Science.gov

Sample records for network flow based

  1. Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.

    PubMed

    Bacik, Karol A; Schaub, Michael T; Beguerisse-Díaz, Mariano; Billeh, Yazan N; Barahona, Mauricio

    2016-08-01

    We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios. PMID:27494178

  2. Flow-Based Network Analysis of the Caenorhabditis elegans Connectome

    PubMed Central

    Bacik, Karol A.; Schaub, Michael T.; Billeh, Yazan N.; Barahona, Mauricio

    2016-01-01

    We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios. PMID:27494178

  3. Cilia-based flow network in the brain ventricles.

    PubMed

    Faubel, Regina; Westendorf, Christian; Bodenschatz, Eberhard; Eichele, Gregor

    2016-07-01

    Cerebrospinal fluid conveys many physiologically important signaling factors through the ventricular cavities of the brain. We investigated the transport of cerebrospinal fluid in the third ventricle of the mouse brain and discovered a highly organized pattern of cilia modules, which collectively give rise to a network of fluid flows that allows for precise transport within this ventricle. We also discovered a cilia-based switch that reliably and periodically alters the flow pattern so as to create a dynamic subdivision that may control substance distribution in the third ventricle. Complex flow patterns were also present in the third ventricles of rats and pigs. Our work suggests that ciliated epithelia can generate and maintain complex, spatiotemporally regulated flow networks. PMID:27387952

  4. International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis

    PubMed Central

    Shen, Bin; Zhang, Jiang; Li, Yixiao; Zheng, Qiuhua; Li, Xingsen

    2015-01-01

    This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries’ roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading “trophic levels” have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows. PMID:26569618

  5. International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis.

    PubMed

    Shen, Bin; Zhang, Jiang; Li, Yixiao; Zheng, Qiuhua; Li, Xingsen

    2015-01-01

    This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries' roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading "trophic levels" have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows. PMID:26569618

  6. Water flow based geometric active deformable model for road network

    NASA Astrophysics Data System (ADS)

    Leninisha, Shanmugam; Vani, Kaliaperumal

    2015-04-01

    A width and color based geometric active deformable model is proposed for road network extraction from remote sensing images with minimal human interception. Orientation and width of road are computed from a single manual seed point, from which the propagation starts both right and left hand directions of the starting point, which extracts the interconnected road network from the aerial or high spatial resolution satellite image automatically. Here the propagation (like water flow in canal with defined boundary) is restricted with color and width of the road. Road extraction is done for linear, curvilinear (U shape and S shape) roads first, irrespective of width and color. Then, this algorithm is improved to extract road with junctions in a shape of L, T and X along with center line. Roads with small break or disconnected roads are also extracts by a modified version of this same algorithm. This methodology is tested and evaluated with various remote sensing images. The experimental results show that the proposed method is efficient and extracting roads accurately with less computation time. However, in complex urban areas, the identification accuracy declines due to the various sizes of obstacles, over bridges, multilane etc.

  7. Architecture Design and Experimental Platform Demonstration of Optical Network based on OpenFlow Protocol

    NASA Astrophysics Data System (ADS)

    Xing, Fangyuan; Wang, Honghuan; Yin, Hongxi; Li, Ming; Luo, Shenzi; Wu, Chenguang

    2016-02-01

    With the extensive application of cloud computing and data centres, as well as the constantly emerging services, the big data with the burst characteristic has brought huge challenges to optical networks. Consequently, the software defined optical network (SDON) that combines optical networks with software defined network (SDN), has attracted much attention. In this paper, an OpenFlow-enabled optical node employed in optical cross-connect (OXC) and reconfigurable optical add/drop multiplexer (ROADM), is proposed. An open source OpenFlow controller is extended on routing strategies. In addition, the experiment platform based on OpenFlow protocol for software defined optical network, is designed. The feasibility and availability of the OpenFlow-enabled optical nodes and the extended OpenFlow controller are validated by the connectivity test, protection switching and load balancing experiments in this test platform.

  8. Multipath protection for data center services in OpenFlow-based software defined elastic optical networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Cheng, Lei; Yuan, Jian; Zhang, Jie; Zhao, Yongli; Lee, Young

    2015-06-01

    With the rapid growth of data center services, the elastic optical network is a very promising networking architecture to interconnect data centers because it can elastically allocate spectrum tailored for various bandwidth requirements. In case of a link failure, to ensure a high-level quality of service (QoS) for user request after the failure becomes a research focus. In light of it, in this paper, we propose and experimentally demonstrate multipath protection for data center services in OpenFlow-based software defined elastic optical network testbed aiming at improving network reliability. We first propose an OpenFlow-based software defined elastic optical network architecture for data center service protection. Then, based on the proposed architecture, multipath protection scheme is figured based on the importance level of the service. To implement the proposed scheme in the architecture, OpenFlow protocol is extended to support multipath protection in elastic optical network. The performance of our proposed multipath protection scheme is evaluated by means of experiment on our OpenFlow-based testbed. The feasibility of our proposed scheme is also demonstrated in software defined elastic optical networks.

  9. Simulation based flow distribution network optimization for vacuum assisted resin transfer moulding process

    NASA Astrophysics Data System (ADS)

    Hsiao, Kuang-Ting; Devillard, Mathieu; Advani, Suresh G.

    2004-05-01

    In the vacuum assisted resin transfer moulding (VARTM) process, using a flow distribution network such as flow channels and high permeability fabrics can accelerate the resin infiltration of the fibre reinforcement during the manufacture of composite parts. The flow distribution network significantly influences the fill time and fill pattern and is essential for the process design. The current practice has been to cover the top surface of the fibre preform with the distribution media with the hope that the resin will flood the top surface immediately and penetrate through the thickness. However, this approach has some drawbacks. One is when the resin finds its way to the vent before it has penetrated the preform entirely, which results in a defective part or resin wastage. Also, if the composite structure contains ribs or inserts, this approach invariably results in dry spots. Instead of this intuitive approach, we propose a science-based approach to design the layout of the distribution network. Our approach uses flow simulation of the resin into the network and the preform and a genetic algorithm to optimize the flow distribution network. An experimental case study of a co-cured rib structure is conducted to demonstrate the design procedure and validate the optimized flow distribution network design. Good agreement between the flow simulations and the experimental results was observed. It was found that the proposed design algorithm effectively optimized the flow distribution network of the part considered in our case study and hence should prove to be a useful tool to extend the VARTM process to manufacture of complex structures with effective use of the distribution network layup.

  10. Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

    NASA Technical Reports Server (NTRS)

    Schallhorn, Paul; Majumdar, Alok

    2012-01-01

    This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

  11. Network-based representation of energy transfer in unsteady separated flow

    NASA Astrophysics Data System (ADS)

    Nair, Aditya; Taira, Kunihiko

    2015-11-01

    We construct a network-based representation of energy pathways in unsteady separated flows using a POD-Galerkin projection model. In this formulation, we regard the POD modes as the network nodes and the energy transfer between the modes as the network edges. Based on the energy transfer analysis performed by Noack et al. (2008), edge weights are characterized on the interaction graph. As an example, we examine the energy transfer within the two-dimensional incompressible flow over a circular cylinder. In particular, we analyze the energy pathways involved in flow transition from the unstable symmetric steady state to periodic shedding cycle. The growth of perturbation energy over the network is examined to highlight key features of flow physics and to determine how the energy transfer can be influenced. Furthermore, we implement closed-loop flow control on the POD-Galerkin model to alter the energy interaction path and modify the global behavior of the wake dynamics. The insights gained will be used to perform further network analysis on fluid flows with added complexity. Work supported by US Army Research Office (W911NF-14-1-0386) and US Air Force Office of Scientific Research (YIP: FA9550-13-1-0183).

  12. Serial Network Flow Monitor

    NASA Technical Reports Server (NTRS)

    Robinson, Julie A.; Tate-Brown, Judy M.

