WorldWideScience

Sample records for networks study phase

  1. Phase-space networks of geometrically frustrated systems.

    Science.gov (United States)

    Han, Yilong

    2009-11-01

    We illustrate a network approach to the phase-space study by using two geometrical frustration models: antiferromagnet on triangular lattice and square ice. Their highly degenerated ground states are mapped as discrete networks such that the quantitative network analysis can be applied to phase-space studies. The resulting phase spaces share some comon features and establish a class of complex networks with unique Gaussian spectral densities. Although phase-space networks are heterogeneously connected, the systems are still ergodic due to the random Poisson processes. This network approach can be generalized to phase spaces of some other complex systems.

  2. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  3. Analyzing phase diagrams and phase transitions in networked competing populations

    Science.gov (United States)

    Ni, Y.-C.; Yin, H. P.; Xu, C.; Hui, P. M.

    2011-03-01

    Phase diagrams exhibiting the extent of cooperation in an evolutionary snowdrift game implemented in different networks are studied in detail. We invoke two independent payoff parameters, unlike a single payoff often used in most previous works that restricts the two payoffs to vary in a correlated way. In addition to the phase transition points when a single payoff parameter is used, phase boundaries separating homogeneous phases consisting of agents using the same strategy and a mixed phase consisting of agents using different strategies are found. Analytic expressions of the phase boundaries are obtained by invoking the ideas of the last surviving patterns and the relative alignments of the spectra of payoff values to agents using different strategies. In a Watts-Strogatz regular network, there exists a re-entrant phenomenon in which the system goes from a homogeneous phase into a mixed phase and re-enters the homogeneous phase as one of the two payoff parameters is varied. The non-trivial phase diagram accompanying this re-entrant phenomenon is quantitatively analyzed. The effects of noise and cooperation in randomly rewired Watts-Strogatz networks are also studied. The transition between a mixed phase and a homogeneous phase is identify to belong to the directed percolation universality class. The methods used in the present work are applicable to a wide range of problems in competing populations of networked agents.

  4. Parameter diagnostics of phases and phase transition learning by neural networks

    Science.gov (United States)

    Suchsland, Philippe; Wessel, Stefan

    2018-05-01

    We present an analysis of neural network-based machine learning schemes for phases and phase transitions in theoretical condensed matter research, focusing on neural networks with a single hidden layer. Such shallow neural networks were previously found to be efficient in classifying phases and locating phase transitions of various basic model systems. In order to rationalize the emergence of the classification process and for identifying any underlying physical quantities, it is feasible to examine the weight matrices and the convolutional filter kernels that result from the learning process of such shallow networks. Furthermore, we demonstrate how the learning-by-confusing scheme can be used, in combination with a simple threshold-value classification method, to diagnose the learning parameters of neural networks. In particular, we study the classification process of both fully-connected and convolutional neural networks for the two-dimensional Ising model with extended domain wall configurations included in the low-temperature regime. Moreover, we consider the two-dimensional XY model and contrast the performance of the learning-by-confusing scheme and convolutional neural networks trained on bare spin configurations to the case of preprocessed samples with respect to vortex configurations. We discuss these findings in relation to similar recent investigations and possible further applications.

  5. Storage of phase-coded patterns via STDP in fully-connected and sparse network: a study of the network capacity

    Directory of Open Access Journals (Sweden)

    Silvia Scarpetta

    2010-08-01

    Full Text Available We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate-and-fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre- and post-synaptic activity. We store multiple patterns and study the network capacity. For the analog model, we find that the network capacity scales linearly with the network size, and that both capacity and the oscillation frequency of the retrieval state depend on the asymmetry of the learning time window. In addition to fully-connected networks, we study sparse networks, where each neuron is connected only to a small number $zll N$ of other neurons. Connections can be short range, between neighboring neurons placed on a regular lattice, or long range, between randomly chosen pairs of neurons. We find that a small fraction of long range connections is able to amplify the capacity of the network. This imply that a small-world-network topology is optimal, as a compromise between the cost of long range connections and the capacity increase. Also in the spiking integrate and fire model the crucial result of storing and retrieval of multiple phase-coded patterns is observed. The capacity of the fully-connected spiking network is investigated, together with the relation between oscillation frequency of retrieval state and window asymmetry.

  6. Tensor Network Wavefunctions for Topological Phases

    Science.gov (United States)

    Ware, Brayden Alexander

    The combination of quantum effects and interactions in quantum many-body systems can result in exotic phases with fundamentally entangled ground state wavefunctions--topological phases. Topological phases come in two types, both of which will be studied in this thesis. In topologically ordered phases, the pattern of entanglement in the ground state wavefunction encodes the statistics of exotic emergent excitations, a universal indicator of a phase that is robust to all types of perturbations. In symmetry protected topological phases, the entanglement instead encodes a universal response of the system to symmetry defects, an indicator that is robust only to perturbations respecting the protecting symmetry. Finding and creating these phases in physical systems is a motivating challenge that tests all aspects--analytical, numerical, and experimental--of our understanding of the quantum many-body problem. Nearly three decades ago, the creation of simple ansatz wavefunctions--such as the Laughlin fractional quantum hall state, the AKLT state, and the resonating valence bond state--spurred analytical understanding of both the role of entanglement in topological physics and physical mechanisms by which it can arise. However, quantitative understanding of the relevant phase diagrams is still challenging. For this purpose, tensor networks provide a toolbox for systematically improving wavefunction ansatz while still capturing the relevant entanglement properties. In this thesis, we use the tools of entanglement and tensor networks to analyze ansatz states for several proposed new phases. In the first part, we study a featureless phase of bosons on the honeycomb lattice and argue that this phase can be topologically protected under any one of several distinct subsets of the crystalline lattice symmetries. We discuss methods of detecting such phases with entanglement and without. In the second part, we consider the problem of constructing fixed-point wavefunctions for

  7. Associative memory in phasing neuron networks

    Energy Technology Data Exchange (ETDEWEB)

    Nair, Niketh S [ORNL; Bochove, Erik J. [United States Air Force Research Laboratory, Kirtland Air Force Base; Braiman, Yehuda [ORNL

    2014-01-01

    We studied pattern formation in a network of coupled Hindmarsh-Rose model neurons and introduced a new model for associative memory retrieval using networks of Kuramoto oscillators. Hindmarsh-Rose Neural Networks can exhibit a rich set of collective dynamics that can be controlled by their connectivity. Specifically, we showed an instance of Hebb's rule where spiking was correlated with network topology. Based on this, we presented a simple model of associative memory in coupled phase oscillators.

  8. Complex network analysis in inclined oil–water two-phase flow

    International Nuclear Information System (INIS)

    Zhong-Ke, Gao; Ning-De, Jin

    2009-01-01

    Complex networks have established themselves in recent years as being particularly suitable and flexible for representing and modelling many complex natural and artificial systems. Oil–water two-phase flow is one of the most complex systems. In this paper, we use complex networks to study the inclined oil–water two-phase flow. Two different complex network construction methods are proposed to build two types of networks, i.e. the flow pattern complex network (FPCN) and fluid dynamic complex network (FDCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K-means clustering, useful and interesting results are found which can be used for identifying three inclined oil–water flow patterns. To investigate the dynamic characteristics of the inclined oil–water two-phase flow, we construct 48 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of the inclined oil–water two-phase flow. In this paper, from a new perspective, we not only introduce a complex network theory into the study of the oil–water two-phase flow but also indicate that the complex network may be a powerful tool for exploring nonlinear time series in practice. (general)

  9. Network periodic solutions: patterns of phase-shift synchrony

    International Nuclear Information System (INIS)

    Golubitsky, Martin; Wang, Yunjiao; Romano, David

    2012-01-01

    We prove the rigid phase conjecture of Stewart and Parker. It then follows from previous results (of Stewart and Parker and our own) that rigid phase-shifts in periodic solutions on a transitive network are produced by a cyclic symmetry on a quotient network. More precisely, let X(t) = (x 1 (t), ..., x n (t)) be a hyperbolic T-periodic solution of an admissible system on an n-node network. Two nodes c and d are phase-related if there exists a phase-shift θ cd in [0, 1) such that x d (t) = x c (t + θ cd T). The conjecture states that if phase relations persist under all small admissible perturbations (that is, the phase relations are rigid), then for each pair of phase-related cells, their input signals are also phase-related to the same phase-shift. For a transitive network, rigid phase relations can also be described abstractly as a Z m permutation symmetry of a quotient network. We discuss how patterns of phase-shift synchrony lead to rigid synchrony, rigid phase synchrony, and rigid multirhythms, and we show that for each phase pattern there exists an admissible system with a periodic solution with that phase pattern. Finally, we generalize the results to nontransitive networks where we show that the symmetry that generates rigid phase-shifts occurs on an extension of a quotient network

  10. Symmetric Topological Phases and Tensor Network States

    Science.gov (United States)

    Jiang, Shenghan

    Classification and simulation of quantum phases are one of main themes in condensed matter physics. Quantum phases can be distinguished by their symmetrical and topological properties. The interplay between symmetry and topology in condensed matter physics often leads to exotic quantum phases and rich phase diagrams. Famous examples include quantum Hall phases, spin liquids and topological insulators. In this thesis, I present our works toward a more systematically understanding of symmetric topological quantum phases in bosonic systems. In the absence of global symmetries, gapped quantum phases are characterized by topological orders. Topological orders in 2+1D are well studied, while a systematically understanding of topological orders in 3+1D is still lacking. By studying a family of exact solvable models, we find at least some topological orders in 3+1D can be distinguished by braiding phases of loop excitations. In the presence of both global symmetries and topological orders, the interplay between them leads to new phases termed as symmetry enriched topological (SET) phases. We develop a framework to classify a large class of SET phases using tensor networks. For each tensor class, we can write down generic variational wavefunctions. We apply our method to study gapped spin liquids on the kagome lattice, which can be viewed as SET phases of on-site symmetries as well as lattice symmetries. In the absence of topological order, symmetry could protect different topological phases, which are often referred to as symmetry protected topological (SPT) phases. We present systematic constructions of tensor network wavefunctions for bosonic symmetry protected topological (SPT) phases respecting both onsite and spatial symmetries.

  11. Phase transitions in Pareto optimal complex networks.

    Science.gov (United States)

    Seoane, Luís F; Solé, Ricard

    2015-09-01

    The organization of interactions in complex systems can be described by networks connecting different units. These graphs are useful representations of the local and global complexity of the underlying systems. The origin of their topological structure can be diverse, resulting from different mechanisms including multiplicative processes and optimization. In spatial networks or in graphs where cost constraints are at work, as it occurs in a plethora of situations from power grids to the wiring of neurons in the brain, optimization plays an important part in shaping their organization. In this paper we study network designs resulting from a Pareto optimization process, where different simultaneous constraints are the targets of selection. We analyze three variations on a problem, finding phase transitions of different kinds. Distinct phases are associated with different arrangements of the connections, but the need of drastic topological changes does not determine the presence or the nature of the phase transitions encountered. Instead, the functions under optimization do play a determinant role. This reinforces the view that phase transitions do not arise from intrinsic properties of a system alone, but from the interplay of that system with its external constraints.

  12. Phase diagram of spiking neural networks.

    Science.gov (United States)

    Seyed-Allaei, Hamed

    2015-01-01

    In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probability of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations, and trials and errors, but here, I take a different perspective, inspired by evolution, I systematically simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable. I stimulate networks with pulses and then measure their: dynamic range, dominant frequency of population activities, total duration of activities, maximum rate of population and the occurrence time of maximum rate. The results are organized in phase diagram. This phase diagram gives an insight into the space of parameters - excitatory to inhibitory ratio, sparseness of connections and synaptic weights. This phase diagram can be used to decide the parameters of a model. The phase diagrams show that networks which are configured according to the common values, have a good dynamic range in response to an impulse and their dynamic range is robust in respect to synaptic weights, and for some synaptic weights they oscillates in α or β frequencies, independent of external stimuli.

  13. Study of pattern formation in multilayer adaptive network of phase oscillators in application to brain dynamics analysis

    Science.gov (United States)

    Kirsanov, Daniil V.; Nedaivozov, Vladimir O.; Makarov, Vladimir V.; Goremyko, Mikhail V.; Hramov, Alexander E.

    2017-04-01

    In the report we study the mechanisms of phase synchronization in the model of adaptive network of Kuramoto phase oscillators and discuss the possibility of the further application of the obtained results for the analysis of the neural network of brain. In our theoretical study the model network represents itself as the multilayer structure, in which the links between the elements belonging to the different layers are arranged according to the competitive rule. In order to analyze the dynamical states of the multilayer network we calculate and compare the values of local and global order parameter, which describe the degree of coherence between the neighboring nodes and the elements over whole network, respectively. We find that the global synchronous dynamics takes place for the large values of the coupling strength and are characterized by the identical topology of the interacting layers and a homogeneous distribution of the link strength within each layer. We also show that the partial (or cluster) synchronization, occurs for the small values of the coupling strength, lead to the emergence of the scale-free topology, within the layers.

  14. Competing dynamic phases of active polymer networks

    Science.gov (United States)

    Freedman, Simon; Banerjee, Shiladitya; Dinner, Aaron R.

    Recent experiments on in-vitro reconstituted assemblies of F-actin, myosin-II motors, and cross-linking proteins show that tuning local network properties can changes the fundamental biomechanical behavior of the system. For example, by varying cross-linker density and actin bundle rigidity, one can switch between contractile networks useful for reshaping cells, polarity sorted networks ideal for directed molecular transport, and frustrated networks with robust structural properties. To efficiently investigate the dynamic phases of actomyosin networks, we developed a coarse grained non-equilibrium molecular dynamics simulation of model semiflexible filaments, molecular motors, and cross-linkers with phenomenologically defined interactions. The simulation's accuracy was verified by benchmarking the mechanical properties of its individual components and collective behavior against experimental results at the molecular and network scales. By adjusting the model's parameters, we can reproduce the qualitative phases observed in experiment and predict the protein characteristics where phase crossovers could occur in collective network dynamics. Our model provides a framework for understanding cells' multiple uses of actomyosin networks and their applicability in materials research. Supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

  15. Phase Diagram of Spiking Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamed eSeyed-Allaei

    2015-03-01

    Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.

  16. Applications of neural networks to the studies of phase transitions of two-dimensional Potts models

    Science.gov (United States)

    Li, C.-D.; Tan, D.-R.; Jiang, F.-J.

    2018-04-01

    We study the phase transitions of two-dimensional (2D) Q-states Potts models on the square lattice, using the first principles Monte Carlo (MC) simulations as well as the techniques of neural networks (NN). We demonstrate that the ideas from NN can be adopted to study these considered phase transitions efficiently. In particular, even with a simple NN constructed in this investigation, we are able to obtain the relevant information of the nature of these phase transitions, namely whether they are first order or second order. Our results strengthen the potential applicability of machine learning in studying various states of matters. Subtlety of applying NN techniques to investigate many-body systems is briefly discussed as well.

  17. Phase separation in living micellar networks

    Science.gov (United States)

    Cristobal, G.; Rouch, J.; Curély, J.; Panizza, P.

    We present a lattice model based on two n→0 spin vectors, capable of treating the thermodynamics of living networks in micellar solutions at any surfactant concentration. We establish an isomorphism between the coupling constants in the two spin vector Hamiltonian and the surfactant energies involved in the micellar situation. Solving this Hamiltonian in the mean-field approximation allows one to calculate osmotic pressure, aggregation number, free end and cross-link densities at any surfactant concentration. We derive a phase diagram, including changes in topology such as the transition between spheres and rods and between saturated and unsaturated networks. A phase separation can be found between a saturated network and a dilute solution composed of long flexible micelles or a saturated network and a solution of spherical micelles.

  18. Youth's social network structures and peer influences: study protocol MyMovez project - Phase I.

    Science.gov (United States)

    Bevelander, Kirsten E; Smit, Crystal R; van Woudenberg, Thabo J; Buijs, Laura; Burk, William J; Buijzen, Moniek

    2018-04-16

    Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and peers) that co-determine their dietary intake and physical activity. However, there is a lack of systematic and comprehensive research on the implementation of a social network approach in health campaigns. The MyMovez research project aims to fill this gap by developing a method for effective social network campaign implementation. This protocol paper describes the design and methods of Phase I of the MyMovez project, aiming to unravel youth's social network structures in combination with individual, psychosocial, and environmental factors related to energy intake and expenditure. In addition, the Wearable Lab is developed to enable an attractive and state-of-the-art way of collecting data and online campaign implementation via social networks. Phase I of the MyMovez project consists of a large-scale cross-sequential cohort study (N = 953; 8-12 and 12-15 y/o). In five waves during a 3-year period (2016-2018), data are collected about youth's social network exposure, media consumption, socialization experiences, psychological determinants of behavior, physical environment, dietary intake (snacking and drinking behavior) and physical activity using the Wearable Lab. The Wearable Lab exists of a smartphone-based research application (app) connected to an activity tracking bracelet, that is developed throughout the duration of the project. It generates peer- and self-reported (e.g., sociometric data and surveys) and experience sampling data, social network beacon data, real-time physical activity data (i.e., steps and cycling), location information, photos and chat conversation data from the app's social media platform Social Buzz. The MyMovez project - Phase I is an innovative cross

  19. Phase multistability in a dynamical small world network

    Energy Technology Data Exchange (ETDEWEB)

    Shabunin, A. V., E-mail: shabuninav@info.sgu.ru [Radiophysics and Nonlinear Dynamics Department, Saratov State University, Saratov (Russian Federation)

    2015-01-15

    The effect of phase multistability is explored in a small world network of periodic oscillators with diffusive couplings. The structure of the network represents a ring with additional non-local links, which spontaneously arise and vanish between arbitrary nodes. The dynamics of random couplings is modeled by “birth” and “death” stochastic processes by means of the cellular automate approach. The evolution of the network under gradual increasing of the number of random couplings goes through stages of phases fluctuations and spatial cluster formation. Finally, in the presence of non-local couplings the phase multistability “dies” and only the in-phase regime survives.

  20. Perfect synchronization in networks of phase-frustrated oscillators

    Science.gov (United States)

    Kundu, Prosenjit; Hens, Chittaranjan; Barzel, Baruch; Pal, Pinaki

    2017-11-01

    Synchronizing phase-frustrated Kuramoto oscillators, a challenge that has found applications from neuronal networks to the power grid, is an eluding problem, as even small phase lags cause the oscillators to avoid synchronization. Here we show, constructively, how to strategically select the optimal frequency set, capturing the natural frequencies of all oscillators, for a given network and phase lags, that will ensure perfect synchronization. We find that high levels of synchronization are sustained in the vicinity of the optimal set, allowing for some level of deviation in the frequencies without significant degradation of synchronization. Demonstrating our results on first- and second-order phase-frustrated Kuramoto dynamics, we implement them on both model and real power grid networks, showing how to achieve synchronization in a phase-frustrated environment.

  1. EEG PHASE RESET OF THE DEFAULT MODE NETWORK

    Directory of Open Access Journals (Sweden)

    Robert W. Thatcher

    2014-07-01

    Full Text Available Objectives: The purpose of this study was to explore phase reset of 3-dimensional current sources located in Brodmann areas located in the human default mode network (DMN using Low Resolution Electromagnetic Tomography (LORETA of the human electroencephalogram (EEG. Methods: The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodman areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st & 2nd derivatives of the time series of phase differences. Results: Phase shift duration exhibited three discrete modes at approximately: 1- 30 msec,, 2- 55 msec and, 3- 65 msec. Phase lock duration present primarily at: 1- 300 to 350 msec and, 2- 350 msec to 450 msec. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. Conclusions: The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a ‘shutter’ that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

  2. Complete and phase synchronization in a heterogeneous small-world neuronal network

    International Nuclear Information System (INIS)

    Fang, Han; Qi-Shao, Lu; Quan-Bao, Ji; Marian, Wiercigroch

    2009-01-01

    Synchronous firing of neurons is thought to be important for information communication in neuronal networks. This paper investigates the complete and phase synchronization in a heterogeneous small-world chaotic Hindmarsh–Rose neuronal network. The effects of various network parameters on synchronization behaviour are discussed with some biological explanations. Complete synchronization of small-world neuronal networks is studied theoretically by the master stability function method. It is shown that the coupling strength necessary for complete or phase synchronization decreases with the neuron number, the node degree and the connection density are increased. The effect of heterogeneity of neuronal networks is also considered and it is found that the network heterogeneity has an adverse effect on synchrony. (general)

  3. Phase reduction and synchronization of a network of coupled dynamical elements exhibiting collective oscillations

    Science.gov (United States)

    Nakao, Hiroya; Yasui, Sho; Ota, Masashi; Arai, Kensuke; Kawamura, Yoji

    2018-04-01

    A general phase reduction method for a network of coupled dynamical elements exhibiting collective oscillations, which is applicable to arbitrary networks of heterogeneous dynamical elements, is developed. A set of coupled adjoint equations for phase sensitivity functions, which characterize the phase response of the collective oscillation to small perturbations applied to individual elements, is derived. Using the phase sensitivity functions, collective oscillation of the network under weak perturbation can be described approximately by a one-dimensional phase equation. As an example, mutual synchronization between a pair of collectively oscillating networks of excitable and oscillatory FitzHugh-Nagumo elements with random coupling is studied.

  4. Quantitative phase microscopy using deep neural networks

    Science.gov (United States)

    Li, Shuai; Sinha, Ayan; Lee, Justin; Barbastathis, George

    2018-02-01

    Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data generated by a phase SLM. The results showed that our DNN was able to reconstruct the profile of the phase target qualitatively. In the meantime, large error still existed, which indicated that our approach still need to be improved.

  5. Numerical simulation for gas-liquid two-phase flow in pipe networks

    International Nuclear Information System (INIS)

    Li Xiaoyan; Kuang Bo; Zhou Guoliang; Xu Jijun

    1998-01-01

    The complex pipe network characters can not directly presented in single phase flow, gas-liquid two phase flow pressure drop and void rate change model. Apply fluid network theory and computer numerical simulation technology to phase flow pipe networks carried out simulate and compute. Simulate result shows that flow resistance distribution is non-linear in two phase pipe network

  6. Flow-pattern identification and nonlinear dynamics of gas-liquid two-phase flow in complex networks.

    Science.gov (United States)

    Gao, Zhongke; Jin, Ningde

    2009-06-01

    The identification of flow pattern is a basic and important issue in multiphase systems. Because of the complexity of phase interaction in gas-liquid two-phase flow, it is difficult to discern its flow pattern objectively. In this paper, we make a systematic study on the vertical upward gas-liquid two-phase flow using complex network. Three unique network construction methods are proposed to build three types of networks, i.e., flow pattern complex network (FPCN), fluid dynamic complex network (FDCN), and fluid structure complex network (FSCN). Through detecting the community structure of FPCN by the community-detection algorithm based on K -mean clustering, useful and interesting results are found which can be used for identifying five vertical upward gas-liquid two-phase flow patterns. To investigate the dynamic characteristics of gas-liquid two-phase flow, we construct 50 FDCNs under different flow conditions, and find that the power-law exponent and the network information entropy, which are sensitive to the flow pattern transition, can both characterize the nonlinear dynamics of gas-liquid two-phase flow. Furthermore, we construct FSCN and demonstrate how network statistic can be used to reveal the fluid structure of gas-liquid two-phase flow. In this paper, from a different perspective, we not only introduce complex network theory to the study of gas-liquid two-phase flow but also indicate that complex network may be a powerful tool for exploring nonlinear time series in practice.

  7. Routing strategies in traffic network and phase transition in network ...

    Indian Academy of Sciences (India)

    3Department of Electronic Engineering, City University of Hong Kong, Hong Kong ... Routing strategy; network traffic flow; hysteretic loop; phase transition from ... ered from two aspects: modifying the underlying network structure or developing ... capacity corresponds to α = −1 in the case of identical nodes' delivering ability.

  8. LORETA EEG phase reset of the default mode network.

    Science.gov (United States)

    Thatcher, Robert W; North, Duane M; Biver, Carl J

    2014-01-01

    The purpose of this study was to explore phase reset of 3-dimensional current sources in Brodmann areas located in the human default mode network (DMN) using Low Resolution Electromagnetic Tomography (LORETA) of the human electroencephalogram (EEG). The EEG was recorded from 19 scalp locations from 70 healthy normal subjects ranging in age from 13 to 20 years. A time point by time point computation of LORETA current sources were computed for 14 Brodmann areas comprising the DMN in the delta frequency band. The Hilbert transform of the LORETA time series was used to compute the instantaneous phase differences between all pairs of Brodmann areas. Phase shift and lock durations were calculated based on the 1st and 2nd derivatives of the time series of phase differences. Phase shift duration exhibited three discrete modes at approximately: (1) 25 ms, (2) 50 ms, and (3) 65 ms. Phase lock duration present primarily at: (1) 300-350 ms and (2) 350-450 ms. Phase shift and lock durations were inversely related and exhibited an exponential change with distance between Brodmann areas. The results are explained by local neural packing density of network hubs and an exponential decrease in connections with distance from a hub. The results are consistent with a discrete temporal model of brain function where anatomical hubs behave like a "shutter" that opens and closes at specific durations as nodes of a network giving rise to temporarily phase locked clusters of neurons for specific durations.

  9. Nonlinear analysis of gas-water/oil-water two-phase flow in complex networks

    CERN Document Server

    Gao, Zhong-Ke; Wang, Wen-Xu

    2014-01-01

    Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination with complex network theory. We systematically carried out gas-water/oil-water two-phase flow experiments for measuring the time series of flow signals which is studied in terms of the mapping from time series to complex networks. Three network mapping methods were proposed for the analysis and identification of flow patterns, i.e. Flow Pattern Complex Network (FPCN), Fluid Dynamic Complex Network (FDCN) and Fluid Structure Complex Network (FSCN). Through detecting the community structure of FPCN based on K-means clustering, distinct flow patterns can be successfully distinguished and identified. A number of FDCN’s under different flow conditions were constructed in order to reveal the dynamical characteristics of two-phase flows. The FDCNs exhibit universal power-law degree distributions. The power-law exponent ...

  10. Design of multi-phase dynamic chemical networks

    Science.gov (United States)

    Chen, Chenrui; Tan, Junjun; Hsieh, Ming-Chien; Pan, Ting; Goodwin, Jay T.; Mehta, Anil K.; Grover, Martha A.; Lynn, David G.

    2017-08-01

    Template-directed polymerization reactions enable the accurate storage and processing of nature's biopolymer information. This mutualistic relationship of nucleic acids and proteins, a network known as life's central dogma, is now marvellously complex, and the progressive steps necessary for creating the initial sequence and chain-length-specific polymer templates are lost to time. Here we design and construct dynamic polymerization networks that exploit metastable prion cross-β phases. Mixed-phase environments have been used for constructing synthetic polymers, but these dynamic phases emerge naturally from the growing peptide oligomers and create environments suitable both to nucleate assembly and select for ordered templates. The resulting templates direct the amplification of a phase containing only chain-length-specific peptide-like oligomers. Such multi-phase biopolymer dynamics reveal pathways for the emergence, self-selection and amplification of chain-length- and possibly sequence-specific biopolymers.

  11. Application of neural networks to prediction of phase transport characteristics in high-pressure two-phase turbulent bubbly flows

    International Nuclear Information System (INIS)

    Yang, A.-S.; Kuo, T.-C.; Ling, P.-H.

    2003-01-01

    The phase transport phenomenon of the high-pressure two-phase turbulent bubbly flow involves complicated interfacial interactions of the mass, momentum, and energy transfer processes between phases, revealing that an enormous effort is required in characterizing the liquid-gas flow behavior. Nonetheless, the instantaneous information of bubbly flow properties is often desired for many industrial applications. This investigation aims to demonstrate the successful use of neural networks in the real-time determination of two-phase flow properties at elevated pressures. Three back-propagation neural networks, trained with the simulation results of a comprehensive theoretical model, are established to predict the transport characteristics (specifically the distributions of void-fraction and axial liquid-gas velocities) of upward turbulent bubbly pipe flows at pressures covering 3.5-7.0 MPa. Comparisons of the predictions with the test target vectors indicate that the averaged root-mean-squared (RMS) error for each one of three back-propagation neural networks is within 4.59%. In addition, this study appraises the effects of different network parameters, including the number of hidden nodes, the type of transfer function, the number of training pairs, the learning rate-increasing ratio, the learning rate-decreasing ratio, and the momentum value, on the training quality of neural networks.

  12. Phased Array Radar Network Experiment for Severe Weather

    Science.gov (United States)

    Ushio, T.; Kikuchi, H.; Mega, T.; Yoshikawa, E.; Mizutani, F.; Takahashi, N.

    2017-12-01

    Phased Array Weather Radar (PAWR) was firstly developed in 2012 by Osaka University and Toshiba under a grant of NICT using the Digital Beamforming Technique, and showed a impressive thunderstorm behavior with 30 second resolution. After that development, second PAWR was installed in Kobe city about 60 km away from the first PAWR site, and Tokyo Metropolitan University, Osaka Univeristy, Toshiba and the Osaka Local Government started a new project to develop the Osaka Urban Demonstration Network. The main sensor of the Osaka Network is a 2-node Phased Array Radar Network and lightning location system. Data products that are created both in local high performance computer and Toshiba Computer Cloud, include single and multi-radar data, vector wind, quantitative precipitation estimation, VIL, nowcasting, lightning location and analysis. Each radar node is calibarated by the baloon measurement and through the comparison with the GPM (Global Precipitation Measurement)/ DPR (Dual Frequency Space borne Radar) within 1 dB. The attenuated radar reflectivities obtained by the Phased Array Radar Network at X band are corrected based on the bayesian scheme proposed in Shimamura et al. [2016]. The obtained high resolution (every 30 seconds/ 100 elevation angles) 3D reflectivity and rain rate fields are used to nowcast the surface rain rate up to 30 minutes ahead. These new products are transferred to Osaka Local Government in operational mode and evaluated by several section in Osaka Prefecture. Furthermore, a new Phased Array Radar with polarimetric function has been developed in 2017, and will be operated in the fiscal year of 2017. In this presentation, Phased Array Radar, network architecuture, processing algorithm, evalution of the social experiment and first Multi-Prameter Phased Array Radar experiment are presented.

  13. Deep Neural Network Detects Quantum Phase Transition

    Science.gov (United States)

    Arai, Shunta; Ohzeki, Masayuki; Tanaka, Kazuyuki

    2018-03-01

    We detect the quantum phase transition of a quantum many-body system by mapping the observed results of the quantum state onto a neural network. In the present study, we utilized the simplest case of a quantum many-body system, namely a one-dimensional chain of Ising spins with the transverse Ising model. We prepared several spin configurations, which were obtained using repeated observations of the model for a particular strength of the transverse field, as input data for the neural network. Although the proposed method can be employed using experimental observations of quantum many-body systems, we tested our technique with spin configurations generated by a quantum Monte Carlo simulation without initial relaxation. The neural network successfully identified the strength of transverse field only from the spin configurations, leading to consistent estimations of the critical point of our model Γc = J.

  14. Periodic Forcing of Inhibition-Stabilized Networks: Nonlinear Resonances and Phase-Amplitude Coupling

    Science.gov (United States)

    Veltz, Romain; Sejnowski, Terrence J.

    2016-01-01

    Inhibition-stabilized networks (ISNs) are neural architectures with strong positive feedback among pyramidal neurons balanced by strong negative feedback from inhibitory interneurons, a circuit element found in the hippocampus and the primary visual cortex. In their working regime, ISNs produce damped oscillations in the γ-range in response to inputs to the inhibitory population. In order to understand the properties of interconnected ISNs, we investigated periodic forcing of ISNs. We show that ISNs can be excited over a range of frequencies and derive properties of the resonance peaks. In particular, we studied the phase-locked solutions, the torus solutions, and the resonance peaks. Periodically forced ISNs respond with (possibly multistable) phase-locked activity, whereas networks with sustained intrinsic oscillations respond more dynamically to periodic inputs with tori. Hence, the dynamics are surprisingly rich, and phase effects alone do not adequately describe the network response. This strengthens the importance of phaseamplitude coupling as opposed to phase-phase coupling in providing multiple frequencies for multiplexing and routing information. PMID:26496044

  15. Motif distributions in phase-space networks for characterizing experimental two-phase flow patterns with chaotic features.

    Science.gov (United States)

    Gao, Zhong-Ke; Jin, Ning-De; Wang, Wen-Xu; Lai, Ying-Cheng

    2010-07-01

    The dynamics of two-phase flows have been a challenging problem in nonlinear dynamics and fluid mechanics. We propose a method to characterize and distinguish patterns from inclined water-oil flow experiments based on the concept of network motifs that have found great usage in network science and systems biology. In particular, we construct from measured time series phase-space complex networks and then calculate the distribution of a set of distinct network motifs. To gain insight, we first test the approach using time series from classical chaotic systems and find a universal feature: motif distributions from different chaotic systems are generally highly heterogeneous. Our main finding is that the distributions from experimental two-phase flows tend to be heterogeneous as well, suggesting the underlying chaotic nature of the flow patterns. Calculation of the maximal Lyapunov exponent provides further support for this. Motif distributions can thus be a feasible tool to understand the dynamics of realistic two-phase flow patterns.

  16. Current distribution in LV networks during 1-phase MV short-circuit

    NARCIS (Netherlands)

    Waes, van J.B.M.; Provoost, F.; Merwe, van der J.; Cobben, J.F.G.; Deursen, van A.P.J.; van Riet, M.J.M.; Laan, van der P.C.T.

    2000-01-01

    This paper describes the consequences of a fault in a medium voltage network on the grounding systems at the LV-side. To study the current distribution and to verify the models, we deliberately introduced one phase to ground faults in the 10 kV floating MV network. The selected site was the end of a

  17. Gait Phases Recognition from Accelerations and Ground Reaction Forces: Application of Neural Networks

    Directory of Open Access Journals (Sweden)

    S. Rafajlović

    2009-06-01

    Full Text Available The goal of this study was to test the applicability of accelerometer as the sensor for assessment of the walking. We present here the comparison of gait phases detected from the data recorded by force sensing resistors mounted in the shoe insoles, non-processed acceleration and processed acceleration perpendicular to the direction of the foot. The gait phases in all three cases were detected by means of a neural network. The output from the neural network was the gait phase, while the inputs were data from the sensors. The results show that the errors were in the ranges: 30 ms (2.7% – force sensors; 150 ms (13.6% – nonprocessed acceleration, and 120 ms (11% – processed acceleration data. This result suggests that it is possible to use the accelerometer as the gait phase detector, however, with the knowledge that the gait phases are time shifted for about 100 ms with respect the neural network predicted times.

  18. Phase transitions in glassy systems via convolutional neural networks

    Science.gov (United States)

    Fang, Chao

    Machine learning is a powerful approach commonplace in industry to tackle large data sets. Most recently, it has found its way into condensed matter physics, allowing for the first time the study of, e.g., topological phase transitions and strongly-correlated electron systems. The study of spin glasses is plagued by finite-size effects due to the long thermalization times needed. Here we use convolutional neural networks in an attempt to detect a phase transition in three-dimensional Ising spin glasses. Our results are compared to traditional approaches.

  19. Phase models and clustering in networks of oscillators with delayed coupling

    Science.gov (United States)

    Campbell, Sue Ann; Wang, Zhen

    2018-01-01

    We consider a general model for a network of oscillators with time delayed coupling where the coupling matrix is circulant. We use the theory of weakly coupled oscillators to reduce the system of delay differential equations to a phase model where the time delay enters as a phase shift. We use the phase model to determine model independent existence and stability results for symmetric cluster solutions. Our results extend previous work to systems with time delay and a more general coupling matrix. We show that the presence of the time delay can lead to the coexistence of multiple stable clustering solutions. We apply our analytical results to a network of Morris Lecar neurons and compare these results with numerical continuation and simulation studies.

  20. Phase-locking and bistability in neuronal networks with synaptic depression

    Science.gov (United States)

    Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

    2018-02-01

    We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.

  1. A multi-scale network method for two-phase flow in porous media

    Energy Technology Data Exchange (ETDEWEB)

    Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

    2017-08-01

    Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

  2. A multi-scale network method for two-phase flow in porous media

    International Nuclear Information System (INIS)

    Khayrat, Karim; Jenny, Patrick

    2017-01-01

    Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

  3. Nonlinear threshold Boolean automata networks and phase transitions

    OpenAIRE

    Demongeot, Jacques; Sené, Sylvain

    2010-01-01

    In this report, we present a formal approach that addresses the problem of emergence of phase transitions in stochastic and attractive nonlinear threshold Boolean automata networks. Nonlinear networks considered are informally defined on the basis of classical stochastic threshold Boolean automata networks in which specific interaction potentials of neighbourhood coalition are taken into account. More precisely, specific nonlinear terms compose local transition functions that define locally t...

  4. Perturbation analysis of complete synchronization in networks of phase oscillators.

    Science.gov (United States)

    Tönjes, Ralf; Blasius, Bernd

    2009-08-01

    The behavior of weakly coupled self-sustained oscillators can often be well described by phase equations. Here we use the paradigm of Kuramoto phase oscillators which are coupled in a network to calculate first- and second-order corrections to the frequency of the fully synchronized state for nonidentical oscillators. The topology of the underlying coupling network is reflected in the eigenvalues and eigenvectors of the network Laplacian which influence the synchronization frequency in a particular way. They characterize the importance of nodes in a network and the relations between them. Expected values for the synchronization frequency are obtained for oscillators with quenched random frequencies on a class of scale-free random networks and for a Erdös-Rényi random network. We briefly discuss an application of the perturbation theory in the second order to network structural analysis.

  5. Complex network analysis of phase dynamics underlying oil-water two-phase flows

    Science.gov (United States)

    Gao, Zhong-Ke; Zhang, Shan-Shan; Cai, Qing; Yang, Yu-Xuan; Jin, Ning-De

    2016-01-01

    Characterizing the complicated flow behaviors arising from high water cut and low velocity oil-water flows is an important problem of significant challenge. We design a high-speed cycle motivation conductance sensor and carry out experiments for measuring the local flow information from different oil-in-water flow patterns. We first use multivariate time-frequency analysis to probe the typical features of three flow patterns from the perspective of energy and frequency. Then we infer complex networks from multi-channel measurements in terms of phase lag index, aiming to uncovering the phase dynamics governing the transition and evolution of different oil-in-water flow patterns. In particular, we employ spectral radius and weighted clustering coefficient entropy to characterize the derived unweighted and weighted networks and the results indicate that our approach yields quantitative insights into the phase dynamics underlying the high water cut and low velocity oil-water flows. PMID:27306101

  6. Markov transition probability-based network from time series for characterizing experimental two-phase flow

    International Nuclear Information System (INIS)

    Gao Zhong-Ke; Hu Li-Dan; Jin Ning-De

    2013-01-01

    We generate a directed weighted complex network by a method based on Markov transition probability to represent an experimental two-phase flow. We first systematically carry out gas—liquid two-phase flow experiments for measuring the time series of flow signals. Then we construct directed weighted complex networks from various time series in terms of a network generation method based on Markov transition probability. We find that the generated network inherits the main features of the time series in the network structure. In particular, the networks from time series with different dynamics exhibit distinct topological properties. Finally, we construct two-phase flow directed weighted networks from experimental signals and associate the dynamic behavior of gas-liquid two-phase flow with the topological statistics of the generated networks. The results suggest that the topological statistics of two-phase flow networks allow quantitative characterization of the dynamic flow behavior in the transitions among different gas—liquid flow patterns. (general)

  7. The default mode network and the working memory network are not anti-correlated during all phases of a working memory task.

    Science.gov (United States)

    Piccoli, Tommaso; Valente, Giancarlo; Linden, David E J; Re, Marta; Esposito, Fabrizio; Sack, Alexander T; Di Salle, Francesco

    2015-01-01

    The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time. To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks. We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between "task-positive" and "task-negative" brain networks. Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.

  8. Generalized network modeling of capillary-dominated two-phase flow.

    Science.gov (United States)

    Raeini, Ali Q; Bijeljic, Branko; Blunt, Martin J

    2018-02-01

    We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network-described in a companion paper [A. Q. Raeini, B. Bijeljic, and M. J. Blunt, Phys. Rev. E 96, 013312 (2017)2470-004510.1103/PhysRevE.96.013312]-which comprises pores that are divided into smaller elements called half-throats and subsequently into corners. Half-throats define the connectivity of the network at the coarsest level, connecting each pore to half-throats of its neighboring pores from their narrower ends, while corners define the connectivity of pore crevices. The corners are discretized at different levels for accurate calculation of entry pressures, fluid volumes, and flow conductivities that are obtained using direct simulation of flow on the underlying image. This paper discusses the two-phase flow model that is used to compute the averaged flow properties of the generalized network, including relative permeability and capillary pressure. We validate the model using direct finite-volume two-phase flow simulations on synthetic geometries, and then present a comparison of the model predictions with a conventional pore-network model and experimental measurements of relative permeability in the literature.

  9. Simulation of two-phase flow in horizontal fracture networks with numerical manifold method

    Science.gov (United States)

    Ma, G. W.; Wang, H. D.; Fan, L. F.; Wang, B.

    2017-10-01

    The paper presents simulation of two-phase flow in discrete fracture networks with numerical manifold method (NMM). Each phase of fluids is considered to be confined within the assumed discrete interfaces in the present method. The homogeneous model is modified to approach the mixed fluids. A new mathematical cover formation for fracture intersection is proposed to satisfy the mass conservation. NMM simulations of two-phase flow in a single fracture, intersection, and fracture network are illustrated graphically and validated by the analytical method or the finite element method. Results show that the motion status of discrete interface significantly depends on the ratio of mobility of two fluids rather than the value of the mobility. The variation of fluid velocity in each fracture segment and the driven fluid content are also influenced by the ratio of mobility. The advantages of NMM in the simulation of two-phase flow in a fracture network are demonstrated in the present study, which can be further developed for practical engineering applications.

  10. Research on three-phase unbalanced distribution network reconfiguration strategy

    Science.gov (United States)

    Hu, Shuang; Li, Ke-Jun; Xu, Yanshun; Liu, Zhijie; Guo, Jing; Wang, Zhuodi

    2017-01-01

    With the development of social economy, the loads installed in the distribution network become more and more complex which may cause the three-phase unbalance problems. This paper proposes an optimal reconfiguration approach based on mixed integer quadric programming (MIQP) method to address the three-phase unbalance problem. It aims to minimize the total network losses of the system. By using several square constraints to substitute the circular constraint, the original optimization problem is linearized and converted into a mixed-integer linear programming (MILP) model. Then this MILP problem is solved in general algebraic model system (GAMS) software using CPLEX solver. The additional losses caused by three-phase unbalanced are also considered. An IEEE 34 nodes test system is used to demonstrate the feasibility and effectiveness of the proposed method. The results show that the losses and the voltage violation mitigation in the network can be reduced significantly.

  11. SELENE - Self-Forming Extensible Lunar EVA Network, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall objective of this research effort (Phase I and Phase II) by Scientific Systems Company, Inc. and BBN Technologies is to develop the SELENE network --...

  12. Multivariate recurrence network analysis for characterizing horizontal oil-water two-phase flow.

    Science.gov (United States)

    Gao, Zhong-Ke; Zhang, Xin-Wang; Jin, Ning-De; Marwan, Norbert; Kurths, Jürgen

    2013-09-01

    Characterizing complex patterns arising from horizontal oil-water two-phase flows is a contemporary and challenging problem of paramount importance. We design a new multisector conductance sensor and systematically carry out horizontal oil-water two-phase flow experiments for measuring multivariate signals of different flow patterns. We then infer multivariate recurrence networks from these experimental data and investigate local cross-network properties for each constructed network. Our results demonstrate that a cross-clustering coefficient from a multivariate recurrence network is very sensitive to transitions among different flow patterns and recovers quantitative insights into the flow behavior underlying horizontal oil-water flows. These properties render multivariate recurrence networks particularly powerful for investigating a horizontal oil-water two-phase flow system and its complex interacting components from a network perspective.

  13. A Two-Phase Coverage-Enhancing Algorithm for Hybrid Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qingguo Zhang

    2017-01-01

    Full Text Available Providing field coverage is a key task in many sensor network applications. In certain scenarios, the sensor field may have coverage holes due to random initial deployment of sensors; thus, the desired level of coverage cannot be achieved. A hybrid wireless sensor network is a cost-effective solution to this problem, which is achieved by repositioning a portion of the mobile sensors in the network to meet the network coverage requirement. This paper investigates how to redeploy mobile sensor nodes to improve network coverage in hybrid wireless sensor networks. We propose a two-phase coverage-enhancing algorithm for hybrid wireless sensor networks. In phase one, we use a differential evolution algorithm to compute the candidate’s target positions in the mobile sensor nodes that could potentially improve coverage. In the second phase, we use an optimization scheme on the candidate’s target positions calculated from phase one to reduce the accumulated potential moving distance of mobile sensors, such that the exact mobile sensor nodes that need to be moved as well as their final target positions can be determined. Experimental results show that the proposed algorithm provided significant improvement in terms of area coverage rate, average moving distance, area coverage–distance rate and the number of moved mobile sensors, when compare with other approaches.

  14. Chiral topological phases from artificial neural networks

    Science.gov (United States)

    Kaubruegger, Raphael; Pastori, Lorenzo; Budich, Jan Carl

    2018-05-01

    Motivated by recent progress in applying techniques from the field of artificial neural networks (ANNs) to quantum many-body physics, we investigate to what extent the flexibility of ANNs can be used to efficiently study systems that host chiral topological phases such as fractional quantum Hall (FQH) phases. With benchmark examples, we demonstrate that training ANNs of restricted Boltzmann machine type in the framework of variational Monte Carlo can numerically solve FQH problems to good approximation. Furthermore, we show by explicit construction how n -body correlations can be kept at an exact level with ANN wave functions exhibiting polynomial scaling with power n in system size. Using this construction, we analytically represent the paradigmatic Laughlin wave function as an ANN state.

  15. Explosive transitions to synchronization in networks of phase oscillators.

    Science.gov (United States)

    Leyva, I; Navas, A; Sendiña-Nadal, I; Almendral, J A; Buldú, J M; Zanin, M; Papo, D; Boccaletti, S

    2013-01-01

    The emergence of dynamical abrupt transitions in the macroscopic state of a system is currently a subject of the utmost interest. The occurrence of a first-order phase transition to synchronization of an ensemble of networked phase oscillators was reported, so far, for very particular network architectures. Here, we show how a sharp, discontinuous transition can occur, instead, as a generic feature of networks of phase oscillators. Precisely, we set conditions for the transition from unsynchronized to synchronized states to be first-order, and demonstrate how these conditions can be attained in a very wide spectrum of situations. We then show how the occurrence of such transitions is always accompanied by the spontaneous setting of frequency-degree correlation features. Third, we show that the conditions for abrupt transitions can be even softened in several cases. Finally, we discuss, as a possible application, the use of this phenomenon to express magnetic-like states of synchronization.

  16. Conducting polymer networks synthesized by photopolymerization-induced phase separation

    Science.gov (United States)

    Yamashita, Yuki; Komori, Kana; Murata, Tasuku; Nakanishi, Hideyuki; Norisuye, Tomohisa; Yamao, Takeshi; Tran-Cong-Miyata, Qui

    2018-03-01

    Polymer mixtures composed of double networks of a polystyrene derivative (PSAF) and poly(methyl methacrylate) (PMMA) were alternatively synthesized by using ultraviolet (UV) and visible (Vis) light. The PSAF networks were generated by UV irradiation to photodimerize the anthracene (A) moieties labeled on the PSAF chains, whereas PMMA networks were produced by photopolymerization of methyl methacrylate (MMA) monomer and the cross-link reaction using ethylene glycol dimethacrylate (EGDMA) under Vis light irradiation. It was found that phase separation process of these networks can be independently induced and promptly controlled by using UV and Vis light. The characteristic length scale distribution of the resulting co-continuous morphology can be well regulated by the UV and Vis light intensity. In order to confirm and utilize the connectivity of the bicontinuous morphology observed by confocal microscopy, a very small amount, 0.1 wt%, of multi-walled carbon nanotubes (MWCNTs) was introduced into the mixture and the current-voltage (I-V) relationship was subsequently examined. Preliminary data show that MWCNTs are preferentially dispersed in the PSAF-rich continuous domains and the whole mixture became electrically conducting, confirming the connectivity of the observed bi-continuous morphology. The experimental data obtained in this study reveal a promising method to design various scaffolds for conducting soft matter taking advantages of photopolymerization-induced phase separation.

  17. Nano-phase separation and structural ordering in silica-rich mixed network former glasses.

    Science.gov (United States)

    Liu, Hao; Youngman, Randall E; Kapoor, Saurabh; Jensen, Lars R; Smedskjaer, Morten M; Yue, Yuanzheng

    2018-06-13

    We investigate the structure, phase separation, glass transition, and crystallization in a mixed network former glass series, i.e., B2O3-Al2O3-SiO2-P2O5 glasses with varying SiO2/B2O3 molar ratio. All the studied glasses exhibit two separate glassy phases: droplet phase (G1) with the size of 50-100 nm and matrix phase (G2), corresponding to a lower calorimetric glass transition temperature (Tg1) and a higher one (Tg2), respectively. Both Tg values decrease linearly with the substitution of B2O3 for SiO2, but the magnitude of the decrease is larger for Tg1. Based on nuclear magnetic resonance and Raman spectroscopy results, we infer that the G1 phase is rich in boroxol rings, while the G2 phase mainly involves the B-O-Si network. Both phases contain BPO4- and AlPO4-like units. Ordered domains occur in G2 upon isothermal and dynamic heating, driven by the structural heterogeneity in the as-prepared glasses. The structural ordering lowers the activation energy of crystal growth, thus promoting partial crystallization of G2. These findings are useful for understanding glass formation and phase separation in mixed network former oxide systems, and for tailoring their properties.

  18. Studies on the phase diagram of boron employing a neural network potential

    Energy Technology Data Exchange (ETDEWEB)

    Morawietz, Tobias; Behler, Joerg [Lehrstuhl fuer Theoretische Chemie, Ruhr-Universitaet Bochum (Germany); Parrinello, Michele [Department of Chemistry and Applied Biosciences, ETH Zuerich (Switzerland)

    2009-07-01

    The crystalline phases of elemental boron have a structural complexity unique in the periodic table. The complex connection pattern of the icosahedral building blocks forms a formidable challenge for the construction of accurate but efficient potentials. We present a high-dimensional neural network potential for boron, which is based on first-principles calculations and can be systematically improved. The potential is several orders of magnitude faster to evaluate than the underlying density-functional theory calculations and allows to perform long molecular dynamics and metadynamics simulations of large system. By a stepwise refinement of the potential and an application of the potential in metadynamics simulations we show that starting from random atomic positions the structure of {alpha}-boron is predicted in agreement with experiment. Further, pressure-induced phase transitions of {alpha}-boron are discussed.

  19. Phase transitions and self-organized criticality in networks of stochastic spiking neurons.

    Science.gov (United States)

    Brochini, Ludmila; de Andrade Costa, Ariadne; Abadi, Miguel; Roque, Antônio C; Stolfi, Jorge; Kinouchi, Osame

    2016-11-07

    Phase transitions and critical behavior are crucial issues both in theoretical and experimental neuroscience. We report analytic and computational results about phase transitions and self-organized criticality (SOC) in networks with general stochastic neurons. The stochastic neuron has a firing probability given by a smooth monotonic function Φ(V) of the membrane potential V, rather than a sharp firing threshold. We find that such networks can operate in several dynamic regimes (phases) depending on the average synaptic weight and the shape of the firing function Φ. In particular, we encounter both continuous and discontinuous phase transitions to absorbing states. At the continuous transition critical boundary, neuronal avalanches occur whose distributions of size and duration are given by power laws, as observed in biological neural networks. We also propose and test a new mechanism to produce SOC: the use of dynamic neuronal gains - a form of short-term plasticity probably located at the axon initial segment (AIS) - instead of depressing synapses at the dendrites (as previously studied in the literature). The new self-organization mechanism produces a slightly supercritical state, that we called SOSC, in accord to some intuitions of Alan Turing.

  20. Plasticity-induced characteristic changes of pattern dynamics and the related phase transitions in small-world neuronal networks

    International Nuclear Information System (INIS)

    Huang Xu-Hui; Hu Gang

    2014-01-01

    Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters (e.g., external stimuli), and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks (LBSW networks) under spike-timing-dependent plasticity (STDP). By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions (SOPTs): repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics. (interdisciplinary physics and related areas of science and technology)

  1. Rounding of abrupt phase transitions in brain networks

    International Nuclear Information System (INIS)

    Martín, Paula Villa; Moretti, Paolo; Muñoz, Miguel A

    2015-01-01

    The observation of critical-like behavior in cortical networks represents a major step forward in elucidating how the brain manages information. Understanding the origin and functionality of critical-like dynamics, as well as its robustness, is a major challenge in contemporary neuroscience. Here, we present an extensive numerical study of a family of simple dynamical models, which describe activity propagation in brain networks through the integration of different neighboring spiking potentials, mimicking basic neural interactions. The requirement of signal integration may lead to discontinuous phase transitions in networks that are well described by the mean-field approximation, thus preventing the emergence of critical points in such systems. Brain networks, however, are finite dimensional and exhibit a heterogeneous hierarchical structure that cannot be encoded in mean-field models. Here we propose that, as a consequence of the presence of such a heterogeneous substrate with its concomitant structural disorder, critical-like features may emerge even in the presence of integration. These conclusions may prove significant in explaining the observation of traits of critical behavior in large-scale measurements of brain activity. (paper)

  2. Social climber attachment in forming networks produces a phase transition in a measure of connectivity

    Science.gov (United States)

    Taylor, Dane; Larremore, Daniel B.

