using rich Danish administrative data, this paper......This paper explores potential explanations behind the educational gap between young natives and immigrants using two measures, negative attitudes towards immigrants and networking, which may influence natives and immigrants differently. The paper considers, both theoretically and empirically...... finds evidence that greater negative attitudes increase incentives for males to acquire education and that networking also increases immigrant education....

Modular analysis of biological networks.

Science.gov (United States)

Kaltenbach, Hans-Michael; Stelling, Jörg

2012-01-01

The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

Pursuit of Excellence in a Networked Society. : Theoretical and Practical Approaches.

NARCIS (Netherlands)

J. J.J.M. Volker; Dr. Marca Wolfensberger; Drs. L. Drayer

2014-01-01

Pursuit of Excellence in a Networked Society gives an overview of research and practice, describing and exploring efforts toward continuous improvement in programming to promote excellence. The talent development of students and teachers is a hot topic in today’s knowledge-based society which

The interplay between social networks and culture: theoretically and among whales and dolphins

OpenAIRE

Cantor, Mauricio; Whitehead, Hal

2013-01-01

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network t...

Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

Directory of Open Access Journals (Sweden)

Nguyen Kim Quoc

2015-08-01

Full Text Available The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.

A novel approach to error function minimization for feedforward neural networks

International Nuclear Information System (INIS)

Sinkus, R.

1995-01-01

Feedforward neural networks with error backpropagation are widely applied to pattern recognition. One general problem encountered with this type of neural networks is the uncertainty, whether the minimization procedure has converged to a global minimum of the cost function. To overcome this problem a novel approach to minimize the error function is presented. It allows to monitor the approach to the global minimum and as an outcome several ambiguities related to the choice of free parameters of the minimization procedure are removed. (orig.)

Mathematical challenges from theoretical/computational chemistry

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-31

The committee believes that this report has relevance and potentially valuable suggestions for a wide range of readers. Target audiences include: graduate departments in the mathematical and chemical sciences; federal and private agencies that fund research in the mathematical and chemical sciences; selected industrial and government research and development laboratories; developers of software and hardware for computational chemistry; and selected individual researchers. Chapter 2 of this report covers some history of computational chemistry for the nonspecialist, while Chapter 3 illustrates the fruits of some past successful cross-fertilization between mathematical scientists and computational/theoretical chemists. In Chapter 4 the committee has assembled a representative, but not exhaustive, survey of research opportunities. Most of these are descriptions of important open problems in computational/theoretical chemistry that could gain much from the efforts of innovative mathematical scientists, written so as to be accessible introductions to the nonspecialist. Chapter 5 is an assessment, necessarily subjective, of cultural differences that must be overcome if collaborative work is to be encouraged between the mathematical and the chemical communities. Finally, the report ends with a brief list of conclusions and recommendations that, if followed, could promote accelerated progress at this interface. Recognizing that bothersome language issues can inhibit prospects for collaborative research at the interface between distinctive disciplines, the committee has attempted throughout to maintain an accessible style, in part by using illustrative boxes, and has included at the end of the report a glossary of technical terms that may be familiar to only a subset of the target audiences listed above.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liu Yang

2015-12-01

Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

Perturbation results for the Estrada index in weighted networks

Energy Technology Data Exchange (ETDEWEB)

Shang Yilun, E-mail: shylmath@hotmail.com [Institute for Cyber Security, University of Texas at San Antonio, San Antonio, TX 78249 (United States)

2011-02-18

The logarithm of the Estrada index has been proposed recently as a spectral measure to character efficiently the robustness of complex networks. In this paper, we explore the Estrada index in weighted networks and develop various perturbation results based on spectral graph theory. It is shown that the robustness of a network may be enhanced even when some edge weights are reduced. This is of particular theoretical and practical significance to network design and optimization.

Perturbation results for the Estrada index in weighted networks

International Nuclear Information System (INIS)

Shang Yilun

2011-01-01

The logarithm of the Estrada index has been proposed recently as a spectral measure to character efficiently the robustness of complex networks. In this paper, we explore the Estrada index in weighted networks and develop various perturbation results based on spectral graph theory. It is shown that the robustness of a network may be enhanced even when some edge weights are reduced. This is of particular theoretical and practical significance to network design and optimization.

Research in high speed fiber optics local area networks

Science.gov (United States)

Tobagi, F. A.