    2009-01-01

    Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

  13. Anisotropic optical flow algorithm based on self-adaptive cellular neural network

    NASA Astrophysics Data System (ADS)

    Zhang, Congxuan; Chen, Zhen; Li, Ming; Sun, Kaiqiong

    2013-01-01

    An anisotropic optical flow estimation method based on self-adaptive cellular neural networks (CNN) is proposed. First, a novel optical flow energy function which contains a robust data term and an anisotropic smoothing term is projected. Next, the CNN model which has the self-adaptive feedback operator and threshold is presented according to the Euler-Lagrange partial differential equations of the proposed optical flow energy function. Finally, the elaborate evaluation experiments indicate the significant effects of the various proposed strategies for optical flow estimation, and the comparison results with the other methods show that the proposed algorithm has better performance in computing accuracy and efficiency.

  14. A neural network-based power system stabilizer using power flow characteristics

    SciTech Connect

    Park, Y.M.; Choi, M.S.; Lee, K.Y.

    1996-06-01

    A neural network-based Power System Stabilizer (Neuro-PSS) is designed for a generator connected to a multi-machine power system utilizing the nonlinear power flow dynamics. The uses of power flow dynamics provide a PSS for a wide range operation with reduced size neutral networks. The Neuro-PSS consists of two neutral networks: Neuro-Identifier and Neuro-Controller. The low-frequency oscillation is modeled by the Neuro-Identifier using the power flow dynamics, then a Generalized Backpropagation-Thorough-Time (GBTT) algorithm is developed to train the Neuro-Controller. The simulation results show that the Neuro-PSS designed in this paper performs well with good damping in a wide operation range compared with the conventional PSS.

  15. Entropy-based snow network design for spring peak flow forecasting

    NASA Astrophysics Data System (ADS)

    Keum, J.; Coulibaly, P. D.; Tapsoba, D.

    2015-12-01

    In northern regions the dominant phase of precipitation is snow, this precipitation persists and accumulates throughout the winter season until freshet. Quantitative information on snow, such as snow water equivalent and snow cover extent, is essential for water resources management in northern regions. Due to the inaccessibility and remoteness of snow course locations, snow surveys are usually expensive. Therefore an efficient network design strategy is required to provide a maximum amount of information while also minimizing the network cost. In this study, an entropy-based multiobjective optimization method is applied to design a snow network by adding new stations to the existing network in the La Grande River Basin of Quebec, Canada. Three hydrologic models, Sacramento, HBV, and HSAMI, are calibrated to 12 subwatersheds in the La Grande River Basin. Pareto optimal networks are given by the multiobjective optimization by maximizing joint entropy and minimizing total correlation. Each of the potential optimal networks is then evaluated using the calibrated hydrologic models to determine the most appropriate network for spring peak flow forecasting. The proposed methodology provides useful information for designing snow network appropriate for spring peak flow forecasting, which is essential for reservoir operation.

  16. Experimental demonstration of time-aware software defined networking for OpenFlow-based intra-datacenter optical interconnection networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Zhang, Jie; Zhao, Yongli; Ji, Yuefeng; Han, Jianrui; Lin, Yi; Qiu, Shaofeng; Lee, Young

    2014-06-01

    Nowadays, most service providers offer their services and support their applications through federated sets of data centers which need to be interconnected using high-capacity optical networks in intra-datacenter networks. Many datacenter applications in the environment require lower delay and higher availability with the end-to-end guaranteed quality of service. In this paper, we propose a novel time-aware software defined networking (TaSDN) architecture for OpenFlow-based intra-datacenter optical interconnection networks. Based on the proposed architecture, a time-aware service scheduling (TaSS) strategy is introduced to allocate the network and datacenter resources optimally, which considers the datacenter service scheduling with flexible service time and service bandwidth according to the various time sensitivity requirements. The TaSDN can arrange and accommodate the applications with required QoS considering the time factor, and enhance the data center responsiveness to quickly provide for intra-datacenter service demands. The overall feasibility of the proposed architecture is experimentally verified on our testbed with real OpenFlow-enabled tunable optical modules. The performance of TaSS strategy under heavy traffic load scenario is also evaluated based on TaSDN architecture in terms of blocking probability and resource occupation rate.

  17. Experimental demonstration of OpenFlow-based control plane for elastic lightpath provisioning in Flexi-Grid optical networks.

    PubMed

    Zhang, Jiawei; Zhang, Jie; Zhao, Yongli; Yang, Hui; Yu, Xiaosong; Wang, Lei; Fu, Xihua

    2013-01-28

    Due to the prominent performance on networking virtualization and programmability, OpenFlow is widely regarded as a promising control plane technology in packet-switched IP networks as well as wavelength-switched optical networks. For the purpose of applying software programmable feature to future optical networks, we propose an OpenFlow-based control plane in Flexi-Grid optical networks. Experimental results demonstrate its feasibility of dynamic lightpath establishment and adjustment via extended OpenFlow protocol. Wireshark captures of the signaling procedure are printed out. Additionally, the overall latency including signaling and hardware for lightpath setup and adjustment is also reported. PMID:23389119

  18. Modality transition-based network from multivariate time series for characterizing horizontal oil-water flow patterns

    NASA Astrophysics Data System (ADS)

    Ding, Mei-Shuang; Jin, Ning-De; Gao, Zhong-Ke

    2015-11-01

    The simultaneous flow of oil and water through a horizontal pipe is a common occurrence during petroleum industrial processes. Characterizing the flow behavior underlying horizontal oil-water flows is a challenging problem of significant importance. In order to solve this problem, we carry out experiment to measure multivariate signals from different flow patterns and then propose a novel modality transition-based network to analyze the multivariate signals. The results suggest that the local betweenness centrality and weighted shortest path of the constructed network can characterize the transitions of flow conditions and further allow quantitatively distinguishing and uncovering the dynamic flow behavior underlying different horizontal oil-water flow patterns.

  19. Characterization of Horizontal Gas-Liquid Two-Phase Flow Using Markov Model-Based Complex Network

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

    Horizontal gas-liquid two-phase flow widely exists in many physical systems and chemical engineering processes. Compared with vertical upward gas-liquid two-phase flow, investigations on dynamic behavior underlying horizontal gas-liquid flows are quite limited. Complex network provides a powerful framework for time series analysis of complex dynamical systems. We use a network generation method based on Markov transition probability to infer directed weighted complex networks from signals measured from horizontal gas-liquid two-phase flow experiment and find that the networks corresponding to different flow patterns exhibit different network structure. To investigate the dynamic characteristics of horizontal gas-liquid flows, we construct a number of complex networks under different flow conditions, and explore the network indices for each constructed network. In addition, we investigate the sample entropy of different flow patterns. Our results suggest that the network statistic can well represent the complexity in the transition among different flow patterns and further allows characterizing the interface fluctuation behavior in horizontal gas-liquid two-phase flow.

  20. MEDUSA - An overset grid flow solver for network-based parallel computer systems

    NASA Technical Reports Server (NTRS)

    Smith, Merritt H.; Pallis, Jani M.

    1993-01-01

    Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

  1. PSO Based Optimal Power Flow with FACTS Devices for Security Enhancement Considering Credible Network Contingencies

    NASA Astrophysics Data System (ADS)

    Rambabu, C.; Obulesu, Y. P.; Saibabu, Ch.

    2014-07-01

    This work presents particle swarm optimization (PSO) based method to solve the optimal power flow in power systems incorporating flexible AC transmission systems controllers such as thyristor controlled phase shifter, thyristor controlled series compensator and unified power flow controller for security enhancement under single network contingencies. A fuzzy contingency ranking method is used in this paper and observed that it effectively eliminates the masking effect when compared with other methods of contingency ranking. The fuzzy based network composite overall severity index is used as an objective to be minimized to improve the security of the power system. The proposed optimization process with PSO is presented with case study example using IEEE 30-bus test system to demonstrate its applicability. The results are presented to show the feasibility and potential of this new approach.