    2012-09-01

    The formation and fragmentation of networks are typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size, examining the emergence of a giant component. This approach does not study the effects of evolving network structure on dynamics that occur at the nodes, such as the synchronization of oscillators and the spread of information, epidemics, and neuronal excitations. We introduce and analyze an alternative link-formation rule, called social climber (SC) attachment, that may be combined with arbitrary percolation models to produce a phase transition using the largest eigenvalue of the network adjacency matrix as the order parameter. This eigenvalue is significant in the analyses of many network-coupled dynamical systems in which it measures the quality of global coupling and is hence a natural measure of connectivity. We highlight the important self-organized properties of SC attachment and discuss implications for controlling dynamics on networks.

  3. Generalized network modeling of capillary-dominated two-phase flow

    Science.gov (United States)

    Raeini, Ali Q.; Bijeljic, Branko; Blunt, Martin J.

    2018-02-01

    We present a generalized network model for simulating capillary-dominated two-phase flow through porous media at the pore scale. Three-dimensional images of the pore space are discretized using a generalized network—described in a companion paper [A. Q. Raeini, B. Bijeljic, and M. J. Blunt, Phys. Rev. E 96, 013312 (2017), 10.1103/PhysRevE.96.013312]—which comprises pores that are divided into smaller elements called half-throats and subsequently into corners. Half-throats define the connectivity of the network at the coarsest level, connecting each pore to half-throats of its neighboring pores from their narrower ends, while corners define the connectivity of pore crevices. The corners are discretized at different levels for accurate calculation of entry pressures, fluid volumes, and flow conductivities that are obtained using direct simulation of flow on the underlying image. This paper discusses the two-phase flow model that is used to compute the averaged flow properties of the generalized network, including relative permeability and capillary pressure. We validate the model using direct finite-volume two-phase flow simulations on synthetic geometries, and then present a comparison of the model predictions with a conventional pore-network model and experimental measurements of relative permeability in the literature.

  4. Macroscopic phase-resetting curves for spiking neural networks

    Science.gov (United States)

    Dumont, Grégory; Ermentrout, G. Bard; Gutkin, Boris

    2017-10-01

    The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

  5. Macroscopic phase-resetting curves for spiking neural networks.

    Science.gov (United States)

    Dumont, Grégory; Ermentrout, G Bard; Gutkin, Boris

    2017-10-01

    The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

  6. Pressure-induced phase transitions in silicon studied by neural network-based metadynamics simulations

    Energy Technology Data Exchange (ETDEWEB)

    Behler, Joerg [Department of Chemistry and Applied Biosciences, ETH Zurich, USI-Campus, Lugano (Switzerland); Lehrstuhl fuer Theoretische Chemie, Ruhr-Universitaet Bochum, 44780 Bochum (Germany); Martonak, Roman [Department of Chemistry and Applied Biosciences, ETH Zurich, USI-Campus, Lugano (Switzerland); Department of Experimental Physics, Faculty of Mathematics, Physics and Informatics, Comenius University, Mlynska dolina F2, 84248 Bratislava (Slovakia); Donadio, Davide [Department of Chemistry and Applied Biosciences, ETH Zurich, USI-Campus, Lugano (Switzerland); Department of Chemistry, UC Davis, One Shields Ave., Davis, CA 95616 (United States); Parrinello, Michele [Department of Chemistry and Applied Biosciences, ETH Zurich, USI-Campus, Lugano (Switzerland)

    2008-12-15

    We present a combination of the metadynamics method for the investigation of pressure-induced phase transitions in solids with a neural network representation of high-dimensional density-functional theory (DFT) potential-energy surfaces. In a recent illustration of the method for the complex high-pressure phase diagram of silicon[Behler et al., Phys. Rev. Lett. 100, 185501 (2008)] we have shown that the full sequence of phases can be reconstructed by a series of subsequent simulations. In the present paper we give a detailed account of the underlying methodology and discuss the scope and limitations of the approach, which promises to be a valuable tool for the investigation of a variety of inorganic materials. The method is several orders of magnitude faster than a direct coupling of metadynamics with electronic structure calculations, while the accuracy is essentially maintained, thus providing access to extended simulations of large systems. (copyright 2008 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  7. NETWORK-CENTRIC TECHNOLOGIES FOR CONTROL OF THREE-PHASE NETWORK OPERATION MODES

    Directory of Open Access Journals (Sweden)

    Ye. I. Sokol

    2017-06-01

    Full Text Available Purpose. The development of the control system for three-phase network is based on intelligent technologies of network-centric control of heterogeneous objects. The introduction of unmanned aerial vehicles for monitoring of three-phase network increases the efficiency of management. Methodology. The case of decomposition of the instantaneous capacities of the fixed and variable components for 3-wire system. The features of power balance for the different modes of its functioning. It should be noted that symmetric sinusoidal mode is balanced and good, but really unbalanced, if the standard reactive power is not zero. To solve the problem of compensation is sufficient knowledge of the total value of the inactive components of full power (value of the inactive power without detail. The creation of a methodology of measurement and assessment will require knowledge of the magnitudes of each inactive component separately, which leads to the development of a unified approach to the measurement and compensation of inactive components of full power and the development of a generalized theory of power. Results. Procedure for the compensation of the current of zero sequence excludes from circuit the source, as the active component of instantaneous power of zero sequence, and a vector due to a current of zero sequence. This procedure is performed without time delay as it does not require integration. Only a 3–wire system with symmetrical voltage eliminates pulsations and symmetrization of the equivalent conductances of the phases of the task. Under asymmetric voltage, the power is different, its analysis requires the creation of a vector mathematical model of the energy processes of asymmetrical modes of 3–phase systems. Originality. The proposed method extends the basis of the vector method for any zero sequence voltages and shows that the various theories of instantaneous power three wired scheme due to the choice of a basis in a two

  8. Complex quantum network geometries: Evolution and phase transitions

    Science.gov (United States)

    Bianconi, Ginestra; Rahmede, Christoph; Wu, Zhihao

    2015-08-01

    Networks are topological and geometric structures used to describe systems as different as the Internet, the brain, or the quantum structure of space-time. Here we define complex quantum network geometries, describing the underlying structure of growing simplicial 2-complexes, i.e., simplicial complexes formed by triangles. These networks are geometric networks with energies of the links that grow according to a nonequilibrium dynamics. The evolution in time of the geometric networks is a classical evolution describing a given path of a path integral defining the evolution of quantum network states. The quantum network states are characterized by quantum occupation numbers that can be mapped, respectively, to the nodes, links, and triangles incident to each link of the network. We call the geometric networks describing the evolution of quantum network states the quantum geometric networks. The quantum geometric networks have many properties common to complex networks, including small-world property, high clustering coefficient, high modularity, and scale-free degree distribution. Moreover, they can be distinguished between the Fermi-Dirac network and the Bose-Einstein network obeying, respectively, the Fermi-Dirac and Bose-Einstein statistics. We show that these networks can undergo structural phase transitions where the geometrical properties of the networks change drastically. Finally, we comment on the relation between quantum complex network geometries, spin networks, and triangulations.

  9. Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks

    Science.gov (United States)

    Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen

    2017-05-01

    In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.

  10. Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases.

    Science.gov (United States)

    Peters, D T J M; Raab, J; Grêaux, K M; Stronks, K; Harting, J

    2017-12-01

    Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as addressing environmental determinants of health. This study examines these relations in different phases of the policy process. A multiple-case study was performed on four public health-related policy networks. Using a snowball method among network actors, overall and sub-networks per policy phase were identified and the policy sector of each actor was assigned. To operationalise the outcome variable, interventions were classified by the proportion of environmental determinants they addressed. In the overall networks, no relation was found between structural network characteristics and network performance. In most effective cases, the policy development sub-networks were characterised by integration with less interrelations between actors (low cohesion), more equally distributed distances between the actors (low closeness centralisation), and horizontal integration in inter-sectoral cliques. The most effective case had non-public health central actors with less connections in all sub-networks. The results suggest that, to address environmental determinants of health, sub-networks should be inter-sectorally composed in the policy development rather than in the intervention development and implementation phases, and that policy development actors should have the opportunity to connect with other actors, without strong direction from a central actor. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Voltage Management in Unbalanced Low Voltage Networks Using a Decoupled Phase-Tap-Changer Transformer

    DEFF Research Database (Denmark)

    Coppo, Massimiliano; Turri, Roberto; Marinelli, Mattia

    2014-01-01

    The paper studies a medium voltage-low voltage transformer with a decoupled on load tap changer capability on each phase. The overall objective is the evaluation of the potential benefits on a low voltage network of such possibility. A realistic Danish low voltage network is used for the analysis...

  12. Prediction of two-phase mixture density using artificial neural networks

    International Nuclear Information System (INIS)

    Lombardi, C.; Mazzola, A.

    1997-01-01

    In nuclear power plants, the density of boiling mixtures has a significant relevance due to its influence on the neutronic balance, the power distribution and the reactor dynamics. Since the determination of the two-phase mixture density on a purely analytical basis is in fact impractical in many situations of interest, heuristic relationships have been developed based on the parameters describing the two-phase system. However, the best or even a good structure for the correlation cannot be determined in advance, also considering that it is usually desired to represent the experimental data with the most compact equation. A possible alternative to empirical correlations is the use of artificial neural networks, which allow one to model complex systems without requiring the explicit formulation of the relationships existing among the variables. In this work, the neural network methodology was applied to predict the density data of two-phase mixtures up-flowing in adiabatic channels under different experimental conditions. The trained network predicts the density data with a root-mean-square error of 5.33%, being ∼ 93% of the data points predicted within 10%. When compared with those of two conventional well-proven correlations, i.e. the Zuber-Findlay and the CISE correlations, the neural network performances are significantly better. In spite of the good accuracy of the neural network predictions, the 'black-box' characteristic of the neural model does not allow an easy physical interpretation of the knowledge integrated in the network weights. Therefore, the neural network methodology has the advantage of not requiring a formal correlation structure and of giving very accurate results, but at the expense of a loss of model transparency. (author)

  13. Phase-synchronisation in continuous flow models of production networks

    Science.gov (United States)

    Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael

    2006-04-01

    To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.

  14. Uganda Health Information Network (UHIN) - Phase IV | IDRC ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    ... reports on drug supplies and use, and continuing education materials. This phase aims to fully integrate the Network into the Ministry of Health district and national ... IWRA/IDRC webinar on climate change and adaptive water management.

  15. Phase synchronization of non-Abelian oscillators on small-world networks

    Energy Technology Data Exchange (ETDEWEB)

    Gu, Zhi-Ming [College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Zhao, Ming [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China); Zhou, Tao [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)]. E-mail: zhutou@ustc.edu; Zhu, Chen-Ping [College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 (China); Wang, Bing-Hong [Department of Modern Physics, University of Science and Technology of China, Hefei 230026 (China)

    2007-02-26

    In this Letter, by extending the concept of Kuramoto oscillator to the left-invariant flow on general Lie group, we investigate the generalized phase synchronization on networks. The analyses and simulations of some typical dynamical systems on Watts-Strogatz networks are given, including the n-dimensional torus, the identity component of 3-dimensional general linear group, the special unitary group, and the special orthogonal group. In all cases, the greater disorder of networks will predict better synchronizability, and the small-world effect ensures the global synchronization for sufficiently large coupling strength. The collective synchronized behaviors of many dynamical systems, such as the integrable systems, the two-state quantum systems and the top systems, can be described by the present phase synchronization frame. In addition, it is intuitive that the low-dimensional systems are more easily to synchronize, however, to our surprise, we found that the high-dimensional systems display obviously synchronized behaviors in regular networks, while these phenomena cannot be observed in low-dimensional systems.

  16. Phase synchronization of non-Abelian oscillators on small-world networks

    International Nuclear Information System (INIS)

    Gu, Zhi-Ming; Zhao, Ming; Zhou, Tao; Zhu, Chen-Ping; Wang, Bing-Hong

    2007-01-01

    In this Letter, by extending the concept of Kuramoto oscillator to the left-invariant flow on general Lie group, we investigate the generalized phase synchronization on networks. The analyses and simulations of some typical dynamical systems on Watts-Strogatz networks are given, including the n-dimensional torus, the identity component of 3-dimensional general linear group, the special unitary group, and the special orthogonal group. In all cases, the greater disorder of networks will predict better synchronizability, and the small-world effect ensures the global synchronization for sufficiently large coupling strength. The collective synchronized behaviors of many dynamical systems, such as the integrable systems, the two-state quantum systems and the top systems, can be described by the present phase synchronization frame. In addition, it is intuitive that the low-dimensional systems are more easily to synchronize, however, to our surprise, we found that the high-dimensional systems display obviously synchronized behaviors in regular networks, while these phenomena cannot be observed in low-dimensional systems

  17. Models for Master-Slave Clock Distribution Networks with Third-Order Phase-Locked Loops

    OpenAIRE

    Piqueira, José Roberto Castilho; de Carvalho Freschi, Marcela

    2007-01-01

    The purpose of this work is to study the processing and transmission of clock signals in networks of geographically distributed nodes, in order to derive conditions for frequency and phase synchronization between the nodes. The focus is on the master-slave architecture, which presents a priority scheme of clock distribution. One-way master-slave (OWMS ) and two-way master-slave (TWMS) chains are studied, considering that the slave nodes are third-order phase-locked loops...

  18. Maxwell rigidity and topological constraints in amorphous phase-change networks

    International Nuclear Information System (INIS)

    Micoulaut, M.; Otjacques, C.; Raty, J.-Y.; Bichara, C.

    2011-01-01

    By analyzing first-principles molecular-dynamics simulations of different telluride amorphous networks, we develop a method for the enumeration of radial and angular topological constraints, and show that the phase diagram of the most popular system Ge-Sb-Te can be split into two compositional elastic phases: a tellurium rich flexible phase and a stressed rigid phase that contains most of the materials used in phase-change applications. This sound atomic scale insight should open new avenues for the understanding of phase-change materials and other complex amorphous materials from the viewpoint of rigidity.

  19. MODELING OF SYMMETRIC THREE-PHASE ASYNCHRONOUS ELECTRIC MOTOR IN ASYMMETRIC CONNECTION TO NETWORK

    Directory of Open Access Journals (Sweden)

    V. I. Lukovnikov

    2005-01-01

    Full Text Available The paper shows how to solve the problem concerning reveal of changes in mathematical models and electric parameters of symmetric three-phase short-circuited asynchronous electric motors in case of their connection to single- or two-phase network in comparison with their connection to three-phase network. The uniform methodological approach permitting to generalize the known data and receive new results is offered in the paper.

  20. Phase synchronization on small-world networks with community structure

    International Nuclear Information System (INIS)

    Xiao-Hua, Wang; Li-Cheng, Jiao; Jian-She, Wu

    2010-01-01

    In this paper, we propose a simple model that can generate small-world network with community structure. The network is introduced as a tunable community organization with parameter r, which is directly measured by the ratio of inter- to intra-community connectivity, and a smaller r corresponds to a stronger community structure. The structure properties, including the degree distribution, clustering, the communication efficiency and modularity are also analysed for the network. In addition, by using the Kuramoto model, we investigated the phase synchronization on this network, and found that increasing the fuzziness of community structure will markedly enhance the network synchronizability; however, in an abnormal region (r ≤ 0.001), the network has even worse synchronizability than the case of isolated communities (r = 0). Furthermore, this network exhibits a remarkable synchronization behaviour in topological scales: the oscillators of high densely interconnected communities synchronize more easily, and more rapidly than the whole network. (general)

  1. A NEW NETWORK FOR HIGHER-TEMPERATURE GAS-PHASE CHEMISTRY. I. A PRELIMINARY STUDY OF ACCRETION DISKS IN ACTIVE GALACTIC NUCLEI

    International Nuclear Information System (INIS)

    Harada, Nanase; Herbst, Eric; Wakelam, Valentine

    2010-01-01

    We present a new interstellar chemical gas-phase reaction network for time-dependent kinetics that can be used for modeling high-temperature sources up to ∼800 K. This network contains an extended set of reactions based on the Ohio State University (OSU) gas-phase chemical network. The additional reactions include processes with significant activation energies, reverse reactions, proton exchange reactions, charge exchange reactions, and collisional dissociation. Rate coefficients already in the OSU network are modified for H 2 formation on grains, ion-neutral dipole reactions, and some radiative association reactions. The abundance of H 2 O is enhanced at high temperature by hydrogenation of atomic O. Much of the elemental oxygen is in the form of water at T ≥ 300 K, leading to effective carbon-rich conditions, which can efficiently produce carbon-chain species such as C 2 H 2 . At higher temperatures, HCN and NH 3 are also produced much more efficiently. We have applied the extended network to a simplified model of the accretion disk of an active galactic nucleus.

  2. Detecting phase synchronization by localized maps: Application to neural networks

    OpenAIRE

    Pereira, T.; Baptista, M. S.; Kurths, J.

    2007-01-01

    We present an approach which enables to state about the existence of phase synchronization in coupled chaotic oscillators without having to measure the phase. This is done by observing the oscillators at special times, and analyzing whether this set of points is localized. In particular, we show that this approach is fruitful to analyze the onset of phase synchronization in chaotic attractors whose phases are not well defined, as well as, in networks of non-identical spiking/bursting neurons ...

  3. Unstable dynamics, nonequilibrium phases, and criticality in networked excitable media

    International Nuclear Information System (INIS)

    Franciscis, S. de; Torres, J. J.; Marro, J.

    2010-01-01

    Excitable systems are of great theoretical and practical interest in mathematics, physics, chemistry, and biology. Here, we numerically study models of excitable media, namely, networks whose nodes may occasionally be dormant and the connection weights are allowed to vary with the system activity on a short-time scale, which is a convenient and realistic representation. The resulting global activity is quite sensitive to stimuli and eventually becomes unstable also in the absence of any stimuli. Outstanding consequences of such unstable dynamics are the spontaneous occurrence of various nonequilibrium phases--including associative-memory phases and one in which the global activity wanders irregularly, e.g., chaotically among all or part of the dynamic attractors--and 1/f noise as the system is driven into the phase region corresponding to the most irregular behavior. A net result is resilience which results in an efficient search in the model attractor space that can explain the origin of some observed behavior in neural, genetic, and ill-condensed matter systems. By extensive computer simulation we also address a previously conjectured relation between observed power-law distributions and the possible occurrence of a ''critical state'' during functionality of, e.g., cortical networks, and describe the precise nature of such criticality in the model which may serve to guide future experiments.

  4. Improving the phase stability of the SLAC rf driveline network for SLC operation

    International Nuclear Information System (INIS)

    Weaver, J.N.; Hogg, H.A.

    1983-01-01

    Successful operation of the Stanford Linear Collider (SLC) will require greater phase stability from the two-mile long rf drive network than previous linac operation did. This paper discusses four proposed modifications of the present system that should help achieve the general objective to reduce all long term temperature and atmospheric pressure induced phase variations to less than 20 0 at 2856 MHz, so that the phase/amplitude detector subsystems, which will control the network output phases relative to a beam reference, will operate within their most accurate ranges

  5. Three-Phase Unbalanced Load Flow Tool for Distribution Networks

    DEFF Research Database (Denmark)

    Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso

    2012-01-01

    This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....

  6. Determining Cloud Thermodynamic Phase from Micropulse Lidar Network Data

    Science.gov (United States)

    Lewis, Jasper R.; Campbell, James; Lolli, Simone; Tan, Ivy; Welton, Ellsworth J.

    2017-01-01

    Determining cloud thermodynamic phase is a critical factor in studies of Earth's radiation budget. Here we use observations from the NASA Micro Pulse Lidar Network (MPLNET) and thermodynamic profiles from the Goddard Earth Observing System, version 5 (GEOS-5) to distinguish liquid water, mixed-phase, and ice water clouds. The MPLNET provides sparse global, autonomous, and continuous measurements of clouds and aerosols which have been used in a number of scientific investigations to date. The use of a standardized instrument and a common suite of data processing algorithms with thorough uncertainty characterization allows for straightforward comparisons between sites. Lidars with polarization capabilities have recently been incorporated into the MPLNET project which allows, for the first time, the ability to infer a cloud thermodynamic phase. This presentation will look specifically at the occurrence of ice and mixed phase clouds in the temperature region of -10 C to -40 C for different climatological regions and seasons. We compare MPLNET occurrences of mixed-phase clouds to an historical climatology based on observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) spacecraft.

  7. Synchronization of Phase Oscillators in Networks with Certain Frequency Sequence

    International Nuclear Information System (INIS)

    Feng Yuan-Yuan; Wu Liang; Zhu Shi-Qun

    2014-01-01

    Synchronization of Kuramoto phase oscillators arranged in real complex neural networks is investigated. It is shown that the synchronization greatly depends on the sets of natural frequencies of the involved oscillators. The influence of network connectivity heterogeneity on synchronization depends particularly on the correlation between natural frequencies and node degrees. This finding implies a potential application that inhibiting the effects caused by the changes of network structure can be balanced out nicely by choosing the correlation parameter appropriately. (general)

  8. Comparison of phase boundaries between kagomé and honeycomb superconducting wire networks

    Science.gov (United States)

    Xiao, Yi; Huse, David A.; Chaikin, Paul M.; Higgins, Mark J.; Bhattacharya, Shobo; Spencer, David

    2002-06-01

    We measure resistively the mean-field superconducting-normal phase boundaries of both kagomé and honeycomb wire networks immersed in a transverse magnetic field. In addition to their agreement with theory about the overall shapes of phase diagrams, they show striking one-to-one correspondence between the cusps in the honeycomb phase boundary and those in the kagomé curve. This correspondence is due to their geometric arrangements and agrees with Lin and Nori's recent calculation. We also find that for the frustrated honeycomb network at f=1/2, the current patterns in the superconducting phase differ between the low-temperature London regime and the higher-temperature Ginzburg-Landau regime near Tc.

  9. Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

    Science.gov (United States)

    Li, Dong; Zhou, Changsong

    2011-01-01

    Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

  10. African Transitional Justice Research Network - Phase II | CRDI ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The African Transitional Justice Research Network (ATJRN) aims to strengthen the capacity of African researchers and civil society institutions to conduct effective human rights advocacy through the production of high-quality, locally based and targeted empirical research. Phase I of the project (102862) focused on creating ...

  11. African Transitional Justice Research Network - Phase II | IDRC ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The African Transitional Justice Research Network (ATJRN) aims to strengthen the capacity of African researchers and civil society institutions to conduct effective human rights advocacy through the production of high-quality, locally based and targeted empirical research. Phase I of the project (102862) focused on creating ...

  12. Phase dynamics of complex-valued neural networks and its application to traffic signal control.

    Science.gov (United States)

    Nishikawa, Ikuko; Iritani, Takeshi; Sakakibara, Kazutoshi; Kuroe, Yasuaki

    2005-01-01

    Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is de-composable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.

  13. Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes

    Science.gov (United States)

    Stamper, I. J.; Jackson, Elais; Wang, Xujing

    2014-01-01

    In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

  14. Organization of anti-phase synchronization pattern in neural networks: what are the key factors?

    Directory of Open Access Journals (Sweden)

    Dong eLi

    2011-12-01

    Full Text Available Anti-phase oscillation has been widely observed in cortical neuralnetwork. Elucidating the mechanism underlying the organization ofanti-phase pattern is of significance for better understanding morecomplicated pattern formations in brain networks. In dynamicalsystems theory, the organization of anti-phase oscillation patternhas usually been considered to relate to time-delay in coupling.This is consistent to conduction delays in real neural networks inthe brain due to finite propagation velocity of action potentials.However, other structural factors in cortical neural network, suchas modular organization (connection density and the coupling types(excitatory or inhibitory, could also play an important role. Inthis work, we investigate the anti-phase oscillation patternorganized on a two-module network of either neuronal cell model orneural mass model, and analyze the impact of the conduction delaytimes, the connection densities, and coupling types. Our resultsshow that delay times and coupling types can play key roles in thisorganization. The connection densities may have an influence on thestability if an anti-phase pattern exists due to the other factors.Furthermore, we show that anti-phase synchronization of slowoscillations can be achieved with small delay times if there isinteraction between slow and fast oscillations. These results aresignificant for further understanding more realistic spatiotemporaldynamics of cortico-cortical communications.

  15. Phase transitions in scale-free neural networks: Departure from the standard mean-field universality class

    International Nuclear Information System (INIS)

    Aldana, Maximino; Larralde, Hernan

    2004-01-01

    We investigate the nature of the phase transition from an ordered to a disordered state that occurs in a family of neural network models with noise. These models are closely related to the majority voter model, where a ferromagneticlike interaction between the elements prevails. Each member of the family is distinguished by the network topology, which is determined by the probability distribution of the number of incoming links. We show that for homogeneous random topologies, the phase transition belongs to the standard mean-field universality class, characterized by the order parameter exponent β=1/2. However, for scale-free networks we obtain phase transition exponents ranging from 1/2 to infinity. Furthermore, we show the existence of a phase transition even for values of the scale-free exponent in the interval (1.5,2], where the average network connectivity diverges

  16. Suppression of phase synchronisation in network based on cat's brain.

    Science.gov (United States)

    Lameu, Ewandson L; Borges, Fernando S; Borges, Rafael R; Iarosz, Kelly C; Caldas, Iberê L; Batista, Antonio M; Viana, Ricardo L; Kurths, Jürgen

    2016-04-01

    We have studied the effects of perturbations on the cat's cerebral cortex. According to the literature, this cortex structure can be described by a clustered network. This way, we construct a clustered network with the same number of areas as in the cat matrix, where each area is described as a sub-network with a small-world property. We focus on the suppression of neuronal phase synchronisation considering different kinds of perturbations. Among the various controlling interventions, we choose three methods: delayed feedback control, external time-periodic driving, and activation of selected neurons. We simulate these interventions to provide a procedure to suppress undesired and pathological abnormal rhythms that can be associated with many forms of synchronisation. In our simulations, we have verified that the efficiency of synchronisation suppression by delayed feedback control is higher than external time-periodic driving and activation of selected neurons of the cat's cerebral cortex with the same coupling strengths.

  17. A Novel Neural Network Vector Control for Single-Phase Grid-Connected Converters with L, LC and LCL Filters

    Directory of Open Access Journals (Sweden)

    Xingang Fu

    2016-04-01

    Full Text Available This paper investigates a novel recurrent neural network (NN-based vector control approach for single-phase grid-connected converters (GCCs with L (inductor, LC (inductor-capacitor and LCL (inductor-capacitor-inductor filters and provides their comparison study with the conventional standard vector control method. A single neural network controller replaces two current-loop PI controllers, and the NN training approximates the optimal control for the single-phase GCC system. The Levenberg–Marquardt (LM algorithm was used to train the NN controller based on the complete system equations without any decoupling policies. The proposed NN approach can solve the decoupling problem associated with the conventional vector control methods for L, LC and LCL-filter-based single-phase GCCs. Both simulation study and hardware experiments demonstrate that the neural network vector controller shows much more improved performance than that of conventional vector controllers, including faster response speed and lower overshoot. Especially, NN vector control could achieve very good performance using low switch frequency. More importantly, the neural network vector controller is a damping free controller, which is generally required by a conventional vector controller for an LCL-filter-based single-phase grid-connected converter and, therefore, can overcome the inefficiency problem caused by damping policies.

  18. Algorithm for detection of the broken phase conductor in the radial networks

    Directory of Open Access Journals (Sweden)

    Ostojić Mladen M.

    2016-01-01

    Full Text Available The paper presents an algorithm for a directional relay to be used for a detection of the broken phase conductor in the radial networks. The algorithm would use synchronized voltages, measured at the beginning and at the end of the line, as input signals. During the process, the measured voltages would be phase-compared. On the basis of the normalized energy, the direction of the phase conductor, with a broken point, would be detected. Software tool Matlab/Simulink package has developed a radial network model which simulates the broken phase conductor. The simulations generated required input signals by which the algorithm was tested. Development of the algorithm along with the formation of the simulation model and the test results of the proposed algorithm are presented in this paper.

  19. Identifying quantum phase transitions with adversarial neural networks

    Science.gov (United States)

    Huembeli, Patrick; Dauphin, Alexandre; Wittek, Peter

    2018-04-01

    The identification of phases of matter is a challenging task, especially in quantum mechanics, where the complexity of the ground state appears to grow exponentially with the size of the system. Traditionally, physicists have to identify the relevant order parameters for the classification of the different phases. We here follow a radically different approach: we address this problem with a state-of-the-art deep learning technique, adversarial domain adaptation. We derive the phase diagram of the whole parameter space starting from a fixed and known subspace using unsupervised learning. This method has the advantage that the input of the algorithm can be directly the ground state without any ad hoc feature engineering. Furthermore, the dimension of the parameter space is unrestricted. More specifically, the input data set contains both labeled and unlabeled data instances. The first kind is a system that admits an accurate analytical or numerical solution, and one can recover its phase diagram. The second type is the physical system with an unknown phase diagram. Adversarial domain adaptation uses both types of data to create invariant feature extracting layers in a deep learning architecture. Once these layers are trained, we can attach an unsupervised learner to the network to find phase transitions. We show the success of this technique by applying it on several paradigmatic models: the Ising model with different temperatures, the Bose-Hubbard model, and the Su-Schrieffer-Heeger model with disorder. The method finds unknown transitions successfully and predicts transition points in close agreement with standard methods. This study opens the door to the classification of physical systems where the phase boundaries are complex such as the many-body localization problem or the Bose glass phase.

  20. Phase-response curves and synchronized neural networks.

    Science.gov (United States)

    Smeal, Roy M; Ermentrout, G Bard; White, John A

    2010-08-12

    We review the principal assumptions underlying the application of phase-response curves (PRCs) to synchronization in neuronal networks. The PRC measures how much a given synaptic input perturbs spike timing in a neural oscillator. Among other applications, PRCs make explicit predictions about whether a given network of interconnected neurons will synchronize, as is often observed in cortical structures. Regarding the assumptions of the PRC theory, we conclude: (i) The assumption of noise-tolerant cellular oscillations at or near the network frequency holds in some but not all cases. (ii) Reduced models for PRC-based analysis can be formally related to more realistic models. (iii) Spike-rate adaptation limits PRC-based analysis but does not invalidate it. (iv) The dependence of PRCs on synaptic location emphasizes the importance of improving methods of synaptic stimulation. (v) New methods can distinguish between oscillations that derive from mutual connections and those arising from common drive. (vi) It is helpful to assume linear summation of effects of synaptic inputs; experiments with trains of inputs call this assumption into question. (vii) Relatively subtle changes in network structure can invalidate PRC-based predictions. (viii) Heterogeneity in the preferred frequencies of component neurons does not invalidate PRC analysis, but can annihilate synchronous activity.

  1. Chaos in generically coupled phase oscillator networks with nonpairwise interactions.

    Science.gov (United States)

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana

    2016-09-01

    The Kuramoto-Sakaguchi system of coupled phase oscillators, where interaction between oscillators is determined by a single harmonic of phase differences of pairs of oscillators, has very simple emergent dynamics in the case of identical oscillators that are globally coupled: there is a variational structure that means the only attractors are full synchrony (in-phase) or splay phase (rotating wave/full asynchrony) oscillations and the bifurcation between these states is highly degenerate. Here we show that nonpairwise coupling-including three and four-way interactions of the oscillator phases-that appears generically at the next order in normal-form based calculations can give rise to complex emergent dynamics in symmetric phase oscillator networks. In particular, we show that chaos can appear in the smallest possible dimension of four coupled phase oscillators for a range of parameter values.

  2. Evaluation of partnership working in cities in phase IV of the WHO Healthy Cities Network.

    Science.gov (United States)

    Lipp, Alistair; Winters, Tim; de Leeuw, Evelyne

    2013-10-01

    An intersectoral partnership for health improvement is a requirement of the WHO European Healthy Cities Network of municipalities. A review was undertaken in 59 cities based on responses to a structured questionnaire covering phase IV of the network (2003-2008). Cities usually combined formal and informal working partnerships in a pattern seen in previous phases. However, these encompassed more sectors than previously and achieved greater degrees of collaborative planning and implementation. Additional WHO technical support and networking in phase IV significantly enhanced collaboration with the urban planning sector. Critical success factors were high-level political commitment and a well-organized Healthy City office. Partnerships remain a successful component of Healthy City working. The core principles, purpose and intellectual rationale for intersectoral partnerships remain valid and fit for purpose. This applied to long-established phase III cities as well as newcomers to phase IV. The network, and in particular the WHO brand, is well regarded and encourages political and organizational engagement and is a source of support and technical expertise. A key challenge is to apply a more rigorous analytical framework and theory-informed approach to reviewing partnership and collaboration parameters.

  3. Integral equation theory study on the phase separation in star polymer nanocomposite melts.

    Science.gov (United States)

    Zhao, Lei; Li, Yi-Gui; Zhong, Chongli

    2007-10-21

    The polymer reference interaction site model theory is used to investigate phase separation in star polymer nanocomposite melts. Two kinds of spinodal curves were obtained: classic fluid phase boundary for relatively low nanoparticle-monomer attraction strength and network phase boundary for relatively high nanoparticle-monomer attraction strength. The network phase boundaries are much more sensitive with nanoparticle-monomer attraction strength than the fluid phase boundaries. The interference among the arm number, arm length, and nanoparticle-monomer attraction strength was systematically investigated. When the arm lengths are short, the network phase boundary shows a marked shift toward less miscibility with increasing arm number. When the arm lengths are long enough, the network phase boundaries show opposite trends. There exists a crossover arm number value for star polymer nanocomposite melts, below which the network phase separation is consistent with that of chain polymer nanocomposite melts. However, the network phase separation shows qualitatively different behaviors when the arm number is larger than this value.

  4. Interictal to Ictal Phase Transition in a Small-World Network

    Science.gov (United States)

    Nemzer, Louis; Cravens, Gary; Worth, Robert

    Real-time detection and prediction of seizures in patients with epilepsy is essential for rapid intervention. Here, we perform a full Hodgkin-Huxley calculation using n 50 in silico neurons configured in a small-world network topology to generate simulated EEG signals. The connectivity matrix, constructed using a Watts-Strogatz algorithm, admits randomized or deterministic entries. We find that situations corresponding to interictal (non-seizure) and ictal (seizure) states are separated by a phase transition that can be influenced by congenital channelopathies, anticonvulsant drugs, and connectome plasticity. The interictal phase exhibits scale-free phenomena, as characterized by a power law form of the spectral power density, while the ictal state suffers from pathological synchronization. We compare the results with intracranial EEG data and show how these findings may be used to detect or even predict seizure onset. Along with the balance of excitatory and inhibitory factors, the network topology plays a large role in determining the overall characteristics of brain activity. We have developed a new platform for testing the conditions that contribute to the phase transition between non-seizure and seizure states.

  5. Analysis of a phase synchronized functional network based on the rhythm of brain activities

    International Nuclear Information System (INIS)

    Li Ling; Jin Zhen-Lan; Li Bin

    2011-01-01

    Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram (EEG) data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta (4–7 Hz), alpha (8–13 Hz) and beta (14–30 Hz) bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coefficient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm. (interdisciplinary physics and related areas of science and technology)

  6. Performance analysis of wavelength/spatial coding system with fixed in-phase code matrices in OCDMA network

    Science.gov (United States)

    Tsai, Cheng-Mu; Liang, Tsair-Chun

    2011-12-01

    This paper proposes a wavelength/spatial (W/S) coding system with fixed in-phase code (FIPC) matrix in the optical code-division multiple-access (OCDMA) network. A scheme is presented to form the FIPC matrix which is applied to construct the W/S OCDMA network. The encoder/decoder in the W/S OCDMA network is fully able to eliminate the multiple-access-interference (MAI) at the balanced photo-detectors (PD), according to fixed in-phase cross correlation. The phase-induced intensity noise (PIIN) related to the power square is markedly suppressed in the receiver by spreading the received power into each PD while the net signal power is kept the same. Simulation results show that the W/S OCDMA network based on the FIPC matrices cannot only completely remove the MAI but effectively suppress the PIIN to upgrade the network performance.

  7. Coordinated single-phase control scheme for voltage unbalance reduction in low voltage network.

    Science.gov (United States)

    Pullaguram, Deepak; Mishra, Sukumar; Senroy, Nilanjan

    2017-08-13

    Low voltage (LV) distribution systems are typically unbalanced in nature due to unbalanced loading and unsymmetrical line configuration. This situation is further aggravated by single-phase power injections. A coordinated control scheme is proposed for single-phase sources, to reduce voltage unbalance. A consensus-based coordination is achieved using a multi-agent system, where each agent estimates the averaged global voltage and current magnitudes of individual phases in the LV network. These estimated values are used to modify the reference power of individual single-phase sources, to ensure system-wide balanced voltages and proper power sharing among sources connected to the same phase. Further, the high X / R ratio of the filter, used in the inverter of the single-phase source, enables control of reactive power, to minimize voltage unbalance locally. The proposed scheme is validated by simulating a LV distribution network with multiple single-phase sources subjected to various perturbations.This article is part of the themed issue 'Energy management: flexibility, risk and optimization'. © 2017 The Author(s).

  8. A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

    Science.gov (United States)

    Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin

    2017-12-01

    Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

  9. Voltage unbalance mitigation in LV networks using three-phase PV systems

    DEFF Research Database (Denmark)

    Garcia Bajo, Cristina; Hashemi Toghroljerdi, Seyedmostafa; Bækhøj Kjær, Søren

    2015-01-01

    In this paper a new method is proposed to mitigate voltage unbalance caused by single-phase solar inverters in low voltage (LV) networks. The method is based on uneven reactive power absorption and injection by three-phase solar inverters. Independent control of each phase is performed to achieve...... this uneven injection. The average values of phase voltages at the connection points of the photovoltaic (PV) inverters are used as the references for the balancing algorithm. Voltage unbalance mitigation is achieved by use of this method in different scenarios with variable three-phase and single......-phase inverters penetration in a realistic LV grid. In addition, the overvoltage is reduced by using this method....

  10. Chaos in generically coupled phase oscillator networks with nonpairwise interactions

    Energy Technology Data Exchange (ETDEWEB)

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana [Centre for Systems, Dynamics and Control and Department of Mathematics, University of Exeter, Exeter EX4 4QF (United Kingdom)

    2016-09-15

    The Kuramoto–Sakaguchi system of coupled phase oscillators, where interaction between oscillators is determined by a single harmonic of phase differences of pairs of oscillators, has very simple emergent dynamics in the case of identical oscillators that are globally coupled: there is a variational structure that means the only attractors are full synchrony (in-phase) or splay phase (rotating wave/full asynchrony) oscillations and the bifurcation between these states is highly degenerate. Here we show that nonpairwise coupling—including three and four-way interactions of the oscillator phases—that appears generically at the next order in normal-form based calculations can give rise to complex emergent dynamics in symmetric phase oscillator networks. In particular, we show that chaos can appear in the smallest possible dimension of four coupled phase oscillators for a range of parameter values.

  11. Chemical and phase structure of poly cyanurate-polyurethane grafted semi interpenetrating polymer networks

    International Nuclear Information System (INIS)

    Fainleib, A.M.; Gomza, Yu.P.; Privalko, V.P.; Bershtein, V.A.; Carini, G.

    2001-01-01

    In this research the phase morphology and properties of dicyanate ester of bisphenol A (DCEBA) based poly cyanurate network (PCN) modified with linear polyurethane (LPU) were successfully studied by the combination of infra-red spectroscopy, small-angle X-ray scattering (SAXS), dynamic mechanical thermal analysis (DMTA), differential scanning calorimetry and laser-interferometric creep rate spectroscopy

  12. NCC simulation model. Phase 2: Simulating the operations of the Network Control Center and NCC message manual

    Science.gov (United States)

    Benjamin, Norman M.; Gill, Tepper; Charles, Mary

    1994-01-01

    The network control center (NCC) provides scheduling, monitoring, and control of services to the NASA space network. The space network provides tracking and data acquisition services to many low-earth orbiting spacecraft. This report describes the second phase in the development of simulation models for the FCC. Phase one concentrated on the computer systems and interconnecting network.Phase two focuses on the implementation of the network message dialogs and the resources controlled by the NCC. Performance measures were developed along with selected indicators of the NCC's operational effectiveness.The NCC performance indicators were defined in terms of the following: (1) transfer rate, (2) network delay, (3) channel establishment time, (4) line turn around time, (5) availability, (6) reliability, (7) accuracy, (8) maintainability, and (9) security. An NCC internal and external message manual is appended to this report.

  13. Detecting phase transitions in a neural network and its application to classification of syndromes in traditional Chinese medicine

    Energy Technology Data Exchange (ETDEWEB)

    Chen, J; Xi, G [Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, 100080, Beijing (China); Wang, W [Beijing University of Chinese Medicine, 100029, Beijing (China)], E-mail: guangcheng.xi@ia.ac.cn

    2008-02-15

    Detecting phase transitions in neural networks (determined or random) presents a challenging subject for phase transitions play a key role in human brain activity. In this paper, we detect numerically phase transitions in two types of random neural network(RNN) under proper parameters.

  14. Wireless Networked Sensors for Remote Monitoring in Propulsion Systems, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This NASA Phase I SBIR program would fabricate wireless networked nanomembrane (NM) based surface pressure sensors for remote monitoring in propulsion systems, using...

  15. A neural network approach to the study of dynamics and structure of molecular systems

    International Nuclear Information System (INIS)

    Getino, C.; Sumpter, B.G.; Noid, D.W.

    1994-01-01

    Neural networks are used to study intramolecular energy flow in molecular systems (tetratomics to macromolecules), developing new techniques for efficient analysis of data obtained from molecular-dynamics and quantum mechanics calculations. Neural networks can map phase space points to intramolecular vibrational energies along a classical trajectory (example of complicated coordinate transformation), producing reasonably accurate values for any region of the multidimensional phase space of a tetratomic molecule. Neural network energy flow predictions are found to significantly enhance the molecular-dynamics method to longer time-scales and extensive averaging of trajectories for macromolecular systems. Pattern recognition abilities of neural networks can be used to discern phase space features. Neural networks can also expand model calculations by interpolation of costly quantum mechanical ab initio data, used to develop semiempirical potential energy functions

  16. A new approach of chaos and complex network method to study fluctuation and phase transition in nuclear collision at high energy

    Energy Technology Data Exchange (ETDEWEB)

    Bhaduri, Susmita; Bhaduri, Anirban; Ghosh, Dipak [Deepa Ghosh Research Foundation, Kolkata (India)

    2017-06-15

    In the endeavour to study fluctuation and a signature of phase transition in ultrarelativistic nuclear collision during the process of particle production, an approach based on chaos and complex network is proposed. In this work we have attempted an exhaustive study of pion fluctuation in η space, φ space, their cross-correlation and finally two-dimensional fluctuation in terms of scaling of void probability distribution. The analysis is done on the η values and their corresponding φ values extracted from the {sup 32}S-Ag/Br interaction at an incident energy of 200 GeV per nucleon. The methods used are Multifractal Detrended Cross-Correlation Analysis (MF-DXA) and a chaos-based rigorous complex network method -Visibility Graph. The analysis reveals that the highest degree of cross-correlation between pseudorapidity and azimuthal angles exists in the most central region of the interaction. The analysis further shows that two-dimensional void distribution corresponding to the η-φ space reveals a strong scaling behaviour. Both cross-correlation coefficients of MF-DXA and PSVG (Power of the Scale-freeness in Visibility Graph, which is implicitly connected with the Hurst exponent) can be effectively used for the quantitative assessment of pion fluctuation in a very precise manner and have the capability to assess the tendency of approaching criticality for phase transitions. (orig.)

  17. Working memory activation of neural networks in the elderly as a function of information processing phase and task complexity.

    Science.gov (United States)

    Charroud, Céline; Steffener, Jason; Le Bars, Emmanuelle; Deverdun, Jérémy; Bonafe, Alain; Abdennour, Meriem; Portet, Florence; Molino, François; Stern, Yaakov; Ritchie, Karen; Menjot de Champfleur, Nicolas; Akbaraly, Tasnime N

    2015-11-01

    Changes in working memory are sensitive indicators of both normal and pathological brain aging and associated disability. The present study aims to further understanding of working memory in normal aging using a large cohort of healthy elderly in order to examine three separate phases of information processing in relation to changes in task load activation. Using covariance analysis, increasing and decreasing neural activation was observed on fMRI in response to a delayed item recognition task in 337 cognitively healthy elderly persons as part of the CRESCENDO (Cognitive REServe and Clinical ENDOphenotypes) study. During three phases of the task (stimulation, retention, probe), increased activation was observed with increasing task load in bilateral regions of the prefrontal cortex, parietal lobule, cingulate gyrus, insula and in deep gray matter nuclei, suggesting an involvement of central executive and salience networks. Decreased activation associated with increasing task load was observed during the stimulation phase, in bilateral temporal cortex, parietal lobule, cingulate gyrus and prefrontal cortex. This spatial distribution of decreased activation is suggestive of the default mode network. These findings support the hypothesis of an increased activation in salience and central executive networks and a decreased activation in default mode network concomitant to increasing task load. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. The impact of intermediate wet states on two-phase flow in porous media, studied by network modelling

    Energy Technology Data Exchange (ETDEWEB)

    Hoeiland, Linda Kaada

    2006-04-15

    Reservoir wettability is a measure of a rocks preference for the oil and/or the brine phase. Wettability has a dominant impact on fluid movements in porous media, hence oil displacement in reservoir rocks. Understanding the local wettability and the effect of wettability on the fluid movements are therefore of interest in relation to oil recovery processes. Contrary to the earlier believed homogenous wetted cases where the porous media was strongly oil-wet for carbonate reservoirs or strongly water-wet for clastic reservoirs, it is now believed that most reservoir rocks experience some kind of intermediate wet state. Since wettability affects oil recovery, different classes of intermediate wettability are expected to have different impacts on the fluid flow processes. The major subject treated in this thesis is how different intermediate wet states affect fluid flow parameters which are important for the oil recovery. This is done by use of a capillary dominated network model of two-phase flow, where the network is based on a model of reconstructed sandstone. The existence of different intermediate wet classes is argued in Paper I, while Paper II, III and IV analyse the effect different intermediate wet classes have on wettability indices, residual oil saturation, capillary pressure and relative permeability (author)

  19. Entraining the topology and the dynamics of a network of phase oscillators

    Science.gov (United States)

    Sendiña-Nadal, I.; Leyva, I.; Buldú, J. M.; Almendral, J. A.; Boccaletti, S.

    2009-04-01

    We show that the topology and dynamics of a network of unsynchronized Kuramoto oscillators can be simultaneously controlled by means of a forcing mechanism which yields a phase locking of the oscillators to that of an external pacemaker in connection with the reshaping of the network’s degree distribution. The entrainment mechanism is based on the addition, at regular time intervals, of unidirectional links from oscillators that follow the dynamics of a pacemaker to oscillators in the pristine graph whose phases hold a prescribed phase relationship. Such a dynamically based rule in the attachment process leads to the emergence of a power-law shape in the final degree distribution of the graph whenever the network is entrained to the dynamics of the pacemaker. We show that the arousal of a scale-free distribution in connection with the success of the entrainment process is a robust feature, characterizing different networks’ initial configurations and parameters.

  20. Methodologies for assessing the use-phase power consumption and greenhouse gas emissions of telecommunications network services.

    Science.gov (United States)

    Chan, Chien A; Gygax, André F; Wong, Elaine; Leckie, Christopher A; Nirmalathas, Ampalavanapillai; Kilper, Daniel C

    2013-01-02

    Internet traffic has grown rapidly in recent years and is expected to continue to expand significantly over the next decade. Consequently, the resulting greenhouse gas (GHG) emissions of telecommunications service-supporting infrastructures have become an important issue. In this study, we develop a set of models for assessing the use-phase power consumption and carbon dioxide emissions of telecom network services to help telecom providers gain a better understanding of the GHG emissions associated with the energy required for their networks and services. Due to the fact that measuring the power consumption and traffic in a telecom network is a challenging task, these models utilize different granularities of available network information. As the granularity of the network measurement information decreases, the corresponding models have the potential to produce larger estimation errors. Therefore, we examine the accuracy of these models under various network scenarios using two approaches: (i) a sensitivity analysis through simulations and (ii) a case study of a deployed network. Both approaches show that the accuracy of the models depends on the network size, the total amount of network service traffic (i.e., for the service under assessment), and the number of network nodes used to process the service.

  1. Identification of lines of electric lines of three-phase distribution networks in the composition of ASMAE

    Directory of Open Access Journals (Sweden)

    Omorov Turatbek

    2017-01-01

    Full Text Available The problem of protection of a three-phase four-wire distribution network (DEN with a voltage of 0.4 kV from the interruption of electric power lines is considered. On the basis of the analysis of the values of complex resistances of interpersonal sections of the main line of the network, criteria are proposed that allow detecting critical situations associated with discontinuities in power transmission lines. Using these criteria makes it possible to localize the places of breaks of phase and neutral wires. Mathematical models and methods that are used to evaluate the complex resistances of interpersonal sections of a three-phase network are briefly considered. The obtained results are oriented for use in the automated system of electricity control and accounting (ASMAE.

  2. Graph and Network for Model Elicitation (GNOME Phase 2)

    Science.gov (United States)

    2013-02-01

    GRAPH AND NETWORK FOR MODEL ELICITATION (GNOME PHASE II) CUBRC FEBRUARY 2013 FINAL TECHNICAL REPORT APPROVED FOR...NUMBER 00 5f. WORK UNIT NUMBER 01 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) CUBRC 4455 Genesee St. Buffalo, NY 14225 8. PERFORMING...Explorer Since the previous version of GNOME was developed as an Eclipse RCP plug-in, it allowed CUBRC to develop the Model Explorer separately without

  3. Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models Using Deep Three-Dimensional Convolutional Neural Network

    Science.gov (United States)

    Mano, Tomohiro; Ohtsuki, Tomi

    2017-11-01

    The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization-localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016), 86, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center.

  4. 3D quantitative phase imaging of neural networks using WDT

    Science.gov (United States)

    Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

    2015-03-01

    White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

  5. Propagation based phase retrieval of simulated intensity measurements using artificial neural networks

    Science.gov (United States)

    Kemp, Z. D. C.

    2018-04-01

    Determining the phase of a wave from intensity measurements has many applications in fields such as electron microscopy, visible light optics, and medical imaging. Propagation based phase retrieval, where the phase is obtained from defocused images, has shown significant promise. There are, however, limitations in the accuracy of the retrieved phase arising from such methods. Sources of error include shot noise, image misalignment, and diffraction artifacts. We explore the use of artificial neural networks (ANNs) to improve the accuracy of propagation based phase retrieval algorithms applied to simulated intensity measurements. We employ a phase retrieval algorithm based on the transport-of-intensity equation to obtain the phase from simulated micrographs of procedurally generated specimens. We then train an ANN with pairs of retrieved and exact phases, and use the trained ANN to process a test set of retrieved phase maps. The total error in the phase is significantly reduced using this method. We also discuss a variety of potential extensions to this work.

  6. The PAGES 2k Network, Phase 3: Themes and Call for Participation

    Science.gov (United States)

    von Gunten, L.; Mcgregor, H. V.; Martrat, B.; St George, S.; Neukom, R.; Bothe, O.; Linderholm, H. W.; Phipps, S. J.; Abram, N.

    2017-12-01

    The past 2000 years (the "2k" interval) provides critical context for understanding recent anthropogenic forcing of the climate and provides baseline information about the characteristics of natural climate variability. It also presents opportunities to improve the interpretation of proxy observations and to evaluate the climate models used to make future projections. Phases 1 and 2 of the PAGES 2k Network focussed on building regional and global surface temperature reconstructions for terrestrial regions and the oceans, and comparing these with model simulations to identify mechanisms of climate variation on interannual to bicentennial time scales. Phase 3 was launched in May 2017 and aims to address major questions around past hydroclimate, climate processes and proxy uncertainties. Its scientific themes are: Theme 1: "Climate Variability, Modes and Mechanisms"Further understand the mechanisms driving regional climate variability and change on interannual to centennial time scales; Theme 2: "Methods and Uncertainties"Reduce uncertainties in the interpretation of observations imprinted in paleoclimatic archives by environmental sensors; Theme 3: "Proxy and Model Understanding"Identify and analyse the extent of agreement between reconstructions and climate model simulations. Research is organized as a linked network of well-defined projects, identified and led by 2k community members. The 2k projects focus on specific scientific questions aligned with Phase 3 themes, rather than being defined along regional boundaries. New 2k projects can be proposed at any time at http://www.pastglobalchanges.org/ini/wg/2k-network/projects An enduring element of PAGES 2k is a culture of collegiality, transparency, and reciprocity. Phase 3 seeks to stimulate community based projects and facilitate collaboration between researchers from different regions and career stages, drawing on the breadth and depth of the global PAGES 2k community. All PAGES 2k projects also promote best

  7. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  8. Multi-Cluster Network on a Chip Reconfigurable Radiation Hardened Radio, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of the Phase-I research is to architect, model and simulate a multi-cluster Network on a Chip (NoC) reconfigurable Radio in SystemC RTL, with...