1986-01-01

The design of high speed local area networks (HSLAN) for communication among distributed devices requires solving problems in three areas: the network medium and its topology, the medium access control, and the network interface. Considerable progress was already made in the first two areas. Accomplishments are divided into two groups according to their theoretical or experimental nature. A brief summary is given.

Consumer Activities and Reactions to Social Network Marketing

OpenAIRE

Bistra Vassileva

2017-01-01

The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM) referral behaviour, and purchase intentions. Consumers are investigated ...

Intervention: Help a Loved One Overcome Addiction

Science.gov (United States)

Intervention: Help a loved one overcome addiction An intervention can motivate someone to seek help for alcohol or drug misuse, compulsive eating, or ... successful. By Mayo Clinic Staff It's challenging to help a loved one struggling with any type of ...

Information processing in the transcriptional regulatory network of yeast: Functional robustness

Directory of Open Access Journals (Sweden)

Dehmer Matthias

2009-03-01

Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.

The Sharing of Benefits from a Logistics Alliance Based on a Hub-Spoke Network: A Cooperative Game Theoretic Approach

Directory of Open Access Journals (Sweden)

Minyoung Yea

2018-06-01

Full Text Available This study investigates a strategic alliance as a horizontal cooperation in the logistics and transportation industries by considering various sharing rules with a cooperative game approach. Through forging a strategic alliance, carriers gain extra benefits from resource sharing and high efficiency resource utilization. In particular, our research focuses on the cost savings from using larger vehicles utilizing collective market demand and regarding them as benefits of cooperation. The model conceptualizes the characteristic function of cost savings by coalitions that take into account the hub-spoke network which is common in transportation services. To share the improved profits fairly between members, we use different allocation schemes: the Shapley value, the core center, the τ -value, and the nucleolus. By analyzing those cooperative game theoretic solutions employing an alliance composed of three carriers, we investigate whether satisfaction in this specific coalition provides an incentive for carriers to join such a coalition. Our results from the analysis, with respect to fair allocation schemes, provide a practical and academic foundation for further research.

Stable architectures for deep neural networks

Science.gov (United States)

Haber, Eldad; Ruthotto, Lars

2018-01-01

Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

Wind power prediction based on genetic neural network

Science.gov (United States)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

Modeling the interdependent network based on two-mode networks

Science.gov (United States)

An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

2017-10-01

Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

Constructing an Intelligent Patent Network Analysis Method

Directory of Open Access Journals (Sweden)

Chao-Chan Wu

2012-11-01

Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

Epidemic transmission on random mobile network with diverse infection periods

Science.gov (United States)

Li, Kezan; Yu, Hong; Zeng, Zhaorong; Ding, Yong; Ma, Zhongjun

2015-05-01

The heterogeneity of individual susceptibility and infectivity and time-varying topological structure are two realistic factors when we study epidemics on complex networks. Current research results have shown that the heterogeneity of individual susceptibility and infectivity can increase the epidemic threshold in a random mobile dynamical network with the same infection period. In this paper, we will focus on random mobile dynamical networks with diverse infection periods due to people's different constitutions and external circumstances. Theoretical results indicate that the epidemic threshold of the random mobile network with diverse infection periods is larger than the counterpart with the same infection period. Moreover, the heterogeneity of individual susceptibility and infectivity can play a significant impact on disease transmission. In particular, the homogeneity of individuals will avail to the spreading of epidemics. Numerical examples verify further our theoretical results very well.

Drivers and barriers to the development of local food networks in rural Denmark

DEFF Research Database (Denmark)

Eriksen, Safania Normann; Sundbo, Jon

2016-01-01

This article examines the growing interest in local food by focusing on local food networks. The objective is to explore what factors drive or hinder the development of local food networks in rural Denmark. For this purpose, we have combined three bodies of theory: local food networks; entrepreneur...... networks; and the experience economy. This provides a valuable contribution to the current discourse on local food networks, as it introduces a novel framework to investigate the localisation of food dynamics. The article presents an explorative, case-based investigation of three Danish local food networks....... The findings demonstrate that the main drivers of the development of local food networks are the pursuance of transparency and knowledge of origin, the existence of entrepreneurship potential, the coordination of networks by means of joint strategies, and the overcoming of conflict patterns. However...