  2. Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

    PubMed Central

    Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

    2016-01-01

    Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

  3. Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

    PubMed

    Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

    2016-01-01

    Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance. PMID:27006977

  4. Classification and Prediction of Traffic Flow Based on Real Data Using Neural Networks

    NASA Astrophysics Data System (ADS)

    Pamuła, Teresa

    2012-12-01

    This paper presents a method of classification of time series of traffic flow, on the section of the main road leading into the city of Gliwice. Video detectors recorded traffic volume data was used, covering the period of one year in 5-minute intervals - from June 2011 to May 2012. In order to classify the data a statistical analysis was performed, which resulted in the proposition of splitting the daily time series into four classes. The series were smoothed to obtain hourly flow rates. The classification was performed using neural networks with different structures and using a variable number of input data. The purpose of classification is the prediction of traffic flow rates in the afternoon basing on the morning traffic and the assessment of daily traffic volumes for a particular day of the week. The results can be utilized by intelligent urban traffic management systems.

  5. Flow distances on open flow networks

    NASA Astrophysics Data System (ADS)

    Guo, Liangzhu; Lou, Xiaodan; Shi, Peiteng; Wang, Jun; Huang, Xiaohan; Zhang, Jiang

    2015-11-01

    An open flow network is a weighted directed graph with a source and a sink, depicting flux distributions on networks in the steady state mode of an open flow system. Energetic food webs, economic input-output networks, and international trade networks are open flow network models of energy flows between species, money or value flows between industrial sectors, and goods flows between countries, respectively. An open flow network is different from a closed flow network because it considers the flows from or to the environment (the source and the sink). For instance, in energetic food webs, species obtain energy not only from other species but also from the environment (sunlight), and species also dissipate energy to the environment. Flow distances between any two nodes i and j are defined as the average number of transition steps of a random walker along the network from i to j. The conventional method for the calculation of the random walk distance on closed flow networks cannot be applied to open flow networks. Therefore, we derive novel explicit expressions for flow distances of open flow networks according to their underlying Markov matrix of the network in this paper. We apply flow distances to two types of empirical open flow networks, including energetic food webs and economic input-output networks. In energetic food webs, we visualize the trophic level of each species and compare flow distances with other distance metrics on the graph. In economic input-output networks, we rank sectors according to their average flow distances and cluster sectors into different industrial groups with strong connections. Other potential applications and mathematical properties are also discussed. To summarize, flow distance is a useful and powerful tool to study open flow systems.

  6. A Line Weighted Frequency Droop Controller for Decentralized Enforcement of Transmission Line Power Flow Constraints in Inverter-Based Networks

    SciTech Connect

    Ainsworth, Nathan G; Grijalva, Prof. Santiago

    2013-01-01

    Recent works have shown that networks of voltagesource inverters implementing frequency droop control may be analyzed as consensus-like networks. Based on this understanding, we show that enforcement of network line power flows can be viewed as an edge-preservation problem in a -disk dynamic interaction graph. Inspired by other works solving similar problems in other domains, we propose a line weighted frequency droop controller such that a network of all active buses implementing this controller enforces the specified line power flow constraints without need for communication. We provide simulation results verifying that our proposed controller limits line power to enforce constraints, and otherwise acts as a traditional droop controller.

  7. Lambda Station: On-demand flow based routing for data intensive Grid applications over multitopology networks

    SciTech Connect

    Bobyshev, A.; Crawford, M.; DeMar, P.; Grigaliunas, V.; Grigoriev, M.; Moibenko, A.; Petravick, D.; Rechenmacher, R.; Newman, H.; Bunn, J.; Van Lingen, F.; Nae, D.; Ravot, S.; Steenberg, C.; Su, X.; Thomas, M.; Xia, Y.; /Caltech

    2006-08-01

    Lambda Station is an ongoing project of Fermi National Accelerator Laboratory and the California Institute of Technology. The goal of this project is to design, develop and deploy network services for path selection, admission control and flow based forwarding of traffic among data-intensive Grid applications such as are used in High Energy Physics and other communities. Lambda Station deals with the last-mile problem in local area networks, connecting production clusters through a rich array of wide area networks. Selective forwarding of traffic is controlled dynamically at the demand of applications. This paper introduces the motivation of this project, design principles and current status. Integration of Lambda Station client API with the essential Grid middleware such as the dCache/SRM Storage Resource Manager is also described. Finally, the results of applying Lambda Station services to development and production clusters at Fermilab and Caltech over advanced networks such as DOE's UltraScience Net and NSF's UltraLight is covered.

  8. An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

    PubMed Central

    Guan, Xiangmin; Zhang, Xuejun; Zhu, Yanbo; Sun, Dengfeng; Lei, Jiaxing

    2015-01-01

    Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

  9. An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework.

    PubMed

    Guan, Xiangmin; Zhang, Xuejun; Zhu, Yanbo; Sun, Dengfeng; Lei, Jiaxing

    2015-01-01

    Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology. PMID:26180840

  10. Constraints of nonresponding flows based on cross layers in the networks

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi-Chao; Xiao, Yang; Wang, Dong

    2016-02-01

    In the active queue management (AQM) scheme, core routers cannot manage and constrain user datagram protocol (UDP) data flows by the sliding window control mechanism in the transport layer due to the nonresponsive nature of such traffic flows. However, the UDP traffics occupy a large part of the network service nowadays which brings a great challenge to the stability of the more and more complex networks. To solve the uncontrollable problem, this paper proposes a cross layers random early detection (CLRED) scheme, which can control the nonresponding UDP-like flows rate effectively when congestion occurs in the access point (AP). The CLRED makes use of the MAC frame acknowledgement (ACK) transmitting congestion information to the sources nodes and utilizes the back-off windows of the MAC layer throttling data rate. Consequently, the UDP-like flows data rate can be restrained timely by the sources nodes in order to alleviate congestion in the complex networks. The proposed CLRED can constrain the nonresponsive flows availably and make the communication expedite, so that the network can sustain stable. The simulation results of network simulator-2 (NS2) verify the proposed CLRED scheme.

  11. A compensation-based power flow method for weakly meshed distribution and transmission networks

    SciTech Connect

    Shirmohammadi, D.; Hong, H.W.; Semlyen, A.; Luo, G.X.

    1988-05-01

    This paper describes a new power flow method for solving weakly meshed distribution and transmission networks, using a multi-port compensation technique and basic formulation of Kirchhoff's laws. This method has excellent convergence characteristics and is very robust. A computer program implementing this power flow solution scheme was developed and successfully applied to several practical distribution networks with radial and weakly meshed structure. This program was also successfully used for solving radial and weakly meshed transmission networks. The method can be applied to the solution of both the three-phase (unbalanced) and single-phase (balanced) representation of the network. In this paper, however, only the single phase representation is treated in detail.

  12. A Network Flow-based Analysis of Cognitive Reserve in Normal Ageing and Alzheimer's Disease.

    PubMed

    Wook Yoo, Sang; Han, Cheol E; Shin, Joseph S; Won Seo, Sang; Na, Duk L; Kaiser, Marcus; Jeong, Yong; Seong, Joon-Kyung

    2015-01-01

    Cognitive reserve is the ability to sustain cognitive function even with a certain amount of brain damages. Here we investigate the neural compensation mechanism of cognitive reserve from the perspective of structural brain connectivity. Our goal was to show that normal people with high education levels (i.e., cognitive reserve) maintain abundant pathways connecting any two brain regions, providing better compensation or resilience after brain damage. Accordingly, patients with high education levels show more deterioration in structural brain connectivity than those with low education levels before symptoms of Alzheimer's disease (AD) become apparent. To test this hypothesis, we use network flow measuring the number of alternative paths between two brain regions in the brain network. The experimental results show that for normal aging, education strengthens network reliability, as measured through flow values, in a subnetwork centered at the supramarginal gyrus. For AD, a subnetwork centered at the left middle frontal gyrus shows a negative correlation between flow and education, which implies more collapse in structural brain connectivity for highly educated patients. We conclude that cognitive reserve may come from the ability of network reorganization to secure the information flow within the brain network, therefore making it more resistant to disease progress. PMID:25992968