  9. CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

    Science.gov (United States)

    Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

    2017-12-01

    We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

  10. ESTABLISHED MODES AND STATIC CHARACTERISTICS OF THREE-PHASE ASYNCHRONOUS MOTOR POWERED WITH SINGLE PHASE NETWORK

    Directory of Open Access Journals (Sweden)

    V. S. Malyar

    2016-01-01

    Full Text Available A mathematical model is developed to study the operation of three-phase asynchronous motor with squirrel-cage rotor when the stator winding is powered from a single phase network. To create a rotating magnetic field one of the phases is fed through the capacitor. Due to the asymmetry of power feed not only transients, but the steady-state regimes are dynamic, so they are described by differential equations in any coordinate system. Their study cannot be carried out with sufficient adequacy on the basis of known equivalent circuits and require the use of dynamic parameters. In the mathematical model the state equations of the circuits of the stator and rotor are composed in the stationary three phase coordinate system. Calculation of the established mode is performed by solving the boundary problem that makes it possible to obtain the coordinate dependences over the period, without calculation of the transient process. In order to perform it, the original nonlinear differential equations are algebraized by approximating the variables with the use of cubic splines. The resulting nonlinear system of algebraic equations is a discrete analogue of the initial system of differential equations. It is solved by parameter continuation method. To calculate the static characteristics as a function of a certain variable, the system is analytically differentiated, and then numerically integrated over this variable. In the process of integration, Newton's refinement is performed at each step or at every few steps, making it possible to implement the integration in just a few steps using Euler's method. Jacobi matrices in both cases are the same. To account for the current displacement in the rods of the squirrel-cage rotor, each of them, along with the squirrel-cage rings, is divided in height into several elements. This results in several squirrel-cage rotor windings which are represented by three-phase windings with magnetic coupling between them.

  11. MONITOR Ionospheric Network: two case studies on scintillation and electron content variability

    Directory of Open Access Journals (Sweden)

    Y. Béniguel

    2017-03-01

    Full Text Available The ESA MONITOR network is composed of high-frequency-sampling global navigation satellite systems (GNSS receivers deployed mainly at low and high latitudes to study ionosphere variability and jointly with global GNSS data and ionospheric processing software in support of the GNSS and its satellite-based augmentation systems (SBAS like the European EGNOS. In a recent phase of the project, the network was merged with the CNES/ASECNA network and new receivers were added to complement the latter in the western African sector. This paper summarizes MONITOR, presenting two case studies on scintillations (using almost 2 years of data measurements. The first case occurred during the major St. Patrick's Day geomagnetic storm in 2015. The second case study was performed in the last phase of the project, which was supported by ESA EGNOS Project Office, when we paid special attention to extreme events that might degrade the system performance of the European EGNOS.

  12. Optimization of Network Topology in Computer-Aided Detection Schemes Using Phased Searching with NEAT in a Time-Scaled Framework.

    Science.gov (United States)

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-01-01

    In the field of computer-aided mammographic mass detection, many different features and classifiers have been tested. Frequently, the relevant features and optimal topology for the artificial neural network (ANN)-based approaches at the classification stage are unknown, and thus determined by trial-and-error experiments. In this study, we analyzed a classifier that evolves ANNs using genetic algorithms (GAs), which combines feature selection with the learning task. The classifier named "Phased Searching with NEAT in a Time-Scaled Framework" was analyzed using a dataset with 800 malignant and 800 normal tissue regions in a 10-fold cross-validation framework. The classification performance measured by the area under a receiver operating characteristic (ROC) curve was 0.856 ± 0.029. The result was also compared with four other well-established classifiers that include fixed-topology ANNs, support vector machines (SVMs), linear discriminant analysis (LDA), and bagged decision trees. The results show that Phased Searching outperformed the LDA and bagged decision tree classifiers, and was only significantly outperformed by SVM. Furthermore, the Phased Searching method required fewer features and discarded superfluous structure or topology, thus incurring a lower feature computational and training and validation time requirement. Analyses performed on the network complexities evolved by Phased Searching indicate that it can evolve optimal network topologies based on its complexification and simplification parameter selection process. From the results, the study also concluded that the three classifiers - SVM, fixed-topology ANN, and Phased Searching with NeuroEvolution of Augmenting Topologies (NEAT) in a Time-Scaled Framework - are performing comparably well in our mammographic mass detection scheme.

  13. Transmission Network Expansion Planning Considering Phase-Shifter Transformers

    Directory of Open Access Journals (Sweden)

    Celso T. Miasaki

    2012-01-01

    Full Text Available This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process.

  14. New all-passive 4x4 planar optical phase diversity network

    NARCIS (Netherlands)

    Soldano, L.B.; Smit, M.K.; Vreede, De A.H.; Uffelen, van J.W.M.; Verbeek, B.H.; Bennekom, van P.K.; Krom, de W.H.C.; Etten, van W.C.

    1991-01-01

    The realisation and performance of an all-passive silicon-based 4*4 planar optical hybrid receiver for operation at 1.55- mu m wavelength is reported here for the first time. Measurements show 5 degrees /12 degrees /12 degrees /9 degrees output phase deviations, without tuning or trimming. Network

  15. Decomposing neural synchrony: toward an explanation for near-zero phase-lag in cortical oscillatory networks.

    Directory of Open Access Journals (Sweden)

    Rajasimhan Rajagovindan

    Full Text Available BACKGROUND: Synchronized oscillation in cortical networks has been suggested as a mechanism for diverse functions ranging from perceptual binding to memory formation to sensorimotor integration. Concomitant with synchronization is the occurrence of near-zero phase-lag often observed between network components. Recent theories have considered the importance of this phenomenon in establishing an effective communication framework among neuronal ensembles. METHODOLOGY/PRINCIPAL FINDINGS: Two factors, among possibly others, can be hypothesized to contribute to the near-zero phase-lag relationship: (1 positively correlated common input with no significant relative time delay and (2 bidirectional interaction. Thus far, no empirical test of these hypotheses has been possible for lack of means to tease apart the specific causes underlying the observed synchrony. In this work simulation examples were first used to illustrate the ideas. A quantitative method that decomposes the statistical interdependence between two cortical areas into a feed-forward, a feed-back and a common-input component was then introduced and applied to test the hypotheses on multichannel local field potential recordings from two behaving monkeys. CONCLUSION/SIGNIFICANCE: The near-zero phase-lag phenomenon is important in the study of large-scale oscillatory networks. A rigorous mathematical theorem is used for the first time to empirically examine the factors that contribute to this phenomenon. Given the critical role that oscillatory activity is likely to play in the regulation of biological processes at all levels, the significance of the proposed method may extend beyond systems neuroscience, the level at which the present analysis is conceived and performed.

  16. A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots.

    Science.gov (United States)

    Jung, Jun-Young; Heo, Wonho; Yang, Hyundae; Park, Hyunsub

    2015-10-30

    An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases.

  17. Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

    Science.gov (United States)

    Liu, Quan-Hui; Wang, Wei; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

    2018-02-01

    Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

  18. Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks.

    Science.gov (United States)

    Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L; Carr, Lincoln D

    2017-12-01

    We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z_{2}, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.

  19. Quantifying Complexity in Quantum Phase Transitions via Mutual Information Complex Networks

    Science.gov (United States)

    Valdez, Marc Andrew; Jaschke, Daniel; Vargas, David L.; Carr, Lincoln D.

    2017-12-01

    We quantify the emergent complexity of quantum states near quantum critical points on regular 1D lattices, via complex network measures based on quantum mutual information as the adjacency matrix, in direct analogy to quantifying the complexity of electroencephalogram or functional magnetic resonance imaging measurements of the brain. Using matrix product state methods, we show that network density, clustering, disparity, and Pearson's correlation obtain the critical point for both quantum Ising and Bose-Hubbard models to a high degree of accuracy in finite-size scaling for three classes of quantum phase transitions, Z2, mean field superfluid to Mott insulator, and a Berzinskii-Kosterlitz-Thouless crossover.

  20. Methods for discriminating gas-liquid two phase flow patterns based on gray neural networks and SVM

    International Nuclear Information System (INIS)

    Li Jingjing; Zhou Tao; Duan Jun; Zhang Lei

    2013-01-01

    Background: The flow patterns of two phase flow will directly influence the heat transfer and mass transfer of the flow. Purpose: By wavelet analysis of the pressure drop experimental data, the wavelet coefficients of different frequency can be obtained. Methods: Get the wavelet energy and then train them in the model of BP neural network to distinguish the flow patterns. Introduced the implant gray neural networks model and use it for the two phase flow for the first time. At the same time, set up the method of training the pressure data and wavelet energy data in the support vector machine. Results: Through treatment of the gray layer, the result of the neural network is more accuracy. It can obviously reduce the effect of data marginalization. The accuracy of the pressure drop Lib-SVM method is 95.2%. Conclusions: The results show that these three methods can make a distinction among the different flow patterns and the Lib-SVM method gets the best result, then the gray neural networks, and at last the BP neural networks. (authors)

  1. Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks

    Science.gov (United States)

    St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.

    2018-02-01

    We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.

  2. Vertical propagation of waves in the solar atmosphere. II. Phase delays in the quiet chromosphere and cell-network distinctions

    International Nuclear Information System (INIS)

    Lites, B.W.; Chipman, E.G.; White, O.R.

    1982-01-01

    The differences in the phase of the velocity oscillations between a pair of chromospheric Ca II lines was measured using the Vacuum Tower Telescope at the Sacramento Peak Observatory. The observed phase differences indicate that the acoustic modes are trapped or envanescent, rather than propagating in the chromosphere. We find systematic distinctions in the phase delays between quiet network and cell interior regions for both intensity and velocity oscillations in photospheric and chromospheric lines. The theory of linear perturbations in a isothermal atmosphere is invoked to interpret these differences. From this analysis we find that one or more of the following explanations is possible. (1) the radiative damping is more effective in the network than in the cell interior; (2) the network features exclude oscillations of large horizontal wavenumber; or (3) the scale height of the chromosphere is larger in the network than in the cell interior

  3. Multi-port network and 3D finite-element models for accurate transformer calculations: Single-phase load-loss test

    Energy Technology Data Exchange (ETDEWEB)

    Escarela-Perez, R. [Departamento de Energia, Universidad Autonoma Metropolitana, Av. San Pablo 180, Col. Reynosa, C.P. 02200, Mexico D.F. (Mexico); Kulkarni, S.V. [Electrical Engineering Department, Indian Institute of Technology, Bombay (India); Melgoza, E. [Instituto Tecnologico de Morelia, Av. Tecnologico 1500, Morelia, Mich., C.P. 58120 (Mexico)

    2008-11-15

    A six-port impedance network for a three-phase transformer is obtained from a 3D time-harmonic finite-element (FE) model. The network model properly captures the eddy current effects of the transformer tank and frame. All theorems and tools of passive linear networks can be used with the multi-port model to simulate several important operating conditions without resorting anymore to computationally expensive 3D FE simulations. The results of the network model are of the same quality as those produced by the FE program. Although the passive network may seem limited by the assumption of linearity, many important transformer operating conditions imply unsaturated states. Single-phase load-loss measurements are employed to demonstrate the effectiveness of the network model and to understand phenomena that could not be explained with conventional equivalent circuits. In addition, formal deduction of novel closed-form formulae is presented for the calculation of the leakage impedance measured at the high and low voltage sides of the transformer. (author)

  4. Three-phase Power Flow Calculation of Low Voltage Distribution Network Considering Characteristics of Residents Load

    Science.gov (United States)

    Wang, Yaping; Lin, Shunjiang; Yang, Zhibin

    2017-05-01

    In the traditional three-phase power flow calculation of the low voltage distribution network, the load model is described as constant power. Since this model cannot reflect the characteristics of actual loads, the result of the traditional calculation is always different from the actual situation. In this paper, the load model in which dynamic load represented by air conditioners parallel with static load represented by lighting loads is used to describe characteristics of residents load, and the three-phase power flow calculation model is proposed. The power flow calculation model includes the power balance equations of three-phase (A,B,C), the current balance equations of phase 0, and the torque balancing equations of induction motors in air conditioners. And then an alternating iterative algorithm of induction motor torque balance equations with each node balance equations is proposed to solve the three-phase power flow model. This method is applied to an actual low voltage distribution network of residents load, and by the calculation of three different operating states of air conditioners, the result demonstrates the effectiveness of the proposed model and the algorithm.

  5. Spontaneous default mode network phase-locking moderates performance perceptions under stereotype threat.

    Science.gov (United States)

    Forbes, Chad E; Leitner, Jordan B; Duran-Jordan, Kelly; Magerman, Adam B; Schmader, Toni; Allen, John J B

    2015-07-01

    This study assessed whether individual differences in self-oriented neural processing were associated with performance perceptions of minority students under stereotype threat. Resting electroencephalographic activity recorded in white and minority participants was used to predict later estimates of task errors and self-doubt on a presumed measure of intelligence. We assessed spontaneous phase-locking between dipole sources in left lateral parietal cortex (LPC), precuneus/posterior cingulate cortex (P/PCC), and medial prefrontal cortex (MPFC); three regions of the default mode network (DMN) that are integral for self-oriented processing. Results revealed that minorities with greater LPC-P/PCC phase-locking in the theta band reported more accurate error estimations. All individuals experienced less self-doubt to the extent they exhibited greater LPC-MPFC phase-locking in the alpha band but this effect was driven by minorities. Minorities also reported more self-doubt to the extent they overestimated errors. Findings reveal novel neural moderators of stereotype threat effects on subjective experience. Spontaneous synchronization between DMN regions may play a role in anticipatory coping mechanisms that buffer individuals from stereotype threat. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  6. Multivariate multiscale complex network analysis of vertical upward oil-water two-phase flow in a small diameter pipe.

    Science.gov (United States)

    Gao, Zhong-Ke; Yang, Yu-Xuan; Zhai, Lu-Sheng; Dang, Wei-Dong; Yu, Jia-Liang; Jin, Ning-De

    2016-02-02

    High water cut and low velocity vertical upward oil-water two-phase flow is a typical complex system with the features of multiscale, unstable and non-homogenous. We first measure local flow information by using distributed conductance sensor and then develop a multivariate multiscale complex network (MMCN) to reveal the dispersed oil-in-water local flow behavior. Specifically, we infer complex networks at different scales from multi-channel measurements for three typical vertical oil-in-water flow patterns. Then we characterize the generated multiscale complex networks in terms of network clustering measure. The results suggest that the clustering coefficient entropy from the MMCN not only allows indicating the oil-in-water flow pattern transition but also enables to probe the dynamical flow behavior governing the transitions of vertical oil-water two-phase flow.

  7. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    Science.gov (United States)

    Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R; Scherer, Norbert F

    2012-01-01

    Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS).

  8. Remoting alternatives for a multiple phased-array antenna network

    Science.gov (United States)

    Shi, Zan; Foshee, James J.

    2001-10-01

    Significant improvements in technology have made phased array antennas an attractive alternative to the traditional dish antenna for use on wide body airplanes. These improvements have resulted in reduced size, reduced cost, reduced losses in the transmit and receive channels (simplifying the design), a significant extension in the bandwidth capability, and an increase in the functional capability. Flush mounting (thus reduced drag) and rapid beam switching are among the evolving desirable features of phased array antennas. Beam scanning of phased array antennas is limited to +/-45 degrees at best and therefore multiple phased array antennas would need to be used to insure instantaneous communications with any ground station (stations located at different geographical locations on the ground) and with other airborne stations. The exact number of phased array antennas and the specific installation location of each antenna on the wide body airplane would need to be determined by the specific communication requirements, but it is conceivable as many as five phased array antennas may need to be used to provide the required coverage. Control and switching of these antennas would need to be accomplished at a centralized location on the airplane and since these antennas would be at different locations on the airplane an efficient scheme of remoting would need to be used. To save in cost and keep the phased array antennas as small as possible the design of the phased array antennas would need to be kept simple. A dish antenna and a blade antenna (small size) could also be used to augment the system. Generating the RF signals at the central location and then using RF cables or waveguide to get the signal to any given antenna could result in significant RF losses. This paper will evaluate a number of remoting alternatives to keep the system design simple, reduce system cost, and utilize the functional capability of networking multiple phased array antennas on a wide body

  9. Forced phase-locked states and information retrieval in a two-layer network of oscillatory neurons with directional connectivity

    International Nuclear Information System (INIS)

    Kazantsev, Victor; Pimashkin, Alexey

    2007-01-01

    We propose two-layer architecture of associative memory oscillatory network with directional interlayer connectivity. The network is capable to store information in the form of phase-locked (in-phase and antiphase) oscillatory patterns. The first (input) layer takes an input pattern to be recognized and their units are unidirectionally connected with all units of the second (control) layer. The connection strengths are weighted using the Hebbian rule. The output (retrieved) patterns appear as forced-phase locked states of the control layer. The conditions are found and analytically expressed for pattern retrieval in response on incoming stimulus. It is shown that the system is capable to recover patterns with a certain level of distortions or noises in their profiles. The architecture is implemented with the Kuramoto phase model and using synaptically coupled neural oscillators with spikes. It is found that the spiking model is capable to retrieve patterns using the spiking phase that translates memorized patterns into the spiking phase shifts at different time scales

  10. Phase Transitions of an Epidemic Spreading Model in Small-World Networks

    Science.gov (United States)

    Hua, Da-Yin; Gao, Ke

    2011-06-01

    We propose a modified susceptible-infected-refractory-susceptible (SIRS) model to investigate the global oscillations of the epidemic spreading in Watts—Strogatz (WS) small-world networks. It is found that when an individual immunity does not change or decays slowly in an immune period, the system can exhibit complex transition from an infecting stationary state to a large amplitude sustained oscillation or an absorbing state with no infection. When the immunity decays rapidly in the immune period, the transition to the global oscillation disappears and there is no oscillation. Furthermore, based on the spatio-temporal evolution patterns and the phase diagram, it is disclosed that a long immunity period takes an important role in the emergence of the global oscillation in small-world networks.

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

    Directory of Open Access Journals (Sweden)

    Ye. I. Sokol

    2017-08-01

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

  12. First principles study of the optical contrast in phase change materials

    Energy Technology Data Exchange (ETDEWEB)

    Caravati, S; Parrinello, M [Department of Chemistry and Applied Biosciences, ETH Zurich, USI Campus, Via Giuseppe Buffi 13, 6900 Lugano (Switzerland); Bernasconi, M, E-mail: marco.bernasconi@mater.unimib.i [Dipartimento di Scienza dei Materiali, Universita di Milano-Bicocca, Via R Cozzi 53, I-20125, Milano (Italy)

    2010-08-11

    We study from first principles the optical properties of the phase change materials Ge{sub 2}Sb{sub 2}Te{sub 5} (GST), GeTe and Sb{sub 2}Te{sub 3} in the crystalline phase and in realistic models of the amorphous phase generated by quenching from the melt in ab initio molecular dynamics simulations. The calculations reproduce the strong optical contrast between the crystalline and amorphous phases measured experimentally and exploited in optical data storage. It is demonstrated that the optical contrast is due to a change in the optical matrix elements across the phase change in all the compounds. It is concluded that the reduction of the optical matrix elements in the amorphous phases is due to angular disorder in p-bonding which dominates the amorphous network in agreement with previous proposals (Huang and Robertson 2010 Phys. Rev. B 81 081204) based on calculations on crystalline models.

  13. Neural network-based voltage regulator for an isolated asynchronous generator supplying three-phase four-wire loads

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Bhim; Kasal, Gaurav Kumar [Department of Electrical Engineering, Indian Institute of Technology, Delhi, Hauz-Khas, New Delhi 110016 (India)

    2008-06-15

    This paper deals with a neural network-based solid state voltage controller for an isolated asynchronous generator (IAG) driven by constant speed prime mover like diesel engine, bio-gas or gasoline engine and supplying three-phase four-wire loads. The proposed control scheme uses an indirect current control and a fast adaptive linear element (adaline) based neural network reference current extractor, which extracts the real positive sequence current component without any phase shift. The neutral current of the source is also compensated by using three single-phase bridge configuration of IGBT (insulated gate bipolar junction transistor) based voltage source converter (VSC) along-with single-phase transformer having self-supported dc bus. The proposed controller provides the functions as a voltage regulator, a harmonic eliminator, a neutral current compensator, and a load balancer. The proposed isolated electrical system with its controller is modeled and simulated in MATLAB along with Simulink and PSB (Power System Block set) toolboxes. The simulated results are presented to demonstrate the capability of an isolated asynchronous generating system driven by a constant speed prime mover for feeding three-phase four-wire loads. (author)

  14. Supervision of care networks for frail community dwelling adults aged 75 years and older: protocol of a mixed methods study

    Science.gov (United States)

    Verver, Didi; Merten, Hanneke; Robben, Paul; Wagner, Cordula

    2015-01-01

    Introduction The Dutch healthcare inspectorate (IGZ) supervises the quality and safety of healthcare in the Netherlands. Owing to the growing population of (community dwelling) older adults and changes in the Dutch healthcare system, the IGZ is exploring new methods to effectively supervise care networks that exist around frail older adults. The composition of these networks, where formal and informal care takes place, and the lack of guidelines and quality and risk indicators make supervision complicated in the current situation. Methods and analysis This study consists of four phases. The first phase identifies risks for community dwelling frail older adults in the existing literature. In the second phase, a qualitative pilot study will be conducted to assess the needs and wishes of the frail older adults concerning care and well-being, perception of risks, and the composition of their networks, collaboration and coordination between care providers involved in the network. In the third phase, questionnaires based on the results of phase II will be sent to a larger group of frail older adults (n=200) and their care providers. The results will describe the composition of their care networks and prioritise risks concerning community dwelling older adults. Also, it will provide input for the development of a new supervision framework by the IGZ. During phase IV, a second questionnaire will be sent to the participants of phase III to establish changes of perception in risks and possible changes in the care networks. The framework will be tested by the IGZ in pilots, and the researchers will evaluate these pilots and provide feedback to the IGZ. Ethics and dissemination The study protocol was approved by the Scientific Committee of the EMGO+institute and the Medical Ethical review committee of the VU University Medical Centre. Results will be presented in scientific articles and reports and at meetings. PMID:26307619

  15. Reconstructing the Hopfield network as an inverse Ising problem

    International Nuclear Information System (INIS)

    Huang Haiping

    2010-01-01

    We test four fast mean-field-type algorithms on Hopfield networks as an inverse Ising problem. The equilibrium behavior of Hopfield networks is simulated through Glauber dynamics. In the low-temperature regime, the simulated annealing technique is adopted. Although performances of these network reconstruction algorithms on the simulated network of spiking neurons are extensively studied recently, the analysis of Hopfield networks is lacking so far. For the Hopfield network, we found that, in the retrieval phase favored when the network wants to memory one of stored patterns, all the reconstruction algorithms fail to extract interactions within a desired accuracy, and the same failure occurs in the spin-glass phase where spurious minima show up, while in the paramagnetic phase, albeit unfavored during the retrieval dynamics, the algorithms work well to reconstruct the network itself. This implies that, as an inverse problem, the paramagnetic phase is conversely useful for reconstructing the network while the retrieval phase loses all the information about interactions in the network except for the case where only one pattern is stored. The performances of algorithms are studied with respect to the system size, memory load, and temperature; sample-to-sample fluctuations are also considered.

  16. Epidemics on interconnected networks

    Science.gov (United States)

    Dickison, Mark; Havlin, S.; Stanley, H. E.

    2012-06-01

    Populations are seldom completely isolated from their environment. Individuals in a particular geographic or social region may be considered a distinct network due to strong local ties but will also interact with individuals in other networks. We study the susceptible-infected-recovered process on interconnected network systems and find two distinct regimes. In strongly coupled network systems, epidemics occur simultaneously across the entire system at a critical infection strength βc, below which the disease does not spread. In contrast, in weakly coupled network systems, a mixed phase exists below βc of the coupled network system, where an epidemic occurs in one network but does not spread to the coupled network. We derive an expression for the network and disease parameters that allow this mixed phase and verify it numerically. Public health implications of communities comprising these two classes of network systems are also mentioned.

  17. Security-Enhanced Autonomous Network Management for Space Networking, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA's Space Communications and Navigation (SCaN) program is integrating its three current agency networks: Space Network (SN), Deep Space Network (DSN), and Near...

  18. Energy efficiency networks; Energieeffizienz-Netzwerke

    Energy Technology Data Exchange (ETDEWEB)

    Gruber, Anna [Forschungsgesellschaft fuer Energiewirtschaft mbH (FfE GmbH), Muenchen (Germany)

    2011-07-01

    Energy efficiency networks are an attractive method to increase the energy efficiency and to reduce the costs and CO{sub 2} emissions of the companies operating in this network. A special feature of the energy efficiency networks is the exchange of experiences and training of the energy managers. Energy efficiency networks consist of about ten to fifteen locally domiciled companies. During the project period of three to four years, there are two main phases. In the first phase, the initial consultation phase, the actual state of a company is captured, and measures to increase the efficiency and energy conservation are identified. Parallel to this, in the second phase every three months a meeting with the participating companies takes place. Experience exchange and implementation of energy efficiency measures are the focus of these meetings. Initial studies show that the increase of the energy efficiency during participating in the energy efficiency network almost can be doubled in comparison to the average of the industry.

  19. Failure detection studies by layered neural network

    International Nuclear Information System (INIS)

    Ciftcioglu, O.; Seker, S.; Turkcan, E.

    1991-06-01

    Failure detection studies by layered neural network (NN) are described. The particular application area is an operating nuclear power plant and the failure detection is of concern as result of system surveillance in real-time. The NN system is considered to be consisting of 3 layers, one of which being hidden, and the NN parameters are determined adaptively by the backpropagation (BP) method, the process being the training phase. Studies are performed using the power spectra of the pressure signal of the primary system of an operating nuclear power plant of PWR type. The studies revealed that, by means of NN approach, failure detection can effectively be carried out using the redundant information as well as this is the case in this work; namely, from measurement of the primary pressure signals one can estimate the primary system coolant temperature and hence the deviation from the operational temperature state, the operational status identified in the training phase being referred to as normal. (author). 13 refs.; 4 figs.; 2 tabs

  20. Phase equilibria and phase structures of polymer blends

    International Nuclear Information System (INIS)

    Chalykh, Anatolii E; Gerasimov, Vladimir K

    2004-01-01

    Experimental, methodical and theoretical studies dealing with phase equilibria and phase structures of polymer blends are generalised. The general and specific features of the change in solubility of polymers with changes in the molecular mass and copolymer composition and upon the formation of three-dimensional cross-linked networks are described. The results of the effect of the prehistory on the phase structure and the non-equilibrium state of polymer blends are considered in detail.

  1. Networked Microgrids Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dobriansky, Larisa [General MicroGrids, San Diego, CA (United States); Glover, Steve [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Liu, Chen-Ching [Washington State Univ., Pullman, WA (United States); Looney, Patrick [Brookhaven National Lab. (BNL), Upton, NY (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pratt, Annabelle [National Renewable Energy Lab. (NREL), Golden, CO (United States); Schneider, Kevin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Jianhui [Argonne National Lab. (ANL), Argonne, IL (United States); Yue, Meng [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-12-05

    Much like individual microgrids, the range of opportunities and potential architectures of networked microgrids is very diverse. The goals of this scoping study are to provide an early assessment of research and development needs by examining the benefits of, risks created by, and risks to networked microgrids. At this time there are very few, if any, examples of deployed microgrid networks. In addition, there are very few tools to simulate or otherwise analyze the behavior of networked microgrids. In this setting, it is very difficult to evaluate networked microgrids systematically or quantitatively. At this early stage, this study is relying on inputs, estimations, and literature reviews by subject matter experts who are engaged in individual microgrid research and development projects, i.e., the authors of this study The initial step of the study gathered input about the potential opportunities provided by networked microgrids from these subject matter experts. These opportunities were divided between the subject matter experts for further review. Part 2 of this study is comprised of these reviews. Part 1 of this study is a summary of the benefits and risks identified in the reviews in Part 2 and synthesis of the research needs required to enable networked microgrids.

  2. Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance.

    Science.gov (United States)

    Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

    2017-01-01

    Introduction and Aim : Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods : Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object's name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion : The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language

  3. Density induced phase transitions in the Schwinger model. A study with matrix product states

    Energy Technology Data Exchange (ETDEWEB)

    Banuls, Mari Carmen; Cirac, J. Ignacio; Kuehn, Stefan [Max-Planck-Institut fuer Quantenoptik (MPQ), Garching (Germany); Cichy, Krzysztof [Frankfurt Univ. (Germany). Inst. fuer Theoretische Physik; Adam Mickiewicz Univ., Poznan (Poland). Faculty of Physics; Jansen, Karl [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC

    2017-02-15

    We numerically study the zero temperature phase structure of the multiflavor Schwinger model at nonzero chemical potential. Using matrix product states, we reproduce analytical results for the phase structure for two flavors in the massless case and extend the computation to the massive case, where no analytical predictions are available. Our calculations allow us to locate phase transitions in the mass-chemical potential plane with great precision and provide a concrete example of tensor networks overcoming the sign problem in a lattice gauge theory calculation.

  4. On network coding and modulation mapping for three-phase bidirectional relaying

    KAUST Repository

    Chang, Ronald Y.; Lin, Sian Jheng; Chung, Wei-Ho

    2015-01-01

    © 2015 IEEE. In this paper, we consider the network coding (NC) enabled three-phase protocol for information exchange between two users in a wireless two-way (bidirectional) relay network. Modulo-based (nonbinary) and XOR-based (binary) NC schemes are considered as information mixture schemes at the relay while all transmissions adopt pulse amplitude modulation (PAM). We first obtain the optimal constellation mapping at the relay that maximizes the decoding performance at the users for each NC scheme. Then, we compare the two NC schemes, each in conjunction with the optimal constellation mapping at the relay, in different conditions. Our results demonstrate that, in the low SNR regime, binary NC outperforms nonbinary NC with 4-PAM, while they have mixed performance with 8-PAM. This observation applies to quadrature amplitude modulation (QAM) composed of two parallel PAMs.

  5. On network coding and modulation mapping for three-phase bidirectional relaying

    KAUST Repository

    Chang, Ronald Y.

    2015-12-03

    © 2015 IEEE. In this paper, we consider the network coding (NC) enabled three-phase protocol for information exchange between two users in a wireless two-way (bidirectional) relay network. Modulo-based (nonbinary) and XOR-based (binary) NC schemes are considered as information mixture schemes at the relay while all transmissions adopt pulse amplitude modulation (PAM). We first obtain the optimal constellation mapping at the relay that maximizes the decoding performance at the users for each NC scheme. Then, we compare the two NC schemes, each in conjunction with the optimal constellation mapping at the relay, in different conditions. Our results demonstrate that, in the low SNR regime, binary NC outperforms nonbinary NC with 4-PAM, while they have mixed performance with 8-PAM. This observation applies to quadrature amplitude modulation (QAM) composed of two parallel PAMs.

  6. Oscillating systems with cointegrated phase processes

    DEFF Research Database (Denmark)

    Østergaard, Jacob; Rahbek, Anders; Ditlevsen, Susanne

    2017-01-01

    We present cointegration analysis as a method to infer the network structure of a linearly phase coupled oscillating system. By defining a class of oscillating systems with interacting phases, we derive a data generating process where we can specify the coupling structure of a network...... that resembles biological processes. In particular we study a network of Winfree oscillators, for which we present a statistical analysis of various simulated networks, where we conclude on the coupling structure: the direction of feedback in the phase processes and proportional coupling strength between...... individual components of the system. We show that we can correctly classify the network structure for such a system by cointegration analysis, for various types of coupling, including uni-/bi-directional and all-to-all coupling. Finally, we analyze a set of EEG recordings and discuss the current...

  7. A neural network approach to the study of internal energy flow in molecular systems

    International Nuclear Information System (INIS)

    Sumpter, B.G.; Getino, C.; Noid, D.W.

    1992-01-01

    Neural networks are used to develop a new technique for efficient analysis of data obtained from molecular-dynamics calculations and is applied to the study of mode energy flow in molecular systems. The methodology is based on teaching an appropriate neural network the relationship between phase-space points along a classical trajectory and mode energies for stretch, bend, and torsion vibrations. Results are discussed for reactive and nonreactive classical trajectories of hydrogen peroxide (H 2 O 2 ) on a semiempirical potential-energy surface. The neural-network approach is shown to produce reasonably accurate values for the mode energies, with average errors between 1% and 12%, and is applicable to any region within the 24-dimensional phase space of H 2 O 2 . In addition, the generic knowledge learned by the neural network allows calculations to be made for other molecular systems. Results are discussed for a series of tetratomic molecules: H 2 X 2 , X=C, N, O, Si, S, or Se, and preliminary results are given for energy flow predictions in macromolecules

  8. Non-invasive classification of gas–liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

    International Nuclear Information System (INIS)

    Abbagoni, Baba Musa; Yeung, Hoi

    2016-01-01

    The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas–liquid flow regimes objectively with the gas–liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elongated bubble, stratified-wavy and, stratified flow regimes. Multilayer perceptron neural networks (MLPNNs) are used to develop the classification model. The classifier requires features as an input which is representative of the signals. Ultrasound signal features are extracted by applying both power spectral density (PSD) and discrete wavelet transform (DWT) methods to the flow signals. A classification scheme of ‘1-of-C coding method for classification’ was adopted to classify features extracted into one of four flow regime categories. To improve the performance of the flow regime classifier network, a second level neural network was incorporated by using the output of a first level networks feature as an input feature. The addition of the two network models provided a combined neural network model which has achieved a higher accuracy than single neural network models. Classification accuracies are evaluated in the form of both the PSD and DWT features. The success rates of the two models are: (1) using PSD features, the classifier missed 3 datasets out of 24 test datasets of the classification and scored 87.5% accuracy; (2) with the DWT features, the network misclassified only one data point and it was able to classify the flow patterns up to 95.8% accuracy. This approach has demonstrated the

  9. Non-invasive classification of gas-liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

    Science.gov (United States)

    Musa Abbagoni, Baba; Yeung, Hoi

    2016-08-01

    The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas-liquid flow regimes objectively with the gas-liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase flow. Experimental data is obtained on a horizontal test rig with a total pipe length of 21 m and 5.08 cm internal diameter carrying air-water two-phase flow under slug, elongated bubble, stratified-wavy and, stratified flow regimes. Multilayer perceptron neural networks (MLPNNs) are used to develop the classification model. The classifier requires features as an input which is representative of the signals. Ultrasound signal features are extracted by applying both power spectral density (PSD) and discrete wavelet transform (DWT) methods to the flow signals. A classification scheme of ‘1-of-C coding method for classification’ was adopted to classify features extracted into one of four flow regime categories. To improve the performance of the flow regime classifier network, a second level neural network was incorporated by using the output of a first level networks feature as an input feature. The addition of the two network models provided a combined neural network model which has achieved a higher accuracy than single neural network models. Classification accuracies are evaluated in the form of both the PSD and DWT features. The success rates of the two models are: (1) using PSD features, the classifier missed 3 datasets out of 24 test datasets of the classification and scored 87.5% accuracy; (2) with the DWT features, the network misclassified only one data point and it was able to classify the flow patterns up to 95.8% accuracy. This approach has demonstrated the

  10. Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

    Science.gov (United States)

    Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

    2016-08-04

    Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

  11. Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays

    National Research Council Canada - National Science Library

    Yang, Kyoung

    2005-01-01

    This final report summarizes the progress during the Phase I SBIR project entitled "Embedded Electro-Optic Sensor Network for the On-Site Calibration and Real-Time Performance Monitoring of Large-Scale Phased Arrays...

  12. Analysis of the error of the developed method of determination the active conductivity reducing the insulation level between one phase of the network and ground, and insulation parameters in a non-symmetric network with isolated neutral with voltage above 1000 V

    Science.gov (United States)

    Utegulov, B. B.

    2018-02-01

    In the work the study of the developed method was carried out for reliability by analyzing the error in indirect determination of the insulation parameters in an asymmetric network with an isolated neutral voltage above 1000 V. The conducted studies of the random relative mean square errors show that the accuracy of indirect measurements in the developed method can be effectively regulated not only by selecting a capacitive additional conductivity, which are connected between phases of the electrical network and the ground, but also by the selection of measuring instruments according to the accuracy class. When choosing meters with accuracy class of 0.5 with the correct selection of capacitive additional conductivity that are connected between the phases of the electrical network and the ground, the errors in measuring the insulation parameters will not exceed 10%.

  13. An amplified coarse wavelength division multiplexing self-referencing sensor network based on phase-shifted FBGs in transmissive configuration

    International Nuclear Information System (INIS)

    Elosua, C; Perez-Herrera, R A; Lopez-Amo, M; Bariain, C; Garcia-Olcina, R; Sales, S; Capmany, J

    2009-01-01

    A new amplified CWDM (coarse wavelength division multiplexing) self-referencing sensor network using phase-shifted fibre Bragg gratings (PS-FBGs) is experimentally demonstrated in this work. The network uses the PS-FBGs to address intensity sensors in a transmissive configuration, obtaining simultaneously in reflection a wavelength encoded reference signal. In order to enable the remote operation of the sensors, we have introduced optical amplification at the interrogation header of the network, using highly doped erbium fibre

  14. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks

    OpenAIRE

    Wang, Yongqiang; Nunez, Felipe; Doyle III, Francis J.

    2012-01-01

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is incr...

  15. Dynamic and interacting complex networks

    Science.gov (United States)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  16. Percolation of interdependent network of networks

    International Nuclear Information System (INIS)

    Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

    2015-01-01

    Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

  17. Frequency transfer via a two-way optical phase comparison on a multiplexed fiber network.

    Science.gov (United States)

    Calosso, C E; Bertacco, E; Calonico, D; Clivati, C; Costanzo, G A; Frittelli, M; Levi, F; Mura, A; Godone, A

    2014-03-01

    We performed a two-way remote optical phase comparison on optical fiber. Two optical frequency signals were launched in opposite directions in an optical fiber and their phases were simultaneously measured at the other end. In this technique, the fiber noise is passively canceled, and we compared two optical frequencies at the ultimate 10(-21) stability level. The experiment was performed on a 47 km fiber that is part of the metropolitan network for Internet traffic. The technique relies on the synchronous measurement of the optical phases at the two ends of the link, which is here performed by digital electronics. This scheme offers some advantages with respect to active noise cancellation schemes, as the light travels only once in the fiber.

  18. Characterisation of UV-cured acrylate networks by means of hydrolysis followed by aqueous size-exclusion combined with reversed-phase chromatography

    NARCIS (Netherlands)

    Peters, R.; Litvinov, V. M.; Steeman, P.; Dias, A. A.; Mengerink, Y.; van Benthem, R.; de Koster, C. G.; van der Wal, S. J.; Schoenmakers, P.

    2007-01-01

    UV-cured networks prepared from mixtures of di-functional (polyethylene-glycol di-acrylate) and mono-functional (2-ethylhexyl acrylate) acrylates were analysed after hydrolysis, by aqueous size-exclusion chromatography coupled to on-line reversed-phase liquid-chromatography. The mean network density

  19. Analysis of structural patterns in the brain with the complex network approach

    Science.gov (United States)

    Maksimenko, Vladimir A.; Makarov, Vladimir V.; Kharchenko, Alexander A.; Pavlov, Alexey N.; Khramova, Marina V.; Koronovskii, Alexey A.; Hramov, Alexander E.

    2015-03-01

    In this paper we study mechanisms of the phase synchronization in a model network of Van der Pol oscillators and in the neural network of the brain by consideration of macroscopic parameters of these networks. As the macroscopic characteristics of the model network we consider a summary signal produced by oscillators. Similar to the model simulations, we study EEG signals reflecting the macroscopic dynamics of neural network. We show that the appearance of the phase synchronization leads to an increased peak in the wavelet spectrum related to the dynamics of synchronized oscillators. The observed correlation between the phase relations of individual elements and the macroscopic characteristics of the whole network provides a way to detect phase synchronization in the neural networks in the cases of normal and pathological activity.

  20. A quantum logic network for implementing optimal symmetric universal and phase-covariant telecloning of a bipartite entangled state

    International Nuclear Information System (INIS)

    Meng Fanyu; Zhu Aidong

    2008-01-01

    A quantum logic network to implement quantum telecloning is presented in this paper. The network includes two parts: the first part is used to create the telecloning channel and the second part to teleport the state. It can be used not only to implement universal telecloning for a bipartite entangled state which is completely unknown, but also to implement the phase-covariant telecloning for one that is partially known. Furthermore, the network can also be used to construct a tele-triplicator. It can easily be implemented in experiment because only single- and two-qubit operations are used in the network.

  1. Flow Regime Identification of Co-Current Downward Two-Phase Flow With Neural Network Approach

    International Nuclear Information System (INIS)

    Hiroshi Goda; Seungjin Kim; Ye Mi; Finch, Joshua P.; Mamoru Ishii; Jennifer Uhle

    2002-01-01

    Flow regime identification for an adiabatic vertical co-current downward air-water two-phase flow in the 25.4 mm ID and the 50.8 mm ID round tubes was performed by employing an impedance void meter coupled with the neural network classification approach. This approach minimizes the subjective judgment in determining the flow regimes. The signals obtained by an impedance void meter were applied to train the self-organizing neural network to categorize these impedance signals into a certain number of groups. The characteristic parameters set into the neural network classification included the mean, standard deviation and skewness of impedance signals in the present experiment. The classification categories adopted in the present investigation were four widely accepted flow regimes, viz. bubbly, slug, churn-turbulent, and annular flows. These four flow regimes were recognized based upon the conventional flow visualization approach by a high-speed motion analyzer. The resulting flow regime maps classified by the neural network were compared with the results obtained through the flow visualization method, and consequently the efficiency of the neural network classification for flow regime identification was demonstrated. (authors)

  2. Generating macroscopic chaos in a network of globally coupled phase oscillators

    Science.gov (United States)

    So, Paul; Barreto, Ernest

    2011-01-01

    We consider an infinite network of globally coupled phase oscillators in which the natural frequencies of the oscillators are drawn from a symmetric bimodal distribution. We demonstrate that macroscopic chaos can occur in this system when the coupling strength varies periodically in time. We identify period-doubling cascades to chaos, attractor crises, and horseshoe dynamics for the macroscopic mean field. Based on recent work that clarified the bifurcation structure of the static bimodal Kuramoto system, we qualitatively describe the mechanism for the generation of such complicated behavior in the time varying case. PMID:21974662

  3. DCE: A Distributed Energy-Efficient Clustering Protocol for Wireless Sensor Network Based on Double-Phase Cluster-Head Election.

    Science.gov (United States)

    Han, Ruisong; Yang, Wei; Wang, Yipeng; You, Kaiming

    2017-05-01

    Clustering is an effective technique used to reduce energy consumption and extend the lifetime of wireless sensor network (WSN). The characteristic of energy heterogeneity of WSNs should be considered when designing clustering protocols. We propose and evaluate a novel distributed energy-efficient clustering protocol called DCE for heterogeneous wireless sensor networks, based on a Double-phase Cluster-head Election scheme. In DCE, the procedure of cluster head election is divided into two phases. In the first phase, tentative cluster heads are elected with the probabilities which are decided by the relative levels of initial and residual energy. Then, in the second phase, the tentative cluster heads are replaced by their cluster members to form the final set of cluster heads if any member in their cluster has more residual energy. Employing two phases for cluster-head election ensures that the nodes with more energy have a higher chance to be cluster heads. Energy consumption is well-distributed in the proposed protocol, and the simulation results show that DCE achieves longer stability periods than other typical clustering protocols in heterogeneous scenarios.

  4. Design of a ring resonator-based optical beam forming network for phased array receive antennas

    NARCIS (Netherlands)

    van 't Klooster, J.W.J.R.; Roeloffzen, C.G.H.; Meijerink, Arjan; Zhuang, L.; Marpaung, D.A.I.; van Etten, Wim; Heideman, Rene; Leinse, Arne; Schippers, H.; Verpoorte, J.; Wintels, M.

    2008-01-01

    A novel squint-free ring resonator-based optical beam forming network (OBFN) for phased array antennas (PAA) is proposed. It is intended to provide broadband connectivity to airborne platforms via geostationary satellites. In this paper, we present the design of the OBFN and its control system. Our

  5. Network structure and thermal stability study of high temperature seal glass

    Science.gov (United States)

    Lu, K.; Mahapatra, M. K.

    2008-10-01

    High temperature seal glass has stringent requirement on glass thermal stability, which is dictated by glass network structures. In this study, a SrO-La2O3-Al2O3-B2O3-SiO2 based glass system was studied using nuclear magnetic resonance, Raman spectroscopy, and x-ray diffraction for solid oxide cell application purpose. Glass structural unit neighboring environment and local ordering were evaluated. Glass network connectivity as well as silicon and boron glass former coordination were calculated for different B2O3:SiO2 ratios. Thermal stability of the borosilicate glasses was studied after thermal treatment at 850 °C. The study shows that high B2O3 content induces BO4 and SiO4 structural unit ordering, increases glass localized inhomogeneity, decreases glass network connectivity, and causes devitrification. Glass modifiers interact with either silicon- or boron-containing structural units and form different devitrified phases at different B2O3:SiO2 ratios. B2O3-free glass shows the best thermal stability among the studied compositions, remaining stable after thermal treatment for 200 h at 850 °C.

  6. Experimental Study on OSNR Requirements for Spectrum-Flexible Optical Networks

    DEFF Research Database (Denmark)

    Borkowski, Robert; Karinou, Fotini; Angelou, Marianna

    2012-01-01

    on adaptive allocation of superchannels in spectrum-flexible heterogeneous optical network. In total, three superchannels were transmitted. Two 5-subcarrier 14-GHz-spaced, 14 Gbaud, polarization-division-multiplexed (PDM) quadrature-phase-shift-keyed (QPSK) superchannels were separated by a spectral gap...... to maintain a 1×10−3 bit error rate of the central BOI subcarrier. The results provide a rule of thumb that can be exploited in resource allocation mechanisms of future spectrum-flexible optical networks.......The flexibility and elasticity of the spectrum is an important topic today. As the capacity of deployed fiber-optic systems is becoming scarce, it is vital to shift towards solutions ensuring higher spectral efficiency. Working in this direction, we report an extensive experimental study...

  7. Networking: a study in planning and developing cross-cultural collaboration

    Directory of Open Access Journals (Sweden)

    Sanjeev Singh

    2002-12-01

    Full Text Available This paper reports on a collaboration between the authors at the University of Brighton (UK and the University of Delhi, South Campus. The collaboration came about as a result of the EU-India Cross-Cultural Innovation Network collaboration programme, a project involving several universities and organizations across Europe and India. The authors of this paper both lecture in the area of computer networking. Following meetings in Delhi, they agreed to work together to produce a Web-based networking resource to be generated by the students of both institutions. The first phase of development involved the mounting of Web-based tutorials and documents produced by the students. The second phase will centre on the development of a knowledge base generated by the interaction of the students within an asynchronous forum. Running alongside these phases will be a collaborative bookmarking system, a database in which the students will post URLs of Web-based resources that they find useful in their studies. This system incorporates a form of collaborative filtering, an evolutionary mechanism which seeks to embody the qualities that students value in resources to provide a dynamic set of ratings to assist in the selection of those of most use. The planning of such a system raises some unusual issues, not least in the process of collaboration itself, with concerns as diverse as technical compatibility, institutional and cultural differences, timezones and the reliability of email. Limited bandwidth between our institutions causes special problems with the interactive elements of the resource. We present the methods we are investigating to reduce the impact of this. The fact that the students share an intellectual discipline but are otherwise separated by a cultural and geographical divide is expected to lead to fruitful diversity in thinking and approaches to problem-solving.

  8. One Core Phase Shifting Transformer for Control of the Power Flow Distribution in Electric Networks

    Directory of Open Access Journals (Sweden)

    Golub I.V.

    2016-08-01

    Full Text Available This paper presents the variant of phase shifting transformer that is made, unlike from traditional technology, on the basis of only one magnetic core. The paper describes the methodology related to the analysis of operation modes of device and its components. Additionally it presents a mathematical model of device with determines the relationship between input and output electric quantities as well as own longitudinal and transverse parameters of an equivalent circuit of phase shifting transformer (PST. Proposed configuration of PST is interesting from an economic and operational consideration; enable continuous control of power flow distribution in electric networks as a result of regulation a phase shift angle between input and output voltages of device.

  9. Co-ordinated experimental research into PV power interaction with the supply network - Phase 2

    Energy Technology Data Exchange (ETDEWEB)

    Hacker, R.; Thornycroft, J.; Knight, J.

    2000-07-01

    This report describes the development of a procedure for type testing photovoltaic inverters that are suitable for connecting to the UK public distribution system based on experimental research and consultation within the industry. Phase 1 of the project investigated the performance of the inverters and the cumulative effect of multiple installation on a section of distributed network, and Phase 2 concentrated on the requirements for PV inverters that would allow them to be connected to the grid without further investigation and to develop a type test procedure. The production of the 'UK Technical Guidelines for Inverter Connected Single Phase Photovoltaic (PV) Generators up to 5kVA' based on the project results and its adoption by the Electricity Association as draft Engineering Recommendations G77 are reported.

  10. The pairwise phase consistency in cortical network and its relationship with neuronal activation

    Directory of Open Access Journals (Sweden)

    Wang Daming

    2017-01-01

    Full Text Available Gamma-band neuronal oscillation and synchronization with the range of 30-90 Hz are ubiquitous phenomenon across numerous brain areas and various species, and correlated with plenty of cognitive functions. The phase of the oscillation, as one aspect of CTC (Communication through Coherence hypothesis, underlies various functions for feature coding, memory processing and behaviour performing. The PPC (Pairwise Phase Consistency, an improved coherence measure, statistically quantifies the strength of phase synchronization. In order to evaluate the PPC and its relationships with input stimulus, neuronal activation and firing rate, a simplified spiking neuronal network is constructed to simulate orientation columns in primary visual cortex. If the input orientation stimulus is preferred for a certain orientation column, neurons within this corresponding column will obtain higher firing rate and stronger neuronal activation, which consequently engender higher PPC values, with higher PPC corresponding to higher firing rate. In addition, we investigate the PPC in time resolved analysis with a sliding window.

  11. Predictors of change in social networks, support and satisfaction following a first episode psychosis: A cohort study.

    Science.gov (United States)

    Renwick, Laoise; Owens, Liz; Lyne, John; O'Donoghue, Brian; Roche, Eric; Drennan, Jonathan; Sheridan, Ann; Pilling, Mark; O'Callaghan, Eadbhard; Clarke, Mary

    2017-11-01

    Diminished social networks are common in psychosis but few studies have measured these comprehensively and prospectively to determine how networks and support evolve during the early phase. There is little information regarding perceived support in the early phase of illness. The aim of this study was to describe social support, networks and perceived satisfaction, explore the clinical correlates of these outcomes and examine whether phases of untreated psychosis are linked with social network variables to determine potential opportunities for intervention. During the study period, we assessed 222 people with first-episode psychosis at entry into treatment using valid and reliable measures of diagnosis, positive and negative symptoms, periods of untreated psychosis and prodrome and premorbid adjustment. For follow-up we contacted participants to conduct a second assessment (n=158). There were 97 people who participated which represented 61% of those eligible. Social network and support information obtained at both time points included the number of friends, self-reported satisfaction with support and social network size and clinician's evaluation of the degree of support received through networks. Mixed effects modelling determined the contribution of potential explanatory variables to social support measured. A number of clinical variables were linked with social networks, support and perceived support and satisfaction. The size of networks did not change over time but those with no friends and duration of untreated psychosis was significantly longer for those with no friends at entry into treatment (n=129, Median=24.5mths, IQR=7.25-69.25; Mann-Whitney U=11.78, p=0.008). Social support at baseline and at one year was predicted by homelessness (t=-2.98, p=0.001, CI -4.74 to -1.21), duration of untreated psychosis (t=-0.86, p=0.031, CI -1.65 to -0.08) and premorbid adjustment (t=-2.26, p=0.017, CI -4.11 to -0.42). Social support improved over time but the duration

  12. Location capability of a sparse regional network (RSTN) using a multi-phase earthquake location algorithm (REGLOC)

    Energy Technology Data Exchange (ETDEWEB)

    Hutchings, L.

    1994-01-01

    The Regional Seismic Test Network (RSTN) was deployed by the US Department of Energy (DOE) to determine whether data recorded by a regional network could be used to detect and accurately locate seismic events that might be clandestine nuclear tests. The purpose of this paper is to evaluate the location capability of the RSTN. A major part of this project was the development of the location algorithm REGLOC and application of Basian a prior statistics for determining the accuracy of the location estimates. REGLOC utilizes all identifiable phases, including backazimuth, in the location. Ninty-four events, distributed throughout the network area, detected by both the RSTN and located by local networks were used in the study. The location capability of the RSTN was evaluated by estimating the location accuracy, error ellipse accuracy, and the percentage of events that could be located, as a function of magnitude. The location accuracy was verified by comparing the RSTN results for the 94 events with published locations based on data from the local networks. The error ellipse accuracy was evaluated by determining whether the error ellipse includes the actual location. The percentage of events located was assessed by combining detection capability with location capability to determine the percentage of events that could be located within the study area. Events were located with both an average crustal model for the entire region, and with regional velocity models along with station corrections obtained from master events. Most events with a magnitude <3.0 can only be located with arrivals from one station. Their average location errors are 453 and 414 km for the average- and regional-velocity model locations, respectively. Single station locations are very unreliable because they depend on accurate backazimuth estimates, and backazimuth proved to be a very unreliable computation.