Handbook on theoretical and algorithmic aspects of sensor, ad hoc wireless, and peer-to-peer networks

CERN Document Server

Wu, Jie

2005-01-01

PrefaceAD HOC WIRELESS NETWORKSA Modular Cross Layer Architecture for Ad Hoc Networks, M. Conti, J. Crowcroft, G. Maselli, and G. TuriRouting Scalability in MANETs, J. Eriksson, S. Krishnamurthy and M. FaloutsosUniformly Distributed Algorithm for Virtual Backbone Routing in Ad Hoc Wireless Networks, D.S. KimMaximum Necessary Hop Count for Packet Routing in MANET, X. Chen and J. ShenEfficient Strategyproof Multicast in Selfish Wireless Networks, X.-Yang LiGeocasting in Ad Hoc and Sensor Networks, I. StojmenovicTopology Control for Ad hoc Networks: Present Solutions and Open Issues, C.-C. Shen a

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.

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

Science.gov (United States)

Hortos, William S.

1997-04-01

of convergence rate and call blocking. Genetic algorithms (GAs) are also considered in PCS networks as a means to overcome the known weakness of Hopfield NNAs in determining global minima. The resulting GAs for DCA in PCS networks are compared to improved DCA algorithms based on Hopfield NNs for stationary cellular networks. Algorithm performance is compared on the basis of rate of convergence, blocking probability, analytic complexity, and parametric sensitivity to transient traffic demands and channel interference.

The Graph Laplacian and the Dynamics of Complex Networks

Energy Technology Data Exchange (ETDEWEB)

Thulasidasan, Sunil [Los Alamos National Laboratory

2012-06-11

In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

Structural Analysis of Complex Networks

CERN Document Server

Dehmer, Matthias

2011-01-01

Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

Challenges confronting female surgical leaders: overcoming the barriers.

Science.gov (United States)

Kass, Rena B; Souba, Wiley W; Thorndyke, Luanne E

2006-05-15

The number of women reaching top ranks in academic surgery is remarkably low. The purpose of this study was to identify: 1) barriers to becoming a female surgical leader; 2) key attributes that enable advancement and success; and 3) current leadership challenges faced as senior leaders. Semi-structured interviews of ten female surgical leaders queried the following dimensions: attributes for success, lessons learned, mistakes, key career steps, the role of mentoring, gender advantages/disadvantages, and challenges. Perseverance (60%) and drive (50%) were identified as critical success factors, as were good communication skills, a passion for scholarship, a stable home life and a positive outlook. Eighty percent identified discrimination or gender prejudice as a major obstacle in their careers. While 90% percent had mentors, 50% acknowledged that they had not been effectively mentored. Career advice included: develop broad career goals (50%); select a conducive environment (30%); find a mentor (60%); take personal responsibility (40%); organize time and achieve balance (40%); network (30%); create a niche (30%); pursue research (30%); publish (50%); speak in public (30%); and enjoy the process (30%). Being in a minority, being highly visible and being collaborative were identified as advantages. Obtaining buy-in and achieving consensus was the greatest leadership challenge reported. Female academic surgeons face challenges to career advancement. While these barriers are real, they can be overcome by resolve, commitment, and developing strong communication skills. These elements should be taken into consideration in designing career development programs for junior female surgical faculty.

Energy Aware Routing Schemes in Solar PoweredWireless Sensor Networks

KAUST Repository

Dehwah, Ahmad H.

2016-10-01

Wireless sensor networks enable inexpensive distributed monitoring systems that are the backbone of smart cities. In this dissertation, we are interested in wireless sensor networks for traffic monitoring and an emergency flood detection to improve the safety of future cities. To achieve real-time traffic monitoring and emergency flood detection, the system has to be continually operational. Accordingly, an energy source is needed to ensure energy availability at all times. The sun provides for the most inexpensive source of energy, and therefore the energy is provided here by a solar panel working in conjunction with a rechargeable battery. Unlike batteries, solar energy fluctuates spatially and temporally due to the panel orientation, seasonal variation and node location, particularly in cities where buildings cast shadows. Especially, it becomes scarce whenever floods are likely to occur, as the weather tends to be cloudy at such times when the emergency detection system is most needed. These considerations lead to the need for the optimization of the energy of the sensor network, to maximize its sensing performance. In this dissertation, we address the challenges associated with long term outdoor deployments along with providing some solutions to overcome part of these challenges. We then introduce the energy optimization problem, as a distributed greedy approach. Motivated by the flood sensing application, our objective is to maximize the energy margin in the solar powered network at the onset of the high rain event, to maximize the network lifetime. The decentralized scheme will achieve this by optimizing the energy over a time horizon T, taking into account the available and predicted energy over the entire routing path. Having a good energy forecasting scheme can significantly enhance the energy optimization in WSN. Thus, this dissertation proposes a new energy forecasting scheme that is compatible with the platform’s capabilities. This proposed

S-curve networks and an approximate method for estimating degree distributions of complex networks

OpenAIRE

Guo, Jin-Li

2010-01-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (Logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference value for optimizing the distribution of IPv4 address resource and the development of IPv6. Based o...