  13. Stochastic cycle selection in active flow networks.

    PubMed

    Woodhouse, Francis G; Forrow, Aden; Fawcett, Joanna B; Dunkel, Jörn

    2016-07-19

    Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. PMID:27382186

  14. A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem

    PubMed Central

    Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

    2015-01-01

    Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity. PMID:26180842

  15. A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

    PubMed

    Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

    2015-01-01

    Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity. PMID:26180842

  16. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

  17. Research on the multicast mechanism based on physical-layer-impairment awareness model for OpenFlow optical network

    NASA Astrophysics Data System (ADS)

    Bai, Hui-feng; Zhou, Zi-guan; Song, Yan-bin

    2016-05-01

    A physical-layer-impairment (PLI)-awareness based optical multicast mechanism is proposed for OpenFlow controlled optical networks. This proposed approach takes the PLI models including linear and non-linear factors into optical multicast controlled by OpenFlow protocol. Thus, the proposed scheme is able to cover nearly all PLI factors of each optical link and to conduct optical multicast with better communication quality. Simulation results show that the proposed scheme can obtain the better performance of OpenFlow controlled optical multicast services.

  18. Modeling of Cerebral Oxygen Transport Based on In vivo Microscopic Imaging of Microvascular Network Structure, Blood Flow, and Oxygenation

    PubMed Central

    Gagnon, Louis; Smith, Amy F.; Boas, David A.; Devor, Anna; Secomb, Timothy W.; Sakadžić, Sava

    2016-01-01

    Oxygen is delivered to brain tissue by a dense network of microvessels, which actively control cerebral blood flow (CBF) through vasodilation and contraction in response to changing levels of neural activity. Understanding these network-level processes is immediately relevant for (1) interpretation of functional Magnetic Resonance Imaging (fMRI) signals, and (2) investigation of neurological diseases in which a deterioration of neurovascular and neuro-metabolic physiology contributes to motor and cognitive decline. Experimental data on the structure, flow and oxygen levels of microvascular networks are needed, together with theoretical methods to integrate this information and predict physiologically relevant properties that are not directly measurable. Recent progress in optical imaging technologies for high-resolution in vivo measurement of the cerebral microvascular architecture, blood flow, and oxygenation enables construction of detailed computational models of cerebral hemodynamics and oxygen transport based on realistic three-dimensional microvascular networks. In this article, we review state-of-the-art optical microscopy technologies for quantitative in vivo imaging of cerebral microvascular structure, blood flow and oxygenation, and theoretical methods that utilize such data to generate spatially resolved models for blood flow and oxygen transport. These “bottom-up” models are essential for the understanding of the processes governing brain oxygenation in normal and disease states and for eventual translation of the lessons learned from animal studies to humans.

  19. Modeling information flow in biological networks

    NASA Astrophysics Data System (ADS)

    Kim, Yoo-Ah; Przytycki, Jozef H.; Wuchty, Stefan; Przytycka, Teresa M.

    2011-06-01

    Large-scale molecular interaction networks are being increasingly used to provide a system level view of cellular processes. Modeling communications between nodes in such huge networks as information flows is useful for dissecting dynamical dependences between individual network components. In the information flow model, individual nodes are assumed to communicate with each other by propagating the signals through intermediate nodes in the network. In this paper, we first provide an overview of the state of the art of research in the network analysis based on information flow models. In the second part, we describe our computational method underlying our recent work on discovering dysregulated pathways in glioma. Motivated by applications to inferring information flow from genotype to phenotype in a very large human interaction network, we generalized previous approaches to compute information flows for a large number of instances and also provided a formal proof for the method.

  20. Hour-Glass Neural Network Based Daily Money Flow Estimation for Automatic Teller Machines

    NASA Astrophysics Data System (ADS)

    Karungaru, Stephen; Akashi, Takuya; Nakano, Miyoko; Fukumi, Minoru

    Monetary transactions using Automated Teller Machines (ATMs) have become a normal part of our daily lives. At ATMs, one can withdraw, send or debit money and even update passbooks among many other possible functions. ATMs are turning the banking sector into a ubiquitous service. However, while the advantages for the ATM users (financial institution customers) are many, the financial institution side faces an uphill task in management and maintaining the cash flow in the ATMs. On one hand, too much money in a rarely used ATM is wasteful, while on the other, insufficient amounts would adversely affect the customers and may result in a lost business opportunity for the financial institution. Therefore, in this paper, we propose a daily cash flow estimation system using neural networks that enables better daily forecasting of the money required at the ATMs. The neural network used in this work is a five layered hour glass shaped structure that achieves fast learning, even for the time series data for which seasonality and trend feature extraction is difficult. Feature extraction is carried out using the Akamatsu Integral and Differential transforms. This work achieves an average estimation accuracy of 92.6%.

  1. Intra-Urban Movement Flow Estimation Using Location Based Social Networking Data

    NASA Astrophysics Data System (ADS)

    Kheiri, A.; Karimipour, F.; Forghani, M.

    2015-12-01

    In recent years, there has been a rapid growth of location-based social networking services, such as Foursquare and Facebook, which have attracted an increasing number of users and greatly enriched their urban experience. Location-based social network data, as a new travel demand data source, seems to be an alternative or complement to survey data in the study of mobility behavior and activity analysis because of its relatively high access and low cost. In this paper, three OD estimation models have been utilized in order to investigate their relative performance when using Location-Based Social Networking (LBSN) data. For this, the Foursquare LBSN data was used to analyze the intra-urban movement behavioral patterns for the study area, Manhattan, the most densely populated of the five boroughs of New York city. The outputs of models are evaluated using real observations based on different criterions including distance distribution, destination travel constraints. The results demonstrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.

  2. Using higher-order Markov models to reveal flow-based communities in networks

    NASA Astrophysics Data System (ADS)

    Salnikov, Vsevolod; Schaub, Michael T.; Lambiotte, Renaud

    2016-03-01

    Complex systems made of interacting elements are commonly abstracted as networks, in which nodes are associated with dynamic state variables, whose evolution is driven by interactions mediated by the edges. Markov processes have been the prevailing paradigm to model such a network-based dynamics, for instance in the form of random walks or other types of diffusions. Despite the success of this modelling perspective for numerous applications, it represents an over-simplification of several real-world systems. Importantly, simple Markov models lack memory in their dynamics, an assumption often not realistic in practice. Here, we explore possibilities to enrich the system description by means of second-order Markov models, exploiting empirical pathway information. We focus on the problem of community detection and show that standard network algorithms can be generalized in order to extract novel temporal information about the system under investigation. We also apply our methodology to temporal networks, where we can uncover communities shaped by the temporal correlations in the system. Finally, we discuss relations of the framework of second order Markov processes and the recently proposed formalism of using non-backtracking matrices for community detection.