  13. Temperature-induced phase transition in hydrogels of interpenetrating networks poly(N-isopropylmethacrylamide)/poly(N-isopropylacrylamide)

    Czech Academy of Sciences Publication Activity Database

    Šťastná, J.; Hanyková, L.; Sedláková, Zdeňka; Valentová, H.; Spěváček, Jiří

    2013-01-01

    Roč. 291, č. 10 (2013), s. 2409-2417 ISSN 0303-402X R&D Projects: GA ČR GA202/09/1281 Institutional support: RVO:61389013 Keywords : temperature-induced volume phase transition * poly (N-isopropylmethacrylamide) poly (Nisopropylacrylamide) interpenetrating network * 1H NMR spectroscopy Subject RIV: CD - Macromolecular Chemistry Impact factor: 2.410, year: 2013

  14. Measurement of void fraction distribution in two-phase flow by impedance CT with neural network

    International Nuclear Information System (INIS)

    Hayashi, Hideaki; Sumida, Isao; Sakai, Sinji; Wakai, Kazunori

    1996-01-01

    This paper describes a new method for measurement of void distribution using impedance CT with a hierarchical neural network. The present method consists of four processes. First, output electric currents are calculated by simulation of various distributions of void fraction. The relationship between distribution of void fraction and electric current is called 'teaching data'. Second, the neural network learns the teaching data by the back propagation method. Third, output electric currents are measured about actual two-phase flow. Finally, distribution of void fraction is calculated by the taught neural network using the measured electric currents. In this paper, measurement and learning parameters are adjusted, experimental results obtained using the impedance CT method are compared with data obtained by the impedance probe method. The results show that our method is effective for measurement of void fraction distribution. (author)

  15. Understanding and designing computer networks

    CERN Document Server

    King, Graham

    1995-01-01

    Understanding and Designing Computer Networks considers the ubiquitous nature of data networks, with particular reference to internetworking and the efficient management of all aspects of networked integrated data systems. In addition it looks at the next phase of networking developments; efficiency and security are covered in the sections dealing with data compression and data encryption; and future examples of network operations, such as network parallelism, are introduced.A comprehensive case study is used throughout the text to apply and illustrate new techniques and concepts as th

  16. Control Method of Single-phase Inverter Based Grounding System in Distribution Networks

    DEFF Research Database (Denmark)

    Wang, Wen; Yan, L.; Zeng, X.

    2016-01-01

    of neutral-to-ground voltage is critical for the safety of distribution networks. An active grounding system based on single-phase inverter is proposed to achieve this objective. Relationship between output current of the system and neutral-to-ground voltage is derived to explain the principle of neutral......The asymmetry of the inherent distributed capacitances causes the rise of neutral-to-ground voltage in ungrounded system or high resistance grounded system. Overvoltage may occur in resonant grounded system if Petersen coil is resonant with the distributed capacitances. Thus, the restraint...

  17. Impedance void-meter and neural networks for vertical two-phase flows

    International Nuclear Information System (INIS)

    Mi, Y.; Li, M.; Xiao, Z.; Tsoukalas, L.H.; Ishii, M.

    1998-01-01

    Most two-phase flow measurements, including void fraction measurements, depend on correct flow regime identification. There are two steps towards successful identification of flow regimes: one is to develop a non-intrusive instrument to demonstrate area-averaged void fluctuations, the other to develop a non-linear mapping approach to perform objective identification of flow regimes. A non-intrusive impedance void-meter provides input signals to a neural mapping approach used to identify flow regimes. After training, both supervised and self-organizing neural network learning paradigms performed flow regime identification successfully. The methodology presented holds considerable promise for multiphase flow diagnostic and measurement applications. (author)

  18. Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

    Science.gov (United States)

    Aoyagi, Toshio; Nomura, Masaki

    1999-08-01

    Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

  19. Liquid-Liquid Phase Separation in Model Nuclear Waste Glasses: A Solid-State Double-Resonance NMR Study

    Energy Technology Data Exchange (ETDEWEB)

    Martineau, Ch.; Michaelis, V.K.; Kroeker, S. [Univ Manitoba, Dept Chem, Winnipeg, MB R3T 2N2 (Canada); Schuller, S. [CEA Valrho Marcoule, LDMC, SECM, DTCD, DEN, F-30207 Bagnols Sur Ceze (France)

    2010-07-01

    Double-resonance nuclear magnetic resonance (NMR) techniques are used in addition to single-resonance NMR experiments to probe the degree of mixing between network-forming cations Si and B, along with the modifier cations Cs{sup +} and Na{sup +} in two molybdenum-bearing model nuclear waste glasses. The double-resonance experiments involving {sup 29}Si in natural abundance are made possible by the implementation of a CPMG pulse-train during the acquisition period of the usual REDOR experiments. For the glass with lower Mo content, the NMR results show a high degree of Si-B mixing, as well as an homogeneous distribution of the cations within the borosilicate network, characteristic of a non-phase-separated glass. For the higher-Mo glass, a decrease of B-Si(Q{sup 4}) mixing is observed, indicating phase separation. {sup 23}Na and {sup 133}Cs NMR results show that although the Cs{sup +} cations, which do not seem to be influenced by the molybdenum content, are spread within the borate network, there is a clustering of the Na{sup +} cations, very likely around the molybdate units. The segregation of a Mo-rich region with Na{sup +} cations appears to shift the bulk borosilicate glass composition toward the metastable liquid liquid immiscibility region and induce additional phase separation. Although no crystallization is observed in the present case, this liquid liquid phase separation is likely to be the first stage of crystallization that can occur at higher Mo loadings or be driven by heat treatment. From this study emerges a consistent picture of the nature and extent of such phase separation phenomena in Mo-bearing glasses, and demonstrates the potential of double-resonance NMR methods for the investigation of phase separation in amorphous materials. (authors)

  20. Nonorthogonal multiple access and carrierless amplitude phase modulation for flexible multiuser provisioning in 5G mobile networks

    NARCIS (Netherlands)

    Altabas, J.A.; Rommel, S.; Puerta, R.; Izquierdo, D.; Ignacio Garces, J.; Antonio Lazaro, J.; Vegas Olmos, J.J.; Tafur Monroy, I.

    2017-01-01

    In this paper, a combined nonorthogonal multiple access (NOMA) and multiband carrierless amplitude phase modulation (multiCAP) scheme is proposed for capacity enhancement of and flexible resource provisioning in 5G mobile networks. The proposed scheme is experimentally evaluated over a W-band

  1. Quantum phase transition of the transverse-field quantum Ising model on scale-free networks.

    Science.gov (United States)

    Yi, Hangmo

    2015-01-01

    I investigate the quantum phase transition of the transverse-field quantum Ising model in which nearest neighbors are defined according to the connectivity of scale-free networks. Using a continuous-time quantum Monte Carlo simulation method and the finite-size scaling analysis, I identify the quantum critical point and study its scaling characteristics. For the degree exponent λ=6, I obtain results that are consistent with the mean-field theory. For λ=4.5 and 4, however, the results suggest that the quantum critical point belongs to a non-mean-field universality class. Further simulations indicate that the quantum critical point remains mean-field-like if λ>5, but it continuously deviates from the mean-field theory as λ becomes smaller.

  2. Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

    Science.gov (United States)

    Liu, W. L.; Dong, F.

    2016-01-01

    Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

  3. Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

    Science.gov (United States)

    Tan, C; Liu, W L; Dong, F

    2016-06-28

    Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

  4. Application of artificial neural networks for the prediction of volume fraction using spectra of gamma rays backscattered by three-phase flows

    Science.gov (United States)

    Gholipour Peyvandi, R.; Islami Rad, S. Z.

    2017-12-01

    The determination of the volume fraction percentage of the different phases flowing in vessels using transmission gamma rays is a conventional method in petroleum and oil industries. In some cases, with access only to the one side of the vessels, attention was drawn toward backscattered gamma rays as a desirable choice. In this research, the volume fraction percentage was measured precisely in water-gasoil-air three-phase flows by using the backscatter gamma ray technique andthe multilayer perceptron (MLP) neural network. The volume fraction determination in three-phase flows requires two gamma radioactive sources or a dual-energy source (with different energies) while in this study, we used just a 137Cs source (with the single energy) and a NaI detector to analyze backscattered gamma rays. The experimental set-up provides the required data for training and testing the network. Using the presented method, the volume fraction was predicted with a mean relative error percentage less than 6.47%. Also, the root mean square error was calculated as 1.60. The presented set-up is applicable in some industries with limited access. Also, using this technique, the cost, radiation safety and shielding requirements are minimized toward the other proposed methods.

  5. Systematic Design of the Lead-Lag Network Method for Active Damping in LCL-Filter Based Three Phase Converters

    DEFF Research Database (Denmark)

    Alzola, Rafael Pena; Liserre, Marco; Blaabjerg, Frede

    2014-01-01

    ) nor its rationale has been explained. Thus, in this paper a straightforward procedure is developed to tune the lead-lag network with the help of software tools. The rationale of this procedure, based on the capacitor current feedback, is elucidated. Stability is studied by means of the root locus......Three-phase active rectifiers guarantee sinusoidal input currents and unity power factor at the price of a high switching frequency ripple. To adopt an LCL-filter, instead of an L-filter, allows using reduced values for the inductances and so preserving dynamics. However, stability problems can...... without using dissipative elements but, sometimes, needing additional sensors. This solution has been addressed in many publications. The lead-lag network method is one of the first reported procedures and continues being in use. However, neither there is a direct tuning procedure (without trial and error...

  6. Youth's social network structures and peer influences: Study protocol MyMovez project - Phase I

    OpenAIRE

    Bevelander, K.E.; Smit, C.R.; Woudenberg, T.J. van; Buijs, L.B.; Burk, W.J.; Buijzen, M.A.

    2018-01-01

    Background: Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and peers) that co-determine their dietary intake and physical activity. However, there is a lack of systematic and comprehensive research on the implementation of a social network approach in health campai...

  7. Hypoxia induces a phase transition within a kinase signaling network in cancer cells

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B.; Shin, Young Shik; Mischel, Paul S.; Levine, R. D.; Heath, James R.

    2013-01-01

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)—a critical component of hypoxic signaling and a compelling cancer drug target—is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier’s principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles. PMID:23530221

  8. Hypoxia induces a phase transition within a kinase signaling network in cancer cells.

    Science.gov (United States)

    Wei, Wei; Shi, Qihui; Remacle, Francoise; Qin, Lidong; Shackelford, David B; Shin, Young Shik; Mischel, Paul S; Levine, R D; Heath, James R

    2013-04-09

    Hypoxia is a near-universal feature of cancer, promoting glycolysis, cellular proliferation, and angiogenesis. The molecular mechanisms of hypoxic signaling have been intensively studied, but the impact of changes in oxygen partial pressure (pO2) on the state of signaling networks is less clear. In a glioblastoma multiforme (GBM) cancer cell model, we examined the response of signaling networks to targeted pathway inhibition between 21% and 1% pO2. We used a microchip technology that facilitates quantification of a panel of functional proteins from statistical numbers of single cells. We find that near 1.5% pO2, the signaling network associated with mammalian target of rapamycin (mTOR) complex 1 (mTORC1)--a critical component of hypoxic signaling and a compelling cancer drug target--is deregulated in a manner such that it will be unresponsive to mTOR kinase inhibitors near 1.5% pO2, but will respond at higher or lower pO2 values. These predictions were validated through experiments on bulk GBM cell line cultures and on neurosphere cultures of a human-origin GBM xenograft tumor. We attempt to understand this behavior through the use of a quantitative version of Le Chatelier's principle, as well as through a steady-state kinetic model of protein interactions, both of which indicate that hypoxia can influence mTORC1 signaling as a switch. The Le Chatelier approach also indicates that this switch may be thought of as a type of phase transition. Our analysis indicates that certain biologically complex cell behaviors may be understood using fundamental, thermodynamics-motivated principles.

  9. Molecular dynamics study on the evolution of interfacial dislocation network and mechanical properties of Ni-based single crystal superalloys

    Science.gov (United States)

    Li, Nan-Lin; Wu, Wen-Ping; Nie, Kai

    2018-05-01

    The evolution of misfit dislocation network at γ /γ‧ phase interface and tensile mechanical properties of Ni-based single crystal superalloys at various temperatures and strain rates are studied by using molecular dynamics (MD) simulations. From the simulations, it is found that with the increase of loading, the dislocation network effectively inhibits dislocations emitted in the γ matrix cutting into the γ‧ phase and absorbs the matrix dislocations to strengthen itself which increases the stability of structure. Under the influence of the temperature, the initial mosaic structure of dislocation network gradually becomes irregular, and the initial misfit stress and the elastic modulus slowly decline as temperature increasing. On the other hand, with the increase of the strain rate, it almost has no effect on the elastic modulus and the way of evolution of dislocation network, but contributes to the increases of the yield stress and tensile strength. Moreover, tension-compression asymmetry of Ni-based single crystal superalloys is also presented based on MD simulations.

  10. Verification of failover effects from distributed control system communication networks in digitalized nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Min, Moon Gi; Lee, Jae Ki; Lee, Kwang Hyun; Lee, Dong Il; Lim, Hee Taek [Korea Hydro and Nuclear Power Co., Ltd, Daejeon (Korea, Republic of)

    2017-08-15

    Distributed Control System (DCS) communication networks, which use Fast Ethernet with redundant networks for the transmission of information, have been installed in digitalized nuclear power plants. Normally, failover tests are performed to verify the reliability of redundant networks during design and manufacturing phases; however, systematic integrity tests of DCS networks cannot be fully performed during these phases because all relevant equipment is not installed completely during these two phases. In additions, practical verification tests are insufficient, and there is a need to test the actual failover function of DCS redundant networks in the target environment. The purpose of this study is to verify that the failover functions works correctly in certain abnormal conditions during installation and commissioning phase and identify the influence of network failover on the entire DCS. To quantify the effects of network failover in the DCS, the packets (Protocol Data Units) must be collected and resource usage of the system has to be monitored and analyzed. This study introduces the use of a new methodology for verification of DCS network failover during the installation and commissioning phases. This study is expected to provide insight into verification methodology and the failover effects from DCS redundant networks. It also provides test results of network performance from DCS network failover in digitalized domestic nuclear power plants (NPPs)

  11. Flexible Tube-Based Network Control, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The Innovation Laboratory, Inc. builds a control system which controls the topology of an air traffic flow network and the network flow properties which enables Air...

  12. Non-invasive classification of gas–liquid two-phase horizontal flow regimes using an ultrasonic Doppler sensor and a neural network

    OpenAIRE

    Abbagoni, Baba Musa; Yeung, Hoi

    2016-01-01

    The identification of flow pattern is a key issue in multiphase flow which is encountered in the petrochemical industry. It is difficult to identify the gas–liquid flow regimes objectively with the gas–liquid two-phase flow. This paper presents the feasibility of a clamp-on instrument for an objective flow regime classification of two-phase flow using an ultrasonic Doppler sensor and an artificial neural network, which records and processes the ultrasonic signals reflected from the two-phase ...

  13. Phase-locked patterns of the Kuramoto model on 3-regular graphs

    Science.gov (United States)

    DeVille, Lee; Ermentrout, Bard

    2016-09-01

    We consider the existence of non-synchronized fixed points to the Kuramoto model defined on sparse networks: specifically, networks where each vertex has degree exactly three. We show that "most" such networks support multiple attracting phase-locked solutions that are not synchronized and study the depth and width of the basins of attraction of these phase-locked solutions. We also show that it is common in "large enough" graphs to find phase-locked solutions where one or more of the links have angle difference greater than π/2.

  14. Thematic Network on The role of Monitoring in a Phased Approach to Disposal - EUR 21025, 2004. Conclusions of the EC Thematic Network on The role of Monitoring in a Phased Approach to Geological Disposal of Radioactive Waste

    International Nuclear Information System (INIS)

    Barlow, Stephen

    2005-01-01

    The EC thematic network on the role of monitoring in a phased approach to the geological disposal of radioactive waste brought together expertise from twelve organisations from ten countries. It was started in 2001 following on from an earlier EC study of retrievability and reversibility (EUR 19145 EN), and completed in 2004 with publication of the final report (EUR 21025 EN). The project mainly aimed to: - Understand the approaches to monitoring in each national programme and their dependency on concepts and approaches. - Distil consensus views and recognise alternative approaches to monitoring. - Share technical knowledge and experience. - Communicate views and experiences. Participants from the projects looked at various definitions of monitoring in relation to a phased approach to disposal, and achieved a consensus on the following: 'Continuous or periodic observations and measurements of engineering, environmental, radiological or other parameters and indicators/characteristics, to help evaluate the behaviour of components of the repository system, or the impacts of the repository and its operation on the environment, and to help in making decisions on the implementation of successive phases of the disposal concept'. That definition is mainly based on an IAEA definition with a few modifications and, in particular, by adding the fact that monitoring has a role in making decisions. Various alternative approaches to make decisions and achieve goals were analysed and the need was stressed for a flexible schedule with a degree of concept flexibility. The project achieved a consensus on the following principles: (i) monitoring has a role in underpinning and verification of operational safety (compliance monitoring); (ii) long-term (post-closure) safety must be assured by design - it cannot rely on monitoring, although monitoring may be implemented for other reasons - monitoring must not be detrimental to long-term (post-closure) safety (iii) monitoring

  15. Network analysis of the transcriptional pattern of young and old cells of Escherichia coli during lag phase

    Directory of Open Access Journals (Sweden)

    Hinton Jay CD

    2009-11-01

    Full Text Available Abstract Background The aging process of bacteria in stationary phase is halted if cells are subcultured and enter lag phase and it is then followed by cellular division. Network science has been applied to analyse the transcriptional response, during lag phase, of bacterial cells starved previously in stationary phase for 1 day (young cells and 16 days (old cells. Results A genome scale network was constructed for E. coli K-12 by connecting genes with operons, transcription and sigma factors, metabolic pathways and cell functional categories. Most of the transcriptional changes were detected immediately upon entering lag phase and were maintained throughout this period. The lag period was longer for older cells and the analysis of the transcriptome revealed different intracellular activity in young and old cells. The number of genes differentially expressed was smaller in old cells (186 than in young cells (467. Relatively, few genes (62 were up- or down-regulated in both cultures. Transcription of genes related to osmotolerance, acid resistance, oxidative stress and adaptation to other stresses was down-regulated in both young and old cells. Regarding carbohydrate metabolism, genes related to the citrate cycle were up-regulated in young cells while old cells up-regulated the Entner Doudoroff and gluconate pathways and down-regulated the pentose phosphate pathway. In both old and young cells, anaerobic respiration and fermentation pathways were down-regulated, but only young cells up-regulated aerobic respiration while there was no evidence of aerobic respiration in old cells. Numerous genes related to DNA maintenance and replication, translation, ribosomal biosynthesis and RNA processing as well as biosynthesis of the cell envelope and flagellum and several components of the chemotaxis signal transduction complex were up-regulated only in young cells. The genes for several transport proteins for iron compounds were up-regulated in both young

  16. Network analysis of the transcriptional pattern of young and old cells of Escherichia coli during lag phase

    LENUS (Irish Health Repository)

    Pin, Carmen

    2009-11-16

    Abstract Background The aging process of bacteria in stationary phase is halted if cells are subcultured and enter lag phase and it is then followed by cellular division. Network science has been applied to analyse the transcriptional response, during lag phase, of bacterial cells starved previously in stationary phase for 1 day (young cells) and 16 days (old cells). Results A genome scale network was constructed for E. coli K-12 by connecting genes with operons, transcription and sigma factors, metabolic pathways and cell functional categories. Most of the transcriptional changes were detected immediately upon entering lag phase and were maintained throughout this period. The lag period was longer for older cells and the analysis of the transcriptome revealed different intracellular activity in young and old cells. The number of genes differentially expressed was smaller in old cells (186) than in young cells (467). Relatively, few genes (62) were up- or down-regulated in both cultures. Transcription of genes related to osmotolerance, acid resistance, oxidative stress and adaptation to other stresses was down-regulated in both young and old cells. Regarding carbohydrate metabolism, genes related to the citrate cycle were up-regulated in young cells while old cells up-regulated the Entner Doudoroff and gluconate pathways and down-regulated the pentose phosphate pathway. In both old and young cells, anaerobic respiration and fermentation pathways were down-regulated, but only young cells up-regulated aerobic respiration while there was no evidence of aerobic respiration in old cells. Numerous genes related to DNA maintenance and replication, translation, ribosomal biosynthesis and RNA processing as well as biosynthesis of the cell envelope and flagellum and several components of the chemotaxis signal transduction complex were up-regulated only in young cells. The genes for several transport proteins for iron compounds were up-regulated in both young and old cells

  17. Phase aided 3D imaging and modeling: dedicated systems and case studies

    Science.gov (United States)

    Yin, Yongkai; He, Dong; Liu, Zeyi; Liu, Xiaoli; Peng, Xiang

    2014-05-01

    Dedicated prototype systems for 3D imaging and modeling (3DIM) are presented. The 3D imaging systems are based on the principle of phase-aided active stereo, which have been developed in our laboratory over the past few years. The reported 3D imaging prototypes range from single 3D sensor to a kind of optical measurement network composed of multiple node 3D-sensors. To enable these 3D imaging systems, we briefly discuss the corresponding calibration techniques for both single sensor and multi-sensor optical measurement network, allowing good performance of the 3DIM prototype systems in terms of measurement accuracy and repeatability. Furthermore, two case studies including the generation of high quality color model of movable cultural heritage and photo booth from body scanning are presented to demonstrate our approach.

  18. Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

    Science.gov (United States)

    Velásquez-Rojas, Fátima; Vazquez, Federico

    2017-05-01

    Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.

  19. Investigation of phase-wise voltage regulator control logics for compensating voltage deviations in an experimental low voltage network

    DEFF Research Database (Denmark)

    Hu, Junjie; Zecchino, Antonio; Marinelli, Mattia

    2016-01-01

    This paper investigates the control logics of an on-load tap-changer (OLTC) transformer by means of an experimental system validation. The experimental low-voltage unbalanced system consists of a decoupled single-phase OLTC transformer, a 75-metre 16 mm2 cable, a controllable single-phase resistive...... load and an electric vehicle, which has the vehicle-to-grid function. Three control logics of the OLTC transformer are described in the study. The three control logics are classified based on their control objectives and control inputs, which include network currents and voltages, and can be measured...... either locally or remotely. To evaluate and compare the control performances of the three control logics, all the tests use the same loading profiles. The experimental results indicate that the modified line compensation control can regulate voltage in a safe band in the case of various load...

  20. Development of the self-learning machine for creating models of microprocessor of single-phase earth fault protection devices in networks with isolated neutral voltage above 1000 V

    Science.gov (United States)

    Utegulov, B. B.; Utegulov, A. B.; Meiramova, S.

    2018-02-01

    The paper proposes the development of a self-learning machine for creating models of microprocessor-based single-phase ground fault protection devices in networks with an isolated neutral voltage higher than 1000 V. Development of a self-learning machine for creating models of microprocessor-based single-phase earth fault protection devices in networks with an isolated neutral voltage higher than 1000 V. allows to effectively implement mathematical models of automatic change of protection settings. Single-phase earth fault protection devices.

  1. Phased-array design for MST and ST radars

    Science.gov (United States)

    Ecklund, W. L.

    1986-01-01

    All of the existing radar systems fully dedicated to clear-air radar studies use some type of phased-array antennas. The effects of beam-steering techniques including feed networks and phase shifters; sidelobe control; ground-clutter suppression; low altitude coverage; arrays with integrated radiating elements and feed networks; analysis of coaxial-collinear antennas; use of arrays with multiple beams; and array testing and measure on structural design of the antenna are discussed.

  2. Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks.

    Science.gov (United States)

    Wang, Yongqiang; Núñez, Felipe; Doyle, Francis J

    2012-07-25

    This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is increased even under a fixed transmission power. Given that energy consumption in synchronization is determined by the product of synchronization time and transformation power, the new strategy reduces energy consumption in clock synchronization. QualNet experiments confirm the theoretical results.

  3. Capacitance estimation algorithm based on DC-link voltage harmonics using artificial neural network in three-phase motor drive systems

    DEFF Research Database (Denmark)

    Soliman, Hammam Abdelaal Hammam; Davari, Pooya; Wang, Huai

    2017-01-01

    to industry. In this digest, a condition monitoring methodology that estimates the capacitance value of the dc-link capacitor in a three phase Front-End diode bridge motor drive is proposed. The proposed software methodology is based on Artificial Neural Network (ANN) algorithm. The harmonics of the dc......-link voltage are used as training data to the Artificial Neural Network. Fast Fourier Transform (FFT) of the dc-link voltage is analysed in order to study the impact of capacitance variation on the harmonics order. Laboratory experiments are conducted to validate the proposed methodology and the error analysis......In modern design of power electronic converters, reliability of dc-link capacitors is one of the critical considered aspects. The industrial field have been attracted to the monitoring of their health condition and the estimation of their ageing process status. However, the existing condition...

  4. ATM Tactical Network - a challenge for the military networks

    NARCIS (Netherlands)

    Waveren, C.J. van; Luiijf, H.A.M.; Burakowski, W.; Kopertowski, Z.

    1997-01-01

    The next generation of tactical networks will be based on the ATM technology. The POST-2000 tactical network is just in the designing phase. The objective of this paper is to point out the main problems which should be solved to adopt ATM technology into the tactical network environment. The

  5. A Predictive Coexpression Network Identifies Novel Genes Controlling the Seed-to-Seedling Phase Transition in Arabidopsis thaliana.

    Science.gov (United States)

    Silva, Anderson Tadeu; Ribone, Pamela A; Chan, Raquel L; Ligterink, Wilco; Hilhorst, Henk W M

    2016-04-01

    The transition from a quiescent dry seed to an actively growing photoautotrophic seedling is a complex and crucial trait for plant propagation. This study provides a detailed description of global gene expression in seven successive developmental stages of seedling establishment in Arabidopsis (Arabidopsis thaliana). Using the transcriptome signature from these developmental stages, we obtained a coexpression gene network that highlights interactions between known regulators of the seed-to-seedling transition and predicts the functions of uncharacterized genes in seedling establishment. The coexpressed gene data sets together with the transcriptional module indicate biological functions related to seedling establishment. Characterization of the homeodomain leucine zipper I transcription factor AtHB13, which is expressed during the seed-to-seedling transition, demonstrated that this gene regulates some of the network nodes and affects late seedling establishment. Knockout mutants for athb13 showed increased primary root length as compared with wild-type (Columbia-0) seedlings, suggesting that this transcription factor is a negative regulator of early root growth, possibly repressing cell division and/or cell elongation or the length of time that cells elongate. The signal transduction pathways present during the early phases of the seed-to-seedling transition anticipate the control of important events for a vigorous seedling, such as root growth. This study demonstrates that a gene coexpression network together with transcriptional modules can provide insights that are not derived from comparative transcript profiling alone. © 2016 American Society of Plant Biologists. All Rights Reserved.

  6. Network Approach in Political Communication Studies

    Directory of Open Access Journals (Sweden)

    Нина Васильевна Опанасенко

    2013-12-01

    Full Text Available The article is devoted to issues of network approach application in political communication studies. The author considers communication in online and offline areas and gives the definition of rhizome, its characteristics, identifies links between rhizome and network approach. The author also analyses conditions and possibilities of the network approach in modern political communication. Both positive and negative features of the network approach are emphasized.

  7. Studying Dynamics in Business Networks

    DEFF Research Database (Denmark)

    Andersen, Poul Houman; Anderson, Helen; Havila, Virpi

    1998-01-01

    This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland......This paper develops a theory on network dynamics using the concepts of role and position from sociological theory. Moreover, the theory is further tested using case studies from Denmark and Finland...

  8. Statistical Power in Longitudinal Network Studies

    NARCIS (Netherlands)

    Stadtfeld, Christoph; Snijders, Tom A. B.; Steglich, Christian; van Duijn, Marijtje

    2018-01-01

    Longitudinal social network studies may easily suffer from a lack of statistical power. This is the case in particular for studies that simultaneously investigate change of network ties and change of nodal attributes. Such selection and influence studies have become increasingly popular due to the

  9. 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...

  10. A new method in prediction of TCP phases formation in superalloys

    International Nuclear Information System (INIS)

    Mousavi Anijdan, S.H.; Bahrami, A.

    2005-01-01

    The purpose of this investigation is to develop a model for prediction of topologically closed-packed (TCP) phases formation in superalloys. In this study, artificial neural networks (ANN), using several different network architectures, were used to investigate the complex relationships between TCP phases and chemical composition of superalloys. In order to develop an optimum ANN structure, more than 200 experimental data were used to train and test the neural network. The results of this investigation shows that a multilayer perceptron (MLP) form of the neural networks with one hidden layer and 10 nodes in the hidden layer has the lowest mean absolute error (MAE) and can be accurately used to predict the electron-hole number (N v ) and TCP phases formation in superalloys

  11. A computational study on altered theta-gamma coupling during learning and phase coding.

    Directory of Open Access Journals (Sweden)

    Xuejuan Zhang

    Full Text Available There is considerable interest in the role of coupling between theta and gamma oscillations in the brain in the context of learning and memory. Here we have used a neural network model which is capable of producing coupling of theta phase to gamma amplitude firstly to explore its ability to reproduce reported learning changes and secondly to memory-span and phase coding effects. The spiking neural network incorporates two kinetically different GABA(A receptor-mediated currents to generate both theta and gamma rhythms and we have found that by selective alteration of both NMDA receptors and GABA(A,slow receptors it can reproduce learning-related changes in the strength of coupling between theta and gamma either with or without coincident changes in theta amplitude. When the model was used to explore the relationship between theta and gamma oscillations, working memory capacity and phase coding it showed that the potential storage capacity of short term memories, in terms of nested gamma-subcycles, coincides with the maximal theta power. Increasing theta power is also related to the precision of theta phase which functions as a potential timing clock for neuronal firing in the cortex or hippocampus.

  12. Single- and two-phase flow simulation based on equivalent pore network extracted from micro-CT images of sandstone core.

    Science.gov (United States)

    Song, Rui; Liu, Jianjun; Cui, Mengmeng

    2016-01-01

    Due to the intricate structure of porous rocks, relationships between porosity or saturation and petrophysical transport properties classically used for reservoir evaluation and recovery strategies are either very complex or nonexistent. Thus, the pore network model extracted from the natural porous media is emphasized as a breakthrough to predict the fluid transport properties in the complex micro pore structure. This paper presents a modified method of extracting the equivalent pore network model from the three-dimensional micro computed tomography images based on the maximum ball algorithm. The partition of pore and throat are improved to avoid tremendous memory usage when extracting the equivalent pore network model. The porosity calculated by the extracted pore network model agrees well with the original sandstone sample. Instead of the Poiseuille's law used in the original work, the Lattice-Boltzmann method is employed to simulate the single- and two- phase flow in the extracted pore network. Good agreements are acquired on relative permeability saturation curves of the simulation against the experiment results.

  13. Remote synchronization reveals network symmetries and functional modules.

    Science.gov (United States)

    Nicosia, Vincenzo; Valencia, Miguel; Chavez, Mario; Díaz-Guilera, Albert; Latora, Vito

    2013-04-26

    We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.

  14. Reactive Power Control of Single-Stage Three-Phase Photovoltaic System during Grid Faults Using Recurrent Fuzzy Cerebellar Model Articulation Neural Network

    Directory of Open Access Journals (Sweden)

    Faa-Jeng Lin

    2014-01-01

    Full Text Available This study presents a new active and reactive power control scheme for a single-stage three-phase grid-connected photovoltaic (PV system during grid faults. The presented PV system utilizes a single-stage three-phase current-controlled voltage-source inverter to achieve the maximum power point tracking (MPPT control of the PV panel with the function of low voltage ride through (LVRT. Moreover, a formula based on positive sequence voltage for evaluating the percentage of voltage sag is derived to determine the ratio of the injected reactive current to satisfy the LVRT regulations. To reduce the risk of overcurrent during LVRT operation, a current limit is predefined for the injection of reactive current. Furthermore, the control of active and reactive power is designed using a two-dimensional recurrent fuzzy cerebellar model articulation neural network (2D-RFCMANN. In addition, the online learning laws of 2D-RFCMANN are derived according to gradient descent method with varied learning-rate coefficients for network parameters to assure the convergence of the tracking error. Finally, some experimental tests are realized to validate the effectiveness of the proposed control scheme.

  15. Controlling the dynamics of multi-state neural networks

    International Nuclear Information System (INIS)

    Jin, Tao; Zhao, Hong

    2008-01-01

    In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

  16. Youth's social network structures and peer influences: study protocol MyMovez project – Phase I

    OpenAIRE

    Bevelander, Kirsten E.; Smit, Crystal R.; van Woudenberg, Thabo J.; Buijs, Laura; Burk, William J.; Buijzen, Moniek

    2018-01-01

    Background: Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and peers) that co-determine their dietary intake and physical activity. However, there is a lack of systematic and comprehensive research on the implementation of a social network approach in health campai...

  17. Self-organized critical neural networks

    International Nuclear Information System (INIS)

    Bornholdt, Stefan; Roehl, Torsten

    2003-01-01

    A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

  18. Robustness and structure of complex networks

    Science.gov (United States)

    Shao, Shuai

    This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks

  19. SuperJet International case study: a business network start-up in the aeronautics industry

    Science.gov (United States)

    Corallo, Angelo; de Maggio, Marco; Storelli, Davide

    This chapter presents the SuperJet International case study, a start-up in the aeronautics industry characterized by a process-oriented approach and a complex and as yet evolving network of partnerships and collaborations. The chapter aims to describe the key points of the start-up process, highlighting common factors and differences compared to the TEKNE Methodology of Change, with particular reference to the second and third phase, namely, the design and deployment of new techno-organizational systems. The SuperJet International startup is presented as a case study where strategic and organizational aspects have been jointly conceived from a network-driven perspective. The chapter compares some of the guidelines of the TEKNE Methodology of Change with experiences and actual practices deriving from interviews with key players in SJI's start-up process.

  20. Visual analytics for multimodal social network analysis: a design study with social scientists.

    Science.gov (United States)

    Ghani, Sohaib; Kwon, Bum Chul; Lee, Seungyoon; Yi, Ji Soo; Elmqvist, Niklas

    2013-12-01

    Social network analysis (SNA) is becoming increasingly concerned not only with actors and their relations, but also with distinguishing between different types of such entities. For example, social scientists may want to investigate asymmetric relations in organizations with strict chains of command, or incorporate non-actors such as conferences and projects when analyzing coauthorship patterns. Multimodal social networks are those where actors and relations belong to different types, or modes, and multimodal social network analysis (mSNA) is accordingly SNA for such networks. In this paper, we present a design study that we conducted with several social scientist collaborators on how to support mSNA using visual analytics tools. Based on an openended, formative design process, we devised a visual representation called parallel node-link bands (PNLBs) that splits modes into separate bands and renders connections between adjacent ones, similar to the list view in Jigsaw. We then used the tool in a qualitative evaluation involving five social scientists whose feedback informed a second design phase that incorporated additional network metrics. Finally, we conducted a second qualitative evaluation with our social scientist collaborators that provided further insights on the utility of the PNLBs representation and the potential of visual analytics for mSNA.

  1. Assembly of Collagen Matrices as a Phase Transition Revealed by Structural and Rheologic Studies

    OpenAIRE

    Forgacs, Gabor; Newman, Stuart A.; Hinner, Bernhard; Maier, Christian W.; Sackmann, Erich

    2003-01-01

    We have studied the structural and viscoelastic properties of assembling networks of the extracellular matrix protein type-I collagen by means of phase contrast microscopy and rotating disk rheometry. The initial stage of the assembly is a nucleation process of collagen monomers associating to randomly distributed branched clusters with extensions of several microns. Eventually a sol-gel transition takes place, which is due to the interconnection of these clusters. We analyzed this transition...

  2. Phase transitions

    CERN Document Server

    Sole, Ricard V; Solé, Ricard V; Solé, Ricard V; Sol, Ricard V; Solé, Ricard V

    2011-01-01

    Phase transitions--changes between different states of organization in a complex system--have long helped to explain physics concepts, such as why water freezes into a solid or boils to become a gas. How might phase transitions shed light on important problems in biological and ecological complex systems? Exploring the origins and implications of sudden changes in nature and society, Phase Transitions examines different dynamical behaviors in a broad range of complex systems. Using a compelling set of examples, from gene networks and ant colonies to human language and the degradation of diverse ecosystems, the book illustrates the power of simple models to reveal how phase transitions occur. Introductory chapters provide the critical concepts and the simplest mathematical techniques required to study phase transitions. In a series of example-driven chapters, Ricard Solé shows how such concepts and techniques can be applied to the analysis and prediction of complex system behavior, including the origins of ...

  3. Comparison of Channel Estimation Protocols for Coherent AF Relaying Networks in the Presence of Additive Noise and LO Phase Noise

    Directory of Open Access Journals (Sweden)

    Stefan Berger

    2010-01-01

    Full Text Available Channel estimation protocols for wireless two-hop networks with amplify-and-forward (AF relays are compared. We consider multiuser relaying networks, where the gain factors are chosen such that the signals from all relays add up coherently at the destinations. While the destinations require channel knowledge in order to decode, our focus lies on the channel estimates that are used to calculate the relay gains. Since knowledge of the compound two-hop channels is generally not sufficient to do this, the protocols considered here measure all single-hop coefficients in the network. We start from the observation that the direction in which the channels are measured determines (1 the number of channel uses required to estimate all coefficient and (2 the need for global carrier phase reference. Four protocols are identified that differ in the direction in which the first-hop and the second-hop channels are measured. We derive a sensible measure for the accuracy of the channel estimates in the presence of additive noise and phase noise and compare the protocols based on this measure. Finally, we provide a quantitative performance comparison for a simple single-user application example. It is important to note that the results can be used to compare the channel estimation protocols for any two-hop network configuration and gain allocation scheme.

  4. Real-Time Network Management

    National Research Council Canada - National Science Library

    Riolo, Joseph

    1998-01-01

    .... According to our Phase I research, it is possible to collect data on the network and morph it into queuing models to produce information about the network and physical layers of nodes on a network...

  5. Regional Educational Laboratory Electronic Network Phase 2 System

    Science.gov (United States)

    Cradler, John

    1995-01-01

    The Far West Laboratory in collaboration with the other regional educational laboratories is establishing a regionally coordinated telecommunication network to electronically interconnect each of the ten regional laboratories with educators and education stakeholders from the school to the state level. For the national distributed information database, each lab is working with mid-level networks to establish a common interface for networking throughout the country and include topics of importance to education reform as assessment and technology planning.

  6. Phase patterns of coupled oscillators with application to wireless communication

    Energy Technology Data Exchange (ETDEWEB)

    Arenas, A.

    2008-01-02

    Here we study the plausibility of a phase oscillators dynamical model for TDMA in wireless communication networks. We show that emerging patterns of phase locking states between oscillators can eventually oscillate in a round-robin schedule, in a similar way to models of pulse coupled oscillators designed to this end. The results open the door for new communication protocols in a continuous interacting networks of wireless communication devices.

  7. Preservation of knowledge through networking with retirees

    International Nuclear Information System (INIS)

    Barroso, A.C.O.; Reis-Junior, J.S.B.; Monteiro, C.A.; Seary, A

    2009-01-01

    Loss of emphasis or phasing down of nuclear programs has reduced substantially the hiring of new employees as a result nuclear organizations, in most countries, are experiencing reduction in the workforce and the average age of their technical professionals are around mid fifties. Knowledge management activities with emphasis on knowledge preservation have become a crucial issue for such organizations. This work studied a spontaneous knowledge preservation mechanism at IPEN that could be leveraged and may be replicated in other organizations. Crossing examining publications and human resources data base, with some alias detecting algorithm a large collaboration network involving retirees and current workers of IPEN was unveiled. Using simple indicators and advance techniques of social network analysis the following studies were performed: assessment of the network performance; characterization of its key global properties and detailed structure; characterization and assessment of the role of its key actors; analysis of groups and subgroups patterns; and longitudinal (time evolution) of the network and assessment of its robustness. Rich insights came from this study concerning the value of this mechanism for IPEN and also about the essence of the common interest that constitutes the 'glue' for such mechanism. While more detailed network analysis will still go on for a couple of months, a new phase has already been started with a formulated conceptual model, consisting of four latent variables and thirty six observable ones, to 'explain' at the actor level, in this particular setting what matters when engaging in collaboration. Upon finishing this new phase network data and actors' survey data will be cross correlate to provide a more fully understanding of this amazing mechanism. (author)

  8. Preservation of knowledge through networking with retirees

    Energy Technology Data Exchange (ETDEWEB)

    Barroso, A.C.O.; Reis-Junior, J.S.B.; Monteiro, C.A. [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)], e-mail: barroso@ipen.br, e-mail: jose.sergio.junior@googlemail.com, e-mail: monteiro@ipen.br; Seary, A [Simon Fraser University School of Comunication, Burnaby, BC (Canada)], e-mail: seary@sfu.ca

    2009-07-01

    Loss of emphasis or phasing down of nuclear programs has reduced substantially the hiring of new employees as a result nuclear organizations, in most countries, are experiencing reduction in the workforce and the average age of their technical professionals are around mid fifties. Knowledge management activities with emphasis on knowledge preservation have become a crucial issue for such organizations. This work studied a spontaneous knowledge preservation mechanism at IPEN that could be leveraged and may be replicated in other organizations. Crossing examining publications and human resources data base, with some alias detecting algorithm a large collaboration network involving retirees and current workers of IPEN was unveiled. Using simple indicators and advance techniques of social network analysis the following studies were performed: assessment of the network performance; characterization of its key global properties and detailed structure; characterization and assessment of the role of its key actors; analysis of groups and subgroups patterns; and longitudinal (time evolution) of the network and assessment of its robustness. Rich insights came from this study concerning the value of this mechanism for IPEN and also about the essence of the common interest that constitutes the 'glue' for such mechanism. While more detailed network analysis will still go on for a couple of months, a new phase has already been started with a formulated conceptual model, consisting of four latent variables and thirty six observable ones, to 'explain' at the actor level, in this particular setting what matters when engaging in collaboration. Upon finishing this new phase network data and actors' survey data will be cross correlate to provide a more fully understanding of this amazing mechanism. (author)

  9. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  10. Finite connectivity attractor neural networks

    International Nuclear Information System (INIS)

    Wemmenhove, B; Coolen, A C C

    2003-01-01

    We study a family of diluted attractor neural networks with a finite average number of (symmetric) connections per neuron. As in finite connectivity spin glasses, their equilibrium properties are described by order parameter functions, for which we derive an integral equation in replica symmetric approximation. A bifurcation analysis of this equation reveals the locations of the paramagnetic to recall and paramagnetic to spin-glass transition lines in the phase diagram. The line separating the retrieval phase from the spin-glass phase is calculated at zero temperature. All phase transitions are found to be continuous

  11. Modeling and Speed Control of Induction Motor Drives Using Neural Networks

    Directory of Open Access Journals (Sweden)

    V. Jamuna

    2010-08-01

    Full Text Available Speed control of induction motor drives using neural networks is presented. The mathematical model of single phase induction motor is developed. A new simulink model for a neural network-controlled bidirectional chopper fed single phase induction motor is proposed. Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. Comparative study has been made between the conventional and neural network controllers. It is observed that the neural network controlled drive system has better dynamic performance, reduced overshoot and faster transient response than the conventional controlled system.

  12. Generalized epidemic process on modular networks.

    Science.gov (United States)

    Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong

    2014-05-01

    Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.

  13. Noise Analysis studies with neural networks

    International Nuclear Information System (INIS)

    Seker, S.; Ciftcioglu, O.

    1996-01-01

    Noise analysis studies with neural network are aimed. Stochastic signals at the input of the network are used to obtain an algorithmic multivariate stochastic signal modeling. To this end, lattice modeling of a stochastic signal is performed to obtain backward residual noise sources which are uncorrelated among themselves. There are applied together with an additional input to the network to obtain an algorithmic model which is used for signal detection for early failure in plant monitoring. The additional input provides the information to the network to minimize the difference between the signal and the network's one-step-ahead prediction. A stochastic algorithm is used for training where the errors reflecting the measurement error during the training are also modelled so that fast and consistent convergence of network's weights is obtained. The lattice structure coupled to neural network investigated with measured signals from an actual power plant. (authors)

  14. Scoping Study: Networked Microgrids.

    Energy Technology Data Exchange (ETDEWEB)

    Trinklei, Eddy; Parker, Gordon; Weaver, Wayne; Robinett, Rush; Babe Gauchia, Lucia; Ten, Chee-Wooi; Bower, Ward; Glover, Steven F.; Bukowski, Steve

    2014-10-01

    This report presents a scoping study for networked microgrids which are defined as "Interoperable groups of multiple Advanced Microgrids that become an integral part of the electricity grid while providing enhanced resiliency through self-healing, aggregated ancillary services, and real-time communication." They result in optimal electrical system configurations and controls whether grid-connected or in islanded modes and enable high penetrations of distributed and renewable energy resources. The vision for the purpose of this document is: "Networked microgrids seamlessly integrate with the electricity grid or other Electric Power Sources (EPS) providing cost effective, high quality, reliable, resilient, self-healing power delivery systems." Scoping Study: Networked Microgrids September 4, 2014 Eddy Trinklein, Michigan Technological University Gordon Parker, Michigan Technological University Wayne Weaver, Michigan Technological University Rush Robinett, Michigan Technological University Lucia Gauchia Babe, Michigan Technological University Chee-Wooi Ten, Michigan Technological University Ward Bower, Ward Bower Innovations LLC Steve Glover, Sandia National Laboratories Steve Bukowski, Sandia National Laboratories Prepared by Michigan Technological University Houghton, Michigan 49931 Michigan Technological University

  15. Autonomous Modeling, Statistical Complexity and Semi-annealed Treatment of Boolean Networks

    Science.gov (United States)

    Gong, Xinwei

    This dissertation presents three studies on Boolean networks. Boolean networks are a class of mathematical systems consisting of interacting elements with binary state variables. Each element is a node with a Boolean logic gate, and the presence of interactions between any two nodes is represented by directed links. Boolean networks that implement the logic structures of real systems are studied as coarse-grained models of the real systems. Large random Boolean networks are studied with mean field approximations and used to provide a baseline of possible behaviors of large real systems. This dissertation presents one study of the former type, concerning the stable oscillation of a yeast cell-cycle oscillator, and two studies of the latter type, respectively concerning the statistical complexity of large random Boolean networks and an extension of traditional mean field techniques that accounts for the presence of short loops. In the cell-cycle oscillator study, a novel autonomous update scheme is introduced to study the stability of oscillations in small networks. A motif that corrects pulse-growing perturbations and a motif that grows pulses are identified. A combination of the two motifs is capable of sustaining stable oscillations. Examining a Boolean model of the yeast cell-cycle oscillator using an autonomous update scheme yields evidence that it is endowed with such a combination. Random Boolean networks are classified as ordered, critical or disordered based on their response to small perturbations. In the second study, random Boolean networks are taken as prototypical cases for the evaluation of two measures of complexity based on a criterion for optimal statistical prediction. One measure, defined for homogeneous systems, does not distinguish between the static spatial inhomogeneity in the ordered phase and the dynamical inhomogeneity in the disordered phase. A modification in which complexities of individual nodes are calculated yields vanishing

  16. Time concurrency/phase-time synchronization in digital communications networks

    Science.gov (United States)

    Kihara, Masami; Imaoka, Atsushi

    1990-01-01

    Digital communications networks have the intrinsic capability of time synchronization which makes it possible for networks to supply time signals to some applications and services. A practical estimation method for the time concurrency on terrestrial networks is presented. By using this method, time concurrency capability of the Nippon Telegraph and Telephone Corporation (NTT) digital communications network is estimated to be better than 300 ns rms at an advanced level, and 20 ns rms at final level.

  17. Study on Network Error Analysis and Locating based on Integrated Information Decision System

    Science.gov (United States)

    Yang, F.; Dong, Z. H.

    2017-10-01

    Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

  18. Stability study of the γ phase in U-Nb-Zr alloys

    International Nuclear Information System (INIS)

    Arico, S.F; Hermida, J.D; Gribaudo, L.M

    2006-01-01

    The development of new low enrichment nuclear fuels for research and radioisotope production reactors imposes the knowledge of properties and behaviors about a series of alloys which the reducing of U 235 (fissionable) concentration is compensated with a greater density of this element inside the fuel. One of these series is composed by U alloys with different contents of alloying, that allow to retain the body centered cubic structure solid solution recognized as phase α in metastable condition at low temperatures. For the present work 10 U based alloys were manufactured with different concentrations containing up to 43,7 % zirconium weight and up to 7,3 % niobium weight. An arch oven was utilized with argon atmosphere. The identification of the present phases in massive samples from the melting was carried out through X-rays diffraction analysis. The results obtained in this work are compared with others results published since the year 1957. In the samples melted the intermetallic UZr 2 diminishes in quantity with the reduction of the composition of Zr in the alloys. In all of them were identified, besides, Zr 6 Fe 3 O, ZrO 0,35 , α and U 3 O 8 present in quantities reduced. The quantity of the two last phases diminishes at the same time with the content in Zr. The parameter of network of the cubic phase γU in these alloys can be represented for the equation: α=(3,5796 -0,1616.x Nb +0,1155.x Zr )/(1.0306+0,003.x Nb -0,0068.x Zr . The parameter of network of the γ phase was measured. Comparing it measured with the value calculated, for eight alloys, the proposed equation showed a very good adjustment (HC)

  19. Study of phase separation and crystallization phenomena in soda-lime borosilicate glass enriched in MoO3

    International Nuclear Information System (INIS)

    Magnin, M.

    2009-09-01

    Molybdenum oxide immobilization (MoO 3 , as fission product) is one of the major challenges in the nuclear glass formulation issues for high level waste solutions conditioning since many years, these solutions arising from spent nuclear fuel reprocessing. Phase separation and crystallisation processes may arise in molten glass when the MoO 3 content is higher than its solubility limit that may depend on glass composition. Molybdenum combined with other elements such as alkali and alkaline-earth may form crystalline molybdates, known as 'yellow phases' in nuclear glasses which may decrease the glass durability. In order to confine high level wastes (HLW) such as the fission product solutions arising from the reprocessing of high burn-up UOX-type nuclear spent fuels, a new glass composition (HLW glass) is being optimized. This work is devoted to the study of the origin and the mechanism of phase separation and crystallization phenomena induced by molybdenum oxide incorporation in the HLW glass. From microstructural and structural point of view, the molybdenum oxide behavior was studied in glass compositions belonging to the SiO 2 -B 2 O 3 - Na 2 O-CaO simplified system which constituted basis for the HLW glass formulation. The structural role of molybdenum oxide in borosilicate network explaining the phase separation and crystallization tendency was studied through the coupling of structural ( 95 Mo, 29 Si, 11 B, 23 Na MAS NMR, XRD) and microstructural (SEM, HRTEM) analysis techniques. The determination of phase separation (critical temperature) and crystallization (liquidus temperature) appearance temperatures by in situ viscosimetry and Raman spectroscopy experiments allowed us to propose a transformation scenario during melt cooling. These processes and the nature of the crystalline phases formed (CaMoO 4 , Na 2 MoO 4 ) that depend on the evolution of MoO 3 , CaO and B 2 O 3 contents were correlated with changes of sodium and calcium cations proportions in the

  20. Fisher information at the edge of chaos in random Boolean networks.

    Science.gov (United States)

    Wang, X Rosalind; Lizier, Joseph T; Prokopenko, Mikhail

    2011-01-01

    We study the order-chaos phase transition in random Boolean networks (RBNs), which have been used as models of gene regulatory networks. In particular we seek to characterize the phase diagram in information-theoretic terms, focusing on the effect of the control parameters (activity level and connectivity). Fisher information, which measures how much system dynamics can reveal about the control parameters, offers a natural interpretation of the phase diagram in RBNs. We report that this measure is maximized near the order-chaos phase transitions in RBNs, since this is the region where the system is most sensitive to its parameters. Furthermore, we use this study of RBNs to clarify the relationship between Shannon and Fisher information measures.

  1. Reliable prediction of heat transfer coefficient in three-phase bubble column reactor via adaptive neuro-fuzzy inference system and regularization network

    Science.gov (United States)

    Garmroodi Asil, A.; Nakhaei Pour, A.; Mirzaei, Sh.

    2018-04-01

    In the present article, generalization performances of regularization network (RN) and optimize adaptive neuro-fuzzy inference system (ANFIS) are compared with a conventional software for prediction of heat transfer coefficient (HTC) as a function of superficial gas velocity (5-25 cm/s) and solid fraction (0-40 wt%) at different axial and radial locations. The networks were trained by resorting several sets of experimental data collected from a specific system of air/hydrocarbon liquid phase/silica particle in a slurry bubble column reactor (SBCR). A special convection HTC measurement probe was manufactured and positioned in an axial distance of 40 and 130 cm above the sparger at center and near the wall of SBCR. The simulation results show that both in-house RN and optimized ANFIS due to powerful noise filtering capabilities provide superior performances compared to the conventional software of MATLAB ANFIS and ANN toolbox. For the case of 40 and 130 cm axial distance from center of sparger, at constant superficial gas velocity of 25 cm/s, adding 40 wt% silica particles to liquid phase leads to about 66% and 69% increasing in HTC respectively. The HTC in the column center for all the cases studied are about 9-14% larger than those near the wall region.