Game-Theoretical Design of an Adaptive Distributed Dissemination Protocol for VANETs.

Science.gov (United States)

Iza-Paredes, Cristhian; Mezher, Ahmad Mohamad; Aguilar Igartua, Mónica; Forné, Jordi

2018-01-19

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposals.

Why and how selection patterns in classroom networks differ between students.The potential influence of networks size preferences, level of information, and group membership.

Directory of Open Access Journals (Sweden)

Baerveldt, Chris

2010-12-01

Full Text Available High school students can select class mates for new friendships using a repertoire of patterns. They can actively pursue new friendships, make use of the existing network structure, and/ or use the scarce and often erroneous information about candidates. In this theoretical paper, we argue that such selection patterns should not be studied as the result of general rules, as is usually done in social network studies. Specifically, we state that network size preferences, the level of information about individual attributes of fellow classmates, and group membership are likely to differ among high school students, and that as a result, also their selection patterns are likely to be different. In this paper we sketch the theoretical articulations between these.

Self-organized topology of recurrence-based complex networks

International Nuclear Information System (INIS)

Yang, Hui; Liu, Gang

2013-01-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks

Thermoelectric properties of semiconductor nanowire networks

Science.gov (United States)

Roslyak, Oleksiy; Piryatinski, Andrei

2016-03-01

To examine the thermoelectric (TE) properties of a semiconductor nanowire (NW) network, we propose a theoretical approach mapping the TE network on a two-port network. In contrast to a conventional single-port (i.e., resistor) network model, our model allows for large scale calculations showing convergence of TE figure of merit, ZT, with an increasing number of junctions. Using this model, numerical simulations are performed for the Bi2Te3 branched nanowire (BNW) and Cayley tree NW (CTNW) network. We find that the phonon scattering at the network junctions plays a dominant role in enhancing the network ZT. Specifically, disordered BNW and CTNW demonstrate an order of magnitude higher ZT enhancement compared to their ordered counterparts. Formation of preferential TE pathways in CTNW makes the network effectively behave as its BNW counterpart. We provide formalism for simulating large scale nanowire networks hinged upon experimentally measurable TE parameters of a single T-junction.

Networking for Education for Sustainable Development in Austria: The Austrian ECOLOG-Schools Programme

Science.gov (United States)

Rauch, Franz

2016-01-01

This case describes networking for education for sustainable development within the Austrian ECOLOG-schools network. The article presents theoretical concepts of networks in education in general, and the organization of the ECOLOG-network in particular. Based upon these foundations, the concept and results of a participatory evaluation study are…

Stability of Ecological Communities and the Architecture of Mutualistic and Trophic Networks

NARCIS (Netherlands)

Thebault, E.M.C.; Fontaine, C.

2010-01-01

Research on the relationship between the architecture of ecological networks and community stability has mainly focused on one type of interaction at a time, making difficult any comparison between different network types. We used a theoretical approach to show that the network architecture favoring

A Neural Network-Based Interval Pattern Matcher

Directory of Open Access Journals (Sweden)

Jing Lu

2015-07-01

Full Text Available One of the most important roles in the machine learning area is to classify, and neural networks are very important classifiers. However, traditional neural networks cannot identify intervals, let alone classify them. To improve their identification ability, we propose a neural network-based interval matcher in our paper. After summarizing the theoretical construction of the model, we take a simple and a practical weather forecasting experiment, which show that the recognizer accuracy reaches 100% and that is promising.

Constructing level-2 phylogenetic networks from triplets

OpenAIRE

Iersel, Leo; Keijsper, J.C.M.; Kelk, Steven; Stougie, Leen; Hagen, F.; Boekhout, T.; Vingron, M.; Wong, L.

2009-01-01

htmlabstractJansson and Sung showed that, given a dense set of input triplets T (representing hypotheses about the local evolutionary relationships of triplets of taxa), it is possible to determine in polynomial time whether there exists a level-1 network consistent with T, and if so to construct such a network (Inferring a Level-1 Phylogenetic Network from a Dense Set of Rooted Triplets, Theoretical Computer Science, 363, pp. 60-68 (2006)). Here we extend this work by showing that this probl...

A Theoretic Basis for IS? The Contribution of ANT