  3. Using higher-order Markov models to reveal flow-based communities in networks

    PubMed Central

    Salnikov, Vsevolod; Schaub, Michael T.; Lambiotte, Renaud

    2016-01-01

    Complex systems made of interacting elements are commonly abstracted as networks, in which nodes are associated with dynamic state variables, whose evolution is driven by interactions mediated by the edges. Markov processes have been the prevailing paradigm to model such a network-based dynamics, for instance in the form of random walks or other types of diffusions. Despite the success of this modelling perspective for numerous applications, it represents an over-simplification of several real-world systems. Importantly, simple Markov models lack memory in their dynamics, an assumption often not realistic in practice. Here, we explore possibilities to enrich the system description by means of second-order Markov models, exploiting empirical pathway information. We focus on the problem of community detection and show that standard network algorithms can be generalized in order to extract novel temporal information about the system under investigation. We also apply our methodology to temporal networks, where we can uncover communities shaped by the temporal correlations in the system. Finally, we discuss relations of the framework of second order Markov processes and the recently proposed formalism of using non-backtracking matrices for community detection. PMID:27029508

  4. Using higher-order Markov models to reveal flow-based communities in networks.

    PubMed

    Salnikov, Vsevolod; Schaub, Michael T; Lambiotte, Renaud

    2016-01-01

    Complex systems made of interacting elements are commonly abstracted as networks, in which nodes are associated with dynamic state variables, whose evolution is driven by interactions mediated by the edges. Markov processes have been the prevailing paradigm to model such a network-based dynamics, for instance in the form of random walks or other types of diffusions. Despite the success of this modelling perspective for numerous applications, it represents an over-simplification of several real-world systems. Importantly, simple Markov models lack memory in their dynamics, an assumption often not realistic in practice. Here, we explore possibilities to enrich the system description by means of second-order Markov models, exploiting empirical pathway information. We focus on the problem of community detection and show that standard network algorithms can be generalized in order to extract novel temporal information about the system under investigation. We also apply our methodology to temporal networks, where we can uncover communities shaped by the temporal correlations in the system. Finally, we discuss relations of the framework of second order Markov processes and the recently proposed formalism of using non-backtracking matrices for community detection. PMID:27029508

  5. Exploring dynamic property of traffic flow time series in multi-states based on complex networks: Phase space reconstruction versus visibility graph

    NASA Astrophysics Data System (ADS)

    Tang, Jinjun; Liu, Fang; Zhang, Weibin; Zhang, Shen; Wang, Yinhai

    2016-05-01

    A new method based on complex network theory is proposed to analyze traffic flow time series in different states. We use the data collected from loop detectors on freeway to establish traffic flow model and classify the flow into three states based on K-means method. We then introduced two widely used methods to convert time series into networks: phase space reconstruction and visibility graph. Furthermore, in phase space reconstruction, we discuss how to determine delay time constant and embedding dimension and how to select optimal critical threshold in terms of cumulative degree distribution. In the visibility graph, we design a method to construct network from multi-variables time series based on logical OR. Finally, we study and compare the statistic features of the networks converted from original traffic time series in three states based on phase space and visibility by using the degree distribution, network structure, correlation of the cluster coefficient to betweenness and degree-degree correlation.

  6. Rod-like particles matching algorithm based on SOM neural network in dispersed two-phase flow measurements

    NASA Astrophysics Data System (ADS)

    Abbasi Hoseini, Afshin; Zavareh, Zahra; Lundell, Fredrik; Anderson, Helge I.

    2014-04-01

    A matching algorithm based on self-organizing map (SOM) neural network is proposed for tracking rod-like particles in 2D optical measurements of dispersed two-phase flows. It is verified by both synthetic images of elongated particles mimicking 2D suspension flows and direct numerical simulations-based results of prolate particles dispersed in a turbulent channel flow. Furthermore, the potential benefit of this algorithm is evaluated by applying it to the experimental data of rod-like fibers tracking in wall turbulence. The study of the behavior of elongated particles suspended in turbulent flows has a practical importance and covers a wide range of applications in engineering and science. In experimental approach, particle tracking velocimetry of the dispersed phase has a key role together with particle image velocimetry of the carrier phase to obtain the velocities of both phases. The essential parts of particle tracking are to identify and match corresponding particles correctly in consecutive images. The present study is focused on the development of an algorithm for pairing non-spherical particles that have one major symmetry axis. The novel idea in the algorithm is to take the orientation of the particles into account for matching in addition to their positions. The method used is based on the SOM neural network that finds the most likely matching link in images on the basis of feature extraction and clustering. The fundamental concept is finding corresponding particles in the images with the nearest characteristics: position and orientation. The most effective aspect of this two-frame matching algorithm is that it does not require any preliminary knowledge of neither the flow field nor the particle behavior. Furthermore, using one additional characteristic of the non-spherical particles, namely their orientation, in addition to its coordinate vector, the pairing is improved both for more reliable matching at higher concentrations of dispersed particles and

  7. An efficient model for solving density driven groundwater flow problems based on the network simulation method

    NASA Astrophysics Data System (ADS)

    Soto Meca, A.; Alhama, F.; González Fernández, C. F.

    2007-06-01

    SummaryThe Henry and Elder problems are once more numerically studied using an efficient model based on the Network Simulation Method, which takes advantage of the powerful algorithms implemented in modern circuit simulation software. The network model of the volume element, which is directly deduced from the finite-difference differential equations of the spatially discretized governing equations, under the streamfunction formulation, is electrically connected to adjacent networks to conform the whole model of the medium to which the boundary conditions are added using adequate electrical devices. Coupling between equations is directly implemented in the model. Very few, simple rules are needed to design the model, which is run in a circuit simulation code to obtain the results with no added mathematical manipulations. Different versions of the Henry problem, as well as the Elder problem, are simulated and the solutions are successfully compared with the analytical and numerical solutions of other authors or codes. A grid convergence study for the Henry problem was also carried out to determine the grid size with negligible numerical dispersion, while a similar study was carried out with the Elder problem in order to compare the patterns of the solution with those of other authors. Computing times are relatively small for this kind of problem.

  8. Spatiotemporal coding in the cortex: information flow-based learning in spiking neural networks.

    PubMed

    Deco, G; Schürmann, B

    1999-05-15

    We introduce a learning paradigm for networks of integrate-and-fire spiking neurons that is based on an information-theoretic criterion. This criterion can be viewed as a first principle that demonstrates the experimentally observed fact that cortical neurons display synchronous firing for some stimuli and not for others. The principle can be regarded as the postulation of a nonparametric reconstruction method as optimization criteria for learning the required functional connectivity that justifies and explains synchronous firing for binding of features as a mechanism for spatiotemporal coding. This can be expressed in an information-theoretic way by maximizing the discrimination ability between different sensory inputs in minimal time. PMID:10226189

  9. Determination of cost coefficients of a priority-based water allocation linear programming model - a network flow approach

    NASA Astrophysics Data System (ADS)

    Chou, F. N.-F.; Wu, C.-W.

    2014-05-01

    This paper presents a method to establish the objective function of a network flow programming model for simulating river-reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and transbasin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients, which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen reservoirs' joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.

  10. Determination of cost coefficients of priority-based water allocation linear programming model - a network flow approach

    NASA Astrophysics Data System (ADS)

    Chou, F. N.-F.; Wu, C.-W.

    2013-12-01

    This paper presents a method to establish the objective function of a network flow programming model for simulating river/reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and trans-basin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen Reservoirs joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.

  11. Entropy-based neural networks model for flow duration curves at ungauged sites

    NASA Astrophysics Data System (ADS)

    Atieh, Maya; Gharabaghi, Bahram; Rudra, Ramesh

    2015-10-01

    An apportionment entropy disorder index (AEDI), capturing both temporal and spatial variability of precipitation, was introduced as a new input parameter to an artificial neural networks (ANN) model to more accurately predict flow duration curves (FDCs) at ungauged sites. The ANN model was trained on the randomly selected 2/3 of the dataset of 147 gauged streams in Ontario, and validated on the remaining 1/3. Both location and scale parameters that define the lognormal distribution for the FDCs were highly sensitive to the driving climatic factors, such as, mean annual precipitation, mean annual snowfall, and AEDI. Of the long list of watershed characteristics, the location parameter was most sensitive to drainage area, shape factor and percent area covered by natural vegetation that enhanced evapotranspiration. However, scale parameter was sensitive to drainage area, watershed slope and the baseflow index. Incorporation of the AEDI in the ANN model improved prediction performance of the location and scale parameters by 7% and 21%, respectively. A case study application of the new model for the design of micro-hydropower generators in ungauged rural headwater streams was presented.

  12. Flows in Polymer Networks

    NASA Astrophysics Data System (ADS)

    Tanaka, Fumihiko

    A simple transient network model is introduced to describe creation and annihilation of junctions in the networks of associating polymers. Stationary non-linear viscosity is calculated by the theory and by Monte Carlo simulation to study shear thickening. The dynamic mechanical moduli are calculated as functions of the frequency and the chain disengagement rate. From the peak of the loss modulus, the lifetime τx of the junction is estimated, and from the high frequency plateau of the storage modulus, the number of elastically effective chains in the network is found. Transient phenomena such as stress relaxation and stress overshoot are also theoretically studied. Results are compared with the recent experimental reports on the rheological study of hydrophobically modified water-soluble polymeters.