  2. Functional Cortical Network in Alpha Band Correlates with Social Bargaining

    Science.gov (United States)

    Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

    2014-01-01

    Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals’ alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts. PMID:25286240

  3. Do governance choices matter in health care networks?: an exploratory configuration study of health care networks

    Science.gov (United States)

    2013-01-01

    Background Health care networks are widely used and accepted as an organizational form that enables integrated care as well as dealing with complex matters in health care. However, research on the governance of health care networks lags behind. The research aim of our study is to explore the type and importance of governance structure and governance mechanisms for network effectiveness. Methods The study has a multiple case study design and covers 22 health care networks. Using a configuration view, combinations of network governance and other network characteristics were studied on the level of the network. Based on interview and questionnaire data, network characteristics were identified and patterns in the data looked for. Results Neither a dominant (or optimal) governance structure or mechanism nor a perfect fit among governance and other characteristics were revealed, but a number of characteristics that need further study might be related to effective networks such as the role of governmental agencies, legitimacy, and relational, hierarchical, and contractual governance mechanisms as complementary factors. Conclusions Although the results emphasize the situational character of network governance and effectiveness, they give practitioners in the health care sector indications of which factors might be more or less crucial for network effectiveness. PMID:23800334

  4. Telecommunications Network Plan

    International Nuclear Information System (INIS)

    1989-05-01

    The Office of Civilian Radioactive Waste Management (OCRWM) must, among other things, be equipped to readily produce, file, store, access, retrieve, and transfer a wide variety of technical and institutional data and information. The data and information regularly produced by members of the OCRWM Program supports, and will continue to support, a wide range of program activities. Some of the more important of these information communication-related activities include: supporting the preparation, submittal, and review of a license application to the Nuclear Regulatory Commission (NRC) to authorize the construction of a geologic repository; responding to requests for information from parties affected by and/or interested in the program; and providing evidence of compliance with all relevant Federal, State, local, and Indian Tribe regulations, statutes, and/or treaties. The OCRWM Telecommunications Network Plan (TNP) is intended to identify, as well as to present the current strategy for satisfying, the telecommunications requirements of the civilian radioactive waste management program. The TNP will set forth the plan for integrating OCRWM's information resources among major program sites. Specifically, this plan will introduce a telecommunications network designed to establish communication linkages across the program's Washington, DC; Chicago, Illinois; and Las Vegas, Nevada, sites. The linkages across these and associated sites will comprise Phase I of the proposed OCRWM telecommunications network. The second phase will focus on the modification and expansion of the Phase I network to fully accommodate access to the OCRWM Licensing Support System (LSS). The primary components of the proposed OCRWM telecommunications network include local area networks; extended local area networks; and remote extended (wide) area networks. 10 refs., 6 figs

  5. Molecular dynamics simulations of disordered materials from network glasses to phase-change memory alloys

    CERN Document Server

    Massobrio, Carlo; Bernasconi, Marco; Salmon, Philip S

    2015-01-01

    This book is a unique reference work in the area of atomic-scale simulation of glasses. For the first time, a highly selected panel of about 20 researchers provides, in a single book, their views, methodologies and applications on the use of molecular dynamics as a tool to describe glassy materials. The book covers a wide range of systems covering ""traditional"" network glasses, such as chalcogenides and oxides, as well as glasses for applications in the area of phase change materials. The novelty of this work is the interplay between molecular dynamics methods (both at the classical and firs

  6. Phase transitions in cooperative coinfections: Simulation results for networks and lattices

    Science.gov (United States)

    Grassberger, Peter; Chen, Li; Ghanbarnejad, Fakhteh; Cai, Weiran

    2016-04-01

    We study the spreading of two mutually cooperative diseases on different network topologies, and with two microscopic realizations, both of which are stochastic versions of a susceptible-infected-removed type model studied by us recently in mean field approximation. There it had been found that cooperativity can lead to first order transitions from spreading to extinction. However, due to the rapid mixing implied by the mean field assumption, first order transitions required nonzero initial densities of sick individuals. For the stochastic model studied here the results depend strongly on the underlying network. First order transitions are found when there are few short but many long loops: (i) No first order transitions exist on trees and on 2-d lattices with local contacts. (ii) They do exist on Erdős-Rényi (ER) networks, on d -dimensional lattices with d ≥4 , and on 2-d lattices with sufficiently long-ranged contacts. (iii) On 3-d lattices with local contacts the results depend on the microscopic details of the implementation. (iv) While single infected seeds can always lead to infinite epidemics on regular lattices, on ER networks one sometimes needs finite initial densities of infected nodes. (v) In all cases the first order transitions are actually "hybrid"; i.e., they display also power law scaling usually associated with second order transitions. On regular lattices, our model can also be interpreted as the growth of an interface due to cooperative attachment of two species of particles. Critically pinned interfaces in this model seem to be in different universality classes than standard critically pinned interfaces in models with forbidden overhangs. Finally, the detailed results mentioned above hold only when both diseases propagate along the same network of links. If they use different links, results can be rather different in detail, but are similar overall.

  7. Power factor improvement in three-phase networks with unbalanced inductive loads using the Roederstein ESTAmat RPR power factor controller

    Science.gov (United States)

    Diniş, C. M.; Cunţan, C. D.; Rob, R. O. S.; Popa, G. N.

    2018-01-01

    The paper presents the analysis of a power factor with capacitors banks, without series coils, used for improving power factor for a three-phase and single-phase inductive loads. In the experimental measurements, to improve the power factor, the Roederstein ESTAmat RPR power factor controller can command up to twelve capacitors banks, while experimenting using only six capacitors banks. Six delta capacitors banks with approximately equal reactive powers were used for experimentation. The experimental measurements were carried out with a three-phase power quality analyser which worked in three cases: a case without a controller with all capacitors banks permanently parallel connected with network, and two other cases with power factor controller (one with setting power factor at 0.92 and the other one at 1). When performing experiments with the power factor controller, a current transformer was used to measure the current on one phase (at a more charged or less loaded phase).

  8. A Three-Phase Microgrid Restoration Model Considering Unbalanced Operation of Distributed Generation

    International Nuclear Information System (INIS)

    Wang, Zeyu; Wang, Jianhui; Chen, Chen

    2016-01-01

    Recent severe outages highlight the urgency of improving grid resiliency in the U.S. Microgrid formation schemes are proposed to restore critical loads after outages occur. Most distribution networks have unbalanced configurations that are not represented in sufficient detail by single-phase models. This study provides a microgrid formation plan that adopts a three-phase network model to represent unbalanced distribution networks. The problem formulation has a quadratic objective function with mixed-integer linear constraints. The three-phase network model enables us to examine the three-phase power outputs of distributed generators (DGs), preventing unbalanced operation that might trip DGs. Because the DG unbalanced operation constraint is non-convex, an iterative process is presented that checks whether the unbalanced operation limits for DGs are satisfied after each iteration of optimization. We also develop a relatively conservative linear approximation on the unbalanced operation constraint to handle larger networks. Compared with the iterative solution process, the conservative linear approximation is able to accelerate the solution process at the cost of sacrificing optimality to a limited extent. Simulation in the IEEE 34 node and IEEE 123 test feeders indicate that the proposed method yields more practical microgrid formations results. In addition, this paper explores the coordinated operation of DGs and energy storage (ES) installations. The unbalanced three-phase outputs of ESs combined with the relatively balanced outputs of DGs could supply unbalanced loads. In conclusion, the case study also validates the DG-ES coordination.

  9. Optimal topology to minimizing congestion in connected communication complex network

    Science.gov (United States)

    Benyoussef, M.; Ez-Zahraouy, H.; Benyoussef, A.

    In this paper, a new model of the interdependent complex network is proposed, based on two assumptions that (i) the capacity of a node depends on its degree, and (ii) the traffic load depends on the distribution of the links in the network. Based on these assumptions, the presented model proposes a method of connection not based on the node having a higher degree but on the region containing hubs. It is found that the final network exhibits two kinds of degree distribution behavior, depending on the kind and the way of the connection. This study reveals a direct relation between network structure and traffic flow. It is found that pc the point of transition between the free flow and the congested phase depends on the network structure and the degree distribution. Moreover, this new model provides an improvement in the traffic compared to the results found in a single network. The same behavior of degree distribution found in a BA network and observed in the real world is obtained; except for this model, the transition point between the free phase and congested phase is much higher than the one observed in a network of BA, for both static and dynamic protocols.

  10. Theta phase precession and phase selectivity: a cognitive device description of neural coding

    Science.gov (United States)

    Zalay, Osbert C.; Bardakjian, Berj L.

    2009-06-01

    Information in neural systems is carried by way of phase and rate codes. Neuronal signals are processed through transformative biophysical mechanisms at the cellular and network levels. Neural coding transformations can be represented mathematically in a device called the cognitive rhythm generator (CRG). Incoming signals to the CRG are parsed through a bank of neuronal modes that orchestrate proportional, integrative and derivative transformations associated with neural coding. Mode outputs are then mixed through static nonlinearities to encode (spatio) temporal phase relationships. The static nonlinear outputs feed and modulate a ring device (limit cycle) encoding output dynamics. Small coupled CRG networks were created to investigate coding functionality associated with neuronal phase preference and theta precession in the hippocampus. Phase selectivity was found to be dependent on mode shape and polarity, while phase precession was a product of modal mixing (i.e. changes in the relative contribution or amplitude of mode outputs resulted in shifting phase preference). Nonlinear system identification was implemented to help validate the model and explain response characteristics associated with modal mixing; in particular, principal dynamic modes experimentally derived from a hippocampal neuron were inserted into a CRG and the neuron's dynamic response was successfully cloned. From our results, small CRG networks possessing disynaptic feedforward inhibition in combination with feedforward excitation exhibited frequency-dependent inhibitory-to-excitatory and excitatory-to-inhibitory transitions that were similar to transitions seen in a single CRG with quadratic modal mixing. This suggests nonlinear modal mixing to be a coding manifestation of the effect of network connectivity in shaping system dynamic behavior. We hypothesize that circuits containing disynaptic feedforward inhibition in the nervous system may be candidates for interpreting upstream rate codes to

  11. Study on the methodology for hydrogeological site descriptive modelling by discrete fracture networks

    International Nuclear Information System (INIS)

    Tanaka, Tatsuya; Ando, Kenichi; Hashimoto, Shuuji; Saegusa, Hiromitsu; Takeuchi, Shinji; Amano, Kenji

    2007-01-01

    This study aims to establish comprehensive techniques for site descriptive modelling considering the hydraulic heterogeneity due to the Water Conducting Features in fractured rocks. The WCFs was defined by the interpretation and integration of geological and hydrogeological data obtained from the deep borehole investigation campaign in the Mizunami URL project and Regional Hydrogeological Study. As a result of surface based investigation phase, the block-scale hydrogeological descriptive model was generated using hydraulic discrete fracture networks. Uncertainties and remaining issues associated with the assumption in interpreting the data and its modelling were addressed in a systematic way. (author)

  12. International network non-energy use and CO2 emissions (NEU-CO2). An activity within the European Commission's ENRICH programme, DG RTD, 'Environment and Climate'. Final report of the first phase of the network (January 1999 - June 2000)

    International Nuclear Information System (INIS)

    Patel, M.; Gielen, D.; Kilde, N.; Simmons, T.

    2000-07-01

    This report concludes the first phase of the NEU-CO 2 network, covering the period from January 1999 to June 2000. Within this period, two workshops were held, one in Paris in September 1999 and the other in Brussels in April 2000. The results of these workshops represent the basis of this report. The workshop papers have also been compiled in workshop proceedings which are publicly available. Due to the success of the NEU-CO 2 network, the partners decided to apply for the continuation of this activity which was recently accepted by the European Commission. The second phase of the of the NEU-CO 2 network will start in Fall 2000 and will continue for 18 months. This will allow the NEU-CO 2 network to improve the methods applied, to close data gaps, to check the preliminary conclusions given in this report and to provide consolidated results and recommendations by mid 2002. The ultimate goal of the NEU-CO 2 network is to contribute to an improvement of the IPCC guidelines in the area of non-energy use and to provide inventorists with tools and methods to estimate more accurately non-energy CO 2 emissions. (orig.)

  13. Equivariant bifurcation in a coupled complex-valued neural network rings

    International Nuclear Information System (INIS)

    Zhang, Chunrui; Sui, Zhenzhang; Li, Hongpeng

    2017-01-01

    Highlights: • Complex value Hopfield-type network with Z4 × Z2 symmetry is discussed. • The spatio-temporal patterns of bifurcating periodic oscillations are obtained. • The oscillations can be in phase or anti-phase depending on the parameters and delay. - Abstract: Network with interacting loops and time delays are common in physiological systems. In the past few years, the dynamic behaviors of coupled interacting loops neural networks have been widely studied due to their extensive applications in classification of pattern recognition, signal processing, image processing, engineering optimization and animal locomotion, and other areas, see the references therein. In a large amount of applications, complex signals often occur and the complex-valued recurrent neural networks are preferable. In this paper, we study a complex value Hopfield-type network that consists of a pair of one-way rings each with four neurons and two-way coupling between each ring. We discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. The existence of multiple branches of bifurcating periodic solution is obtained. We also found that the spatio-temporal patterns of bifurcating periodic oscillations alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural network oscillators. The oscillations of corresponding neurons in the two loops can be in phase or anti-phase depending on the parameters and delay. Some numerical simulations support our analysis results.

  14. Life cycle assessment of second generation (2G) and third generation (3G) mobile phone networks.

    Science.gov (United States)

    Scharnhorst, Wolfram; Hilty, Lorenz M; Jolliet, Olivier

    2006-07-01

    The environmental performance of presently operated GSM and UMTS networks was analysed concentrating on the environmental effects of the End-of-Life (EOL) phase using the Life Cycle Assessment (LCA) method. The study was performed based on comprehensive life cycle inventory and life cycle modelling. The environmental effects were quantified using the IMPACT2002+ method. Based on technological forecasts, the environmental effects of forthcoming mobile telephone networks were approximated. The results indicate that a parallel operation of GSM and UMTS networks is environmentally detrimental and the transition phase should be kept as short as possible. The use phase (i.e. the operation) of the radio network components account for a large fraction of the total environmental impact. In particular, there is a need to lower the energy consumption of those network components. Seen in relation to each other, UMTS networks provide an environmentally more efficient mobile communication technology than GSM networks. In assessing the EOL phase, recycling the electronic scrap of mobile phone networks was shown to have clear environmental benefits. Under the present conditions, material recycling could help lower the environmental impact of the production phase by up to 50%.

  15. Artificial neural network modelling of retention of pesticides in various octadecylsiloxane-bonded reversed-phase columns and water-acetonitrile mobile phase

    Energy Technology Data Exchange (ETDEWEB)

    D' Archivio, Angelo Antonio, E-mail: angeloantonio.darchivio@univaq.it [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy); Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio [Dipartimento di Chimica, Ingegneria Chimica e Materiali, Universita degli Studi di L' Aquila, Via Vetoio, 67010 Coppito, L' Aquila (Italy)

    2009-07-30

    Previously, retention of 26 pesticides in the reversed-phase column Gemini (Phenomenex) and water-acetonitrile mobile phase was modelled using a feed-forward artificial neural network (ANN) learned by error back-propagation, accounting for both the effect of solute structure and mobile phase composition. To this end, log K{sub ow} of solutes and four quantum chemical molecular descriptors (the dipole moment, the mean polarizability, the anisotropy of the polarizability and an hydrogen-bonding descriptor based on the atomic charges located on the acid and basic functional groups) and acetonitrile % (v/v) in the eluent (%ACN) were used as ANN inputs. The above ANN-based approach is here tested on further five similar octadecylsiloxane-bonded columns in water-acetonitrile mobile phase within the %ACN range 30-70%. A quite good predictive performance evaluated on three external solutes in the whole %ACN range is observed, prediction errors being lower than {+-}0.1 log k units or slightly higher although still within {+-}0.15 log k units. On the other hand, multilinear regression used in place of ANN provides a more diffuse and non-uniform residual distribution for all the investigated columns. ANN multiple-column retention prediction is attempted by adding to the above variables a column descriptor defined as the average retention of calibration solutes extrapolated to 100% water. This more general model is built using 16 solutes and five 5-{mu}m columns in calibration, while its predictive performance is tested on the remaining 10 compounds. Under these conditions, prediction errors are generally within {+-}0.2 log k units regardless of the kind of column. The possibility of cross-column prediction is evaluated by column leave-one-out cross-validation within the five 5-{mu}m stationary phases and on a 4-{mu}m external column. This analysis reveals that accuracy of retention prediction for unknown solutes in unknown columns is acceptable provided that the external

  16. Artificial neural network modelling of retention of pesticides in various octadecylsiloxane-bonded reversed-phase columns and water-acetonitrile mobile phase

    International Nuclear Information System (INIS)

    D'Archivio, Angelo Antonio; Maggi, Maria Anna; Mazzeo, Pietro; Ruggieri, Fabrizio

    2009-01-01

    Previously, retention of 26 pesticides in the reversed-phase column Gemini (Phenomenex) and water-acetonitrile mobile phase was modelled using a feed-forward artificial neural network (ANN) learned by error back-propagation, accounting for both the effect of solute structure and mobile phase composition. To this end, log K ow of solutes and four quantum chemical molecular descriptors (the dipole moment, the mean polarizability, the anisotropy of the polarizability and an hydrogen-bonding descriptor based on the atomic charges located on the acid and basic functional groups) and acetonitrile % (v/v) in the eluent (%ACN) were used as ANN inputs. The above ANN-based approach is here tested on further five similar octadecylsiloxane-bonded columns in water-acetonitrile mobile phase within the %ACN range 30-70%. A quite good predictive performance evaluated on three external solutes in the whole %ACN range is observed, prediction errors being lower than ±0.1 log k units or slightly higher although still within ±0.15 log k units. On the other hand, multilinear regression used in place of ANN provides a more diffuse and non-uniform residual distribution for all the investigated columns. ANN multiple-column retention prediction is attempted by adding to the above variables a column descriptor defined as the average retention of calibration solutes extrapolated to 100% water. This more general model is built using 16 solutes and five 5-μm columns in calibration, while its predictive performance is tested on the remaining 10 compounds. Under these conditions, prediction errors are generally within ±0.2 log k units regardless of the kind of column. The possibility of cross-column prediction is evaluated by column leave-one-out cross-validation within the five 5-μm stationary phases and on a 4-μm external column. This analysis reveals that accuracy of retention prediction for unknown solutes in unknown columns is acceptable provided that the external column is not very

  17. Youth's social network structures and peer influences: Study protocol MyMovez project - Phase I

    NARCIS (Netherlands)

    Bevelander, K.E.; Smit, C.R.; Woudenberg, T.J. van; Buijs, L.B.; Burk, W.J.; Buijzen, M.A.

    2018-01-01

    Background: Youth are an important target group for social network interventions, because they are particularly susceptible to the adaptation of healthy and unhealthy habits and behaviors of others. They are surrounded by 'social influence agents' (i.e., role models such as family, friends and

  18. WDM Phase-Modulated Millimeter-Wave Fiber Systems

    DEFF Research Database (Denmark)

    Yu, Xianbin; Prince, Kamau; Gibbon, Timothy Braidwood

    2012-01-01

    This chapter presents a computer simulation case study of two typical WDM phase-modulated millimeter-wave systems. The phase-modulated 60 GHz fiber multi-channel transmission systems employ single sideband (SSB) and double sideband subcarrier modulation (DSB-SC) schemes and present one of the lat......This chapter presents a computer simulation case study of two typical WDM phase-modulated millimeter-wave systems. The phase-modulated 60 GHz fiber multi-channel transmission systems employ single sideband (SSB) and double sideband subcarrier modulation (DSB-SC) schemes and present one...... of the latest research efforts in the rapidly emerging Radio-over-Fiber (RoF) application space for in-house access networks....

  19. 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.

  20. Scalable Lunar Surface Networks and Adaptive Orbit Access, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Innovative network architecture, protocols, and algorithms are proposed for both lunar surface networks and orbit access networks. Firstly, an overlaying...

  1. TELEVISION AND THE CONTINUING EDUCATION OF TEACHERS, A FEASIBILITY STUDY OF THE POTENTIAL OF NETWORK TELEVISION FOR DISSEMINATION OF EDUCATIONAL RESEARCH INFORMATION. FINAL REPORT.

    Science.gov (United States)

    CRESHKOFF, LAWRENCE

    THIS 3-PHASE STUDY SOUGHT TO BRIDGE THE GAP BETWEEN THE PRODUCER OF NEW EDUCATIONAL IDEAS AND THE PRACTITIONER, OR TEACHER, BY EFFECTIVE USE OF NETWORK TELEVISION. PHASE I, DATA GATHERING, INCLUDED REVIEW OF THE LITERATURE, AND IDENTIFICATION OF INNOVATIONAL PROJECTS BY CONSULTATION, FIELD VISITS, AND A QUESTIONNAIRE SENT TO MEMBERS OF 2 NATIONAL…

  2. Internet and social network recruitment: two case studies.

    Science.gov (United States)

    Johnson, Kathy A; Peace, Jane

    2012-01-01

    The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that the relationship with the source of the research and the purpose of the engaged social network should be a consideration in Internet or social network recruitment strategies.

  3. Routing strategies in traffic network and phase transition in network ...

    Indian Academy of Sciences (India)

    The dynamics of information traffic over scale-free networks has been investigated systematically. A series of routing strategies of data packets have been proposed, including the local routing strategy, the next-nearest-neighbour routing strategy, and the mixed routing strategy based on local static and dynamic information.

  4. A computational study of the effect of capillary network anastomoses and tortuosity on oxygen transport.

    Science.gov (United States)

    Goldman, D; Popel, A S

    2000-09-21

    The objective of this study was to investigate the effects of capillary network anastomoses and tortuosity on oxygen transport in skeletal muscle, as well as the importance of muscle fibers in determining the arrangement of parallel capillaries. Countercurrent flow and random capillary blockage (e.g. by white blood cells) were also studied. A general computational model was constructed to simulate oxygen transport from a network of blood vessels within a rectangular volume of tissue. A geometric model of the capillary network structure, based on hexagonally packed muscle fibers, was constructed to produce networks of straight unbranched capillaries, capillaries with anastomoses, and capillaries with tortuosity, in order to examine the effects of these geometric properties. Quantities examined included the tissue oxygen tension and the capillary oxyhemoglobin saturation. The computational model included a two-phase simulation of blood flow. Appropriate parameters were chosen for working hamster cheek-pouch retractor muscle. Our calculations showed that the muscle-fiber geometry was important in reducing oxygen transport heterogeneity, as was countercurrent flow. Tortuosity was found to increase tissue oxygenation, especially when combined with anastomoses. In the absence of tortuosity, anastomoses had little effect on oxygen transport under normal conditions, but significantly improved transport when vessel blockages were present. Copyright 2000 Academic Press.

  5. Route planning with transportation network maps: an eye-tracking study.

    Science.gov (United States)

    Grison, Elise; Gyselinck, Valérie; Burkhardt, Jean-Marie; Wiener, Jan Malte

    2017-09-01

    Planning routes using transportation network maps is a common task that has received little attention in the literature. Here, we present a novel eye-tracking paradigm to investigate psychological processes and mechanisms involved in such a route planning. In the experiment, participants were first presented with an origin and destination pair before we presented them with fictitious public transportation maps. Their task was to find the connecting route that required the minimum number of transfers. Based on participants' gaze behaviour, each trial was split into two phases: (1) the search for origin and destination phase, i.e., the initial phase of the trial until participants gazed at both origin and destination at least once and (2) the route planning and selection phase. Comparisons of other eye-tracking measures between these phases and the time to complete them, which depended on the complexity of the planning task, suggest that these two phases are indeed distinct and supported by different cognitive processes. For example, participants spent more time attending the centre of the map during the initial search phase, before directing their attention to connecting stations, where transitions between lines were possible. Our results provide novel insights into the psychological processes involved in route planning from maps. The findings are discussed in relation to the current theories of route planning.

  6. A Unified Network Security Architecture for Large, Distributed Networks, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — In typical, multi-organizational networking environments, it is difficult to define and maintain a uniform authentication scheme that provides users with easy access...

  7. Length-Scale-Dependent Phase Transformation of LiFePO4 : An In situ and Operando Study Using Micro-Raman Spectroscopy and XRD.

    Science.gov (United States)

    Siddique, N A; Salehi, Amir; Wei, Zi; Liu, Dong; Sajjad, Syed D; Liu, Fuqiang

    2015-08-03

    The charge and discharge of lithium ion batteries are often accompanied by electrochemically driven phase-transformation processes. In this work, two in situ and operando methods, that is, micro-Raman spectroscopy and X-ray diffraction (XRD), have been combined to study the phase-transformation process in LiFePO4 at two distinct length scales, namely, particle-level scale (∼1 μm) and macroscopic scale (∼several cm). In situ Raman studies revealed a discrete mode of phase transformation at the particle level. Besides, the preferred electrochemical transport network, particularly the carbon content, was found to govern the sequence of phase transformation among particles. In contrast, at the macroscopic level, studies conducted at four different discharge rates showed a continuous but delayed phase transformation. These findings uncovered the intricate phase transformation in LiFePO4 and potentially offer valuable insights into optimizing the length-scale-dependent properties of battery materials. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. The study of diffusion mechanism in network-forming liquid: Silica liquid

    Directory of Open Access Journals (Sweden)

    P. K. Hung

    2016-12-01

    Full Text Available Molecular dynamics simulation is employed to investigate the diffusion mechanism in silica melt, a typical network-forming liquid. From the analysis of SiOx→SiOx±1 and OSiy→OSiy±1 reactions we reveal two moving modes: fast hopping and slow collective moving. Accordingly the atoms diffuse in the melt by simple hopping or through displacing of super-molecule (SM. A cluster analysis is performed for several of atom sets. It is shown that the melt exhibits non-uniform spatial distribution of reaction which causes the dynamics heterogeneity (DH. Further, the network structure of the melt consists of main subnet and large defective subnets. These subnets differ strongly in local environment, chemical composition and atomic density. This result evidences two distinct phases, the structure heterogeneity in silica melt and supports the polymorphism of network-forming liquid. We also find out that the node transformation spreads non-uniformly through the network structure. It takes place mainly in large defective subnet. The strong localization of node transformation is responsible for dynamical slowdown.

  9. Shear-induced network-to-network transition in a block copolymer melt

    International Nuclear Information System (INIS)

    Cochran, Eric W.; Bates, Frank S.

    2004-01-01

    A tricontinuous (10,3)c network phase is documented in a poly(cyclohexylethylene-b-ethylethylene-b-ethylene) triblock copolymer melt based on small-angle x-ray scattering. Application of shear transforms the self-assembled soft material into a single crystal (10,3)d network while preserving the short-range threefold connector geometry. Long-range topological restructuring reduces the space group symmetry, from Fddd to Pnna, maintaining orthorhombic lattice symmetry. Both phases are stable to long time annealing, indicative of nearly degenerate free energies and prohibitive kinetic barriers

  10. A Multi-site, Two-Phase, Prescription Opioid Addiction Treatment Study (POATS): Rationale, Design, and Methodology

    Science.gov (United States)

    Weiss, Roger D.; Potter, Jennifer Sharpe; Provost, Scott E.; Huang, Zhen; Jacobs, Petra; Hasson, Albert; Lindblad, Robert; Connery, Hilary Smith; Prather, Kristi; Ling, Walter

    2010-01-01

    The National Institute on Drug Abuse Clinical Trials Network launched the Prescription Opioid Addiction Treatment Study (POATS) in response to rising rates of prescription opioid dependence and gaps in understanding the optimal course of treatment for this population. POATS employed a multi-site, two-phase adaptive, sequential treatment design to approximate clinical practice. The study took place at 10 community treatment programs around the United States. Participants included men and women age ≥18 who met Diagnostic and Statistical Manual, 4th Edition criteria for dependence upon prescription opioids, with physiologic features; those with a prominent history of heroin use (according to pre-specified criteria) were excluded. All participants received buprenorphine/naloxone (bup/nx). Phase 1 consisted of 4 weeks of bup/nx treatment, including a 14-day dose taper, with 8 weeks of follow-up. Phase 1 participants were monitored for treatment response during these 12 weeks. Those who relapsed to opioid use, as defined by pre-specified criteria, were invited to enter Phase 2; Phase 2 consisted of 12 weeks of bup/nx stabilization treatment, followed by a 4-week taper and 8 weeks of post-treatment follow-up. Participants were randomized at the beginning of Phase 1 to receive bup/nx, paired with either Standard Medical Management (SMM) or Enhanced Medical Management (EMM; defined as SMM plus individual drug counseling). Eligible participants entering Phase 2 were re-randomized to either EMM or SMM. POATS was developed to determine what benefit, if any, EMM offers over SMM in short-term and longer-term treatment paradigm. This paper describes the rationale and design of the study. PMID:20116457

  11. Functional and Structural Network Recovery after Mild Traumatic Brain Injury: A 1-Year Longitudinal Study

    Directory of Open Access Journals (Sweden)

    Patrizia Dall’Acqua

    2017-05-01

    Full Text Available Brain connectivity after mild traumatic brain injury (mTBI has not been investigated longitudinally with respect to both functional and structural networks together within the same patients, crucial to capture the multifaceted neuropathology of the injury and to comprehensively monitor the course of recovery and compensatory reorganizations at macro-level. We performed a prospective study with 49 mTBI patients at an average of 5 days and 1 year post-injury and 49 healthy controls. Neuropsychological assessments as well as resting-state functional and diffusion-weighted magnetic resonance imaging were obtained. Functional and structural connectome analyses were performed using network-based statistics. They included a cross-sectional group comparison and a longitudinal analysis with the factors group and time. The latter tracked the subnetworks altered at the early phase and, in addition, included a whole-brain group × time interaction analysis. Finally, we explored associations between the evolution of connectivity and changes in cognitive performance. The early phase of mTBI was characterized by a functional hypoconnectivity in a subnetwork with a large overlap of regions involved within the classical default mode network. In addition, structural hyperconnectivity in a subnetwork including central hub areas such as the cingulate cortex was found. The impaired functional and structural subnetworks were strongly correlated and revealed a large anatomical overlap. One year after trauma and compared to healthy controls we observed a partial normalization of both subnetworks along with a considerable compensation of functional and structural connectivity subsequent to the acute phase. Connectivity changes over time were correlated with improvements in working memory, divided attention, and verbal recall. Neuroplasticity-induced recovery or compensatory processes following mTBI differ between brain regions with respect to their time course and are

  12. Influence of Chirality in Ordered Block Copolymer Phases

    Science.gov (United States)

    Prasad, Ishan; Grason, Gregory

    2015-03-01

    Block copolymers are known to assemble into rich spectrum of ordered phases, with many complex phases driven by asymmetry in copolymer architecture. Despite decades of study, the influence of intrinsic chirality on equilibrium mesophase assembly of block copolymers is not well understood and largely unexplored. Self-consistent field theory has played a major role in prediction of physical properties of polymeric systems. Only recently, a polar orientational self-consistent field (oSCF) approach was adopted to model chiral BCP having a thermodynamic preference for cholesteric ordering in chiral segments. We implement oSCF theory for chiral nematic copolymers, where segment orientations are characterized by quadrupolar chiral interactions, and focus our study on the thermodynamic stability of bi-continuous network morphologies, and the transfer of molecular chirality to mesoscale chirality of networks. Unique photonic properties observed in butterfly wings have been attributed to presence of chiral single-gyroid networks, this has made it an attractive target for chiral metamaterial design.

  13. Study of SmS properties in the low pressure phase (black phase)

    International Nuclear Information System (INIS)

    Bordier, G.

    1986-01-01

    SmS was studied for the transition from low pressure phase (black phase) to high pressure phase with an intermediate valence. But the study of the black phase is very rich. The variations of electron transport properties with pressure at low temperature show a semi-metal phase located, in the pressure-temperature diagram in the black phase for pressure over 4 kbars, corresponding to the phase B'of the doping-temperature diagram. Electron spin resonance shows a lack of sulfur and nearby this defect a samarium ion, magnetically coupled with the matrix, presents a divalent trivalent transition. Resonance lines are broadened with temperature. Conductivity relaxations occur at low pressure and low temperature by trapping a conduction electron, by magnetic exchange giving a bounded magnetic polaron. The relaxation time at null magnetic field is activated. An approximation of trapping barrier and critical field corresponding the maximum magnetoresistance is given by a model [fr

  14. 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.

  15. Centrifuge workers study. Phase II, completion report

    International Nuclear Information System (INIS)

    Wooten, H.D.

    1994-09-01

    Phase II of the Centrifuge Workers Study was a follow-up to the Phase I efforts. The Phase I results had indicated a higher risk than expected among centrifuge workers for developing bladder cancer when compared with the risk in the general population for developing this same type of cancer. However, no specific agent could be identified as the causative agent for these bladder cancers. As the Phase II Report states, Phase I had been limited to workers who had the greatest potential for exposure to substances used in the centrifuge process. Phase II was designed to expand the survey to evaluate the health of all employees who had ever worked in Centrifuge Program Departments 1330-1339 but who had not been interviewed in Phase I. Employees in analytical laboratories and maintenance departments who provided support services for the Centrifuge Program were also included in Phase II. In December 1989, the Oak Ridge Associated Universities (ORAU), now known as Oak Ridge Institute for Science and Education (ORISE), was contracted to conduct a follow-up study (Phase II). Phase H of the Centrifuge Workers Study expanded the survey to include all former centrifuge workers who were not included in Phase I. ORISE was chosen because they had performed the Phase I tasks and summarized the corresponding survey data therefrom

  16. Centrifuge workers study. Phase II, completion report

    Energy Technology Data Exchange (ETDEWEB)

    Wooten, H.D.

    1994-09-01

    Phase II of the Centrifuge Workers Study was a follow-up to the Phase I efforts. The Phase I results had indicated a higher risk than expected among centrifuge workers for developing bladder cancer when compared with the risk in the general population for developing this same type of cancer. However, no specific agent could be identified as the causative agent for these bladder cancers. As the Phase II Report states, Phase I had been limited to workers who had the greatest potential for exposure to substances used in the centrifuge process. Phase II was designed to expand the survey to evaluate the health of all employees who had ever worked in Centrifuge Program Departments 1330-1339 but who had not been interviewed in Phase I. Employees in analytical laboratories and maintenance departments who provided support services for the Centrifuge Program were also included in Phase II. In December 1989, the Oak Ridge Associated Universities (ORAU), now known as Oak Ridge Institute for Science and Education (ORISE), was contracted to conduct a follow-up study (Phase II). Phase H of the Centrifuge Workers Study expanded the survey to include all former centrifuge workers who were not included in Phase I. ORISE was chosen because they had performed the Phase I tasks and summarized the corresponding survey data therefrom.

  17. Quarantine-generated phase transition in epidemic spreading

    Science.gov (United States)

    Lagorio, C.; Dickison, M.; Vazquez, F.; Braunstein, L. A.; Macri, P. A.; Migueles, M. V.; Havlin, S.; Stanley, H. E.

    2011-02-01

    We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold wc separating a phase (wspread out. We find that in our model the topology of the network strongly affects the size of the propagation and that wc increases with the mean degree and heterogeneity of the network. We also find that wc is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes.

  18. Networking and Information Technology Workforce Study: Final Report

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — This report presents the results of a study of the global Networking and Information Technology NIT workforce undertaken for the Networking and Information...

  19. Dynamic reconfiguration of human brain functional networks through neurofeedback.

    Science.gov (United States)

    Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

    2013-11-01

    Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. Performance Enhancement of Optical CDMA by Differential-Phase Method for Radio-over-Fiber Transmissions

    Directory of Open Access Journals (Sweden)

    Hsu-Chih Cheng

    2013-01-01

    Full Text Available The study proposes the differential-phase optical code-division multiple-access (OCDMA network for radio-over-fiber (RoF transmissions, and the characteristics are numerically analyzed. The network coder/decoders (codecs are structured on the basis of arrayed-waveguide-grating (AWG routers with complementary Walsh-Hadamard (CWH signature codes. In the proposed system, the network requires only two AWG routers to accomplish spectral encoding of radio base station (RBS and decoding of control station for the complementary keying, thus resulting in a simpler and low cost system. Performance analyses are evaluated with the dominant noise of phase-induced intensity noise (PIIN in spectral code OCDMA network. By the proposed AWG-based OCDMA with the differential-phase scheme, it is possible to establish interference-free and low crosstalk beat noise RoF systems.

  1. SANS from interpenetrating polymer networks

    International Nuclear Information System (INIS)

    Markotsis, M.G.; Burford, R.P.; Knott, R.B.; Australian Nuclear Science and Technology Organisation, Menai, NSW; Hanley, T.L.; CRC for Polymers,; Australian Nuclear Science and Technology Organisation, Menai, NSW; Papamanuel, N.

    2003-01-01

    Full text: Interpenetrating polymer networks (IPNs) have been formed by combining two polymeric systems in order to gain enhanced material properties. IPNs are a combination of two or more polymers in network form with one network polymerised and/or crosslinked in the immediate presence of the other(s).1 IPNs allow better blending of two or more crosslinked networks. In this study two sets of IPNs were produced and their microstructure studied using a variety of techniques including small angle neutron scattering (SANS). The first system combined a glassy polymer (polystyrene) with an elastomeric polymer (SBS) with the glassy polymer predominating, to give a high impact plastic. The second set of IPNs contained epichlorohydrin (CO) and nitrile rubber (NBR), and was formed in order to produce novel materials with enhanced chemical and gas barrier properties. In both cases if the phase mixing is optimised the probability of controlled morphologies and synergistic behaviour is increased. The PS/SBS IPNs were prepared using sequential polymerisation. The primary SBS network was thermally crosslinked, then the polystyrene network was polymerised and crosslinked using gamma irradiation to avoid possible thermal degradation of the butadiene segment of the SBS. Tough transparent systems were produced with no apparent thermal degradation of the polybutadiene segments. The epichlorohydrin/nitrile rubber IPNs were formed by simultaneous thermal crosslinking reactions. The epichlorohydrin network was formed using lead based crosslinker, while the nitrile rubber was crosslinked by peroxide methods. The use of two different crosslinking systems was employed in order to achieve independent crosslinking thus resulting in an IPN with minimal grafting between the component networks. SANS, Transmission electron microscopy (TEM), and atomic force microscopy (AFM) were used to examine the size and shape of the phase domains and investigate any variation with crosslinking level and

  2. CCNA Cisco Certified Network Associate Study Guide

    CERN Document Server

    Lammle, Todd

    2011-01-01

    Learn from the Best - Cisco Networking Authority Todd LammleWritten by Cisco networking authority Todd Lammle, this comprehensive guide has been completely updated to reflect the latest CCNA 640-802 exam. Todd's straightforward style provides lively examples, hands on and written labs, easy-to-understand analogies, and real-world scenarios that will not only help you prepare for the exam, but also give you a solid foundation as a Cisco networking professional.This Study Guide teaches you how toDescribe how a network worksConfigure, verify and troubleshoot a switch with VLANs and interswitch co

  3. An empirical study of an agglomeration network

    International Nuclear Information System (INIS)

    Zhang, Yichao; Zhang, Zhaochun; Guan, Jihong

    2007-01-01

    Recently, researchers have reported many models mimicking real network evolution growth, among which some are based on network aggregation growth. However, until now, relatively few experiments have been reported. Accordingly, in this paper, photomicrographs of real materials (the agglomeration in the filtrate of slurry formed by a GaP-nanoparticle conglomerate dispersed in water) are analyzed within the framework of complex network theory. By data mapping from photomicrographs we generate undirected networks and as a definition of degree we adopt the number of pixel's nearest neighbors while adjacent pixels define a connection or an edge. We study the topological structure of these networks including degree distribution, clustering coefficient and average path length. In addition, we discuss the self-similarity and synchronizability of the networks. We find that the synchronizability of high-concentration agglomeration is better than that of low-concentration agglomeration; we also find that agglomeration networks possess good self-similar features

  4. Associative memory in an analog iterated-map neural network

    Science.gov (United States)

    Marcus, C. M.; Waugh, F. R.; Westervelt, R. M.

    1990-03-01

    The behavior of an analog neural network with parallel dynamics is studied analytically and numerically for two associative-memory learning algorithms, the Hebb rule and the pseudoinverse rule. Phase diagrams in the parameter space of analog gain β and storage ratio α are presented. For both learning rules, the networks have large ``recall'' phases in which retrieval states exist and convergence to a fixed point is guaranteed by a global stability criterion. We also demonstrate numerically that using a reduced analog gain increases the probability of recall starting from a random initial state. This phenomenon is comparable to thermal annealing used to escape local minima but has the advantage of being deterministic, and therefore easily implemented in electronic hardware. Similarities and differences between analog neural networks and networks with two-state neurons at finite temperature are also discussed.

  5. Results from a model system of superconducting solenoids and phase shifting bridge for pulsed power studies for proposed tokamak EF coils

    International Nuclear Information System (INIS)

    Fuja, R.E.; Kustom, R.L.; Smith, R.P.

    1977-01-01

    A matched pair of superconducting solenoids and a phase-shifting bridge circuit has been constructed to study energy storage and transfer for application to tokamak EF coils. The intrinsically stable solenoids, each with 4 H self-inductance, incorporate sufficient cooling to allow charging at several hundred volts, corresponding to B = 1 T/sec. The three-phase inductor-convertor capacitive bridge network operating at up to 150 V rms transfers energy reversibly and at controllable rates from the storage coil to the load coil

  6. A Probabilistic Model of the LMAC Protocol for Concurrent Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Esparza, Luz Judith R; Zeng, Kebin; Nielsen, Bo Friis

    2011-01-01

    We present a probabilistic model for the network setup phase of the Lightweight Medium Access Protocol (LMAC) for concurrent Wireless Sensor Networks. In the network setup phase, time slots are allocated to the individual sensors through resolution of successive collisions. The setup phase...

  7. Tunable photonic crystals with partial bandgaps from blue phase colloidal crystals and dielectric-doped blue phases.

    Science.gov (United States)

    Stimulak, Mitja; Ravnik, Miha

    2014-09-07

    Blue phase colloidal crystals and dielectric nanoparticle/polymer doped blue phases are demonstrated to combine multiple components with different symmetries in one photonic material, creating a photonic crystal with variable and micro-controllable photonic band structure. In this composite photonic material, one contribution to the band structure is determined by the 3D periodic birefringent orientational profile of the blue phases, whereas the second contribution emerges from the regular array of the colloidal particles or from the dielectric/nanoparticle-doped defect network. Using the planewave expansion method, optical photonic bands of the blue phase I and II colloidal crystals and related nanoparticle/polymer doped blue phases are calculated, and then compared to blue phases with no particles and to face-centred-cubic and body-centred-cubic colloidal crystals in isotropic background. We find opening of local band gaps at particular points of Brillouin zone for blue phase colloidal crystals, where there were none in blue phases without particles or dopants. Particle size and filling fraction of the blue phase defect network are demonstrated as parameters that can directly tune the optical bands and local band gaps. In the blue phase I colloidal crystal with an additionally doped defect network, interestingly, we find an indirect total band gap (with the exception of one point) at the entire edge of SC irreducible zone. Finally, this work demonstrates the role of combining multiple - by symmetry - differently organised components in one photonic crystal material, which offers a novel approach towards tunable soft matter photonic materials.

  8. Flexible and re-configurable optical three-input XOR logic gate of phase-modulated signals with multicast functionality for potential application in optical physical-layer network coding.

    Science.gov (United States)

    Lu, Guo-Wei; Qin, Jun; Wang, Hongxiang; Ji, XuYuefeng; Sharif, Gazi Mohammad; Yamaguchi, Shigeru

    2016-02-08

    Optical logic gate, especially exclusive-or (XOR) gate, plays important role in accomplishing photonic computing and various network functionalities in future optical networks. On the other hand, optical multicast is another indispensable functionality to efficiently deliver information in optical networks. In this paper, for the first time, we propose and experimentally demonstrate a flexible optical three-input XOR gate scheme for multiple input phase-modulated signals with a 1-to-2 multicast functionality for each XOR operation using four-wave mixing (FWM) effect in single piece of highly-nonlinear fiber (HNLF). Through FWM in HNLF, all of the possible XOR operations among input signals could be simultaneously realized by sharing a single piece of HNLF. By selecting the obtained XOR components using a followed wavelength selective component, the number of XOR gates and the participant light in XOR operations could be flexibly configured. The re-configurability of the proposed XOR gate and the function integration of the optical logic gate and multicast in single device offer the flexibility in network design and improve the network efficiency. We experimentally demonstrate flexible 3-input XOR gate for four 10-Gbaud binary phase-shift keying signals with a multicast scale of 2. Error-free operations for the obtained XOR results are achieved. Potential application of the integrated XOR and multicast function in network coding is also discussed.

  9. CrowdPhase: crowdsourcing the phase problem

    International Nuclear Information System (INIS)

    Jorda, Julien; Sawaya, Michael R.; Yeates, Todd O.

    2014-01-01

    The idea of attacking the phase problem by crowdsourcing is introduced. Using an interactive, multi-player, web-based system, participants work simultaneously to select phase sets that correspond to better electron-density maps in order to solve low-resolution phasing problems. The human mind innately excels at some complex tasks that are difficult to solve using computers alone. For complex problems amenable to parallelization, strategies can be developed to exploit human intelligence in a collective form: such approaches are sometimes referred to as ‘crowdsourcing’. Here, a first attempt at a crowdsourced approach for low-resolution ab initio phasing in macromolecular crystallography is proposed. A collaborative online game named CrowdPhase was designed, which relies on a human-powered genetic algorithm, where players control the selection mechanism during the evolutionary process. The algorithm starts from a population of ‘individuals’, each with a random genetic makeup, in this case a map prepared from a random set of phases, and tries to cause the population to evolve towards individuals with better phases based on Darwinian survival of the fittest. Players apply their pattern-recognition capabilities to evaluate the electron-density maps generated from these sets of phases and to select the fittest individuals. A user-friendly interface, a training stage and a competitive scoring system foster a network of well trained players who can guide the genetic algorithm towards better solutions from generation to generation via gameplay. CrowdPhase was applied to two synthetic low-resolution phasing puzzles and it was shown that players could successfully obtain phase sets in the 30° phase error range and corresponding molecular envelopes showing agreement with the low-resolution models. The successful preliminary studies suggest that with further development the crowdsourcing approach could fill a gap in current crystallographic methods by making it

  10. CrowdPhase: crowdsourcing the phase problem

    Energy Technology Data Exchange (ETDEWEB)

    Jorda, Julien; Sawaya, Michael R. [Institute for Genomics and Proteomics, 611 Charles Young Drive East, Los Angeles, CA 90095 (United States); Yeates, Todd O., E-mail: yeates@mbi.ucla.edu [Institute for Genomics and Proteomics, 611 Charles Young Drive East, Los Angeles, CA 90095 (United States); Molecular Biology Institute, 611 Charles Young Drive East, Los Angeles, CA 90095 (United States); University of California, 611 Charles Young Drive East, Los Angeles, CA 90095 (United States)

    2014-06-01

    The idea of attacking the phase problem by crowdsourcing is introduced. Using an interactive, multi-player, web-based system, participants work simultaneously to select phase sets that correspond to better electron-density maps in order to solve low-resolution phasing problems. The human mind innately excels at some complex tasks that are difficult to solve using computers alone. For complex problems amenable to parallelization, strategies can be developed to exploit human intelligence in a collective form: such approaches are sometimes referred to as ‘crowdsourcing’. Here, a first attempt at a crowdsourced approach for low-resolution ab initio phasing in macromolecular crystallography is proposed. A collaborative online game named CrowdPhase was designed, which relies on a human-powered genetic algorithm, where players control the selection mechanism during the evolutionary process. The algorithm starts from a population of ‘individuals’, each with a random genetic makeup, in this case a map prepared from a random set of phases, and tries to cause the population to evolve towards individuals with better phases based on Darwinian survival of the fittest. Players apply their pattern-recognition capabilities to evaluate the electron-density maps generated from these sets of phases and to select the fittest individuals. A user-friendly interface, a training stage and a competitive scoring system foster a network of well trained players who can guide the genetic algorithm towards better solutions from generation to generation via gameplay. CrowdPhase was applied to two synthetic low-resolution phasing puzzles and it was shown that players could successfully obtain phase sets in the 30° phase error range and corresponding molecular envelopes showing agreement with the low-resolution models. The successful preliminary studies suggest that with further development the crowdsourcing approach could fill a gap in current crystallographic methods by making it

  11. Sejarah, Penerapan, dan Analisis Resiko dari Neural Network: Sebuah Tinjauan Pustaka

    Directory of Open Access Journals (Sweden)

    Cristina Cristina

    2018-05-01

    Full Text Available A neural network is a form of artificial intelligence that has the ability to learn, grow, and adapt in a dynamic environment. Neural network began since 1890 because a great American psychologist named William James created the book "Principles of Psycology". James was the first one publish a number of facts related to the structure and function of the brain. The history of neural network development is divided into 4 epochs, the Camelot era, the Depression, the Renaissance, and the Neoconnectiosm era. Neural networks used today are not 100 percent accurate. However, neural networks are still used because of better performance than alternative computing models. The use of neural network consists of pattern recognition, signal analysis, robotics, and expert systems. For risk analysis of the neural network, it is first performed using hazards and operability studies (HAZOPS. Determining the neural network requirements in a good way will help in determining its contribution to system hazards and validating the control or mitigation of any hazards. After completion of the first stage at HAZOPS and the second stage determines the requirements, the next stage is designing. Neural network underwent repeated design-train-test development. At the design stage, the hazard analysis should consider the design aspects of the development, which include neural network architecture, size, intended use, and so on. It will be continued at the implementation stage, test phase, installation and inspection phase, operation phase, and ends at the maintenance stage.

  12. Spatial networks

    Science.gov (United States)

    Barthélemy, Marc

    2011-02-01

    Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, and neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields, ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated with the length of edges which in turn has dramatic effects on the topological structure of these networks. We will thoroughly explain the current state of our understanding of how the spatial constraints affect the structure and properties of these networks. We will review the most recent empirical observations and the most important models of spatial networks. We will also discuss various processes which take place on these spatial networks, such as phase transitions, random walks, synchronization, navigation, resilience, and disease spread.

  13. Innovation Network Development Model in Telemedicine: A Change in Participation.

    Science.gov (United States)

    Goodarzi, Maryam; Torabi, Mashallah; Safdari, Reza; Dargahi, Hossein; Naeimi, Sara

    2015-10-01

    This paper introduces a telemedicine innovation network and reports its implementation in Tehran University of Medical Sciences. The required conditions for the development of future projects in the field of telemedicine are also discussed; such projects should be based on the common needs and opportunities in the areas of healthcare, education, and technology. The development of the telemedicine innovation network in Tehran University of Medical Sciences was carried out in two phases: identifying the beneficiaries of telemedicine, and codification of the innovation network memorandum; and brainstorming of three workgroup members, and completion and clustering ideas. The present study employed a qualitative survey by using brain storming method. Thus, the ideas of the innovation network members were gathered, and by using Freeplane software, all of them were clustered and innovation projects were defined. In the services workgroup, 87 and 25 ideas were confirmed in phase 1 and phase 2, respectively. In the education workgroup, 8 new programs in the areas of telemedicine, tele-education and teleconsultation were codified. In the technology workgroup, 101 and 11 ideas were registered in phase 1 and phase 2, respectively. Today, innovation is considered a major infrastructural element of any change or progress. Thus, the successful implementation of a telemedicine project not only needs funding, human resources, and full equipment. It also requires the use of innovation models to cover several different aspects of change and progress. The results of the study can provide a basis for the implementation of future telemedicine projects using new participatory, creative, and innovative models.

  14. Exacerbated vulnerability of coupled socio-economic risk in complex networks

    Science.gov (United States)

    Zhang, Xin; Feng, Ling; Berman, Yonatan; Hu, Ning; Stanley, H. Eugene

    2016-10-01

    The study of risk contagion in economic networks has most often focused on the financial liquidities of institutions and assets. In practice the agents in a network affect each other through social contagion, i.e., through herd behavior and the tendency to follow leaders. We study the coupled risk between social and economic contagion and find it significantly more severe than when economic risk is considered alone. Using the empirical network from the China venture capital market we find that the system exhibits an extreme risk of abrupt phase transition and large-scale damage, which is in clear contrast to the smooth phase transition traditionally observed in economic contagion alone. We also find that network structure impacts market resilience and that the randomization of the social network of the market participants can reduce system fragility when there is herd behavior. Our work indicates that under coupled contagion mechanisms network resilience can exhibit a fundamentally different behavior, i.e., an abrupt transition. It also reveals the extreme risk when a system has coupled socio-economic risks, and this could be of interest to both policy makers and market practitioners.

  15. EEG Oscillations Are Modulated in Different Behavior-Related Networks during Rhythmic Finger Movements.

    Science.gov (United States)

    Seeber, Martin; Scherer, Reinhold; Müller-Putz, Gernot R

    2016-11-16

    Sequencing and timing of body movements are essential to perform motoric tasks. In this study, we investigate the temporal relation between cortical oscillations and human motor behavior (i.e., rhythmic finger movements). High-density EEG recordings were used for source imaging based on individual anatomy. We separated sustained and movement phase-related EEG source amplitudes based on the actual finger movements recorded by a data glove. Sustained amplitude modulations in the contralateral hand area show decrease for α (10-12 Hz) and β (18-24 Hz), but increase for high γ (60-80 Hz) frequencies during the entire movement period. Additionally, we found movement phase-related amplitudes, which resembled the flexion and extension sequence of the fingers. Especially for faster movement cadences, movement phase-related amplitudes included high β (24-30 Hz) frequencies in prefrontal areas. Interestingly, the spectral profiles and source patterns of movement phase-related amplitudes differed from sustained activities, suggesting that they represent different frequency-specific large-scale networks. First, networks were signified by the sustained element, which statically modulate their synchrony levels during continuous movements. These networks may upregulate neuronal excitability in brain regions specific to the limb, in this study the right hand area. Second, movement phase-related networks, which modulate their synchrony in relation to the movement sequence. We suggest that these frequency-specific networks are associated with distinct functions, including top-down control, sensorimotor prediction, and integration. The separation of different large-scale networks, we applied in this work, improves the interpretation of EEG sources in relation to human motor behavior. EEG recordings provide high temporal resolution suitable to relate cortical oscillations to actual movements. Investigating EEG sources during rhythmic finger movements, we distinguish sustained from

  16. Networked ATM for Efficient Routing, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — We developed a EFB Data Communication Network (EDCN) concept that offers a more capable air-ground communications architecture. The solution takes full advantage of...

  17. Discrete fracture modelling of the Finnsjoen rock mass. Phase 1: Feasibility study

    International Nuclear Information System (INIS)

    Geier, J.E.; Axelsson, C.L.

    1991-03-01

    The geometry and properties of discrete fractures are expected to control local heterogeneity in flow and solute transport within crystalline rock in the Finnsjoen area. The present report describes the first phase of a discrete-fracture modelling study, the goal of which is to develop stochastic-continuum and hydrologic properties. In the first phase of this study, the FracMan discrete fracture modelling package was used to analyse discrete fracture geometrical and hyrological data. Constant-pressure packer tests were analysed using fractional dimensional methods to estimate effective transmissivities and flow dimension for the packer test intervals. Discrete fracture data on orientation, size, shape, and location were combined with hydrologic data to develop a preliminary conceptual model for the conductive fractures at the site. The variability of fracture properties was expressed in the model by probability distributions. The preliminary conceptual model was used to simulate three-dimensional populations of conductive fractures in 25 m and 50 m cubes of rock. Transient packer tests were simulated in these fracture populations, and the simulated results were used to validate the preliminary conceptual model. The calibrated model was used to estimate the components of effective conductivity tensors for the rock by simulating steady-state groundwater flow through the cubes in three orthogonal directions. Monte Carlo stochastic simulations were performed for alternative realizations of the conceptual model. The number of simulations was insufficient to give a quantitative prediction of the effective conductivity heterogeneity and anisotropy on the scales of the cubes. However, the results give preliminary, rough estimates of these properties, and provide a demonstration of how the discrete-fracture network concept can be applied to derive data that is necessary for stochastic continuum and channel network modelling. (authors)

  18. Quarantine-generated phase transition in epidemic spreading.

    Science.gov (United States)

    Lagorio, C; Dickison, M; Vazquez, F; Braunstein, L A; Macri, P A; Migueles, M V; Havlin, S; Stanley, H E

    2011-02-01

    We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold w(c) separating a phase (wspread out. We find that in our model the topology of the network strongly affects the size of the propagation and that w(c) increases with the mean degree and heterogeneity of the network. We also find that w(c) is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes. ©2011 American Physical Society

  19. Quarantine generated phase transition in epidemic spreading

    Science.gov (United States)

    Dicksion, Mark; Lagorio, Cecilia; Vazquez, F.; Braunstein, L.; Macri, P. A.; Migueles, M. V.; Havlin, S.; Stanley, H. E.

    2011-03-01

    We study the critical effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered (SIR) model in the presence of quarantine, where susceptible individuals protect themselves by disconnecting their links to infected neighbors with probability w, and reconnecting them to other susceptible individuals chosen at random. Starting from a single infected individual, we show by an analytical approach and simulations that there is a phase transition at a critical rewiring (quarantine) threshold wc separating a phase (w =wc) where the disease does not spread out. We find that in our model the topology of the network strongly affects the size of the propagation, and that wc increases with the mean degree and heterogeneity of the network. We also find that wc is reduced if we perform a preferential rewiring, in which the rewiring probability is proportional to the degree of infected nodes.

  20. Identification method of gas-liquid two-phase flow regime based on image wavelet packet information entropy and genetic neural network

    International Nuclear Information System (INIS)

    Zhou Yunlong; Chen Fei; Sun Bin

    2008-01-01

    Based on the characteristic that wavelet packet transform image can be decomposed by different scales, a flow regime identification method based on image wavelet packet information entropy feature and genetic neural network was proposed. Gas-liquid two-phase flow images were captured by digital high speed video systems in horizontal pipe. The information entropy feature from transformation coefficients were extracted using image processing techniques and multi-resolution analysis. The genetic neural network was trained using those eigenvectors, which was reduced by the principal component analysis, as flow regime samples, and the flow regime intelligent identification was realized. The test result showed that image wavelet packet information entropy feature could excellently reflect the difference between seven typical flow regimes, and the genetic neural network with genetic algorithm and BP algorithm merits were with the characteristics of fast convergence for simulation and avoidance of local minimum. The recognition possibility of the network could reach up to about 100%, and a new and effective method was presented for on-line flow regime. (authors)

  1. Pore network modeling of drainage process in patterned porous media: a quasi-static study

    KAUST Repository

    Zhang, Tao; Salama, Amgad; Sun, Shuyu; El-Amin, Mohamed

    2015-01-01

    -saturation relationships, it is quite challenging to isolate its effects explicitly in real porous media applications. However, within the framework of pore network models, it is easy to highlight the effects of wettability conditions on the transport of two-phase systems

  2. A universal order parameter for synchrony in networks of limit cycle oscillators

    Science.gov (United States)

    Schröder, Malte; Timme, Marc; Witthaut, Dirk

    2017-07-01

    We analyze the properties of order parameters measuring synchronization and phase locking in complex oscillator networks. First, we review network order parameters previously introduced and reveal several shortcomings: none of the introduced order parameters capture all transitions from incoherence over phase locking to full synchrony for arbitrary, finite networks. We then introduce an alternative, universal order parameter that accurately tracks the degree of partial phase locking and synchronization, adapting the traditional definition to account for the network topology and its influence on the phase coherence of the oscillators. We rigorously prove that this order parameter is strictly monotonously increasing with the coupling strength in the phase locked state, directly reflecting the dynamic stability of the network. Furthermore, it indicates the onset of full phase locking by a diverging slope at the critical coupling strength. The order parameter may find applications across systems where different types of synchrony are possible, including biological networks and power grids.

  3. Application of Detailed Phase Comparison Protection Models for the Analysis of its Operation in Networks with Facts Devices

    Directory of Open Access Journals (Sweden)

    Ruban Nikolay Yu.

    2015-01-01

    Full Text Available The problem of relay protection misoperations in networks with FACTS devices is considered in the paper. It is offered a solution to this problem for a phase comparison protection of transmission power line through the use of its detailed model for the analysis of the functioning for a case of various normal, emergency and post-emergency modes of electric power systems. The research results of this approach are given in the paper.

  4. Optical Techniques for Millimeter-Wave Phased Array Communications Antennas

    National Research Council Canada - National Science Library

    Edge, Colin

    1998-01-01

    The scope of this program was to study the application of optical techniques to signal distribution and beamforming networks in phased array antennas for Army mobile tactical communications systems...

  5. Internet and Social Network Recruitment: Two Case Studies

    OpenAIRE

    Johnson, Kathy A.; Peace, Jane

    2012-01-01

    The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that th...

  6. An Application of Social Network Analysis on Military Strategy, System Networks and the Phases of War

    Science.gov (United States)

    2015-03-26

    power grid network also used by Watts and Strogatz [53]. A summary of all exemplar networks is located in Table 9 below: Table 9: Full Exemplar...53] D. J. Watts and S. H. Strogatz , “Collective Dynamics of “Small World” networks,” Nature, no. 393, pp. 440-442, 1998. [54] M. E. Porter

  7. Synchronization challenges in packet-based Cloud-RAN fronthaul for mobile networks

    DEFF Research Database (Denmark)

    Checko, Aleksandra; Juul, Anders Christian; Christiansen, Henrik Lehrmann

    2015-01-01

    In this paper, we look at reusing existing packet-based network (e.g. Ethernet) to possibly decrease deployment costs of fronthaul Cloud Radio Access Network (C-RAN) network and cost of Baseband Unit (BBU) resources. The challenge of this solution is that it requires mobile traffic (until now...... transmitted over synchronous protocols) to traverse the asynchronous Ethernet without losing synchronization. We analyze synchronization requirements of mobile networks and present an overview of solutions that fulfill them in traditional mobile networks. Then we elaborate on challenges that packet-based...... fronthaul imposes. We analyze possible contributions to frequency and phase error. We verify the feasibility of using the IEEE 1588v2 also know as Precision Time Protocol (PTP) for providing accurate phase and frequency synchronization. The study is based on simulations made in OPNET modeler. Thereby we...

  8. Core Support to Global Development Network (GND) - Phase II ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    The Global Development Network (GDN) was launched by the World Bank in 1999 on the premise that good policy research, properly applied, can accelerate development and improve people's lives. Working mainly through regional networks, GDN supports economic and, increasingly, social science research in and on ...

  9. Study on the Microstructure and Liquid Phase Formation in a Semisolid Gray Cast Iron

    Science.gov (United States)

    Benati, Davi Munhoz; Ito, Kazuhiro; Kohama, Kazuyuki; Yamamoto, Hajime; Zoqui, Eugenio José

    2017-10-01

    The development of high-quality semisolid raw materials requires an understanding of the phase transformations that occur as the material is heated up to the semisolid state, i.e., its melting behavior. The microstructure of the material plays a very important role during semisolid processing as it determines the flow behavior of the material when it is formed, making a thorough understanding of the microstructural evolution essential. In this study, the phase transformations and microstructural evolution in Fe2.5C1.5Si gray cast iron specially designed for thixoforming processes as it was heated to the semisolid state were observed using in situ high-temperature confocal laser scanning microscopy. At room temperature, the alloy has a matrix of pearlite and ferrite with fine interdendritic type D flake graphite. During heating, the main transformations observed were graphite precipitation inside the grains and at the austenite grain boundaries; graphite flakes and graphite precipitates growing and becoming coarser with the increasing temperature; and the beginning of melting at around 1413 K to 1423 K (1140 °C to 1150 °C). Melting begins with the eutectic phase ( i.e., the carbon-rich phase) and continues with the primary phase (primary austenite), which is consumed as the temperature increases. Melting of the eutectic phase composed by coarsened interdendritic graphite flakes produced a semi-continuous liquid network homogeneously surrounding and wetting the dendrites of the solid phase, causing grains to detach from each other and producing the intended solid globules immersed in liquid.

  10. The Evolution of Network-based Business Models Illustrated Through the Case Study of an Entrepreneurship Project

    Directory of Open Access Journals (Sweden)

    Morten Lund

    2014-08-01

    Full Text Available Purpose: Existing frameworks for understanding and analyzing the value configuration and structuring of partnerships in relation such network-based business models are found to be inferior. The purpose of this paper is therefore to broaden our understanding of how business models may change over time and how the role of strategic partners may differ over time too. Design/methodology/approach: A longitudinal case study spanning over years and mobilising multiple qualitative methods such as interviews, observation and participative observation forms the basis of the data collection. Findings: This paper illustrates how a network-based business model arises and evolves and how the forces of a network structure impact the development of its partner relationships. The contribution of this article is to understanding how partners positioned around a business model can be organized into a network-based business model that generates additional value for the core business model and for both the partners and the customers. Research limitations/implications: The results should be taken with caution as they are based on the case study of a single network-based business model. Practical implications: Managers can gain insight into barriers and enablers relating to different types of loose organisations and how to best manage such relationships and interactions Originality/value: This study adds value to the existing literature by reflecting the dynamics created in the interactions between a business model’s strategic partners and how a how a business model can evolve in a series of distinct phases

  11. Results from a model system of superconducting solenoids and phase shifting bridge for pulsed power studies for proposed tokamak EF coils

    International Nuclear Information System (INIS)

    Fuja, R.E.; Kustom, R.L.; Smith, R.P.

    1977-01-01

    A matched pair of superconducting solenoids and a phase-shifting bridge circuit has been constructed to study energy storage and transfer for application to tokamak EF coils. The intrinsically stable solenoids, each with 4 H self-inductance, incorporate sufficient cooling to allow charging at several hundred volts, corresponding to B approximately equal 1 T/sec. The three-phase inductor-convertor capacitive bridge network operating at up to 150 V rms transfers energy reversibly and at controllable rates from the storage coil to the load coil

  12. Viet Nam Economic Research Network (VERN) - Phase II | CRDI ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    VERN I (101273) constituted the first network for young economic researchers in Viet Nam, where previously there had been no modality for cooperation or peer review. Guided by the philosophy of "understanding and managing globalization" that underpinned the earlier project, VERN II proposes to expand the network, ...

  13. Recognition and detection of seismic phases by artificial neural network detector; Jinko neural network ni yoru jishinha no ninshiki to kenshutsu

    Energy Technology Data Exchange (ETDEWEB)

    Yamazaki, K; Wang, W [Tokyo Gakugei University, Tokyo (Japan)

    1997-05-27

    Initial parts of P-waves, medium or high in intensity, are detected using an artificial neural network (ANN). The ANN is the generic name given to information processing systems of the non-Neumann type configured to human brain in point of information processing function, and is packaged into computers in the form of software capable of parallel processing, self-organizing, learning, etc. In this paper, a hierarchical ANN-assisted seismic motion recognition system is constructed on the basis of an error reverse propagation algorithm. It is reported here, with a remark that this study wants much more data from tests for the evaluation of the quality of the recognition, that P-wave recognition has been achieved. When this technique is applied to the S-wave, much more real-time information will become available. For the improvement of the system, a number of problems have to be solved, including the establishment of automatic refurbishment through adaptation-and-learning and configuration that incorporates frequency-related matters. It is found that this system is effective in seismic wave phase recognition but that it is not suitable for precision measurement. 7 refs., 4 figs.

  14. CompTIA Network+ Study Guide Exam N10-005

    CERN Document Server

    Lammle, Todd

    2012-01-01

    Todd Lammle's latest CompTIA Network+ Study Guide, now updated for the new exam! CompTIA's Network+ certification tells the world you have the skills to install, configure, and troubleshoot today's basic networking hardware peripherals and protocols. But first, you have to pass the exam! This detailed CompTIA Authorized study guide by networking guru Todd Lammle has everything you need to prepare for the CompTIA's new Network+Exam N10-005. All exam objectives are covered. He thoroughly explains key topics, offers plenty of practical examples, and draws upon his own invaluable 25+ years of netw

  15. Network structure of multivariate time series.

    Science.gov (United States)

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-10-21

    Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

  16. V-Band Wireless Surface Networks, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA GLENN RESEARCH CENTER in Topic O1.10 has identified the need to provide surface communications networks for human and robotic missions to explore the Moon and...

  17. First-principles study of amorphous Ga4Sb6Te3 phase-change alloys

    Science.gov (United States)

    Bouzid, Assil; Gabardi, Silvia; Massobrio, Carlo; Boero, Mauro; Bernasconi, Marco

    2015-05-01

    First-principles molecular dynamics simulations within the density functional theory framework were performed to generate amorphous models of the Ga4Sb6Te3 phase change alloy by quenching from the melt. We find that Ga-Sb and Ga-Te are the most abundant bonds with only a minor amount of Sb-Te bonds participating to the alloy network. Ga and four-coordinated Sb atoms present a tetrahedral-like geometry, whereas three-coordinated Sb atoms are in a pyramidal configuration. The tetrahedral-like geometries are similar to those of the crystalline phase of the two binary compounds GaTe and GaSb. A sizable fraction of Sb-Sb bonds is also present, indicating a partial nanoscale segregation of Sb. Despite the fact that the composition Ga4Sb6Te3 lies on the pseudobinary Ga Sb -Sb2Te3 tie line, the amorphous network can be seen as a mixture of the two binary compounds GaTe and GaSb with intertwined elemental Sb.

  18. Network Efficiency and Posterior Alpha Patterns Are Markers of Recovery from General Anesthesia: A High-Density Electroencephalography Study in Healthy Volunteers

    Directory of Open Access Journals (Sweden)

    Stefanie Blain-Moraes

    2017-06-01

    Full Text Available Recent studies have investigated local oscillations, long-range connectivity, and global network patterns to identify neural changes associated with anesthetic-induced unconsciousness. These studies typically employ anesthetic protocols that either just cross the threshold of unconsciousness, or induce deep unconsciousness for a brief period of time—neither of which models general anesthesia for major surgery. To study neural patterns of unconsciousness and recovery in a clinically-relevant context, we used a realistic anesthetic regimen to induce and maintain unconsciousness in eight healthy participants for 3 h. High-density electroencephalogram (EEG was acquired throughout and for another 3 h after emergence. Seven epochs of 5-min eyes-closed resting states were extracted from the data at baseline as well as 30, 60, 90, 120, 150, and 180-min post-emergence. Additionally, 5-min epochs were extracted during induction, unconsciousness, and immediately prior to recovery of consciousness, for a total of 10 analysis epochs. The EEG data in each epoch were analyzed using source-localized spectral analysis, phase-lag index, and graph theoretical techniques. Posterior alpha power was significantly depressed during unconsciousness, and gradually approached baseline levels over the 3 h recovery period. Phase-lag index did not distinguish between states of consciousness or stages of recovery. Network efficiency was significantly depressed and network clustering coefficient was significantly increased during unconsciousness; these graph theoretical measures returned to baseline during the 3 h recovery period. Posterior alpha power may be a potential biomarker for normal recovery of functional brain networks after general anesthesia.

  19. Dynamical Encoding by Networks of Competing Neuron Groups: Winnerless Competition

    International Nuclear Information System (INIS)

    Rabinovich, M.; Volkovskii, A.; Lecanda, P.; Huerta, R.; Abarbanel, H. D. I.; Laurent, G.

    2001-01-01

    Following studies of olfactory processing in insects and fish, we investigate neural networks whose dynamics in phase space is represented by orbits near the heteroclinic connections between saddle regions (fixed points or limit cycles). These networks encode input information as trajectories along the heteroclinic connections. If there are N neurons in the network, the capacity is approximately e(N-1) ! , i.e., much larger than that of most traditional network structures. We show that a small winnerless competition network composed of FitzHugh-Nagumo spiking neurons efficiently transforms input information into a spatiotemporal output

  20. Machine Learning Phases of Strongly Correlated Fermions

    Directory of Open Access Journals (Sweden)

    Kelvin Ch’ng

    2017-08-01

    Full Text Available Machine learning offers an unprecedented perspective for the problem of classifying phases in condensed matter physics. We employ neural-network machine learning techniques to distinguish finite-temperature phases of the strongly correlated fermions on cubic lattices. We show that a three-dimensional convolutional network trained on auxiliary field configurations produced by quantum Monte Carlo simulations of the Hubbard model can correctly predict the magnetic phase diagram of the model at the average density of one (half filling. We then use the network, trained at half filling, to explore the trend in the transition temperature as the system is doped away from half filling. This transfer learning approach predicts that the instability to the magnetic phase extends to at least 5% doping in this region. Our results pave the way for other machine learning applications in correlated quantum many-body systems.

  1. c-T phase diagram and Landau free energies of (AgAu)55 nanoalloy via neural-network molecular dynamic simulations.

    Science.gov (United States)

    Chiriki, Siva; Jindal, Shweta; Bulusu, Satya S

    2017-10-21

    For understanding the structure, dynamics, and thermal stability of (AgAu) 55 nanoalloys, knowledge of the composition-temperature (c-T) phase diagram is essential due to the explicit dependence of properties on composition and temperature. Experimentally, generating the phase diagrams is very challenging, and therefore theoretical insight is necessary. We use an artificial neural network potential for (AgAu) 55 nanoalloys. Predicted global minimum structures for pure gold and gold rich compositions are lower in energy compared to previous reports by density functional theory. The present work based on c-T phase diagram, surface area, surface charge, probability of isomers, and Landau free energies supports the enhancement of catalytic property of Ag-Au nanoalloys by incorporation of Ag up to 24% by composition in Au nanoparticles as found experimentally. The phase diagram shows that there is a coexistence temperature range of 70 K for Ag 28 Au 27 compared to all other compositions. We propose the power spectrum coefficients derived from spherical harmonics as an order parameter to calculate Landau free energies.

  2. Formal Food-related Networks in Ireland: A Case Study Analysis

    Directory of Open Access Journals (Sweden)

    Maeve Henchion

    2012-03-01

    Full Text Available  Strategic networking is of crucial importance for innovation in small and medium sized enterprises (SMEs as it enables these companies access external resources and overcome internal constraints. However, SMEs often lack the skills and competencies to engage in and benefit from networks. Consequently SMEs often fail in establishing strategic and efficient networks. To date, there is limited guidance available on the optimal design of such networks. Furthermore, limited guidance is available on the number of networks, and level of engagement therein, that companies should be involved with. Using case studies across a range of formal networks within the food sector in Ireland, insights into the success factors and barriers to network learning are presented, which provide a foundation for such guidelines. Three case studies were selected for analysis in Ireland. Up to ten in-depth interviews were scheduled with the network managers and key informants from the triple helix (i.e. policy, research and industry sectors within each formal network. Initially, interviewees were identified as a result of a review of secondary sources and personal knowledge of the authors. The snowball sampling technique was then employed to identify additional interviewees within each network. The findings from this study revealed that some formal networks had a strong institutional influence, including significant financial inputs, whilst others had bottom-up origins. Many networks had strong levels of interaction prior to formalisation, which provided solid trust-based foundations. Innovation and/or learning were not the expressed objectives of all networks at the outset. However, interviewees across all three networks felt that positive impacts had been achieved in these areas. Whilst being involved in a broad network can provide access to a wider range of ideas, these case studies suggest that being involved in a smaller, dense network, with high levels of IP

  3. EFFECTS OF STEEL PLANTS WITH THREE-PHASE INDUCTION FURNACES ON POWER DISTRIBUTION QUALITY OF THE EXISTING 33 kV NETWORK IN NIGERIA

    Directory of Open Access Journals (Sweden)

    Saheed Lekan Gbadamosi

    2015-08-01

    Full Text Available This study aimed at evaluating and analyzing the voltage and current distortions on the introduction of a steel production plant in a typical 33 kV distribution system in Nigeria, with a view to assisting decisions made in the present system operation and planning effective service delivery in terms of quality. A three phase induction furnace was developed using MatLab Simulink software and the effects of steel plant loads on the quality of electric power system supply to electricity users on the same distribution network was analyzed in terms of total harmonic distortions of voltage and current. In order to evaluate voltage magnitude profile on the network, load flow computation and analyses were carried out on the 33 kV distribution network before and after the introduction of steel plant loads, using Successive Approximation Method. The results showed critical voltage magnitude profile below -5% of nominal voltage at the receiving end nodes. With the aid of the Matlab Simulink model, inadmissible voltage and current distortions of 15.47% and 10.35% were measured. Passive filter was proposed, designed and simulated, in order to mitigate these distortions caused by the steel production plant loads. By simulation, the installation of the designed passive filter gave a reduction of the distortions to permissible values. Further, for every 1 MW load increment when the steel plant is connected, network losses increased by 94%; however, for every of Mvar of filter capacity, loss reduction in the network is 5.1 MW.

  4. What are the reasons for clinical network success? A qualitative study.

    Science.gov (United States)

    McInnes, Elizabeth; Haines, Mary; Dominello, Amanda; Kalucy, Deanna; Jammali-Blasi, Asmara; Middleton, Sandy; Klineberg, Emily

    2015-11-05

    Clinical networks have been established to improve patient outcomes and processes of care by implementing a range of innovations and undertaking projects based on the needs of local health services. Given the significant investment in clinical networks internationally, it is important to assess their effectiveness and sustainability. This qualitative study investigated the views of stakeholders on the factors they thought were influential in terms of overall network success. Ten participants were interviewed using face-to-face, audio-recorded semi-structured interviews about critical factors for networks' successes over the study period 2006-2008. Respondents were purposively selected from two stakeholder groups: i) chairs of networks during the study period of 2006-2008 from high- moderate- and low-impact networks (as previously determined by an independent review panel) and ii) experts in the clinical field of the network who had a connection to the network but who were not network members. Participants were blind to the performance of the network they were interviewed about. Transcribed data were coded and analysed to generate themes relating to the study aims. Themes relating to influential factors critical to network success were: network model principles; leadership; formal organisational structures and processes; nature of network projects; external relationships; profile and credibility of the network. This study provides clinical networks with guidance on essential factors for maximising optimal network outcomes and that may assist networks to move from being a 'low-impact' to 'high-impact' network. Important ingredients for successful clinical networks were visionary and strategic leadership with strong links to external stakeholders; and having formal infrastructure and processes to enable the development and management of work plans aligned with health priorities.

  5. 3D network single-phase Ni0.9Zn0.1O as anode materials for lithium-ion batteries

    DEFF Research Database (Denmark)

    Huang, Guoyong; Guo, Xueyi; Cao, Xiao

    2016-01-01

    A novel 3D network single-phase Ni0.9Zn0.1O has been designed and synthesized by calcining a special metal-organic precursor (MOP) (MeO2C3H6, Me=Ni and Zn, the molar ratio of Ni: Zn=9:1) as the self-sacrificing template for the first time. Comparing with NiO or the mixture of NiO and ZnO, the new...

  6. Breadth-First Search-Based Single-Phase Algorithms for Bridge Detection in Wireless Sensor Networks

    Science.gov (United States)

    Akram, Vahid Khalilpour; Dagdeviren, Orhan

    2013-01-01

    Wireless sensor networks (WSNs) are promising technologies for exploring harsh environments, such as oceans, wild forests, volcanic regions and outer space. Since sensor nodes may have limited transmission range, application packets may be transmitted by multi-hop communication. Thus, connectivity is a very important issue. A bridge is a critical edge whose removal breaks the connectivity of the network. Hence, it is crucial to detect bridges and take preventions. Since sensor nodes are battery-powered, services running on nodes should consume low energy. In this paper, we propose energy-efficient and distributed bridge detection algorithms for WSNs. Our algorithms run single phase and they are integrated with the Breadth-First Search (BFS) algorithm, which is a popular routing algorithm. Our first algorithm is an extended version of Milic's algorithm, which is designed to reduce the message length. Our second algorithm is novel and uses ancestral knowledge to detect bridges. We explain the operation of the algorithms, analyze their proof of correctness, message, time, space and computational complexities. To evaluate practical importance, we provide testbed experiments and extensive simulations. We show that our proposed algorithms provide less resource consumption, and the energy savings of our algorithms are up by 5.5-times. PMID:23845930

  7. Hofstadter's Butterfly and Phase Transition of Checkerboard Superconducting Network in a Magnetic Field

    International Nuclear Information System (INIS)

    Hou Jingmin; Tian, Li-Jim

    2010-01-01

    We study the magnetic effect of the checkerboard superconducting wire network. Based on the de Gennes-Alexader theory, we obtain difference equations for superconducting order parameter in the wire network. Through solving these difference equations, we obtain the eigenvalues, linked to the coherence length, as a function of magnetic field. The diagram of eigenvalues shows a fractal structure, being so-called Hofstadter's butterfly. We also calculate and discuss the dependence of the transition temperature of the checkerboard superconducting wire network on the applied magnetic field, which is related to up-edge of the Hofstadter's butterfly spectrum. (condensed matter: electronic structure, electrical, magnetic, and optical properties)

  8. Social networks and health: a systematic review of sociocentric network studies in low- and middle-income countries.

    Science.gov (United States)

    Perkins, Jessica M; Subramanian, S V; Christakis, Nicholas A

    2015-01-01

    In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex

  9. Social Networks and Health: A Systematic Review of Sociocentric Network Studies in Low- and Middle-Income Countries

    Science.gov (United States)

    Perkins, Jessica M; Subramanian, S V; Christakis, Nicholas A

    2015-01-01

    In low- and middle-income countries (LMICs), naturally occurring social networks may be particularly vital to health outcomes as extended webs of social ties often are the principal source of various resources. Understanding how social network structure, and influential individuals within the network, may amplify the effects of interventions in LMICs, by creating, for example, cascade effects to non-targeted participants, presents an opportunity to improve the efficiency and effectiveness of public health interventions in such settings. We conducted a systematic review of PubMed, Econlit, Sociological Abstracts, and PsycINFO to identify a sample of 17 sociocentric network papers (arising from 10 studies) that specifically examined health issues in LMICs. We also separately selected to review 19 sociocentric network papers (arising from 10 other studies) on development topics related to wellbeing in LMICs. First, to provide a methodological resource, we discuss the sociocentric network study designs employed in the selected papers, and then provide a catalog of 105 name generator questions used to measure social ties across all the LMIC network papers (including both ego- and sociocentric network papers) cited in this review. Second, we show that network composition, individual network centrality, and network structure are associated with important health behaviors and health and development outcomes in different contexts across multiple levels of analysis and across distinct network types. Lastly, we highlight the opportunities for health researchers and practitioners in LMICs to 1) design effective studies and interventions in LMICs that account for the sociocentric network positions of certain individuals and overall network structure, 2) measure the spread of outcomes or intervention externalities, and 3) enhance the effectiveness and efficiency of aid based on knowledge of social structure. In summary, human health and wellbeing are connected through complex

  10. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  11. Prediksi Pergerakan Harga Valas Menggunakan Algoritma Neural Network

    Directory of Open Access Journals (Sweden)

    Castaka Agus Sugianto

    2018-01-01

    Full Text Available World currency market trading has become one of the many types of work that has been done by the public due to the convenience offered, big profits and the flexibility of time and place in trading. This study aims to predict the movement of EUR / USD currency trends using data mining techniques combined with neural network algorithms compared by linear regression algorithm that can be used as one of the references for traders as an open trading position. Attributes were used in this study namely Open (Opening Price, Close (Closing Price, Highest (Highest Price, Lowest (Lowest Price, for time frame price used is with time frame 1 day and the time period is taken from 3 January 2011 to 15 November 2016. The result of this research is Root Mean Squared Error (RMSE percentage number as well as additional label prediction result that obtained after validation using sliding windows validation. Best result obtained from testing phase using neural network algorithm which uses 0.006 and 0.003 windowing which results is equal to testing phase that does not use windowing. In other hands, testing phase on linear regression algorithm using windowing resulted in 0.007 and testing phase that does not use windowing that is equal to 0.004. T-test showed that neural network has insignificant result compared with linear regression. T-test result value is 1.00 for testing with windowing and 0.077 for windowless test.

  12. Networks and Interactivity

    DEFF Research Database (Denmark)

    Considine, Mark; Lewis, Jenny

    2012-01-01

    of `street-level' employment services staff for the impacts of this. Contrary to expectations, networking has generally declined over the last decade. There are signs of path dependence in networking patterns within each country, but also a convergence of patterns for the UK and Australia......The systemic reform of employment services in OECD countries was driven by New Public Management (NPM) and then post-NPM reforms, when first-phase changes such as privatization were amended with `joined up' processes to help manage fragmentation. This article examines the networking strategies......, but not The Netherlands. Networking appears to be mediated by policy and regulatory imperatives....

  13. Open quantum generalisation of Hopfield neural networks

    Science.gov (United States)

    Rotondo, P.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.; Müller, M.

    2018-03-01

    We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain.

  14. Structural parameter identifiability analysis for dynamic reaction networks

    DEFF Research Database (Denmark)

    Davidescu, Florin Paul; Jørgensen, Sten Bay

    2008-01-01

    method based on Lie derivatives. The proposed systematic two phase methodology is illustrated on a mass action based model for an enzymatically catalyzed reaction pathway network where only a limited set of variables is measured. The methodology clearly pinpoints the structurally identifiable parameters...... where for a given set of measured variables it is desirable to investigate which parameters may be estimated prior to spending computational effort on the actual estimation. This contribution addresses the structural parameter identifiability problem for the typical case of reaction network models....... The proposed analysis is performed in two phases. The first phase determines the structurally identifiable reaction rates based on reaction network stoichiometry. The second phase assesses the structural parameter identifiability of the specific kinetic rate expressions using a generating series expansion...

  15. The Hierarchy of Brain Networks Is Related to Insulin Growth Factor-1 in a Large, Middle-Aged, Healthy Cohort: An Exploratory Magnetoencephalography Study.

    Science.gov (United States)

    Sorrentino, Pierpaolo; Nieboer, Dagmar; Twisk, Jos W R; Stam, Cornelis J; Douw, Linda; Hillebrand, Arjan

    2017-06-01

    Recently, a large study demonstrated that lower serum levels of insulin growth factor-1 (IGF-1) relate to brain atrophy and to a greater risk for developing Alzheimer's disease in a healthy elderly population. We set out to test if functional brain networks relate to IGF-1 levels in the middle aged. Hence, we studied the association between IGF-1 and magnetoencephalography-based functional network characteristics in a middle-aged population. The functional connections between brain areas were estimated for six frequency bands (delta, theta, alpha1, alpha2, beta, gamma) using the phase lag index. Subsequently, the topology of the frequency-specific functional networks was characterized using the minimum spanning tree. Our results showed that lower levels of serum IGF-1 relate to a globally less integrated functional network in the beta and theta band. The associations remained significant when correcting for gender and systemic effects of IGF-1 that might indirectly affect the brain. The value of this exploratory study is the demonstration that lower levels of IGF-1 are associated with brain network topology in the middle aged.

  16. Duality in Phase Space and Complex Dynamics of an Integrated Pest Management Network Model

    Science.gov (United States)

    Yuan, Baoyin; Tang, Sanyi; Cheke, Robert A.

    Fragmented habitat patches between which plants and animals can disperse can be modeled as networks with varying degrees of connectivity. A predator-prey model with network structures is proposed for integrated pest management (IPM) with impulsive control actions. The model was analyzed using numerical methods to investigate how factors such as the impulsive period, the releasing constant of natural enemies and the mode of connections between the patches affect pest outbreak patterns and the success or failure of pest control. The concept of the cluster as defined by Holland and Hastings is used to describe variations in results ranging from global synchrony when all patches have identical fluctuations to n-cluster solutions with all patches having different dynamics. Heterogeneity in the initial densities of either pest or natural enemy generally resulted in a variety of cluster oscillations. Surprisingly, if n > 1, the clusters fall into two groups one with low amplitude fluctuations and the other with high amplitude fluctuations (i.e. duality in phase space), implying that control actions radically alter the system's characteristics by inducing duality and more complex dynamics. When the impulsive period is small enough, i.e. the control strategy is undertaken frequently, the pest can be eradicated. As the period increases, the pest's dynamics shift from a steady state to become chaotic with periodic windows and more multicluster oscillations arise for heterogenous initial density distributions. Period-doubling bifurcation and periodic halving cascades occur as the releasing constant of the natural enemy increases. For the same ecological system with five differently connected networks, as the randomness of the connectedness increases, the transient duration becomes smaller and the probability of multicluster oscillations appearing becomes higher.

  17. An improved fault detection classification and location scheme based on wavelet transform and artificial neural network for six phase transmission line using single end data only.

    Science.gov (United States)

    Koley, Ebha; Verma, Khushaboo; Ghosh, Subhojit

    2015-01-01

    Restrictions on right of way and increasing power demand has boosted development of six phase transmission. It offers a viable alternative for transmitting more power, without major modification in existing structure of three phase double circuit transmission system. Inspite of the advantages, low acceptance of six phase system is attributed to the unavailability of a proper protection scheme. The complexity arising from large number of possible faults in six phase lines makes the protection quite challenging. The proposed work presents a hybrid wavelet transform and modular artificial neural network based fault detector, classifier and locator for six phase lines using single end data only. The standard deviation of the approximate coefficients of voltage and current signals obtained using discrete wavelet transform are applied as input to the modular artificial neural network for fault classification and location. The proposed scheme has been tested for all 120 types of shunt faults with variation in location, fault resistance, fault inception angles. The variation in power system parameters viz. short circuit capacity of the source and its X/R ratio, voltage, frequency and CT saturation has also been investigated. The result confirms the effectiveness and reliability of the proposed protection scheme which makes it ideal for real time implementation.

  18. The effects of music on brain functional networks: a network analysis.

    Science.gov (United States)

    Wu, J; Zhang, J; Ding, X; Li, R; Zhou, C

    2013-10-10

    The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  19. Distribution Network Design--literature study based

    OpenAIRE

    LI, ANG

    2012-01-01

    The focus of this research is companies' outbound distribution network design in supply chain management. Within the present competitive market, it is a fundamental importance for companies to achieve high level business performance with an effective supply chain. Outbound distribution network design as an important part in supply chain management, to a large extent decides whether companies can fulfill customers' requirement or not. Therefore, such a study is important for manufacturers and ...

  20. A Microfluidics Study to Quantify the Impact of Microfracture Properties on Two-Phase Flow in Tight Rocks

    Science.gov (United States)

    Mehmani, A.; Kelly, S. A.; Torres-Verdin, C.; Balhoff, M.

    2017-12-01

    Microfluidics provides the opportunity for controlled experiments of immiscible fluid dynamics in quasi two-dimensional permeable media and allows their direct observation. We leverage microfluidics to investigate the impact of microfracture properties on water imbibition and drainage in a porous matrix. In the context of this work, microfractures are defined as apertures or preferential flow paths formed along planes of weakness, such as between two different rock fabrics. Patterns of pseudo-microfractures with orientations from parallel and perpendicular to fluid flow as well as variations in their connectivity were fabricated in glass micromodels; surface roughness of the micromodels was also varied utilizing a new method. Light microscopy and image analysis were used to quantify transient front advancement and trapped non-wetting phase saturation during imbibition as well as residual wetting phase saturation and its spatial distribution following drainage. Our experiments enable the assessment of quantitative relationships between fluid invasion rate and residual phase distributions as functions of microfracture network properties. Ultimately, the wide variety of microfluidic experiments performed in this study provide valuable insight into two-phase fluid dynamics in microfracture/matrix networks, the extent of fracture fluid invasion, and the saturation of trapped phases. In reservoir description, the geometries of subsurface fractures are often difficult to ascertain, but the distribution of rock types in a zone, from highly laminated to homogenous, can be reliably assessed with core data and well logs. Assuming that microcracks are functions of lamination planes (thin beds), then a priori predictions of the effect of microcracks on two-phase fluid flow across various geological conditions can possibly be upscaled via effective lamination properties. Such upscaling can significantly reduce the uncertainties associated with subsurface operations, including

  1. Stability of Boolean multilevel networks.

    Science.gov (United States)

    Cozzo, Emanuele; Arenas, Alex; Moreno, Yamir

    2012-09-01

    The study of the interplay between the structure and dynamics of complex multilevel systems is a pressing challenge nowadays. In this paper, we use a semiannealed approximation to study the stability properties of random Boolean networks in multiplex (multilayered) graphs. Our main finding is that the multilevel structure provides a mechanism for the stabilization of the dynamics of the whole system even when individual layers work on the chaotic regime, therefore identifying new ways of feedback between the structure and the dynamics of these systems. Our results point out the need for a conceptual transition from the physics of single-layered networks to the physics of multiplex networks. Finally, the fact that the coupling modifies the phase diagram and the critical conditions of the isolated layers suggests that interdependency can be used as a control mechanism.

  2. Functional Disorganization of Small-World Brain Networks in mild Alzheimer’s Disease and amnestic Mild Cognitive Impairment: An EEG Study using Relative Wavelet Entropy (RWE

    Directory of Open Access Journals (Sweden)

    Christos A. Frantzidis

    2014-08-01

    Full Text Available Previous neuroscientific findings have linked Alzheimer’s disease (AD with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD. Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT, and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N=500, 600, 700, 800 edges across all participants and groups (fixed density values. All groups exhibited a small-world (SW brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant’s generic cognitive status. The deterioration of the network’s organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.

  3. Two statistical mechanics aspects of complex networks

    Science.gov (United States)

    Thurner, Stefan; Biely, Christoly

    2006-12-01

    By adopting an ensemble interpretation of non-growing rewiring networks, network theory can be reduced to a counting problem of possible network states and an identification of their associated probabilities. We present two scenarios of how different rewirement schemes can be used to control the state probabilities of the system. In particular, we review how by generalizing the linking rules of random graphs, in combination with superstatistics and quantum mechanical concepts, one can establish an exact relation between the degree distribution of any given network and the nodes’ linking probability distributions. In a second approach, we control state probabilities by a network Hamiltonian, whose characteristics are motivated by biological and socio-economical statistical systems. We demonstrate that a thermodynamics of networks becomes a fully consistent concept, allowing to study e.g. ‘phase transitions’ and computing entropies through thermodynamic relations.

  4. STUDY OF TCP PHASE PRECIPITATING IN GH4199 SUPERALLOY

    Institute of Scientific and Technical Information of China (English)

    T.Cui; Y.S.Zhang; S.W.Guo; L.Wang; H.C.Yang

    2004-01-01

    The precipitating regulation and mechanism of TCP phasephase and σ phase) are studied, using electron hole number (EHN) theory, phase analysis technology and TEM observation. The results indicate that the EHN in studied alloy is 2.311-2.348 which is higher than that of critical EHN of μ phase precipitate (2.30), so μ phase could precipitate if there is enough thermo-exposition. In contrast, the calculated EHN is less than that of critical EHN of σ phase precipitate (2.52). However the σ phase is also observed by TEM.Enrich of Cr and Mo around γ phase after γ' phase precipitated leads to σ phase precipitated.

  5. Study of hourly and daily solar irradiation forecast using diagonal recurrent wavelet neural networks

    International Nuclear Information System (INIS)

    Cao Jiacong; Lin Xingchun

    2008-01-01

    An accurate forecast of solar irradiation is required for various solar energy applications and environmental impact analyses in recent years. Comparatively, various irradiation forecast models based on artificial neural networks (ANN) perform much better in accuracy than many conventional prediction models. However, the forecast precision of most existing ANN based forecast models has not been satisfactory to researchers and engineers so far, and the generalization capability of these networks needs further improving. Combining the prominent dynamic properties of a recurrent neural network (RNN) with the enhanced ability of a wavelet neural network (WNN) in mapping nonlinear functions, a diagonal recurrent wavelet neural network (DRWNN) is newly established in this paper to perform fine forecasting of hourly and daily global solar irradiance. Some additional steps, e.g. applying historical information of cloud cover to sample data sets and the cloud cover from the weather forecast to network input, are adopted to help enhance the forecast precision. Besides, a specially scheduled two phase training algorithm is adopted. As examples, both hourly and daily irradiance forecasts are completed using sample data sets in Shanghai and Macau, and comparisons between irradiation models show that the DRWNN models are definitely more accurate

  6. Neural network prediction of relativistic electrons at geosynchronous orbit during the storm recovery phase: effects of recurring substorms

    Directory of Open Access Journals (Sweden)

    M. Fukata

    2002-07-01

    Full Text Available During the recovery phase of geomagnetic storms, the flux of relativistic (>2 MeV electrons at geosynchronous orbits is enhanced. This enhancement reaches a level that can cause devastating damage to instruments on satellites. To predict these temporal variations, we have developed neural network models that predict the flux for the period 1–12 h ahead. The electron-flux data obtained during storms, from the Space Environment Monitor on board a Geostationary Meteorological Satellite, were used to construct the model. Various combinations of the input parameters AL, SAL, Dst and SDst were tested (where S denotes the summation from the time of the minimum Dst. It was found that the model, including SAL as one of the input parameters, can provide some measure of relativistic electron-flux prediction at geosynchronous orbit during the recovery phase. We suggest from this result that the relativistic electron-flux enhancement during the recovery phase is associated with recurring substorms after Dst minimum and their accumulation effect.Key words. Magnetospheric physics (energetic particles, trapped; magnetospheric configuration and dynamics; storms and substorms

  7. PROFEAT Update: A Protein Features Web Server with Added Facility to Compute Network Descriptors for Studying Omics-Derived Networks.

    Science.gov (United States)

    Zhang, P; Tao, L; Zeng, X; Qin, C; Chen, S Y; Zhu, F; Yang, S Y; Li, Z R; Chen, W P; Chen, Y Z

    2017-02-03

    The studies of biological, disease, and pharmacological networks are facilitated by the systems-level investigations using computational tools. In particular, the network descriptors developed in other disciplines have found increasing applications in the study of the protein, gene regulatory, metabolic, disease, and drug-targeted networks. Facilities are provided by the public web servers for computing network descriptors, but many descriptors are not covered, including those used or useful for biological studies. We upgraded the PROFEAT web server http://bidd2.nus.edu.sg/cgi-bin/profeat2016/main.cgi for computing up to 329 network descriptors and protein-protein interaction descriptors. PROFEAT network descriptors comprehensively describe the topological and connectivity characteristics of unweighted (uniform binding constants and molecular levels), edge-weighted (varying binding constants), node-weighted (varying molecular levels), edge-node-weighted (varying binding constants and molecular levels), and directed (oriented processes) networks. The usefulness of the network descriptors is illustrated by the literature-reported studies of the biological networks derived from the genome, interactome, transcriptome, metabolome, and diseasome profiles. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Assembly of collagen matrices as a phase transition revealed by structural and rheologic studies.

    Science.gov (United States)

    Forgacs, Gabor; Newman, Stuart A; Hinner, Bernhard; Maier, Christian W; Sackmann, Erich

    2003-02-01

    We have studied the structural and viscoelastic properties of assembling networks of the extracellular matrix protein type-I collagen by means of phase contrast microscopy and rotating disk rheometry. The initial stage of the assembly is a nucleation process of collagen monomers associating to randomly distributed branched clusters with extensions of several microns. Eventually a sol-gel transition takes place, which is due to the interconnection of these clusters. We analyzed this transition in terms of percolation theory. The viscoelastic parameters (storage modulus G' and loss modulus G") were measured as a function of time for five different frequencies ranging from omega = 0.2 rad/s to 6.9 rad/s. We found that at the gel point both G' and G" obey a scaling law, with the critical exponent Delta = 0.7 and a critical loss angle being independent of frequency as predicted by percolation theory. Gelation of collagen thus represents a second order phase transition.

  9. Study on Dissemination Patterns in Location-Aware Gossiping Networks

    Science.gov (United States)

    Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

    We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

  10. Constructing ordinal partition transition networks from multivariate time series.

    Science.gov (United States)

    Zhang, Jiayang; Zhou, Jie; Tang, Ming; Guo, Heng; Small, Michael; Zou, Yong

    2017-08-10

    A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

  11. Broadcast Expenses Controlling Techniques in Mobile Ad-hoc Networks: A Survey

    Directory of Open Access Journals (Sweden)

    Naeem Ahmad

    2016-07-01

    Full Text Available The blind flooding of query packets in route discovery more often characterizes the broadcast storm problem, exponentially increases energy consumption of intermediate nodes and congests the entire network. In such a congested network, the task of establishing the path between resources may become very complex and unwieldy. An extensive research work has been done in this area to improve the route discovery phase of routing protocols by reducing broadcast expenses. The purpose of this study is to provide a comparative analysis of existing broadcasting techniques for the route discovery phase, in order to bring about an efficient broadcasting technique for determining the route with minimum conveying nodes in ad-hoc networks. The study is designed to highlight the collective merits and demerits of such broadcasting techniques along with certain conclusions that would contribute to the choice of broadcasting techniques.

  12. Assessing harmonic current source modelling and power definitions in balanced and unbalanced networks

    Energy Technology Data Exchange (ETDEWEB)

    Atkinson-Hope, Gary; Stemmet, W.C. [Cape Peninsula University of Technology, Cape Town Campus, Cape Town (South Africa)

    2006-07-01

    The purpose of this paper is to assess the DlgSILENT PowerFactory software power definitions (indices) in terms of phase and sequence components for balanced and unbalanced networks when harmonic distortion is present and to compare its results to hand calculations done, following recommendation made by the IEEE Working Group on this topic. This paper also includes the development of a flowchart for calculating power indices in balanced and unbalanced three-phase networks when non-sinusoidal voltages and currents are present. A further purpose is to determine how two industrial grade harmonic analysis software packages (DlgSILENT and ERACS) model three-phase harmonic sources used for current penetration studies and to compare their results when applied to a network. From the investigations, another objective was to develop a methodology for modelling harmonic current sources based on a spectrum obtained from measurements. Three case studies were conducted and the assessment and developed methodologies were shown to be effective. (Author)

  13. Asymmetrically extremely dilute neural networks with Langevin dynamics and unconventional results

    International Nuclear Information System (INIS)

    Hatchett, J P L; Coolen, A C C

    2004-01-01

    We study graded response attractor neural networks with asymmetrically extremely dilute interactions and Langevin dynamics. We solve our model in the thermodynamic limit using generating functional analysis, and find (in contrast to the binary neurons case) that even in statics, for T > 0 or large α, one cannot eliminate the non-persistent order parameters, atypically for recurrent neural network models. The macroscopic dynamics is driven by the (non-trivial) joint distribution of neurons and fields, rather than just the (Gaussian) field distribution. We calculate phase transition lines and find, as may be expected for this asymmetric model, that there is no spin-glass phase, only recall and paramagnetic phases. We present simulation results in support of our theory

  14. Determinants of successful clinical networks: the conceptual framework and study protocol.

    Science.gov (United States)

    Haines, Mary; Brown, Bernadette; Craig, Jonathan; D'Este, Catherine; Elliott, Elizabeth; Klineberg, Emily; McInnes, Elizabeth; Middleton, Sandy; Paul, Christine; Redman, Sally; Yano, Elizabeth M

    2012-03-13

    Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.

  15. Predicting Traffic Flow in Local Area Networks by the Largest Lyapunov Exponent

    Directory of Open Access Journals (Sweden)

    Yan Liu

    2016-01-01

    Full Text Available The dynamics of network traffic are complex and nonlinear, and chaotic behaviors and their prediction, which play an important role in local area networks (LANs, are studied in detail, using the largest Lyapunov exponent. With the introduction of phase space reconstruction based on the time sequence, the high-dimensional traffic is projected onto the low dimension reconstructed phase space, and a reduced dynamic system is obtained from the dynamic system viewpoint. Then, a numerical method for computing the largest Lyapunov exponent of the low-dimensional dynamic system is presented. Further, the longest predictable time, which is related to chaotic behaviors in the system, is studied using the largest Lyapunov exponent, and the Wolf method is used to predict the evolution of the traffic in a local area network by both Dot and Interval predictions, and a reliable result is obtained by the presented method. As the conclusion, the results show that the largest Lyapunov exponent can be used to describe the sensitivity of the trajectory in the reconstructed phase space to the initial values. Moreover, Dot Prediction can effectively predict the flow burst. The numerical simulation also shows that the presented method is feasible and efficient for predicting the complex dynamic behaviors in LAN traffic, especially for congestion and attack in networks, which are the main two complex phenomena behaving as chaos in networks.

  16. Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

    Science.gov (United States)

    Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

    2015-09-15

    A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

  17. A COMPARATIVE STUDY OF SYSTEM NETWORK ARCHITECTURE Vs DIGITAL NETWORK ARCHITECTURE

    OpenAIRE

    Seema; Mukesh Arya

    2011-01-01

    The efficient managing system of sources is mandatory for the successful running of any network. Here this paper describes the most popular network architectures one of developed by IBM, System Network Architecture (SNA) and other is Digital Network Architecture (DNA). As we know that the network standards and protocols are needed for the network developers as well as users. Some standards are The IEEE 802.3 standards (The Institute of Electrical and Electronics Engineers 1980) (LAN), IBM Sta...

  18. Study of energetic consumptions and of renewable energy production potential for the Dordogne district. Phase 1 - Status and stakes, Phase 2 - Assessment of territory potentialities

    International Nuclear Information System (INIS)

    2013-01-01

    This document gathers reports made for phases 1 and 2 of a study which aimed at assessing the potential energy production by renewable energies in the French district of Dordogne. The first phase aimed at providing an overview of the present situation and an identification of stakes through an identification of electric and thermal energy sources (renewable or not) on this territory, and an analysis of energy consumptions per sector (housing and so on) in the district. Thus, it presents the district in its geographical, administrative, and demographic dimensions, as well as its local expertise. It gives an overview of the energy situation (energy and renewable energy production, electric power sector, gas sector, fuel supply network), and an overview of energy consumptions in the different sectors (housing, office building, industry, agriculture, transports). The second phase aimed at identifying and at assessing the potential energy production by renewable resources on the territory, and of the economic potential associated with renewable energy development. Raw, net and likely resources are assessed for hydroelectricity, solar sectors, wood energy, geothermal energy, aero-thermal energy, methanization, wind energy, and heat recovery

  19. Network stigma towards people living with HIV/AIDS and their caregivers: An egocentric network study.

    Science.gov (United States)

    Wu, Fei; He, Xin; Guida, Jennifer; Xu, Yongfang; Liu, Hongjie

    2015-10-01

    HIV stigma occurs among peers in social networks. However, the features of social networks that drive HIV stigma are not well understood. The objective of this study is to investigate anticipated HIV stigma within the social networks of people living with HIV/AIDS (PLWHA) (N = 147) and the social networks of PLWHA's caregivers (N = 148). The egocentric social network data were collected in Guangxi, China. More than half of PLWHA (58%) and their caregivers (53%) anticipated HIV stigma from their network peers. Both PLWHA and their caregivers anticipated that spouses or other family members were less likely to stigmatise them, compared to friend peers or other relationships. Married network peers were believed to stigmatise caregivers more than unmarried peers. The association between frequent contacts and anticipated stigma was negative among caregivers. Being in a close relationship with PLWHA or caregivers (e.g., a spouse or other family member) was associated with less anticipated stigma. Lower network density was associated with higher anticipated stigma among PLWHA's alters, but not among caregivers' alters. Findings may shed light on innovative stigma reduction interventions at the social network level and therefore improve HIV/AIDS treatment utilisation.