  13. Modeling total phosphorus removal in an aquatic environment restoring horizontal subsurface flow constructed wetland based on artificial neural networks.

    PubMed

    Li, Wei; Zhang, Yan; Cui, Lijuan; Zhang, Manyin; Wang, Yifei

    2015-08-01

    A horizontal subsurface flow constructed wetland (HSSF-CW) was designed to improve the water quality of an artificial lake in Beijing Wildlife Rescue and Rehabilitation Center, Beijing, China. Artificial neural networks (ANNs), including multilayer perceptron (MLP) and radial basis function (RBF), were used to model the removal of total phosphorus (TP). Four variables were selected as the input parameters based on the principal component analysis: the influent TP concentration, water temperature, flow rate, and porosity. In order to improve model accuracy, alternative ANNs were developed by incorporating meteorological variables, including precipitation, air humidity, evapotranspiration, solar heat flux, and barometric pressure. A genetic algorithm and cross-validation were used to find the optimal network architectures for the ANNs. Comparison of the observed data and the model predictions indicated that, with careful variable selection, ANNs appeared to be an efficient and robust tool for predicting TP removal in the HSSF-CW. Comparison of the accuracy and efficiency of MLP and RBF for predicting TP removal showed that the RBF with additional meteorological variables produced the most accurate results, indicating a high potentiality for modeling TP removal in the HSSF-CW. PMID:25903184

  14. Neural network model for extracting optic flow.

    PubMed

    Tohyama, Kazuya; Fukushima, Kunihiko

    2005-01-01

    When we travel in an environment, we have an optic flow on the retina. Neurons in the area MST of macaque monkeys are reported to have a very large receptive field and analyze optic flows on the retina. Many MST-cells respond selectively to rotation, expansion/contraction and planar motion of the optic flow. Many of them show position-invariant responses to optic flow, that is, their responses are maintained during the shift of the center of the optic flow. It has long been suggested mathematically that vector-field calculus is useful for analyzing optic flow field. Biologically, plausible neural network models based on this idea, however, have little been proposed so far. This paper, based on vector-field hypothesis, proposes a neural network model for extracting optic flows. Our model consists of hierarchically connected layers: retina, V1, MT and MST. V1-cells measure local velocity. There are two kinds of MT-cell: one is for extracting absolute velocities, the other for extracting relative velocities with their antagonistic inputs. Collecting signals from MT-cells, MST-cells respond selectively to various types of optic flows. We demonstrate through a computer simulation that this simple network is enough to explain a variety of results of neurophysiological experiments. PMID:16112546

  15. Methodologies and techniques for analysis of network flow data

    SciTech Connect

    Bobyshev, A.; Grigoriev, M.; /Fermilab

    2004-12-01

    Network flow data gathered at the border routers and core switches is used at Fermilab for statistical analysis of traffic patterns, passive network monitoring, and estimation of network performance characteristics. Flow data is also a critical tool in the investigation of computer security incidents. Development and enhancement of flow based tools is an on-going effort. This paper describes the most recent developments in flow analysis at Fermilab.

  16. Treelike networks accelerating capillary flow

    NASA Astrophysics Data System (ADS)

    Shou, Dahua; Ye, Lin; Fan, Jintu

    2014-05-01

    Transport in treelike networks has received wide attention in natural systems, oil recovery, microelectronic cooling systems, and textiles. Existing studies are focused on transport behaviors under a constant potential difference (including pressure, temperature, and voltage) in a steady state [B. Yu and B. Li, Phys. Rev. E 73, 066302 (2006), 10.1103/PhysRevE.73.066302; J. Chen, B. Yu, P. Xu, and Y. Li, Phys. Rev. E 75, 056301 (2007), 10.1103/PhysRevE.75.056301]. However, dynamic (time-dependent) transport in such systems has rarely been concerned. In this work, we theoretically investigate the dynamics of capillary flow in treelike networks and design the distribution of radius and length of local branches for the fastest capillary flow. It is demonstrated that capillary flow in the optimized tree networks is faster than in traditional parallel tube nets under fixed constraints. As well, the flow time of the liquid is found to increase approximately linearly with penetration distance, which differs from Washburn's classic description that flow time increases as the square of penetration distance in a uniform tube.

  17. Treelike networks accelerating capillary flow.

    PubMed

    Shou, Dahua; Ye, Lin; Fan, Jintu

    2014-05-01

    Transport in treelike networks has received wide attention in natural systems, oil recovery, microelectronic cooling systems, and textiles. Existing studies are focused on transport behaviors under a constant potential difference (including pressure, temperature, and voltage) in a steady state [B. Yu and B. Li, Phys. Rev. E 73, 066302 (2006); J. Chen, B. Yu, P. Xu, and Y. Li, Phys. Rev. E 75, 056301 (2007)]. However, dynamic (time-dependent) transport in such systems has rarely been concerned. In this work, we theoretically investigate the dynamics of capillary flow in treelike networks and design the distribution of radius and length of local branches for the fastest capillary flow. It is demonstrated that capillary flow in the optimized tree networks is faster than in traditional parallel tube nets under fixed constraints. As well, the flow time of the liquid is found to increase approximately linearly with penetration distance, which differs from Washburn's classic description that flow time increases as the square of penetration distance in a uniform tube. PMID:25353880

  18. Carbon Emission Flow in Networks

    PubMed Central

    Kang, Chongqing; Zhou, Tianrui; Chen, Qixin; Xu, Qianyao; Xia, Qing; Ji, Zhen

    2012-01-01

    As the human population increases and production expands, energy demand and anthropogenic carbon emission rates have been growing rapidly, and the need to decrease carbon emission levels has drawn increasing attention. The link between energy production and consumption has required the large-scale transport of energy within energy transmission networks. Within this energy flow, there is a virtual circulation of carbon emissions. To understand this circulation and account for the relationship between energy consumption and carbon emissions, this paper introduces the concept of “carbon emission flow in networks” and establishes a method to calculate carbon emission flow in networks. Using an actual analysis of China's energy pattern, the authors discuss the significance of this new concept, not only as a feasible approach but also as an innovative theoretical perspective. PMID:22761988

  19. Experimental demonstration of an OpenFlow based software-defined optical network employing packet, fixed and flexible DWDM grid technologies on an international multi-domain testbed.

    PubMed

    Channegowda, M; Nejabati, R; Rashidi Fard, M; Peng, S; Amaya, N; Zervas, G; Simeonidou, D; Vilalta, R; Casellas, R; Martínez, R; Muñoz, R; Liu, L; Tsuritani, T; Morita, I; Autenrieth, A; Elbers, J P; Kostecki, P; Kaczmarek, P

    2013-03-11

    Software defined networking (SDN) and flexible grid optical transport technology are two key technologies that allow network operators to customize their infrastructure based on application requirements and therefore minimizing the extra capital and operational costs required for hosting new applications. In this paper, for the first time we report on design, implementation & demonstration of a novel OpenFlow based SDN unified control plane allowing seamless operation across heterogeneous state-of-the-art optical and packet transport domains. We verify and experimentally evaluate OpenFlow protocol extensions for flexible DWDM grid transport technology along with its integration with fixed DWDM grid and layer-2 packet switching. PMID:23482120

  20. A Network Flow-based Analysis of Cognitive Reserve in Normal Ageing and Alzheimer’s Disease

    PubMed Central

    Wook Yoo, Sang; Han, Cheol E.; Shin, Joseph S.; Won Seo, Sang; Na, Duk L.; Kaiser, Marcus; Jeong, Yong; Seong, Joon-Kyung