  20. A control strategy for induction motors fed from single phase supply

    DEFF Research Database (Denmark)

    Søndergård, Lars Møller

    1993-01-01

    It is often required that a three-phased asynchronous motor can run at variable speed, which makes it necessary to use a three-phase inverter driven from a DC-source. Today, most inverters are driven from the network using a simple diode bridge and an electrolytic capacitor. The problem with the ......It is often required that a three-phased asynchronous motor can run at variable speed, which makes it necessary to use a three-phase inverter driven from a DC-source. Today, most inverters are driven from the network using a simple diode bridge and an electrolytic capacitor. The problem...... with the simple diode bridge and the electrolytic capacitor is that current is only drawn for short periods, which gives rise to harmonic currents in the network. For small drive systems (motor+inverter), i.e. less than 1.5 kW, a single phase network outlet is often used. The author describes a method whereby...

  1. Machine Learning Topological Invariants with Neural Networks

    Science.gov (United States)

    Zhang, Pengfei; Shen, Huitao; Zhai, Hui

    2018-02-01

    In this Letter we supervisedly train neural networks to distinguish different topological phases in the context of topological band insulators. After training with Hamiltonians of one-dimensional insulators with chiral symmetry, the neural network can predict their topological winding numbers with nearly 100% accuracy, even for Hamiltonians with larger winding numbers that are not included in the training data. These results show a remarkable success that the neural network can capture the global and nonlinear topological features of quantum phases from local inputs. By opening up the neural network, we confirm that the network does learn the discrete version of the winding number formula. We also make a couple of remarks regarding the role of the symmetry and the opposite effect of regularization techniques when applying machine learning to physical systems.

  2. Dual phase evolution

    CERN Document Server

    Green, David G; Abbass, Hussein A

    2014-01-01

    This book explains how dual phase evolution operates in all these settings and provides a detailed treatment of the subject. The authors discuss the theoretical foundations for the theory, how it relates to other phase transition phenomena and its advantages in evolutionary computation and complex adaptive systems. The book provides methods and techniques to use this concept for problem solving. Dual phase evolution concerns systems that evolve via repeated phase shifts in the connectivity of their elements. It occurs in vast range of settings, including natural systems (species evolution, landscape ecology, geomorphology), socio-economic systems (social networks) and in artificial systems (annealing, evolutionary computing).

  3. Network connection of distributed electricity production - a preliminary study

    International Nuclear Information System (INIS)

    Pleym, Anngjerd; Mogstad, Olve

    2002-01-01

    It will be necessary to lower the barriers for utilisation of distributed energy sources in order to increase the use of such sources in Norway. A relatively extensive R and D activity would be required for reaching this goal. Available Norwegian and international guidelines and technical requirements with respect to network connection of the distributed energy sources are studied with the aim of exposing needs for further R and D initiatives. A limited monitor is also carried out among the Norwegian network businesses with distributed units in their networks. The results show that the main focus in the R and D activities has drifted away from establishing guidelines for technical requirements for network coupling. Some verification work remains in investigating the usefulness of the existing international and the specific commercial network guidelines. For the network industry the main focus must be on the two following areas: 1) How will large concentrations of distributed production units connected to the same network influence the voltage quality and the delivery reliability in the networks. 2) How can the network businesses employ the distributed production units in their networks. A Nordic project (Finland, Sweden, Norway) which will study these problems is being established. Large national scientific institutions will be involved. The executive committee will consist of representatives from Finenergy, Elforsk and EBL Kompetanse and other financing institutions and industries. A Finnish business Merinova, is to be appointed to the project leadership

  4. Carolina Offshore Wind Integration Case Study: Phases I and II Final Technical Report

    Energy Technology Data Exchange (ETDEWEB)

    Fallon, Christopher [Duke Energy Business Services, LLC, Charlotte, NC (United States); Piper, Orvane [Duke Energy Business Services, LLC, Charlotte, NC (United States); Hazelip, William [Duke Energy Business Services, LLC, Charlotte, NC (United States); Zhao, Yishan [Duke Energy Business Services, LLC, Charlotte, NC (United States); Salvador, Lisa [Duke Energy Business Services, LLC, Charlotte, NC (United States); Pruitt, Tom [Duke Energy Business Services, LLC, Charlotte, NC (United States); Peterson, Jeffrey [Duke Energy Business Services, LLC, Charlotte, NC (United States); Ashby, Rebecca [Duke Energy Business Services, LLC, Charlotte, NC (United States); Pierce, Bob [Duke Energy Business Services, LLC, Charlotte, NC (United States); Burner, Bob [Duke Energy Business Services, LLC, Charlotte, NC (United States); Daniel, John [ABB, Inc., Cary, NC (United States); Zhu, Jinxiang [ABB, Inc., Cary, NC (United States); Moore, Maria [ABB, Inc., Cary, NC (United States); Liu, Shu [ABB, Inc., Cary, NC (United States); Pennock, Ken [AWS Truepower, LLC, Albany, NY (United States); Frank, Jaclyn [AWS Truepower, LLC, Albany, NY (United States); Ibanez, Eduardo [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heaney, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bloom, Aaron [National Renewable Energy Lab. (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Lab. (NREL), Golden, CO (United States); Elliott, Dennis [National Renewable Energy Lab. (NREL), Golden, CO (United States); Seim, Harvey E. [Univ. of North Carolina, Chapel Hill, NC (United States)

    2015-04-30

    Duke Energy performed a phase 1 study to assess the impact of offshore wind development in the waters off the coasts of North Carolina and South Carolina. The study analyzed the impacts to the Duke Energy Carolinas electric power system of multiple wind deployment scenarios. Focusing on an integrated utility system in the Carolinas provided a unique opportunity to assess the impacts of offshore wind development in a region that has received less attention regarding renewables than others in the US. North Carolina is the only state in the Southeastern United States that currently has a renewable portfolio standard (RPS) which requires that 12.5% of the state’s total energy requirements be met with renewable resources by 2021. 12.5% of the state’s total energy requirements in 2021 equates to approximately 17,000 GWH of energy needed from renewable resources. Wind resources represent one of the ways to potentially meet this requirement. The study builds upon and augments ongoing work, including a study by UNC to identify potential wind development sites and the analysis of impacts to the regional transmission system performed by the NCTPC, an Order 890 planning entity of which DEC is a member. Furthermore, because the region does not have an independent system operator (ISO) or regional transmission organization (RTO), the study will provide additional information unique to non-RTO/ISO systems. The Phase 2 study builds on the results of Phase 1 and investigates the dynamic stability of the electrical network in Task 4, the operating characteristics of the wind turbines as they impact operating reserve requirements of the DEC utility in Task 5, and the production cost of integrating the offshore wind resources into the DEC generation fleet making comparisons to future planned operation without the addition of the wind resources in Task 6.

  5. Quantitative analysis of aqueous phase composition of model dentin adhesives experiencing phase separation

    Science.gov (United States)

    Ye, Qiang; Park, Jonggu; Parthasarathy, Ranganathan; Pamatmat, Francis; Misra, Anil; Laurence, Jennifer S.; Marangos, Orestes; Spencer, Paulette

    2013-01-01

    There have been reports of the sensitivity of our current dentin adhesives to excess moisture, for example, water-blisters in adhesives placed on over-wet surfaces, and phase separation with concomitant limited infiltration of the critical dimethacrylate component into the demineralized dentin matrix. To determine quantitatively the hydrophobic/hydrophilic components in the aqueous phase when exposed to over-wet environments, model adhesives were mixed with 16, 33, and 50 wt % water to yield well-separated phases. Based upon high-performance liquid chromatography coupled with photodiode array detection, it was found that the amounts of hydrophobic BisGMA and hydrophobic initiators are less than 0.1 wt % in the aqueous phase. The amount of these compounds decreased with an increase in the initial water content. The major components of the aqueous phase were hydroxyethyl methacrylate (HEMA) and water, and the HEMA content ranged from 18.3 to 14.7 wt %. Different BisGMA homologues and the relative content of these homologues in the aqueous phase have been identified; however, the amount of crosslinkable BisGMA was minimal and, thus, could not help in the formation of a crosslinked polymer network in the aqueous phase. Without the protection afforded by a strong crosslinked network, the poorly photoreactive compounds of this aqueous phase could be leached easily. These results suggest that adhesive formulations should be designed to include hydrophilic multimethacrylate monomers and water compatible initiators. PMID:22331596

  6. COHERENT NETWORK ANALYSIS FOR CONTINUOUS GRAVITATIONAL WAVE SIGNALS IN A PULSAR TIMING ARRAY: PULSAR PHASES AS EXTRINSIC PARAMETERS

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yan [MOE Key Laboratory of Fundamental Physical Quantities Measurements, School of Physics, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, Hubei Province 430074 (China); Mohanty, Soumya D.; Jenet, Fredrick A., E-mail: ywang12@hust.edu.cn [Department of Physics, University of Texas Rio Grande Valley, 1 West University Boulevard, Brownsville, TX 78520 (United States)

    2015-12-20

    Supermassive black hole binaries are one of the primary targets of gravitational wave (GW) searches using pulsar timing arrays (PTAs). GW signals from such systems are well represented by parameterized models, allowing the standard Generalized Likelihood Ratio Test (GLRT) to be used for their detection and estimation. However, there is a dichotomy in how the GLRT can be implemented for PTAs: there are two possible ways in which one can split the set of signal parameters for semi-analytical and numerical extremization. The straightforward extension of the method used for continuous signals in ground-based GW searches, where the so-called pulsar phase parameters are maximized numerically, was addressed in an earlier paper. In this paper, we report the first study of the performance of the second approach where the pulsar phases are maximized semi-analytically. This approach is scalable since the number of parameters left over for numerical optimization does not depend on the size of the PTA. Our results show that for the same array size (9 pulsars), the new method performs somewhat worse in parameter estimation, but not in detection, than the previous method where the pulsar phases were maximized numerically. The origin of the performance discrepancy is likely to be in the ill-posedness that is intrinsic to any network analysis method. However, the scalability of the new method allows the ill-posedness to be mitigated by simply adding more pulsars to the array. This is shown explicitly by taking a larger array of pulsars.

  7. Protocol for Communication Networking for Formation Flying

    Science.gov (United States)

    Jennings, Esther; Okino, Clayton; Gao, Jay; Clare, Loren

    2009-01-01

    An application-layer protocol and a network architecture have been proposed for data communications among multiple autonomous spacecraft that are required to fly in a precise formation in order to perform scientific observations. The protocol could also be applied to other autonomous vehicles operating in formation, including robotic aircraft, robotic land vehicles, and robotic underwater vehicles. A group of spacecraft or other vehicles to which the protocol applies could be characterized as a precision-formation- flying (PFF) network, and each vehicle could be characterized as a node in the PFF network. In order to support precise formation flying, it would be necessary to establish a corresponding communication network, through which the vehicles could exchange position and orientation data and formation-control commands. The communication network must enable communication during early phases of a mission, when little positional knowledge is available. Particularly during early mission phases, the distances among vehicles may be so large that communication could be achieved only by relaying across multiple links. The large distances and need for omnidirectional coverage would limit communication links to operation at low bandwidth during these mission phases. Once the vehicles were in formation and distances were shorter, the communication network would be required to provide high-bandwidth, low-jitter service to support tight formation-control loops. The proposed protocol and architecture, intended to satisfy the aforementioned and other requirements, are based on a standard layered-reference-model concept. The proposed application protocol would be used in conjunction with conventional network, data-link, and physical-layer protocols. The proposed protocol includes the ubiquitous Institute of Electrical and Electronics Engineers (IEEE) 802.11 medium access control (MAC) protocol to be used in the datalink layer. In addition to its widespread and proven use in

  8. Evolution of opinions on social networks in the presence of competing committed groups.

    Science.gov (United States)

    Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

    2012-01-01

    Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions A and B, and constituting fractions pA and pB of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space (pA,pB) consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.

  9. Discovering network behind infectious disease outbreak

    Science.gov (United States)

    Maeno, Yoshiharu

    2010-11-01

    Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on the SARS outbreak.

  10. Model checking the FlexRay startup phase

    NARCIS (Netherlands)

    Cranen, S.

    2012-01-01

    This report describes a discrete-time model of the startup phase of a FlexRay network. The startup behaviour of this network is analysed in the presence of several faults. It is shown that in certain cases a faulty node can prevent the network from communicating altogether. One previously unknown

  11. Knowledge Access in Rural Inter-connected Areas Network ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... the existing network to include two thematic networks on food security and rural ... Woman conquering male business in Yemen : Waleya's micro-enterprise.

  12. Evolution of hybrid defect networks

    International Nuclear Information System (INIS)

    Martins, C. J. A. P.

    2009-01-01

    We apply a recently developed analytic model for the evolution of monopole networks to the case of monopoles attached to one string, usually known as hybrid networks. We discuss scaling solutions for both local and global hybrid networks, and also find an interesting application for the case of vortons. Our quantitative results agree with previous estimates in indicating that the hybrid networks will usually annihilate soon after the string-forming phase transition. However, we also show that in some specific circumstances these networks can survive considerably more than a Hubble time.

  13. Technology Transfer at Edgar Mine: Phase 1; October 2016

    Energy Technology Data Exchange (ETDEWEB)

    Augustine, Chad R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bauer, Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Nakagawa, Masami [Colorado School of Mines, Golden, CO (United States); Zhou, Wendy [Colorado School of Mines, Golden, CO (United States)

    2017-09-14

    The objective of this project is to study the flow of fluid through the fractures and to characterize the efficiency of heat extraction (heat transfer) from the test rock mass in the Edgar Mine, managed by Colorado School of Mines in Idaho Springs, CO. The experiment consists of drilling into the wall of the mine and fracturing the rock, characterizing the size and nature of the fracture network, circulating fluid through the network, and measuring the efficiency of heat extraction from the 'reservoir' by monitoring the temperature of the 'produced' fluid with time. This is a multi-year project performed as a collaboration between the National Renewable Energy Laboratory, Colorado School of Mines and Sandia National Laboratories and carried out in phases. This report summarizes Phase 1: Selection and characterization of the location for the experiment, and outlines the steps for Phase 2: Circulation Experiments.

  14. Information processing in echo state networks at the edge of chaos.

    Science.gov (United States)

    Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

    2012-09-01

    We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.

  15. Converging Redundant Sensor Network Information for Improved Building Control

    Energy Technology Data Exchange (ETDEWEB)

    Dale Tiller; D. Phil; Gregor Henze; Xin Guo

    2007-09-30

    This project investigated the development and application of sensor networks to enhance building energy management and security. Commercial, industrial and residential buildings often incorporate systems used to determine occupancy, but current sensor technology and control algorithms limit the effectiveness of these systems. For example, most of these systems rely on single monitoring points to detect occupancy, when more than one monitoring point could improve system performance. Phase I of the project focused on instrumentation and data collection. During the initial project phase, a new occupancy detection system was developed, commissioned and installed in a sample of private offices and open-plan office workstations. Data acquisition systems were developed and deployed to collect data on space occupancy profiles. Phase II of the project demonstrated that a network of several sensors provides a more accurate measure of occupancy than is possible using systems based on single monitoring points. This phase also established that analysis algorithms could be applied to the sensor network data stream to improve the accuracy of system performance in energy management and security applications. In Phase III of the project, the sensor network from Phase I was complemented by a control strategy developed based on the results from the first two project phases: this controller was implemented in a small sample of work areas, and applied to lighting control. Two additional technologies were developed in the course of completing the project. A prototype web-based display that portrays the current status of each detector in a sensor network monitoring building occupancy was designed and implemented. A new capability that enables occupancy sensors in a sensor network to dynamically set the 'time delay' interval based on ongoing occupant behavior in the space was also designed and implemented.

  16. CompTIA Network+ Certification Study Guide, Exam N10-004

    CERN Document Server

    Shimonski, Robert

    2009-01-01

    CompTIA's Network+ certification is a globally-recognized, vendor neutral exam that has helped over 235,000 IT professionals reach further and higher in their careers. The 2009 Network+ exam (N10-004) is a major update with more focus on security and wireless aspects of networking. Our new study guide has been updated accordingly with focus on network, systems, and WAN security and complete coverage of today's wireless networking standards. As always this companion covers the core Network+ material including basic design principles, management and operation of a network infrastructure, and tes

  17. CUFID-query: accurate network querying through random walk based network flow estimation.

    Science.gov (United States)

    Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

    2017-12-28

    Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

  18. Multiplex Recurrence Networks

    Science.gov (United States)

    Eroglu, Deniz; Marwan, Norbert

    2017-04-01

    The complex nature of a variety of phenomena in physical, biological, or earth sciences is driven by a large number of degrees of freedom which are strongly interconnected. Although the evolution of such systems is described by multivariate time series (MTS), so far research mostly focuses on analyzing these components one by one. Recurrence based analyses are powerful methods to understand the underlying dynamics of a dynamical system and have been used for many successful applications including examples from earth science, economics, or chemical reactions. The backbone of these techniques is creating the phase space of the system. However, increasing the dimension of a system requires increasing the length of the time series in order get significant and reliable results. This requirement is one of the challenges in many disciplines, in particular in palaeoclimate, thus, it is not easy to create a phase space from measured MTS due to the limited number of available obervations (samples). To overcome this problem, we suggest to create recurrence networks from each component of the system and combine them into a multiplex network structure, the multiplex recurrence network (MRN). We test the MRN by using prototypical mathematical models and demonstrate its use by studying high-dimensional palaeoclimate dynamics derived from pollen data from the Bear Lake (Utah, US). By using the MRN, we can distinguish typical climate transition events, e.g., such between Marine Isotope Stages.

  19. Equilibrium & Nonequilibrium Fluctuation Effects in Biopolymer Networks

    Science.gov (United States)

    Kachan, Devin Michael

    Fluctuation-induced interactions are an important organizing principle in a variety of soft matter systems. In this dissertation, I explore the role of both thermal and active fluctuations within cross-linked polymer networks. The systems I study are in large part inspired by the amazing physics found within the cytoskeleton of eukaryotic cells. I first predict and verify the existence of a thermal Casimir force between cross-linkers bound to a semi-flexible polymer. The calculation is complicated by the appearance of second order derivatives in the bending Hamiltonian for such polymers, which requires a careful evaluation of the the path integral formulation of the partition function in order to arrive at the physically correct continuum limit and properly address ultraviolet divergences. I find that cross linkers interact along a filament with an attractive logarithmic potential proportional to thermal energy. The proportionality constant depends on whether and how the cross linkers constrain the relative angle between the two filaments to which they are bound. The interaction has important implications for the synthesis of biopolymer bundles within cells. I model the cross-linkers as existing in two phases: bound to the bundle and free in solution. When the cross-linkers are bound, they behave as a one-dimensional gas of particles interacting with the Casimir force, while the free phase is a simple ideal gas. Demanding equilibrium between the two phases, I find a discontinuous transition between a sparsely and a densely bound bundle. This discontinuous condensation transition induced by the long-ranged nature of the Casimir interaction allows for a similarly abrupt structural transition in semiflexible filament networks between a low cross linker density isotropic phase and a higher cross link density bundle network. This work is supported by the results of finite element Brownian dynamics simulations of semiflexible filaments and transient cross-linkers. I

  20. Phase equilibrium of binary system carbon dioxide - methanol at high pressure using artificial neural network

    International Nuclear Information System (INIS)

    Nasri, F.; Hatami, T.

    2012-01-01

    Interest in supercritical fluids extraction (SFE ) is increasing throughout many scientific and industrial fields. The common solvent for use in SFE is carbon dioxide. However, pure carbon dioxide frequently fails to efficiently extract the essential oil from a sample matrix, and modifier fluids such as methanol should be used to enhance extraction yield. A more efficient use of SFE requires quantitative prediction of phase equilibrium of this binary system, carbon dioxide - methanol. The purpose of the current research is modeling carbon dioxide - methanol system using artificial neural network (ANN). Results of ANN modeling has been compared with experimental data as well as thermodynamic equations of state. The comparison shows that the ANN modeling has a higher accuracy than thermodynamic models. (author)

  1. EEG classification of emotions using emotion-specific brain functional network.

    Science.gov (United States)

    Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

    2015-08-01

    The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

  2. Earth Regimes Network Evolution Study (ERNESt): Introducing the Space Mobile Network

    Science.gov (United States)

    Menrad, Bob

    2016-01-01

    Speaker and Presenter at the Lincoln Laboratory Communications Workshop on April 5, 2016 at the Massachusetts Institute of Technology Lincoln Laboratory in Lexington, MA. A visual presentation titled Earth Regimes Network Evolution Study (ERNESt).

  3. Sampling from complex networks with high community structures.

    Science.gov (United States)

    Salehi, Mostafa; Rabiee, Hamid R; Rajabi, Arezo

    2012-06-01

    In this paper, we propose a novel link-tracing sampling algorithm, based on the concepts from PageRank vectors, to sample from networks with high community structures. Our method has two phases; (1) Sampling the closest nodes to the initial nodes by approximating personalized PageRank vectors and (2) Jumping to a new community by using PageRank vectors and unknown neighbors. Empirical studies on several synthetic and real-world networks show that the proposed method improves the performance of network sampling compared to the popular link-based sampling methods in terms of accuracy and visited communities.

  4. Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection.

    Science.gov (United States)

    Wahab, Noorul; Khan, Asifullah; Lee, Yeon Soo

    2017-06-01

    Different types of breast cancer are affecting lives of women across the world. Common types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular carcinoma, Medullary carcinoma, and Invasive lobular carcinoma (ILC). While detecting cancer, one important factor is mitotic count - showing how rapidly the cells are dividing. But the class imbalance problem, due to the small number of mitotic nuclei in comparison to the overwhelming number of non-mitotic nuclei, affects the performance of classification models. This work presents a two-phase model to mitigate the class biasness issue while classifying mitotic and non-mitotic nuclei in breast cancer histopathology images through a deep convolutional neural network (CNN). First, nuclei are segmented out using blue ratio and global binary thresholding. In Phase-1 a CNN is then trained on the segmented out 80×80 pixel patches based on a standard dataset. Hard non-mitotic examples are identified and augmented; mitotic examples are oversampled by rotation and flipping; whereas non-mitotic examples are undersampled by blue ratio histogram based k-means clustering. Based on this information from Phase-1, the dataset is modified for Phase-2 in order to reduce the effects of class imbalance. The proposed CNN architecture and data balancing technique yielded an F-measure of 0.79, and outperformed all the methods relying on specific handcrafted features, as well as those using a combination of handcrafted and CNN-generated features. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Geometrical characterization of interconnected phase networks in three dimensions

    DEFF Research Database (Denmark)

    Jørgensen, Peter Stanley; Hansen, Karin Vels; Larsen, Rasmus

    2011-01-01

    In electrochemical devices such as fuel cells or batteries the microstructure is a determining factor for the performance of the device. To be able to optimize the microstructure it is important to be able to quantitatively measure key structural parameters, such that systematic studies can be made...... to the analysis of each of the three phases in a solid oxide fuel cell sample....

  6. Interdependent networks - Topological percolation research and application in finance

    Science.gov (United States)

    Zhou, Di

    This dissertation covers the two major parts of my Ph.D. research: i) developing a theoretical framework of complex networks and applying simulation and numerical methods to study the robustness of the network system, and ii) applying statistical physics concepts and methods to quantitatively analyze complex systems and applying the theoretical framework to study real-world systems. In part I, we focus on developing theories of interdependent networks as well as building computer simulation models, which includes three parts: 1) We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the networks significantly changes the critical density of failures, which can trigger the total disruption of the two-network system. Specifically, we find that the assortativity within a single network decreases the robustness of the entire system. 2) We study the percolation behavior of two interdependent scale-free (SF) networks under random failure of 1-p fraction of nodes. We find that as the coupling strength q between the two networks reduces from 1 (fully coupled) to 0 (no coupling), there exist two critical coupling strengths q1 and q2 , which separate the behaviors of the giant component as a function of p into three different regions, and for q2 relationship both analytically and numerically. We study a starlike network of n Erdos-Renyi (ER), SF networks and a looplike network of n ER networks, and we find for starlike networks, their phase transition regions change with n, but for looplike networks the phase regions change with average degree k . In part II, we apply concepts and methods developed in statistical physics to study economic systems. We analyze stock market indices and foreign exchange daily returns for 60 countries over the period of 1999-2012. We build a multi-layer network model based on different correlation measures, and introduce a

  7. Generalized model for k -core percolation and interdependent networks

    Science.gov (United States)

    Panduranga, Nagendra K.; Gao, Jianxi; Yuan, Xin; Stanley, H. Eugene; Havlin, Shlomo

    2017-09-01

    Cascading failures in complex systems have been studied extensively using two different models: k -core percolation and interdependent networks. We combine the two models into a general model, solve it analytically, and validate our theoretical results through extensive simulations. We also study the complete phase diagram of the percolation transition as we tune the average local k -core threshold and the coupling between networks. We find that the phase diagram of the combined processes is very rich and includes novel features that do not appear in the models studying each of the processes separately. For example, the phase diagram consists of first- and second-order transition regions separated by two tricritical lines that merge and enclose a two-stage transition region. In the two-stage transition, the size of the giant component undergoes a first-order jump at a certain occupation probability followed by a continuous second-order transition at a lower occupation probability. Furthermore, at certain fixed interdependencies, the percolation transition changes from first-order → second-order → two-stage → first-order as the k -core threshold is increased. The analytic equations describing the phase boundaries of the two-stage transition region are set up, and the critical exponents for each type of transition are derived analytically.

  8. Distribution network fault section identification and fault location using artificial neural network

    DEFF Research Database (Denmark)

    Dashtdar, Masoud; Dashti, Rahman; Shaker, Hamid Reza

    2018-01-01

    In this paper, a method for fault location in power distribution network is presented. The proposed method uses artificial neural network. In order to train the neural network, a series of specific characteristic are extracted from the recorded fault signals in relay. These characteristics...... components of the sequences as well as three-phase signals could be obtained using statistics to extract the hidden features inside them and present them separately to train the neural network. Also, since the obtained inputs for the training of the neural network strongly depend on the fault angle, fault...... resistance, and fault location, the training data should be selected such that these differences are properly presented so that the neural network does not face any issues for identification. Therefore, selecting the signal processing function, data spectrum and subsequently, statistical parameters...

  9. International and Domestic Business Cycles as Dynamics of a Network of Networks

    Science.gov (United States)

    Ikeda, Yuichi; Iyetomi, Hiroshi; Aoyama, Hideaki; Yoshikawa, Hiroshi

    2014-03-01

    Synchronization in business cycles has attracted economists and physicists as self-organization in the time domain. From a different point of view, international and domestic business cycles are also interesting as dynamics of a network of networks or a multi-level network. In this paper, we analyze the Indices of Industrial Production monthly time-series in Japan from January 1988 to December 2007 to develop a deeper understanding of domestic business cycles. The frequency entrainment and the partial phase locking were observed for the 16 sectors to be direct evidence of synchronization. We also showed that the information of the economic shock is carried by the phase time-series. The common shock and individual shocks are separated using phase time-series. The former dominates the economic recession in all of 1992, 1998 and 2001. In addition to the above analysis, we analyze the quarterly GDP time series for Australia, Canada, France, Italy, the United Kingdom, and the United States from Q2 1960 to Q1 2010 in order to clarify its origin. We find frequency entrainment and partial phase locking. Furthermore, a coupled limit-cycle oscillator model is developed to explain the mechanism of synchronization. In this model, the interaction due to international trade is interpreted as the origin of the synchronization. The obtained results suggest that the business cycle may be described as a dynamics of the multi-level coupled oscillators exposed to random individual shocks.

  10. Driving Interconnected Networks to Supercriticality

    Directory of Open Access Journals (Sweden)

    Filippo Radicchi

    2014-04-01

    Full Text Available Networks in the real world do not exist as isolated entities, but they are often part of more complicated structures composed of many interconnected network layers. Recent studies have shown that such mutual dependence makes real networked systems potentially exposed to atypical structural and dynamical behaviors, and thus there is an urgent necessity to better understand the mechanisms at the basis of these anomalies. Previous research has mainly focused on the emergence of atypical properties in relation to the moments of the intra- and interlayer degree distributions. In this paper, we show that an additional ingredient plays a fundamental role for the possible scenario that an interconnected network can face: the correlation between intra- and interlayer degrees. For sufficiently high amounts of correlation, an interconnected network can be tuned, by varying the moments of the intra- and interlayer degree distributions, in distinct topological and dynamical regimes. When instead the correlation between intra- and interlayer degrees is lower than a critical value, the system enters in a supercritical regime where dynamical and topological phases are no longer distinguishable.

  11. Co-expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

    Science.gov (United States)

    Mukund, Kavitha; Ward, Samuel R; Lieber, Richard L; Subramaniam, Shankar

    2017-10-16

    Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous workBotulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules

  12. Pore network modeling of drainage process in patterned porous media: a quasi-static study

    KAUST Repository

    Zhang, Tao

    2015-04-17

    This work represents a preliminary investigation on the role of wettability conditions on the flow of a two-phase system in porous media. Since such effects have been lumped implicitly in relative permeability-saturation and capillary pressure-saturation relationships, it is quite challenging to isolate its effects explicitly in real porous media applications. However, within the framework of pore network models, it is easy to highlight the effects of wettability conditions on the transport of two-phase systems. We employ quasi-static investigation in which the system undergo slow movement based on slight increment of the imposed pressure. Several numerical experiments of the drainage process are conducted to displace a wetting fluid with a non-wetting one. In all these experiments the network is assigned different scenarios of various wettability patterns. The aim is to show that the drainage process is very much affected by the imposed pattern of wettability. The wettability conditions are imposed by assigning the value of contact angle to each pore throat according to predefined patterns.

  13. Resilient distributed control in the presence of misbehaving agents in networked control systems.

    Science.gov (United States)

    Zeng, Wente; Chow, Mo-Yuen

    2014-11-01

    In this paper, we study the problem of reaching a consensus among all the agents in the networked control systems (NCS) in the presence of misbehaving agents. A reputation-based resilient distributed control algorithm is first proposed for the leader-follower consensus network. The proposed algorithm embeds a resilience mechanism that includes four phases (detection, mitigation, identification, and update), into the control process in a distributed manner. At each phase, every agent only uses local and one-hop neighbors' information to identify and isolate the misbehaving agents, and even compensate their effect on the system. We then extend the proposed algorithm to the leaderless consensus network by introducing and adding two recovery schemes (rollback and excitation recovery) into the current framework to guarantee the accurate convergence of the well-behaving agents in NCS. The effectiveness of the proposed method is demonstrated through case studies in multirobot formation control and wireless sensor networks.

  14. Phase controlled rectifier study

    International Nuclear Information System (INIS)

    Bronner, G.; Murray, J.G.

    1976-03-01

    This report introduces the results of an engineering study incorporating a computer program to determine the transient and steady-state voltage and current wave shapes for a 12-pulse rectifier system. Generally, rectifier engineering studies are completed by making simplified assumptions and neglecting many circuit parameters. The studies incorporate the 3-phase AC parameters including nonlinear source or generator, 3-winding transformer impedances, and shunt and series capacitors. It includes firing angle control, and DC filter circuits with inductive loads

  15. Spiral Wave in Small-World Networks of Hodgkin-Huxley Neurons

    International Nuclear Information System (INIS)

    Ma Jun; Zhang Cairong; Yang Lijian; Wu Ying

    2010-01-01

    The effect of small-world connection and noise on the formation and transition of spiral wave in the networks of Hodgkin-Huxley neurons are investigated in detail. Some interesting results are found in our numerical studies. i) The quiescent neurons are activated to propagate electric signal to others by generating and developing spiral wave from spiral seed in small area. ii) A statistical factor is defined to describe the collective properties and phase transition induced by the topology of networks and noise. iii) Stable rotating spiral wave can be generated and keeps robust when the rewiring probability is below certain threshold, otherwise, spiral wave can not be developed from the spiral seed and spiral wave breakup occurs for a stable rotating spiral wave. iv) Gaussian white noise is introduced on the membrane of neurons to study the noise-induced phase transition on spiral wave in small-world networks of neurons. It is confirmed that Gaussian white noise plays active role in supporting and developing spiral wave in the networks of neurons, and appearance of smaller factor of synchronization indicates high possibility to induce spiral wave. (interdisciplinary physics and related areas of science and technology)

  16. Asymptotics of relativistic spin networks

    International Nuclear Information System (INIS)

    Barrett, John W; Steele, Christopher M

    2003-01-01

    The stationary phase technique is used to calculate asymptotic formulae for SO(4) relativistic spin networks. For the tetrahedral spin network this gives the square of the Ponzano-Regge asymptotic formula for the SU(2) 6j-symbol. For the 4-simplex (10j-symbol) the asymptotic formula is compared with numerical calculations of the spin network evaluation. Finally, we discuss the asymptotics of the SO(3, 1) 10j-symbol

  17. In Situ Decommissioning Sensor Network, Meso-Scale Test Bed - Phase 3 Fluid Injection Test Summary Report

    International Nuclear Information System (INIS)

    Serrato, M. G.

    2013-01-01

    located at the Florida International University Applied Research Center, Miami, FL (FIU-ARC). A follow-on fluid injection test was developed to detect fluid and ion migration in a cementitious material/grouted test cube using a limited number of existing embedded sensor systems. This In Situ Decommissioning Sensor Network, Meso-Scale Test Bed (ISDSN-MSTB) - Phase 3 Fluid Injection Test Summary Report summarizes the test implementation, acquired and processed data, and results from the activated embedded sensor systems used during the fluid injection test. The ISDSN-MSTB Phase 3 Fluid Injection Test was conducted from August 27 through September 6, 2013 at the FIU-ARC ISDSN-MSTB test cube. The fluid injection test activated a portion of the existing embedded sensor systems in the ISDSN-MSTB test cube: Electrical Resistivity Tomography-Thermocouple Sensor Arrays, Advance Tensiometer Sensors, and Fiber Loop Ringdown Optical Sensors. These embedded sensor systems were activated 15 months after initial placement. All sensor systems were remotely operated and data acquisition was completed through the established Sensor Remote Access System (SRAS) hosted on the DOE D&D Knowledge Management Information Tool (D&D DKM-IT) server. The ISDN Phase 3 Fluid Injection Test successfully demonstrated the feasibility of embedding sensor systems to assess moisture-fluid flow and resulting transport potential for contaminate mobility through a cementitious material/grout monolith. The ISDSN embedded sensor systems activated for the fluid injection test highlighted the robustness of the sensor systems and the importance of configuring systems in-depth (i.e., complementary sensors and measurements) to alleviate data acquisition gaps

  18. In Situ Decommissioning Sensor Network, Meso-Scale Test Bed - Phase 3 Fluid Injection Test Summary Report

    Energy Technology Data Exchange (ETDEWEB)

    Serrato, M. G.

    2013-09-27

    located at the Florida International University Applied Research Center, Miami, FL (FIU-ARC). A follow-on fluid injection test was developed to detect fluid and ion migration in a cementitious material/grouted test cube using a limited number of existing embedded sensor systems. This In Situ Decommissioning Sensor Network, Meso-Scale Test Bed (ISDSN-MSTB) - Phase 3 Fluid Injection Test Summary Report summarizes the test implementation, acquired and processed data, and results from the activated embedded sensor systems used during the fluid injection test. The ISDSN-MSTB Phase 3 Fluid Injection Test was conducted from August 27 through September 6, 2013 at the FIU-ARC ISDSN-MSTB test cube. The fluid injection test activated a portion of the existing embedded sensor systems in the ISDSN-MSTB test cube: Electrical Resistivity Tomography-Thermocouple Sensor Arrays, Advance Tensiometer Sensors, and Fiber Loop Ringdown Optical Sensors. These embedded sensor systems were activated 15 months after initial placement. All sensor systems were remotely operated and data acquisition was completed through the established Sensor Remote Access System (SRAS) hosted on the DOE D&D Knowledge Management Information Tool (D&D DKM-IT) server. The ISDN Phase 3 Fluid Injection Test successfully demonstrated the feasibility of embedding sensor systems to assess moisture-fluid flow and resulting transport potential for contaminate mobility through a cementitious material/grout monolith. The ISDSN embedded sensor systems activated for the fluid injection test highlighted the robustness of the sensor systems and the importance of configuring systems in-depth (i.e., complementary sensors and measurements) to alleviate data acquisition gaps.

  19. Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators

    Science.gov (United States)

    Papadopoulos, Lia; Kim, Jason Z.; Kurths, Jürgen; Bassett, Danielle S.

    2017-07-01

    Synchronization of non-identical oscillators coupled through complex networks is an important example of collective behavior, and it is interesting to ask how the structural organization of network interactions influences this process. Several studies have explored and uncovered optimal topologies for synchronization by making purposeful alterations to a network. On the other hand, the connectivity patterns of many natural systems are often not static, but are rather modulated over time according to their dynamics. However, this co-evolution and the extent to which the dynamics of the individual units can shape the organization of the network itself are less well understood. Here, we study initially randomly connected but locally adaptive networks of Kuramoto oscillators. In particular, the system employs a co-evolutionary rewiring strategy that depends only on the instantaneous, pairwise phase differences of neighboring oscillators, and that conserves the total number of edges, allowing the effects of local reorganization to be isolated. We find that a simple rule—which preserves connections between more out-of-phase oscillators while rewiring connections between more in-phase oscillators—can cause initially disordered networks to organize into more structured topologies that support enhanced synchronization dynamics. We examine how this process unfolds over time, finding a dependence on the intrinsic frequencies of the oscillators, the global coupling, and the network density, in terms of how the adaptive mechanism reorganizes the network and influences the dynamics. Importantly, for large enough coupling and after sufficient adaptation, the resulting networks exhibit interesting characteristics, including degree-frequency and frequency-neighbor frequency correlations. These properties have previously been associated with optimal synchronization or explosive transitions in which the networks were constructed using global information. On the contrary, by

  20. Adaptive autonomous Communications Routing Optimizer for Network Efficiency Management, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Maximizing network efficiency for NASA's Space Networking resources is a large, complex, distributed problem, requiring substantial collaboration. We propose the...

  1. Relaxation of synchronization on complex networks.

    Science.gov (United States)

    Son, Seung-Woo; Jeong, Hawoong; Hong, Hyunsuk

    2008-07-01

    We study collective synchronization in a large number of coupled oscillators on various complex networks. In particular, we focus on the relaxation dynamics of the synchronization, which is important from the viewpoint of information transfer or the dynamics of system recovery from a perturbation. We measure the relaxation time tau that is required to establish global synchronization by varying the structural properties of the networks. It is found that the relaxation time in a strong-coupling regime (K>Kc) logarithmically increases with network size N , which is attributed to the initial random phase fluctuation given by O(N-1/2) . After elimination of the initial-phase fluctuation, the relaxation time is found to be independent of the system size; this implies that the local interaction that depends on the structural connectivity is irrelevant in the relaxation dynamics of the synchronization in the strong-coupling regime. The relaxation dynamics is analytically derived in a form independent of the system size, and it exhibits good consistency with numerical simulations. As an application, we also explore the recovery dynamics of the oscillators when perturbations enter the system.

  2. Emerging trends in communication networks

    CERN Document Server

    Hasan, Syed Faraz

    2014-01-01

    This book covers the state of the art in communication networks with the help of illustrative diagrams and recent references published in reputed journals and magazines. The book gives readers a glimpse into the next generation of communication networks. It explores topics that are currently in the research phase and/or are expected to be deployed in recent future such as LTE networks and IPv6 networks. This book is written for students/researchers who wish to come up to date with the recent trends in telecommunications.

  3. Structural Behavioral Study on the General Aviation Network Based on Complex Network

    Science.gov (United States)

    Zhang, Liang; Lu, Na

    2017-12-01

    The general aviation system is an open and dissipative system with complex structures and behavioral features. This paper has established the system model and network model for general aviation. We have analyzed integral attributes and individual attributes by applying the complex network theory and concluded that the general aviation network has influential enterprise factors and node relations. We have checked whether the network has small world effect, scale-free property and network centrality property which a complex network should have by applying degree distribution of functions and proved that the general aviation network system is a complex network. Therefore, we propose to achieve the evolution process of the general aviation industrial chain to collaborative innovation cluster of advanced-form industries by strengthening network multiplication effect, stimulating innovation performance and spanning the structural hole path.

  4. Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

    Directory of Open Access Journals (Sweden)

    T. Sigi eHale

    2014-07-01

    Full Text Available Background: A growing body of research has identified abnormal visual information processing in ADHD. In particular, slow processing speed and increased reliance on visuo-perceptual strategies have become evident. Objective: The current study used recently developed fMRI methods to replicate and further examine abnormal rightward biased visual information processing in ADHD and to further characterize the nature of this effect; we tested its association to several large-scale distributed network systems. Method: We examined fMRI BOLD response during letter and location judgment tasks, and directly assessed visual network asymmetry and its association to large-scale networks using both a voxelwise and an averaged signal approach. Results: Initial within-group analyses revealed a pattern of left lateralized visual cortical activity in controls but right lateralized visual cortical activity in ADHD children. Direct analyses of visual network asymmetry confirmed atypical rightward bias in ADHD children compared to controls. This ADHD characteristic was atypically associated with reduced activation across several extra-visual networks, including the default mode network (DMN. We also found atypical associations between DMN activation and ADHD subjects’ inattentive symptoms and task performance. Conclusion: The current study demonstrated rightward VNA in ADHD during a simple letter discrimination task. This result adds an important novel consideration to the growing literature identifying abnormal visual processing in ADHD. We postulate that this characteristic reflects greater perceptual engagement of task-extraneous content, and that it may be a basic feature of less efficient top-down task-directed control over visual processing. We additionally argue that abnormal DMN function may contribute to this characteristic.

  5. Flux lattice commensurability and the resistive transition of wire networks

    International Nuclear Information System (INIS)

    Wilks, C.W.

    1992-01-01

    The commensurability of one structure with one length scale with that of another with a different length scale is a familiar problem. For a superconducting wire network in a magnetic field the two competing length scales are that of the network and that of the magnetic flux lattice. The superconducting to normal state phase boundary, Tc(H), of a periodic network shows periodic oscillations with a period of H 0 = Φ 0 /A where Φ 0 = hc/2e and A is the area of the elementary tile. These oscillations are due to flux quantization around the individual tiles of the network. In addition, within each period, there is structure at H = (p/q)H 0 (p,q integers) which is due to the vortices forming energetically favorable commensurate arrangements on top of the underlying lattice. The authors have studied the broadening of the zero field resistive transition with the application of a magnetic field for networks of various geometries. This was done by either directly measuring the resistive transitions at the commensurate fields or by using a technique that utilizes phase boundary measurements and yields the field induced width of the resistive transition as a continued function of the field. There is a striking dependence of the field induced width on whether or not the field is commensurate with the network. The broadening at the commensurate flux filling is well described by thermally activated vortex motion using the formalism of Ambegoakar and Halperin which allows us to extract numbers for the pinning potentials at the various commensurate states. The authors have found that the size of the discontinuity in the slope of the phase boundary at a commensurate filling is related to the strength of the lattice and therefore to the broadening of the transition at that filling so that by just looking at the phase boundary of a network one can gauge the relative broadening of the resistive transitions at the commensurate flux fillings

  6. Network planning study of the metro-optical-network-oriented 3G application

    Science.gov (United States)

    Gong, Qian; Xu, Rong; Lin, Jin Tong

    2005-02-01

    To compare with the 2G mobile communication, 3G technologies can supply the perfect service scope and performance. 3G is the trend of the mobile communication. So now to build the transmission network, it is needed to consider how the transmission network to support the 3G applications. For the 3G network architecture, it include the 2 part: Utran access network and core network. So the metro optical network should consider how to build the network to adapt the 3G applications. Include the metro core and access layer. In the metro core, we should consider the network should evolved towards the Mesh architecture with ASON function to realize the fast protection and restoration, quick end-to-end service provision, and high capacity cross-connect matrix etc. In the access layer, the network should have the ability to access the 3G services such as ATM interface with IMA function. In addition, the traffic grooming should be provided to improve the bandwidth utility. In this paper, first we present the MCC network situation, the network planning model will be introduced. Then we present the topology architecture, node capacity and traffic forecast. At last, based on our analysis, we will give a total solution to MCC to build their metro optical network toward to the mesh network with the consideration of 3G services.

  7. Studies on a network of complex neurons

    Science.gov (United States)

    Chakravarthy, Srinivasa V.; Ghosh, Joydeep

    1993-09-01

    In the last decade, much effort has been directed towards understanding the role of chaos in the brain. Work with rabbits reveals that in the resting state the electrical activity on the surface of the olfactory bulb is chaotic. But, when the animal is involved in a recognition task, the activity shifts to a specific pattern corresponding to the odor that is being recognized. Unstable, quasiperiodic behavior can be found in a class of conservative, deterministic physical systems called the Hamiltonian systems. In this paper, we formulate a complex version of Hopfield's network of real parameters and show that a variation on this model is a conservative system. Conditions under which the complex network can be used as a Content Addressable memory are studied. We also examine the effect of singularities of the complex sigmoid function on the network dynamics. The network exhibits unpredictable behavior at the singularities due to the failure of a uniqueness condition for the solution of the dynamic equations. On incorporating a weight adaptation rule, the structure of the resulting complex network equations is shown to have an interesting similarity with Kosko's Adaptive Bidirectional Associative Memory.

  8. Co-ordinated experimental research into PV power interaction with the supply network - Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Hacker, R.; Thornycroft, J.; Munro, D.; Rudkin, E.

    1999-07-01

    This report summarises the findings of a study examining the integration of photovoltaic systems into the UK electricity supply network. Details of research and development in the UK, and the participants in the research project are given. Information on photovoltaics as embedded generators, power conditioner design and performance, and the effects of photovoltaics on the network are outlined, and AC modules, standards, testing and approval schemes are considered. (UK)

  9. A Network SIG is born, DECUS (Switzerland) Newsletter, May 1990

    CERN Document Server

    Heagerty, Denise

    1990-01-01

    This article announces the formation of a Swiss DECUS (DEC Users Group) Network SIG in May 1990. The goal of this SIG is to help Swiss DECnet managers to plan transition from their proprietary DECnet Phase IV networks (e.g. the HEP/SPAN DECnet) to open networks based on DECnet Phase V/OSI. The SIG also proposes to address integration with UNIX based workstations using the Internet's TCP/IP protocols.

  10. An in-building network based on community access television integration with quadrature phase-shift keying orthogonal frequency-division multiplexing

    International Nuclear Information System (INIS)

    Chen, Chia-Yi; Lin, Ying-Pyng; Lu, Hai-Han; Wu, Po-Yi; Lin, Huang-Chang; Wu, Hsiao-Wen

    2012-01-01

    An in-building network based on cable television (CATV) integration with quadrature phase-shift keying (QPSK) orthogonal frequency-division multiplexing (OFDM) transport over a combination of single-mode fibers (SMF) and perfluorinated graded-index plastic optical fibers (GI-POF) is proposed and experimentally demonstrated. In this system, a 1558.5 nm optical signal is directly transmitted along two fiber spans (20 km SMF + 25 m GI-POF). An optimum guard band is carefully established to ensure that no very substantial signal interference is induced between the CATV and QPSK OFDM bands. Error free transmission with sufficiently low bit error rate values was achieved for 1.25 Gbps/771.5 MHz QPSK OFDM signals; also, acceptable carrier-to-noise ratio, composite second-order, and composite triple-beat performances were obtained for CATV signals. This proposed network is significant because it is economical and convenient to install. (paper)

  11. Critical Fluctuations in Spatial Complex Networks

    Science.gov (United States)

    Bradde, Serena; Caccioli, Fabio; Dall'Asta, Luca; Bianconi, Ginestra

    2010-05-01

    An anomalous mean-field solution is known to capture the nontrivial phase diagram of the Ising model in annealed complex networks. Nevertheless, the critical fluctuations in random complex networks remain mean field. Here we show that a breakdown of this scenario can be obtained when complex networks are embedded in geometrical spaces. Through the analysis of the Ising model on annealed spatial networks, we reveal, in particular, the spectral properties of networks responsible for critical fluctuations and we generalize the Ginsburg criterion to complex topologies.

  12. Options Study - Phase II

    Energy Technology Data Exchange (ETDEWEB)

    R. Wigeland; T. Taiwo; M. Todosow; W. Halsey; J. Gehin

    2010-09-01

    The Options Study has been conducted for the purpose of evaluating the potential of alternative integrated nuclear fuel cycle options to favorably address the issues associated with a continuing or expanding use of nuclear power in the United States. The study produced information that can be used to inform decisions identifying potential directions for research and development on such fuel cycle options. An integrated nuclear fuel cycle option is defined in this study as including all aspects of the entire nuclear fuel cycle, from obtaining natural resources for fuel to the ultimate disposal of used nuclear fuel (UNF) or radioactive wastes. Issues such as nuclear waste management, especially the increasing inventory of used nuclear fuel, the current uncertainty about used fuel disposal, and the risk of nuclear weapons proliferation have contributed to the reluctance to expand the use of nuclear power, even though it is recognized that nuclear power is a safe and reliable method of producing electricity. In this Options Study, current, evolutionary, and revolutionary nuclear energy options were all considered, including the use of uranium and thorium, and both once-through and recycle approaches. Available information has been collected and reviewed in order to evaluate the ability of an option to clearly address the challenges associated with the current implementation and potential expansion of commercial nuclear power in the United States. This Options Study is a comprehensive consideration and review of fuel cycle and technology options, including those for disposal, and is not constrained by any limitations that may be imposed by economics, technical maturity, past policy, or speculated future conditions. This Phase II report is intended to be used in conjunction with the Phase I report, and much information in that report is not repeated here, although some information has been updated to reflect recent developments. The focus in this Options Study was to

  13. Spontaneous formation of dynamical groups in an adaptive networked system

    International Nuclear Information System (INIS)

    Li Menghui; Guan Shuguang; Lai, C-H

    2010-01-01

    In this work, we investigate a model of an adaptive networked dynamical system, where the coupling strengths among phase oscillators coevolve with the phase states. It is shown that in this model the oscillators can spontaneously differentiate into two dynamical groups after a long time evolution. Within each group, the oscillators have similar phases, while oscillators in different groups have approximately opposite phases. The network gradually converts from the initial random structure with a uniform distribution of connection strengths into a modular structure that is characterized by strong intra-connections and weak inter-connections. Furthermore, the connection strengths follow a power-law distribution, which is a natural consequence of the coevolution of the network and the dynamics. Interestingly, it is found that if the inter-connections are weaker than a certain threshold, the two dynamical groups will almost decouple and evolve independently. These results are helpful in further understanding the empirical observations in many social and biological networks.

  14. INNOVATION NETWORKS AND MARKETING MIX: AN EXPLORATORY STUDY ON PRODUCT'S DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Thel Augusto Monteiro

    2013-12-01

    Full Text Available The purpose of this paper is to present how innovation networks can be used to develop a new product or service, using the marketing compound. The study methodology consists of an exploratory research from literature review on this subject. After an initial discussion of the characteristics of innovation networks and marketing functions, the study presents proposals that allow adequately addressing the main difficulties in the management of marketing in innovation networks. Through this study it can be stated that these networks have been identified as an attractive alternative for the development of new products, when using the marketing mix, given the dynamics of the contemporary market. Innovation networks bring a lot of benefits to companies that embrace the relationship between these networks and marketing. The discussion reveals that the structure in the form of innovation networks can bring effective results in the organization which adopt it, providing competitiveness and adaptability in the face of its target market.

  15. Fabrication of PVDF-based blend membrane with a thin hydrophilic deposition layer and a network structure supporting layer via the thermally induced phase separation followed by non-solvent induced phase separation process

    Science.gov (United States)

    Wu, Zhiguo; Cui, Zhenyu; Li, Tianyu; Qin, Shuhao; He, Benqiao; Han, Na; Li, Jianxin

    2017-10-01

    A simple strategy of thermally induced phase separation followed by non-solvent induced phase separation (TIPS-NIPS) is reported to fabricate poly (vinylidene fluoride) (PVDF)-based blend membrane. The dissolved poly (styrene-co-maleic anhydride) (SMA) in diluent prevents the crystallization of PVDF during the cooling process and deposites on the established PVDF matrix in the later extraction. Compared with traditional coating technique, this one-step TIPS-NIPS method can not only fabricate a supporting layer with an interconnected network structure even via solid-liquid phase separation of TIPS, but also form a uniform SMA skin layer approximately as thin as 200 nm via surface deposition of NIPS. Besides the better hydrophilicity, what's interesting is that the BSA rejection ratio increases from 48% to 94% with the increase of SMA, which indicates that the separation performance has improved. This strategy can be conveniently extended to the creation of firmly thin layer, surface functionalization and structure controllability of the membrane.

  16. Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

    Science.gov (United States)

    Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

    2012-06-01

    This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

  17. AMETH laboratories network activities; Activites du reseau de Laboratoires AMETH

    Energy Technology Data Exchange (ETDEWEB)

    Marimbordes, T.; Ould El Moctar, A.; Peerhossaini, H. [Nantes Univ., Ecole Polytechnique, UMR CNRS 6607, Lab. de Thermocinetique, 44 (France)] [and others

    2000-07-01

    The AMETH laboratories are a network for the improvement of thermal exchanges for one or two phases. This meeting of the 15 november 2000, dealt with the activities of this network of laboratories in the following topics: thermal-hydrodynamic instabilities and control of the limit layer; transfers with change in the liquid-vapor phase; transfers with change in the solid-liquid phase. Ten papers were presented. (A.L.B.)

  18. Transcriptomic network analysis of micronuclei-related genes: a case study

    DEFF Research Database (Denmark)

    van Leeuwen, D. M.; Pedersen, Marie; Knudsen, Lisbeth E.

    2011-01-01

    checkpoint and aneuploidy. The MN-related gene network was tested against a transcriptomics case study associated with MN measurements. In this case study, transcriptomic data from children and adults differentially exposed to ambient air pollution in the Czech Republic were analysed and visualised......Mechanistically relevant information on responses of humans to xenobiotic exposure in relation to chemically induced biological effects, such as micronuclei (MN) formation can be obtained through large-scale transcriptomics studies. Network analysis may enhance the analysis and visualisation...... of such data. Therefore, this study aimed to develop a 'MN formation' network based on a priori knowledge, by using the pathway tool MetaCore. The gene network contained 27 genes and three gene complexes that are related to processes involved in MN formation, e.g. spindle assembly checkpoint, cell cycle...

  19. Phase 1 study of metallic cask systems for spent fuel management from reactor to repository. Volume I. Phase 1 study summary

    International Nuclear Information System (INIS)

    1986-02-01

    It was proposed to perform a systems evaluation of metallic cask systems in order to define and examine the use of various metallic cask concepts or combination of concepts for the overall inventory management of spent fuel starting with its discharge from reactors to its emplacement in geologic repositories. This systems evaluation occurs in three phases. This three phase systems evaluation leads to a definition and recommendation of a sound and practical metallic cask system to accomplish efficient and effective management of spent fuel in the back end of the nuclear fuel cycle. Phase 1 Study objectives: establish system-wide functional criteria and assumptions; perform the systems engineering needed to define the metallic cask concepts and their feasibility; perform a screening evaluation of the technical and economic merits of the concepts; and recommend those to be included for a more detailed systems evaluation in Phase 2. Phase 2 Study objectives: refine the system-wide functional criteria and assumptions; perform the design engineering needed to enhance the validity and workability of those concepts recommended in Phase 1; and perform a more detailed systems evaluation. Phase 3 Study objectives: conclude the systems evaluation and develop an implementation plan. Volume I presents an overview of the detailed systems evaluation presented in Volume II

  20. Inferring the physical connectivity of complex networks from their functional dynamics

    Directory of Open Access Journals (Sweden)

    Holm Liisa

    2010-05-01

    Full Text Available Abstract Background Biological networks, such as protein-protein interactions, metabolic, signalling, transcription-regulatory networks and neural synapses, are representations of large-scale dynamic systems. The relationship between the network structure and functions remains one of the central problems in current multidisciplinary research. Significant progress has been made toward understanding the implication of topological features for the network dynamics and functions, especially in biological networks. Given observations of a network system's behaviours or measurements of its functional dynamics, what can we conclude of the details of physical connectivity of the underlying structure? Results We modelled the network system by employing a scale-free network of coupled phase oscillators. Pairwise phase coherence (PPC was calculated for all the pairs of oscillators to present functional dynamics induced by the system. At the regime of global incoherence, we observed a Significant pairwise synchronization only between two nodes that are physically connected. Right after the onset of global synchronization, disconnected nodes begin to oscillate in a correlated fashion and the PPC of two nodes, either connected or disconnected, depends on their degrees. Based on the observation of PPCs, we built a weighted network of synchronization (WNS, an all-to-all functionally connected network where each link is weighted by the PPC of two oscillators at the ends of the link. In the regime of strong coupling, we observed a Significant similarity in the organization of WNSs induced by systems sharing the same substrate network but different configurations of initial phases and intrinsic frequencies of oscillators. We reconstruct physical network from the WNS by choosing the links whose weights are higher than a given threshold. We observed an optimal reconstruction just before the onset of global synchronization. Finally, we correlated the topology of the

  1. NMR studies of phase behaviour in polyacrylonitrile solutions

    International Nuclear Information System (INIS)

    Golightly, J.A.

    1998-10-01

    The aim of the thesis was to study the phase behaviour of aqueous polyacrylonitrile/NaSCN solutions using a variety of nuclear magnetic resonance techniques. Polyacrylonitrile (PAN) is the basis of the acrylic fibre industry, as such fibres contain at least 85% PAN. Despite this industrial importance, the available literature describing the phase behaviour of PAN in solution is far from comprehensive. Bulk 1 H NMR relaxation measurements were carried out over a wide range of concentrations and temperatures to probe the molecular dynamics of the PAN and water molecules. The relaxation data was found to be biexponential decay for all samples, the relative amplitudes of which were shown to be equal to the ratio of PAN protons to water protons. Both species were found to be in the regime of rapid molecular motion. Bulk 1 H NMR self diffusion measurements, using the PFGSTE technique, exhibited a bi-exponential decay of the echo amplitudes. By careful selection of the observation time, Δ, it was possible to independently probe the water and PAN translational diffusion. A background gradient, resulting from inhomogeneities of the magnetic field, complicated the analysis of the data and a novel polynomial least squares fitting procedure was devised to overcome this effect. The measured attenuation of the water diffusion coefficients (D∼10 -6 -10 -5 cm 2 s -1 ) with increasing PAN volume fraction was modelled according to various theories, including free volume and scaling laws. The study of the PAN diffusion coefficient (D∼10 -7 -10 -6 cm 2 s -1 ) was limited by the experimental constraints of the NMR spectrometer. A 1 H NMR one-dimensional imaging technique was used to study the non-solvent induced phase separation (coagulation) of a PAN solution. The time dependence of the measured profiles allowed observation of the coagulation process. A diffusion model was developed to fit the experimental data using a semi-infinite diffusion framework. The fitting parameters

  2. Elimination of numerical diffusion in 1 - phase and 2 - phase flows

    Energy Technology Data Exchange (ETDEWEB)

    Rajamaeki, M. [VTT Energy (Finland)

    1997-07-01

    The new hydraulics solution method PLIM (Piecewise Linear Interpolation Method) is capable of avoiding the excessive errors, numerical diffusion and also numerical dispersion. The hydraulics solver CFDPLIM uses PLIM and solves the time-dependent one-dimensional flow equations in network geometry. An example is given for 1-phase flow in the case when thermal-hydraulics and reactor kinetics are strongly coupled. Another example concerns oscillations in 2-phase flow. Both the example computations are not possible with conventional methods.

  3. Elimination of numerical diffusion in 1 - phase and 2 - phase flows

    International Nuclear Information System (INIS)

    Rajamaeki, M.

    1997-01-01

    The new hydraulics solution method PLIM (Piecewise Linear Interpolation Method) is capable of avoiding the excessive errors, numerical diffusion and also numerical dispersion. The hydraulics solver CFDPLIM uses PLIM and solves the time-dependent one-dimensional flow equations in network geometry. An example is given for 1-phase flow in the case when thermal-hydraulics and reactor kinetics are strongly coupled. Another example concerns oscillations in 2-phase flow. Both the example computations are not possible with conventional methods

  4. Void fraction prediction in two-phase flows independent of the liquid phase density changes

    International Nuclear Information System (INIS)

    Nazemi, E.; Feghhi, S.A.H.; Roshani, G.H.

    2014-01-01

    Gamma-ray densitometry is a frequently used non-invasive method to determine void fraction in two-phase gas liquid pipe flows. Performance of flow meters using gamma-ray attenuation depends strongly on the fluid properties. Variations of the fluid properties such as density in situations where temperature and pressure fluctuate would cause significant errors in determination of the void fraction in two-phase flows. A conventional solution overcoming such an obstacle is periodical recalibration which is a difficult task. This paper presents a method based on dual modality densitometry using Artificial Neural Network (ANN), which offers the advantage of measuring the void fraction independent of the liquid phase changes. An experimental setup was implemented to generate the required input data for training the network. ANNs were trained on the registered counts of the transmission and scattering detectors in different liquid phase densities and void fractions. Void fractions were predicted by ANNs with mean relative error of less than 0.45% in density variations range of 0.735 up to 0.98 gcm −3 . Applying this method would improve the performance of two-phase flow meters and eliminates the necessity of periodical recalibration. - Highlights: • Void fraction was predicted independent of density changes. • Recorded counts of detectors/void fraction were used as inputs/output of ANN. • ANN eliminated necessity of recalibration in changeable density of two-phase flows

  5. Theoretical study of titanium phases; Etude theorique des phases du titane

    Energy Technology Data Exchange (ETDEWEB)

    Trinite, V

    2006-10-15

    The aim of this work is to obtain a good understanding of the phase diagram of titanium within density functional theory. This diagram is composed of the alpha phase, the high pressure omega phase and the high temperature beta phase. This requires the differences in total energy to be predicted with a great precision, because these differences are around 50 meV. I find the omega phase to be the most stable one by ab initio calculation at zero temperature and pressure, in contradiction to the experimental results. I find this inversion of the stability also appears in titanium dioxide and zirconium. I have analyzed all the approximations brought into play in the ab initio approach. I have estimated the zero point energy and studied the impact of including the semi-core states as well as the effect of the exchange-correlation functionals. The conclusion is that the usual approximations for the exchange-correlation generate the biggest part of the error. A possible correction is to take into account the electronic self-interaction. I have apply this correction to the semi-core states and find a systematic improvement of the cell parameters, but no improvement on the phase stability. So I can conclude that a better description of the exchange interaction on the localized 3d states is needed. Although the standard functionals of exchange-correlation are not accurate enough to predict the phase diagrams of titanium, they perform well in describing physical properties less demanding in terms of precision, like elastic constants. However, I find important that the predicted equilibrium volume must be precise, as these properties are found strongly dependent on the volume. (author)

  6. Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

    Directory of Open Access Journals (Sweden)

    Taras A Gritsun

    Full Text Available A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP synapses (so, no long-term potentiation, LTP, or depression, LTD, was included. However, elevated pre-phases (burst leaders and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

  7. Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

    KAUST Repository

    Marquet, Pierre

    2014-09-22

    Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

  8. Learning disordered topological phases by statistical recovery of symmetry

    Science.gov (United States)

    Yoshioka, Nobuyuki; Akagi, Yutaka; Katsura, Hosho

    2018-05-01

    We apply the artificial neural network in a supervised manner to map out the quantum phase diagram of disordered topological superconductors in class DIII. Given the disorder that keeps the discrete symmetries of the ensemble as a whole, translational symmetry which is broken in the quasiparticle distribution individually is recovered statistically by taking an ensemble average. By using this, we classify the phases by the artificial neural network that learned the quasiparticle distribution in the clean limit and show that the result is totally consistent with the calculation by the transfer matrix method or noncommutative geometry approach. If all three phases, namely the Z2, trivial, and thermal metal phases, appear in the clean limit, the machine can classify them with high confidence over the entire phase diagram. If only the former two phases are present, we find that the machine remains confused in a certain region, leading us to conclude the detection of the unknown phase which is eventually identified as the thermal metal phase.

  9. Non-consensus Opinion Models on Complex Networks

    Science.gov (United States)

    Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo

    2013-04-01

    Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not

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

    Science.gov (United States)

    Shaffer, Steven C.

    2014-05-01

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

  11. A Re-entrant Phase Transition in the Survival of Secondary Infections on Networks

    Science.gov (United States)

    Moore, Sam; Mörters, Peter; Rogers, Tim

    2018-06-01

    We study the dynamics of secondary infections on networks, in which only the individuals currently carrying a certain primary infection are susceptible to the secondary infection. In the limit of large sparse networks, the model is mapped to a branching process spreading in a random time-sensitive environment, determined by the dynamics of the underlying primary infection. When both epidemics follow the Susceptible-Infective-Recovered model, we show that in order to survive, it is necessary for the secondary infection to evolve on a timescale that is closely matched to that of the primary infection on which it depends.

  12. Phase behavior of model ABC triblock copolymers

    Science.gov (United States)

    Chatterjee, Joon

    The phase behavior of poly(isoprene-b-styrene- b-ethylene oxide) (ISO), a model ABC triblock copolymer has been studied. This class of materials exhibit self-assembly, forming a large array of ordered morphologies at length scales of 5-100 nm. The formation of stable three-dimensionally continuous network morphologies is of special interest in this study. Since these nanostructures considerably impact the material properties, fundamental knowledge for designing ABC systems have high technological importance for realizing applications in the areas of nanofabrication, nanoporous media, separation membranes, drug delivery and high surface area catalysts. A comprehensive framework was developed to describe the phase behavior of the ISO triblock copolymers at weak to intermediate segregation strengths spanning a wide range of composition. Phases were characterized through a combination of characterization techniques, including small angle x-ray scattering, dynamic mechanical spectroscopy, transmission electron microscopy, and birefringence measurements. Combined with previous investigations on ISO, six different stable ordered state symmetries have been identified: lamellae (LAM), Fddd orthorhombic network (O70), double gyroid (Q230), alternating gyroid (Q214), hexagonal (HEX), and body-centered cubic (BCC). The phase map was found to be somewhat asymmetric around the fI = fO isopleth. This work provides a guide for theoretical studies and gives insight into the intricate effects of various parameters on the self-assembly of ABC triblock copolymers. Experimental SAXS data evaluated with a simple scattering intensity model show that local mixing varies continuously across the phase map between states of two- and three-domain segregation. Strategies of blending homopolymers with ISO triblock copolymer were employed for studying the swelling properties of a lamellar state. Results demonstrate that lamellar domains swell or shrink depending upon the type of homopolymer that

  13. Diamond network: template-free fabrication and properties.

    Science.gov (United States)

    Zhuang, Hao; Yang, Nianjun; Fu, Haiyuan; Zhang, Lei; Wang, Chun; Huang, Nan; Jiang, Xin

    2015-03-11

    A porous diamond network with three-dimensionally interconnected pores is of technical importance but difficult to be produced. In this contribution, we demonstrate a simple, controllable, and "template-free" approach to fabricate diamond networks. It combines the deposition of diamond/β-SiC nanocomposite film with a wet-chemical selective etching of the β-SiC phase. The porosity of these networks was tuned from 15 to 68%, determined by the ratio of the β-SiC phase in the composite films. The electrochemical working potential and the reactivity of redox probes on the diamond networks are similar to those of a flat nanocrystalline diamond film, while their surface areas are hundreds of times larger than that of a flat diamond film (e.g., 490-fold enhancement for a 3 μm thick diamond network). The marriage of the unprecedented physical/chemical features of diamond with inherent advantages of the porous structure makes the diamond network a potential candidate for various applications such as water treatment, energy conversion (batteries or fuel cells), and storage (capacitors), as well as electrochemical and biochemical sensing.

  14. Network chemistry, network toxicology, network informatics, and network behavioristics: A scientific outline

    OpenAIRE

    WenJun Zhang

    2016-01-01

    In present study, I proposed some new sciences: network chemistry, network toxicology, network informatics, and network behavioristics. The aims, scope and scientific foundation of these sciences are outlined.

  15. Multipurpose exciter with low phase noise

    Science.gov (United States)

    Conroy, B.; Le, D.

    1989-01-01

    Results of an effort to develop a lower-cost exciter with high stability, low phase noise, and controllable phase and frequency for use in Deep Space Network and Goldstone Solar System Radar applications are discussed. Included is a discussion of the basic concept, test results, plans, and concerns.

  16. Studying Suspended Sediment Mechanism with Two-Phase PIV

    Science.gov (United States)

    Matinpour, H.; Atkinson, J. F.; Bennett, S. J.; Guala, M.

    2017-12-01

    Suspended sediment transport affects soil erosion, agriculture and water resources quality. Turbulent diffusion is the most primary force to maintain sediments in suspension. Although extensive previous literature have been studying the interactions between turbulent motion and suspended sediment, mechanism of sediments in suspension is still poorly understood. In this study, we investigate suspension of sediments as two distinct phases: one phase of sediments and another phase of fluid with turbulent motions. We designed and deployed a state-of-the-art two-phase PIV measurement technique to discriminate these two phases and acquire velocities of each phase separately and simultaneously. The technique that we have developed is employing a computer-vision based method, which enables us to discriminate sediment particles from fluid tracer particles based on two thresholds, dissimilar particle sizes and different particle intensities. Results indicate that fluid turbulence decreases in the presence of suspended sediments. Obtaining only sediment phase consecutive images enable us to compute fluctuation sediment concentration. This result enlightens understanding of complex interaction between the fluctuation velocities and the fluctuation of associated mass and compares turbulent viscosity with turbulent eddy diffusivity experimentally.

  17. Longitudinal social networks impacts on weight and weight-related behaviors assessed using mobile-based ecological momentary assessments: Study Protocols for the SPARC study

    Directory of Open Access Journals (Sweden)

    Meg Bruening

    2016-08-01

    Full Text Available Abstract Background The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life. Methods The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month. University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS locations of these activities relative to other students in their social networks. Discussion Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.

  18. Longitudinal social networks impacts on weight and weight-related behaviors assessed using mobile-based ecological momentary assessments: Study Protocols for the SPARC study.

    Science.gov (United States)

    Bruening, Meg; Ohri-Vachaspati, Punam; Brewis, Alexandra; Laska, Melissa; Todd, Michael; Hruschka, Daniel; Schaefer, David R; Whisner, Corrie M; Dunton, Genevieve

    2016-08-30

    The transition from the home to college is a phase in which emerging adults shift toward more unhealthy eating and physical activity patterns, higher body mass indices, thus increasing risk of overweight/obesity. Currently, little is understood about how changing friendship networks shape weight gain behaviors. This paper describes the recruitment, data collection, and data analytic protocols for the SPARC (Social impact of Physical Activity and nutRition in College) study, a longitudinal examination of the mechanisms by which friends and friendship networks influence nutrition and physical activity behaviors and weight gain in the transition to college life. The SPARC study aims to follow 1450 university freshmen from a large university over an academic year, collecting data on multiple aspects of friends and friendship networks. Integrating multiple types of data related to student lives, ecological momentary assessments (EMAs) are administered via a cell phone application, devilSPARC. EMAs collected in four 1-week periods (a total of 4 EMA waves) are integrated with linked data from web-based surveys and anthropometric measurements conducted at four times points (for a total of eight data collection periods including EMAs, separated by ~1 month). University databases will provide student card data, allowing integration of both time-dated data on food purchasing, use of physical activity venues, and geographical information system (GIS) locations of these activities relative to other students in their social networks. Findings are intended to guide the development of more effective interventions to enhance behaviors among college students that protect against weight gain during college.

  19. Controlling An Inverter-Driven Three-Phase Motor

    Science.gov (United States)

    Dolland, C.

    1984-01-01

    Control system for three-phase permanent-magnet motor driven by linecommutated inverter uses signals generated by integrating back emf of each phase of motor. High-pass filter network eliminates low-frequency components from control loop while maintaining desired power factor.

  20. Phase-flip bifurcation in a coupled Josephson junction neuron system

    Energy Technology Data Exchange (ETDEWEB)

    Segall, Kenneth, E-mail: ksegall@colgate.edu [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States); Guo, Siyang; Crotty, Patrick [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States); Schult, Dan [Department of Mathematics, Colgate University, Hamilton, NY 13346 (United States); Miller, Max [Department of Physics and Astronomy, Colgate University, Hamilton, NY 13346 (United States)

    2014-12-15

    Aiming to understand group behaviors and dynamics of neural networks, we have previously proposed the Josephson junction neuron (JJ neuron) as a fast analog model that mimics a biological neuron using superconducting Josephson junctions. In this study, we further analyze the dynamics of the JJ neuron numerically by coupling one JJ neuron to another. In this coupled system we observe a phase-flip bifurcation, where the neurons synchronize out-of-phase at weak coupling and in-phase at strong coupling. We verify this by simulation of the circuit equations and construct a bifurcation diagram for varying coupling strength using the phase response curve and spike phase difference map. The phase-flip bifurcation could be observed experimentally using standard digital superconducting circuitry.

  1. Phase-flip bifurcation in a coupled Josephson junction neuron system

    International Nuclear Information System (INIS)

    Segall, Kenneth; Guo, Siyang; Crotty, Patrick; Schult, Dan; Miller, Max

    2014-01-01

    Aiming to understand group behaviors and dynamics of neural networks, we have previously proposed the Josephson junction neuron (JJ neuron) as a fast analog model that mimics a biological neuron using superconducting Josephson junctions. In this study, we further analyze the dynamics of the JJ neuron numerically by coupling one JJ neuron to another. In this coupled system we observe a phase-flip bifurcation, where the neurons synchronize out-of-phase at weak coupling and in-phase at strong coupling. We verify this by simulation of the circuit equations and construct a bifurcation diagram for varying coupling strength using the phase response curve and spike phase difference map. The phase-flip bifurcation could be observed experimentally using standard digital superconducting circuitry

  2. Photoelastic studies of some polybutadiene networks

    Energy Technology Data Exchange (ETDEWEB)

    Mark, J E; Llorente, M A [Cincinnati Univ., OH (USA). Dept. of Chemistry

    1981-06-01

    Two butadiene polymers were used in this investigation, one with 98.5% cis-1,4 units and the other with an approximately equibinary mixture of cis and trans units. Elastomeric networks prepared from these polymers were studied in elongation, in both the swollen and unswollen states over the temperature range -30 to 95/sup 0/C. There is evidence for crystallization in these networks, particularly as manifested by marked increases in birefringence at relatively low elongation and at temperatures as high as 40/sup 0/C. As expected, the birefringence and related quantities were found to be more sensitive to crystallization than the force, with the optical-configuration parameter and the stress-optical coefficient showing the greatest sensitivity. In the case of the cis-trans copolymer, the crystallization involves trans sequences, which are of relatively high melting point, and thus occurs at a temperature higher than for the lower melting cis sequences in the high-cis networks. The results which were free from the effects of network crystallization were used to calculate values of the temperature coefficient of the unperturbed dimensions of the chains, and values of the optical-configuration parameter. These configuration-dependent properties were found to be in satisfactory agreement with previously published theoretical results based on a rotational isomeric state model of these chain molecules.

  3. Migrant Networks across Borders: The Case of Brazilian Entrepreneurs in Japan

    Directory of Open Access Journals (Sweden)

    Naoto HIGUCHI

    2010-05-01

    Full Text Available Classical studies on migration as those of the Chicago school emphasized the social disorganization of migrants. However, migration researchers have regarded social networks as the key to understanding migration processes. Social capital generated by migrant networks is now considered as essential for the social mobility of migrants. Indeed, the contrasting views of migrant networks are too simple to clarify the dynamic processes of network formation. Few studies have tested how migrant networks are changing in host societies, which ties are transplanted from the home country, and which of them are utilized. This paper aims to clarify the missing link between pre-migration and post-migration social networks, examining the multiplicity of migrants’ social networks. This study tested three hypotheses of social capital on Brazilian entrepreneurs in Japan. By analyzing the social capital these migrant entrepreneurs mobilized to start businesses, this study found that while most depended on social capital in the initial phase of their businesses, they relied less on social relationships transplanted to Japan than on other sources. In addition, Brazilian entrepreneurs selectively used different sources of social capital. These results show that migrants selectively maintain and reconstruct social networks in the process of migration.

  4. Case studies of attacks on communication networks

    Energy Technology Data Exchange (ETDEWEB)

    Kang, Sin Bok; Han, Eon Suk [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1996-06-15

    Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

  5. Case studies of attacks on communication networks

    International Nuclear Information System (INIS)

    Kang, Sin Bok; Han, Eon Suk

    1996-06-01

    Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

  6. Increased phase synchronization during continuous face integration measured simultaneously with EEG and fMRI.

    Science.gov (United States)

    Kottlow, Mara; Jann, Kay; Dierks, Thomas; Koenig, Thomas

    2012-08-01

    Gamma zero-lag phase synchronization has been measured in the animal brain during visual binding. Human scalp EEG studies used a phase locking factor (trial-to-trial phase-shift consistency) or gamma amplitude to measure binding but did not analyze common-phase signals so far. This study introduces a method to identify networks oscillating with near zero-lag phase synchronization in human subjects. We presented unpredictably moving face parts (NOFACE) which - during some periods - produced a complete schematic face (FACE). The amount of zero-lag phase synchronization was measured using global field synchronization (GFS). GFS provides global information on the amount of instantaneous coincidences in specific frequencies throughout the brain. Gamma GFS was increased during the FACE condition. To localize the underlying areas, we correlated gamma GFS with simultaneously recorded BOLD responses. Positive correlates comprised the bilateral middle fusiform gyrus and the left precuneus. These areas may form a network of areas transiently synchronized during face integration, including face-specific as well as binding-specific regions and regions for visual processing in general. Thus, the amount of zero-lag phase synchronization between remote regions of the human visual system can be measured with simultaneously acquired EEG/fMRI. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  7. Toward IMRT 2D dose modeling using artificial neural networks: A feasibility study

    Energy Technology Data Exchange (ETDEWEB)

    Kalantzis, Georgios; Vasquez-Quino, Luis A.; Zalman, Travis; Pratx, Guillem; Lei, Yu [Radiation Oncology Department, University of Texas, Health Science Center San Antonio, Texas 78229 and Radiation Oncology Department, Stanford University School of Medicine, Stanford, California 94305 (United States); Radiation Oncology Department, University of Texas, Health Science Center San Antonio, Texas 78229 (United States); Radiation Oncology Department, Stanford University School of Medicine, Stanford, California 94305 (United States); Radiation Oncology Department, University of Texas, Health Science Center San Antonio, Texas 78229 (United States)

    2011-10-15

    Purpose: To investigate the feasibility of artificial neural networks (ANN) to reconstruct dose maps for intensity modulated radiation treatment (IMRT) fields compared with those of the treatment planning system (TPS). Methods: An artificial feed forward neural network and the back-propagation learning algorithm have been used to replicate dose calculations of IMRT fields obtained from PINNACLE{sup 3} v9.0. The ANN was trained with fluence and dose maps of IMRT fields for 6 MV x-rays, which were obtained from the amorphous silicon (a-Si) electronic portal imaging device of Novalis TX. Those fluence distributions were imported to the TPS and the dose maps were calculated on the horizontal midpoint plane of a water equivalent homogeneous cylindrical virtual phantom. Each exported 2D dose distribution from the TPS was classified into two clusters of high and low dose regions, respectively, based on the K-means algorithm and the Euclidian metric in the fluence-dose domain. The data of each cluster were divided into two sets for the training and validation phase of the ANN, respectively. After the completion of the ANN training phase, 2D dose maps were reconstructed by the ANN and isodose distributions were created. The dose maps reconstructed by ANN were evaluated and compared with the TPS, where the mean absolute deviation of the dose and the {gamma}-index were used. Results: A good agreement between the doses calculated from the TPS and the trained ANN was achieved. In particular, an average relative dosimetric difference of 4.6% and an average {gamma}-index passing rate of 93% were obtained for low dose regions, and a dosimetric difference of 2.3% and an average {gamma}-index passing rate of 97% for high dose region. Conclusions: An artificial neural network has been developed to convert fluence maps to corresponding dose maps. The feasibility and potential of an artificial neural network to replicate complex convolution kernels in the TPS for IMRT dose calculations

  8. Toward IMRT 2D dose modeling using artificial neural networks: A feasibility study

    International Nuclear Information System (INIS)

    Kalantzis, Georgios; Vasquez-Quino, Luis A.; Zalman, Travis; Pratx, Guillem; Lei, Yu

    2011-01-01

    Purpose: To investigate the feasibility of artificial neural networks (ANN) to reconstruct dose maps for intensity modulated radiation treatment (IMRT) fields compared with those of the treatment planning system (TPS). Methods: An artificial feed forward neural network and the back-propagation learning algorithm have been used to replicate dose calculations of IMRT fields obtained from PINNACLE 3 v9.0. The ANN was trained with fluence and dose maps of IMRT fields for 6 MV x-rays, which were obtained from the amorphous silicon (a-Si) electronic portal imaging device of Novalis TX. Those fluence distributions were imported to the TPS and the dose maps were calculated on the horizontal midpoint plane of a water equivalent homogeneous cylindrical virtual phantom. Each exported 2D dose distribution from the TPS was classified into two clusters of high and low dose regions, respectively, based on the K-means algorithm and the Euclidian metric in the fluence-dose domain. The data of each cluster were divided into two sets for the training and validation phase of the ANN, respectively. After the completion of the ANN training phase, 2D dose maps were reconstructed by the ANN and isodose distributions were created. The dose maps reconstructed by ANN were evaluated and compared with the TPS, where the mean absolute deviation of the dose and the γ-index were used. Results: A good agreement between the doses calculated from the TPS and the trained ANN was achieved. In particular, an average relative dosimetric difference of 4.6% and an average γ-index passing rate of 93% were obtained for low dose regions, and a dosimetric difference of 2.3% and an average γ-index passing rate of 97% for high dose region. Conclusions: An artificial neural network has been developed to convert fluence maps to corresponding dose maps. The feasibility and potential of an artificial neural network to replicate complex convolution kernels in the TPS for IMRT dose calculations have been

  9. Exact tensor network ansatz for strongly interacting systems

    Science.gov (United States)

    Zaletel, Michael P.

    It appears that the tensor network ansatz, while not quite complete, is an efficient coordinate system for the tiny subset of a many-body Hilbert space which can be realized as a low energy state of a local Hamiltonian. However, we don't fully understand precisely which phases are captured by the tensor network ansatz, how to compute their physical observables (even numerically), or how to compute a tensor network representation for a ground state given a microscopic Hamiltonian. These questions are algorithmic in nature, but their resolution is intimately related to understanding the nature of quantum entanglement in many-body systems. For this reason it is useful to compute the tensor network representation of various `model' wavefunctions representative of different phases of matter; this allows us to understand how the entanglement properties of each phase are expressed in the tensor network ansatz, and can serve as test cases for algorithm development. Condensed matter physics has many illuminating model wavefunctions, such as Laughlin's celebrated wave function for the fractional quantum Hall effect, the Bardeen-Cooper-Schrieffer wave function for superconductivity, and Anderson's resonating valence bond ansatz for spin liquids. This thesis presents some results on exact tensor network representations of these model wavefunctions. In addition, a tensor network representation is given for the time evolution operator of a long-range one-dimensional Hamiltonian, which allows one to numerically simulate the time evolution of power-law interacting spin chains as well as two-dimensional strips and cylinders.

  10. European ecological networks and greenways

    DEFF Research Database (Denmark)

    Kristiansen, Ib; Jongman, Rob H.G.; Kulvik, Mart

    2004-01-01

    renewed. Within the framework of nature conservation, the notion of an ecological network has become increasingly important. Throughout Europe, regional and national approaches are in different phases of development, which are all based on recent landscape ecological principles. Ecological networks......In the context of European integration, networks are becoming increasingly important in both social and ecological sense. Since the beginning of the 1990s, societal and scientific exchanges are being restructured as the conceptual approaches towards new nature conservation strategies have been....... This complex interaction between cultural and natural features results in quite different ways for the elaboration of ecological networks and greenways....

  11. Social Networking Services in E-Learning

    Science.gov (United States)

    Weber, Peter; Rothe, Hannes

    2016-01-01

    This paper is a report on the findings of a study conducted on the use of the social networking service NING in a cross-location e-learning setting named "Net Economy." We describe how we implemented NING as a fundamental part of the setting through a special phase concept and team building approach. With the help of user statistics, we…

  12. Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

    Science.gov (United States)

    Kalesse, H.; Luke, E. P.; Seifert, P.

    2017-12-01

    The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

  13. Structural network heterogeneities and network dynamics: a possible dynamical mechanism for hippocampal memory reactivation.

    Science.gov (United States)

    Jablonski, Piotr; Poe, Gina; Zochowski, Michal

    2007-03-01

    The hippocampus has the capacity for reactivating recently acquired memories and it is hypothesized that one of the functions of sleep reactivation is the facilitation of consolidation of novel memory traces. The dynamic and network processes underlying such a reactivation remain, however, unknown. We show that such a reactivation characterized by local, self-sustained activity of a network region may be an inherent property of the recurrent excitatory-inhibitory network with a heterogeneous structure. The entry into the reactivation phase is mediated through a physiologically feasible regulation of global excitability and external input sources, while the reactivated component of the network is formed through induced network heterogeneities during learning. We show that structural changes needed for robust reactivation of a given network region are well within known physiological parameters.

  14. Simulation of Stimuli-Responsive Polymer Networks

    Directory of Open Access Journals (Sweden)

    Thomas Gruhn

    2013-11-01

    Full Text Available The structure and material properties of polymer networks can depend sensitively on changes in the environment. There is a great deal of progress in the development of stimuli-responsive hydrogels for applications like sensors, self-repairing materials or actuators. Biocompatible, smart hydrogels can be used for applications, such as controlled drug delivery and release, or for artificial muscles. Numerical studies have been performed on different length scales and levels of details. Macroscopic theories that describe the network systems with the help of continuous fields are suited to study effects like the stimuli-induced deformation of hydrogels on large scales. In this article, we discuss various macroscopic approaches and describe, in more detail, our phase field model, which allows the calculation of the hydrogel dynamics with the help of a free energy that considers physical and chemical impacts. On a mesoscopic level, polymer systems can be modeled with the help of the self-consistent field theory, which includes the interactions, connectivity, and the entropy of the polymer chains, and does not depend on constitutive equations. We present our recent extension of the method that allows the study of the formation of nano domains in reversibly crosslinked block copolymer networks. Molecular simulations of polymer networks allow the investigation of the behavior of specific systems on a microscopic scale. As an example for microscopic modeling of stimuli sensitive polymer networks, we present our Monte Carlo simulations of a filament network system with crosslinkers.

  15. Interaction of chimera states in a multilayered network of nonlocally coupled oscillators

    Science.gov (United States)

    Goremyko, M. V.; Maksimenko, V. A.; Makarov, V. V.; Ghosh, D.; Bera, B.; Dana, S. K.; Hramov, A. E.

    2017-08-01

    The processes of formation and evolution of chimera states in the model of a multilayered network of nonlinear elements with complex coupling topology are studied. A two-layered network of nonlocally intralayer-coupled Kuramoto-Sakaguchi phase oscillators is taken as the object of investigation. Different modes implemented in this system upon variation of the degree of interlayer interaction are demonstrated.

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

    African Journals Online (AJOL)

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

  17. A Planning Guide for Instructional Networks, Part I.

    Science.gov (United States)

    Daly, Kevin F.

    1994-01-01

    Discusses three phases in implementing a master plan for a school-based local area network (LAN): (1) network software selection; (2) hardware selection, network topology, and site preparation; and (3) implementation time table. Sample planning and specification worksheets and a list of planning guides are included. (Contains six references.) (KRN)

  18. Phase field model for the study of boiling

    International Nuclear Information System (INIS)

    Ruyer, P.

    2006-07-01

    This study concerns both the modeling and the numerical simulation of boiling flows. First we propose a review concerning nucleate boiling at high wall heat flux and focus more particularly on the current understanding of the boiling crisis. From this analysis we deduce a motivation for the numerical simulation of bubble growth dynamics. The main and remaining part of this study is then devoted to the development and analyze of a phase field model for the liquid-vapor flows with phase change. We propose a thermodynamic quasi-compressible formulation whose properties match the one required for the numerical study envisaged. The system of governing equations is a thermodynamically consistent regularization of the sharp interface model, that is the advantage of the di use interface models. We show that the thickness of the interface transition layer can be defined independently from the thermodynamic description of the bulk phases, a property that is numerically attractive. We derive the kinetic relation that allows to analyze the consequences of the phase field formulation on the model of the dissipative mechanisms. Finally we study the numerical resolution of the model with the help of simulations of phase transition in simple configurations as well as of isothermal bubble dynamics. (author)

  19. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

    Directory of Open Access Journals (Sweden)

    Firoozeh Zare-Farashbandi

    2014-01-01

    Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

  20. A Bayesian Approach to Measurement Bias in Networking Studies

    NARCIS (Netherlands)

    Zhu, Ling; Robinson, Scott E.; Torenvlied, René

    2014-01-01

    The study of managerial networking has been growing in the field of public administration; a field that analyzes how managers in open system organizations interact with different external actors and organizations. Coincident with this interest in managerial networking is the use of self-reported

  1. German risk study, phase (DRS-B)

    International Nuclear Information System (INIS)

    Werner, W.

    1992-01-01

    The first risk investigations were primarily intended to estimate the risk of accidents in nuclear power plants and to compare it with other natural risk and civilization risks. The American reactor safety study WASH 1400 and the German risk study phase A (DRS-A) gave a detailed analyses of the offsite consequences of accidents, especially the magnitude and frequency of health damage for the population. Risk investigations today are primarily used to examine the design of safety systems and to further develop the entire safety concept. Safety investigations have shown that nuclear power plants still possess safety reserves if safety systems do not operate as planned. These safety reserves can be exploited in the sense of a further development of safety by plant internal emergency measures. One purpose of risk analyses is to identify such measures and to evaluate their feasibility and effectiveness. The most important goals of the investigations in DRS-B were: Identification of vulnerabilities and possible safety improvements; determination of safety reserves during accident sequences exceeding the design limits; evaluation of plant internal emergency measures. Thus, goals in phase B compared with phase A have changed from investigations of the magnitude of damage to detailed analysis of the plant systems response under accident conditions. The magnitude of possible fission product releases is also determined in phase B. However, no new accident consequence calculations are performed. Figs and tabs

  2. Continuous-variable Measurement-device-independent Quantum Relay Network with Phase-sensitive Amplifiers

    Science.gov (United States)

    Li, Fei; Zhao, Wei; Guo, Ying

    2018-01-01

    Continuous-variable (CV) measurement-device-independent (MDI) quantum cryptography is now heading towards solving the practical problem of implementing scalable quantum networks. In this paper, we show that a solution can come from deploying an optical amplifier in the CV-MDI system, aiming to establish a high-rate quantum network. We suggest an improved CV-MDI protocol using the EPR states coupled with optical amplifiers. It can implement a practical quantum network scheme, where the legal participants create the secret correlations by using EPR states connecting to an untrusted relay via insecure links and applying the multi-entangled Greenberger-Horne-Zeilinger (GHZ) state analysis at relay station. Despite the possibility that the relay could be completely tampered with and imperfect links are subject to the powerful attacks, the legal participants are still able to extract a secret key from network communication. The numerical simulation indicates that the quantum network communication can be achieved in an asymmetric scenario, fulfilling the demands of a practical quantum network. Furthermore, we show that the use of optical amplifiers can compensate the inherent imperfections and improve the secret key rate of the CV-MDI system.

  3. Next Generation Access Network Deployment in Croatia: Optical Access Networks and Current IoT/5G Status

    Science.gov (United States)

    Breskovic, Damir; Sikirica, Mladen; Begusic, Dinko

    2018-05-01

    This paper gives an overview and background of optical access network deployment in Croatia. Optical access network development in Croatia has been put into a global as well as in the European Union context. All the challenges and the driving factors for optical access networks deployment are considered. Optical access network architectures that have been deployed by most of the investors in Croatian telecommunication market are presented, as well as the architectures that are in early phase of deployment. Finally, an overview on current status of mobile networks of the fifth generation and Internet of Things is given.

  4. Multiscale unfolding of real networks by geometric renormalization

    Science.gov (United States)

    García-Pérez, Guillermo; Boguñá, Marián; Serrano, M. Ángeles

    2018-06-01

    Symmetries in physical theories denote invariance under some transformation, such as self-similarity under a change of scale. The renormalization group provides a powerful framework to study these symmetries, leading to a better understanding of the universal properties of phase transitions. However, the small-world property of complex networks complicates application of the renormalization group by introducing correlations between coexisting scales. Here, we provide a framework for the investigation of complex networks at different resolutions. The approach is based on geometric representations, which have been shown to sustain network navigability and to reveal the mechanisms that govern network structure and evolution. We define a geometric renormalization group for networks by embedding them into an underlying hidden metric space. We find that real scale-free networks show geometric scaling under this renormalization group transformation. We unfold the networks in a self-similar multilayer shell that distinguishes the coexisting scales and their interactions. This in turn offers a basis for exploring critical phenomena and universality in complex networks. It also affords us immediate practical applications, including high-fidelity smaller-scale replicas of large networks and a multiscale navigation protocol in hyperbolic space, which betters those on single layers.

  5. Improving Focal Depth Estimates: Studies of Depth Phase Detection at Regional Distances

    Science.gov (United States)

    Stroujkova, A.; Reiter, D. T.; Shumway, R. H.

    2006-12-01

    The accurate estimation of the depth of small, regionally recorded events continues to be an important and difficult explosion monitoring research problem. Depth phases (free surface reflections) are the primary tool that seismologists use to constrain the depth of a seismic event. When depth phases from an event are detected, an accurate source depth is easily found by using the delay times of the depth phases relative to the P wave and a velocity profile near the source. Cepstral techniques, including cepstral F-statistics, represent a class of methods designed for the depth-phase detection and identification; however, they offer only a moderate level of success at epicentral distances less than 15°. This is due to complexities in the Pn coda, which can lead to numerous false detections in addition to the true phase detection. Therefore, cepstral methods cannot be used independently to reliably identify depth phases. Other evidence, such as apparent velocities, amplitudes and frequency content, must be used to confirm whether the phase is truly a depth phase. In this study we used a variety of array methods to estimate apparent phase velocities and arrival azimuths, including beam-forming, semblance analysis, MUltiple SIgnal Classification (MUSIC) (e.g., Schmidt, 1979), and cross-correlation (e.g., Cansi, 1995; Tibuleac and Herrin, 1997). To facilitate the processing and comparison of results, we developed a MATLAB-based processing tool, which allows application of all of these techniques (i.e., augmented cepstral processing) in a single environment. The main objective of this research was to combine the results of three focal-depth estimation techniques and their associated standard errors into a statistically valid unified depth estimate. The three techniques include: 1. Direct focal depth estimate from the depth-phase arrival times picked via augmented cepstral processing. 2. Hypocenter location from direct and surface-reflected arrivals observed on sparse

  6. Mass media influence spreading in social networks with community structure

    Science.gov (United States)

    Candia, Julián; Mazzitello, Karina I.

    2008-07-01

    We study an extension of Axelrod's model for social influence, in which cultural drift is represented as random perturbations, while mass media are introduced by means of an external field. In this scenario, we investigate how the modular structure of social networks affects the propagation of mass media messages across a society. The community structure of social networks is represented by coupled random networks, in which two random graphs are connected by intercommunity links. Considering inhomogeneous mass media fields, we study the conditions for successful message spreading and find a novel phase diagram in the multidimensional parameter space. These findings show that social modularity effects are of paramount importance for designing successful, cost-effective advertising campaigns.

  7. Knowledge Access in Rural Inter-connected Areas Network ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Knowledge Access in Rural Inter-connected Areas Network (KariaNet) - Phase II ... poor by sharing innovations, best practices and indigenous knowledge using ... A third thematic network - on knowledge management strategies - will play an ...

  8. Study of the full-service and low-cost carriers network configuration

    Directory of Open Access Journals (Sweden)

    Oriol Lordan

    2014-10-01

    Full Text Available Purpose: The network strategies used by airline carriers have been a recurring subject in air transport research. The aim of this paper is to investigate the relationship between the different operational characteristics of the airline and its route network configuration. Design/methodology/approach: The two main airline carrier typologies - Full-Service and Low-Cost carriers – are analysed using empirical models developed on complex network research relating them to the business model of the airlines. Findings and Originality/value: Just in Europe, one can differentiate between Full-Service and Low-Cost Carriers by complex network analyses. In this process, it has been also found that new concept Low-Cost Carriers, such as Vueling, have network properties closer to Full-Service Carriers. Research limitations/implications: This paper has a limited sample, as includes 26 airline case studies from Europe, United States and Asia. Practical implications: The analysis carried out in this research can help to the assessment of the evolution of the strategies of airline carriers, and has also operational implications, since the configuration of an airline route network can determine its resilience to attacks and errors. Social implications: A better understanding of the properties of airline route networks can benefit airlines, passengers and another stakeholders of the air transport industry. Originality/value: Current research on air transport networks has only considered the global or regional level, but few studies have addressed the study of airline transport networks, and its relationship with their business model.

  9. Oak Ridge Health Studies phase 1 report, Volume 1: Oak Ridge Phase 1 overview

    International Nuclear Information System (INIS)

    Yarbrough, M.I.; Van Cleave, M.L.; Turri, P.; Daniel, J.

    1993-09-01

    In July 1991, the State of Tennessee initiated the Health Studies Agreement with the United States Department of Energy to carry out independent studies of possible adverse health effects in people living in the vicinity of the Oak Ridge Reservation. The health studies focus on those effects that could have resulted or could result from exposures to chemicals and radioactivity released at the Reservation since 1942. The major focus of the first phase was to complete a Dose Reconstruction Feasibility Study. This study was designed to find out if enough data exist about chemical and radionuclide releases from the Oak Ridge Reservation to conduct a second phase. The second phase will lead to estimates of the actual amounts or the ''doses'' of various contaminants received by people as a result of off-site releases. Once the doses of various contaminants have been estimated, scientists and physicians will be better able to evaluate whether adverse health effects could have resulted from the releases

  10. Oak Ridge Health Studies phase 1 report, Volume 1: Oak Ridge Phase 1 overview

    Energy Technology Data Exchange (ETDEWEB)

    Yarbrough, M.I.; Van Cleave, M.L.; Turri, P.; Daniel, J.

    1993-09-01

    In July 1991, the State of Tennessee initiated the Health Studies Agreement with the United States Department of Energy to carry out independent studies of possible adverse health effects in people living in the vicinity of the Oak Ridge Reservation. The health studies focus on those effects that could have resulted or could result from exposures to chemicals and radioactivity released at the Reservation since 1942. The major focus of the first phase was to complete a Dose Reconstruction Feasibility Study. This study was designed to find out if enough data exist about chemical and radionuclide releases from the Oak Ridge Reservation to conduct a second phase. The second phase will lead to estimates of the actual amounts or the ``doses`` of various contaminants received by people as a result of off-site releases. Once the doses of various contaminants have been estimated, scientists and physicians will be better able to evaluate whether adverse health effects could have resulted from the releases.

  11. German risk study on nuclear power stations. Phase B

    International Nuclear Information System (INIS)

    1989-11-01

    The German Risk Study on Nuclear Power Stations is concerned with investigations of accidents in nuclear facilities and their associated risks. These investigations are undertaken on behalf of the federal Minister of Research and Technology. They have been broken down into two phases (Phase A and Phase B). The results of Phase A were published in 1979 (GRS 79). This report contains a summary of the investigations relating to Phase B. After an introduction setting out the basic principles and aim of the study, a general review will be given of the most important results. The course of the investigations and the results have already been published in a Technical Report (GRS 89). (author)

  12. SELENE - Self-Forming Extensible Lunar EVA Network, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The Lunar EVA network will exhibit a wide range of connectivity levels due to the challenging communications environment and mission dynamics. Disruption-Tolerant...

  13. Synchronization in a non-uniform network of excitatory spiking neurons

    Science.gov (United States)

    Echeveste, Rodrigo; Gros, Claudius

    Spontaneous synchronization of pulse coupled elements is ubiquitous in nature and seems to be of vital importance for life. Networks of pacemaker cells in the heart, extended populations of southeast asian fireflies, and neuronal oscillations in cortical networks, are examples of this. In the present work, a rich repertoire of dynamical states with different degrees of synchronization are found in a network of excitatory-only spiking neurons connected in a non-uniform fashion. In particular, uncorrelated and partially correlated states are found without the need for inhibitory neurons or external currents. The phase transitions between these states, as well the robustness, stability, and response of the network to external stimulus are studied.

  14. A novel use of a statewide telecolposcopy network for recruitment of participants in a Phase I clinical trial of a human papillomavirus therapeutic vaccine.

    Science.gov (United States)

    Stratton, Shawna L; Spencer, Horace J; Greenfield, William W; Low, Gordon; Hitt, Wilbur C; Quick, Charles M; Jeffus, Susanne K; Blackmon, Victoria; Nakagawa, Mayumi

    2015-06-01

    Historically, recruitment and retention of young women in intervention-based clinical trials have been challenging. In August 2012, enrollment for a clinical trial testing of an investigational human papillomavirus therapeutic vaccine called PepCan was opened at our institution. This study was an open-label, single-arm, single-institution, dose-escalation Phase I clinical trial. Women with recent Papanicolaou smear results showing high-grade squamous intraepithelial lesions or results that could not rule out high-grade squamous intraepithelial lesion were eligible to enroll. Patients with biopsy-confirmed high-grade squamous intraepithelial lesion were also eligible. Colposcopy was performed at the screening visit, and participants became eligible for vaccination when the diagnosis of high-grade squamous intraepithelial lesion was confirmed with biopsy and other inclusion criteria were met. The aim of this study was to identify strategies and factors effective in recruitment and retention of study participants. Potential vaccine candidates were recruited through direct advertisement as well as referrals, including referrals through the Arkansas telecolposcopy network. The network is a federally funded program, administered by physicians and advanced practice nurses. The network telemedically links rural health sites and allows physician-guided colposcopy and biopsies to be conducted by advanced practice nurses. A variety of strategies were employed to assure good retention, including face-to-face contact with the study coordinator at the time of consent and most of study visits; frequent contact using text messaging, phone calls, and e-mails; and creation of a private Facebook page to improve communication among research staff and study participants. A questionnaire, inquiring about motivation for joining the study, occupation, education, household income, number of children, and number of sexual partners, was administered at the screening visit with the intent of

  15. Predicting geomagnetic storms from solar-wind data using time-delay neural networks

    Directory of Open Access Journals (Sweden)

    H. Gleisner

    1996-07-01

    Full Text Available We have used time-delay feed-forward neural networks to compute the geomagnetic-activity index Dst one hour ahead from a temporal sequence of solar-wind data. The input data include solar-wind density n, velocity V and the southward component Bz of the interplanetary magnetic field. Dst is not included in the input data. The networks implement an explicit functional relationship between the solar wind and the geomagnetic disturbance, including both direct and time-delayed non-linear relations. In this study we especially consider the influence of varying the temporal size of the input-data sequence. The networks are trained on data covering 6600 h, and tested on data covering 2100 h. It is found that the initial and main phases of geomagnetic storms are well predicted, almost independent of the length of the input-data sequence. However, to predict the recovery phase, we have to use up to 20 h of solar-wind input data. The recovery phase is mainly governed by the ring-current loss processes, and is very much dependent on the ring-current history, and thus also the solar-wind history. With due consideration of the time history when optimizing the networks, we can reproduce 84% of the Dst variance.

  16. Reconstruction of networks from one-step data by matching positions

    Science.gov (United States)

    Wu, Jianshe; Dang, Ni; Jiao, Yang

    2018-05-01

    It is a challenge in estimating the topology of a network from short time series data. In this paper, matching positions is developed to reconstruct the topology of a network from only one-step data. We consider a general network model of coupled agents, in which the phase transformation of each node is determined by its neighbors. From the phase transformation information from one step to the next, the connections of the tail vertices are reconstructed firstly by the matching positions. Removing the already reconstructed vertices, and repeatedly reconstructing the connections of tail vertices, the topology of the entire network is reconstructed. For sparse scale-free networks with more than ten thousands nodes, we almost obtain the actual topology using only the one-step data in simulations.

  17. Studying Policy Transfer through the Lens of Social Network Analysis

    DEFF Research Database (Denmark)

    Staunæs, Dorthe; Brøgger, Katja; Steiner-Khamsi, Gita

    Studying Policy Transfer through the Lens of Social Network Analysis The panelists present the findings of a joint empirical research project carried out at Aarhus University (DPU/Copenhagen) and at Teachers College, Columbia University (New York). The research project succeeded to identify...... discursive networks of political stakeholders and policy advisors that were considered key actors in the Danish school reform. The research team investigated how these networks interrelate, change over time, and represent different constituents (government, academe, business), at times contradicting...... or collaborating with each other, respectively. Against the backdrop of globalization studies in comparative education, the research project attempted to identify borrowers, translators, and brokers of educational reform drawing on a complementary set of expertise from social network analysis methodology (Oren...

  18. A soil moisture network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, N.; Jensen, Karsten Høgh

    2012-01-01

    network was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS...... between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved soil moisture (R2 of 0.49) as well as initial soil......). Based on these findings, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies...

  19. Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

    Science.gov (United States)

    Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

    2016-05-01

    Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

  20. Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

    Science.gov (United States)

    Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca

    2014-12-01

    The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.