    2015-01-01

    Cognitive reserve is the ability to sustain cognitive function even with a certain amount of brain damages. Here we investigate the neural compensation mechanism of cognitive reserve from the perspective of structural brain connectivity. Our goal was to show that normal people with high education levels (i.e., cognitive reserve) maintain abundant pathways connecting any two brain regions, providing better compensation or resilience after brain damage. Accordingly, patients with high education levels show more deterioration in structural brain connectivity than those with low education levels before symptoms of Alzheimer’s disease (AD) become apparent. To test this hypothesis, we use network flow measuring the number of alternative paths between two brain regions in the brain network. The experimental results show that for normal aging, education strengthens network reliability, as measured through flow values, in a subnetwork centered at the supramarginal gyrus. For AD, a subnetwork centered at the left middle frontal gyrus shows a negative correlation between flow and education, which implies more collapse in structural brain connectivity for highly educated patients. We conclude that cognitive reserve may come from the ability of network reorganization to secure the information flow within the brain network, therefore making it more resistant to disease progress. PMID:25992968

  1. A physiologically-based flow network model for hepatic drug elimination I: regular lattice lobule model

    PubMed Central

    2013-01-01

    We develop a physiologically-based lattice model for the transport and metabolism of drugs in the functional unit of the liver, called the lobule. In contrast to earlier studies, we have emphasized the dominant role of convection in well-vascularized tissue with a given structure. Estimates of convective, diffusive and reaction contributions are given. We have compared drug concentration levels observed exiting the lobule with their predicted detailed distribution inside the lobule, assuming that most often the former is accessible information while the latter is not. PMID:24007328

  2. Neural network system for traffic flow management

    NASA Astrophysics Data System (ADS)

    Gilmore, John F.; Elibiary, Khalid J.; Petersson, L. E. Rickard

    1992-09-01

    Atlanta will be the home of several special events during the next five years ranging from the 1996 Olympics to the 1994 Super Bowl. When combined with the existing special events (Braves, Falcons, and Hawks games, concerts, festivals, etc.), the need to effectively manage traffic flow from surface streets to interstate highways is apparent. This paper describes a system for traffic event response and management for intelligent navigation utilizing signals (TERMINUS) developed at Georgia Tech for adaptively managing special event traffic flows in the Atlanta, Georgia area. TERMINUS (the original name given Atlanta, Georgia based upon its role as a rail line terminating center) is an intelligent surface street signal control system designed to manage traffic flow in Metro Atlanta. The system consists of three components. The first is a traffic simulation of the downtown Atlanta area around Fulton County Stadium that models the flow of traffic when a stadium event lets out. Parameters for the surrounding area include modeling for events during various times of day (such as rush hour). The second component is a computer graphics interface with the simulation that shows the traffic flows achieved based upon intelligent control system execution. The final component is the intelligent control system that manages surface street light signals based upon feedback from control sensors that dynamically adapt the intelligent controller's decision making process. The intelligent controller is a neural network model that allows TERMINUS to control the configuration of surface street signals to optimize the flow of traffic away from special events.

  3. Cascades in interdependent flow networks

    NASA Astrophysics Data System (ADS)

    Scala, Antonio; De Sanctis Lucentini, Pier Giorgio; Caldarelli, Guido; D'Agostino, Gregorio

    2016-06-01

    In this manuscript, we investigate the abrupt breakdown behavior of coupled distribution grids under load growth. This scenario mimics the ever-increasing customer demand and the foreseen introduction of energy hubs interconnecting the different energy vectors. We extend an analytical model of cascading behavior due to line overloads to the case of interdependent networks and find evidence of first order transitions due to the long-range nature of the flows. Our results indicate that the foreseen increase in the couplings between the grids has two competing effects: on the one hand, it increases the safety region where grids can operate without withstanding systemic failures; on the other hand, it increases the possibility of a joint systems' failure.

  4. Computer program for compressible flow network analysis

    NASA Technical Reports Server (NTRS)

    Wilton, M. E.; Murtaugh, J. P.

    1973-01-01

    Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

  5. Optimization neural network for solving flow problems.

    PubMed

    Perfetti, R

    1995-01-01

    This paper describes a neural network for solving flow problems, which are of interest in many areas of application as in fuel, hydro, and electric power scheduling. The neural network consist of two layers: a hidden layer and an output layer. The hidden units correspond to the nodes of the flow graph. The output units represent the branch variables. The network has a linear order of complexity, it is easily programmable, and it is suited for analog very large scale integration (VLSI) realization. The functionality of the proposed network is illustrated by a simulation example concerning the maximal flow problem. PMID:18263420

  6. Predicting Information Flows in Network Traffic.

    ERIC Educational Resources Information Center

    Hinich, Melvin J.; Molyneux, Robert E.

    2003-01-01

    Discusses information flow in networks and predicting network traffic and describes a study that uses time series analysis on a day's worth of Internet log data. Examines nonlinearity and traffic invariants, and suggests that prediction of network traffic may not be possible with current techniques. (Author/LRW)

  7. Base Flow Model Validation

    NASA Technical Reports Server (NTRS)

    Sinha, Neeraj; Brinckman, Kevin; Jansen, Bernard; Seiner, John

    2011-01-01

    A method was developed of obtaining propulsive base flow data in both hot and cold jet environments, at Mach numbers and altitude of relevance to NASA launcher designs. The base flow data was used to perform computational fluid dynamics (CFD) turbulence model assessments of base flow predictive capabilities in order to provide increased confidence in base thermal and pressure load predictions obtained from computational modeling efforts. Predictive CFD analyses were used in the design of the experiments, available propulsive models were used to reduce program costs and increase success, and a wind tunnel facility was used. The data obtained allowed assessment of CFD/turbulence models in a complex flow environment, working within a building-block procedure to validation, where cold, non-reacting test data was first used for validation, followed by more complex reacting base flow validation.

  8. Neural Flows in Hopfield Network Approach

    NASA Astrophysics Data System (ADS)

    Ionescu, Carmen; Panaitescu, Emilian; Stoicescu, Mihai

    2013-12-01

    In most of the applications involving neural networks, the main problem consists in finding an optimal procedure to reduce the real neuron to simpler models which still express the biological complexity but allow highlighting the main characteristics of the system. We effectively investigate a simple reduction procedure which leads from complex models of Hodgkin-Huxley type to very convenient binary models of Hopfield type. The reduction will allow to describe the neuron interconnections in a quite large network and to obtain information concerning its symmetry and stability. Both cases, on homogeneous voltage across the membrane and inhomogeneous voltage along the axon will be tackled out. Few numerical simulations of the neural flow based on the cable-equation will be also presented.

  9. An extended signal control strategy for urban network traffic flow

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Tian, Fuli; Shi, Zhongke

    2016-03-01

    Traffic flow patterns are in general repeated on a daily or weekly basis. To improve the traffic conditions by using the inherent repeatability of traffic flow, a novel signal control strategy for urban networks was developed via iterative learning control (ILC) approach. Rigorous analysis shows that the proposed learning control method can guarantee the asymptotic convergence. The impacts of the ILC-based signal control strategy on the macroscopic fundamental diagram (MFD) were analyzed by simulations on a test road network. The results show that the proposed ILC strategy can evenly distribute the accumulation in the network and improve the network mobility.

  10. Performance measurements of mixed data acquisition and LAN traffic on a credit-based flow-controlled ATM network

    SciTech Connect

    Nomachi, M.; Sugaya, Y.; Togawa, H.; Yasuda, K.; Mandjavidze, I.

    1998-08-01

    The high speed network is a key component in networked data acquisition systems. An ATM switch is a candidate for the network system in DAQ (data acquisition system). The authors have studied the DAQ performance of the ATM network at RCNP (Research Center for Nuclear Physics), Osaka University. Data traffic on DAQ system has a very much different traffic pattern from the other network traffic. It may slow down the network performance. The authors have studied the network performance on several traffic patterns.

  11. High-performance flat data center network architecture based on scalable and flow-controlled optical switching system

    NASA Astrophysics Data System (ADS)

    Calabretta, Nicola; Miao, Wang; Dorren, Harm

    2016-03-01

    Traffic in data centers networks (DCNs) is steadily growing to support various applications and virtualization technologies. Multi-tenancy enabling efficient resource utilization is considered as a key requirement for the next generation DCs resulting from the growing demands for services and applications. Virtualization mechanisms and technologies can leverage statistical multiplexing and fast switch reconfiguration to further extend the DC efficiency and agility. We present a novel high performance flat DCN employing bufferless and distributed fast (sub-microsecond) optical switches with wavelength, space, and time switching operation. The fast optical switches can enhance the performance of the DCNs by providing large-capacity switching capability and efficiently sharing the data plane resources by exploiting statistical multiplexing. Benefiting from the Software-Defined Networking (SDN) control of the optical switches, virtual DCNs can be flexibly created and reconfigured by the DCN provider. Numerical and experimental investigations of the DCN based on the fast optical switches show the successful setup of virtual network slices for intra-data center interconnections. Experimental results to assess the DCN performance in terms of latency and packet loss show less than 10^-5 packet loss and 640ns end-to-end latency with 0.4 load and 16- packet size buffer. Numerical investigation on the performance of the systems when the port number of the optical switch is scaled to 32x32 system indicate that more than 1000 ToRs each with Terabit/s interface can be interconnected providing a Petabit/s capacity. The roadmap to photonic integration of large port optical switches will be also presented.

  12. A fracture network model for water flow and solute transport

    SciTech Connect

    Robinson, B.A.

    1989-01-01

    This paper summarizes code development work and sample calculations for FRACNET, a two-dimensional steady state simulator of fluid flow and solute transport in fractured porous media. The model analyzes flow and transport by generating a fracture network based on statistical characteristics of fractures obtained from well logs and other data. After a network is generated, flow and tracer transport are computed for appropriate boundary conditions and wellbore source/sink terms. In addition, for a given realization, the code can be used to indicate whether the medium can be treated as an equivalent porous medium. 18 refs., 7 figs.

  13. Incorporation of Condensation Heat Transfer in a Flow Network Code

    NASA Technical Reports Server (NTRS)

    Anthony, Miranda; Majumdar, Alok; McConnaughey, Paul K. (Technical Monitor)

    2001-01-01

    In this paper we have investigated the condensation of water vapor in a short tube. A numerical model of condensation heat transfer was incorporated in a flow network code. The flow network code that we have used in this paper is Generalized Fluid System Simulation Program (GFSSP). GFSSP is a finite volume based flow network code. Four different condensation models were presented in the paper. Soliman's correlation has been found to be the most stable in low flow rates which is of particular interest in this application. Another highlight of this investigation is conjugate or coupled heat transfer between solid or fluid. This work was done in support of NASA's International Space Station program.

  14. Network structure of inter-industry flows

    NASA Astrophysics Data System (ADS)

    McNerney, James; Fath, Brian D.; Silverberg, Gerald

    2013-12-01

    We study the structure of inter-industry relationships using networks of money flows between industries in 45 national economies. We find these networks vary around a typical structure characterized by a Weibull link weight distribution, exponential industry size distribution, and a common community structure. The community structure is hierarchical, with the top level of the hierarchy comprising five industry communities: food industries, chemical industries, manufacturing industries, service industries, and extraction industries.

  15. Hierarchical social networks and information flow

    NASA Astrophysics Data System (ADS)

    López, Luis; F. F. Mendes, Jose; Sanjuán, Miguel A. F.

    2002-12-01

    Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders, because the global influence each actor has within the network is completely determined by the hierarchical level occupied.

  16. Spike Code Flow in Cultured Neuronal Networks.

    PubMed

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

    2016-01-01

    We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network. PMID:27217825

  17. Spike Code Flow in Cultured Neuronal Networks

    PubMed Central

    Tamura, Shinichi; Nishitani, Yoshi; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

    2016-01-01

    We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of “1101” and “1011,” which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the “maximum cross-correlations” among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network. PMID:27217825

  18. Do Brain Networks Evolve by Maximizing Their Information Flow Capacity?

    PubMed Central

    Antonopoulos, Chris G.; Srivastava, Shambhavi; Pinto, Sandro E. de S.; Baptista, Murilo S.

    2015-01-01

    We propose a working hypothesis supported by numerical simulations that brain networks evolve based on the principle of the maximization of their internal information flow capacity. We find that synchronous behavior and capacity of information flow of the evolved networks reproduce well the same behaviors observed in the brain dynamical networks of Caenorhabditis elegans and humans, networks of Hindmarsh-Rose neurons with graphs given by these brain networks. We make a strong case to verify our hypothesis by showing that the neural networks with the closest graph distance to the brain networks of Caenorhabditis elegans and humans are the Hindmarsh-Rose neural networks evolved with coupling strengths that maximize information flow capacity. Surprisingly, we find that global neural synchronization levels decrease during brain evolution, reflecting on an underlying global no Hebbian-like evolution process, which is driven by no Hebbian-like learning behaviors for some of the clusters during evolution, and Hebbian-like learning rules for clusters where neurons increase their synchronization. PMID:26317592

  19. Estimation of selected streamflow statistics for a network of low-flow partial-record stations in areas affected by Base Realignment and Closure (BRAC) in Maryland

    USGS Publications Warehouse

    Ries, Kernell G., III; Eng, Ken

    2010-01-01

    The U.S. Geological Survey, in cooperation with the Maryland Department of the Environment, operated a network of 20 low-flow partial-record stations during 2008 in a region that extends from southwest of Baltimore to the northeastern corner of Maryland to obtain estimates of selected streamflow statistics at the station locations. The study area is expected to face a substantial influx of new residents and businesses as a result of military and civilian personnel transfers associated with the Federal Base Realignment and Closure Act of 2005. The estimated streamflow statistics, which include monthly 85-percent duration flows, the 10-year recurrence-interval minimum base flow, and the 7-day, 10-year low flow, are needed to provide a better understanding of the availability of water resources in the area to be affected by base-realignment activities. Streamflow measurements collected for this study at the low-flow partial-record stations and measurements collected previously for 8 of the 20 stations were related to concurrent daily flows at nearby index streamgages to estimate the streamflow statistics. Three methods were used to estimate the streamflow statistics and two methods were used to select the index streamgages. Of the three methods used to estimate the streamflow statistics, two of them--the Moments and MOVE1 methods--rely on correlating the streamflow measurements at the low-flow partial-record stations with concurrent streamflows at nearby, hydrologically similar index streamgages to determine the estimates. These methods, recommended for use by the U.S. Geological Survey, generally require about 10 streamflow measurements at the low-flow partial-record station. The third method transfers the streamflow statistics from the index streamgage to the partial-record station based on the average of the ratios of the measured streamflows at the partial-record station to the concurrent streamflows at the index streamgage. This method can be used with as few as

  20. A Remote Sensing Based Approach for the Assessment of Debris Flow Hazards Using Artificial Neural Network and Binary Logistic Regression Modeling

    NASA Astrophysics Data System (ADS)

    El Kadiri, R.; Sultan, M.; Elbayoumi, T.; Sefry, S.

    2013-12-01

    Efforts to map the distribution of debris flows, to assess the factors controlling their development, and to identify the areas prone to their development are often hampered by the absence or paucity of appropriate monitoring systems and historical databases and the inaccessibility of these areas in many parts of the world. We developed methodologies that heavily rely on readily available observations extracted from remote sensing datasets and successfully applied these techniques over the the Jazan province, in the Red Sea hills of Saudi Arabia. We first identified debris flows (10,334 locations) from high spatial resolution satellite datasets (e.g., GeoEye, Orbview), and verified a subset of these occurrences in the field. We then constructed a GIS to host the identified debris flow locations together with co-registered relevant data (e.g., lithology, elevation) and derived products (e.g., slope, normalized difference vegetation index, etc). Spatial analysis of the data sets in the GIS sets indicated various degrees of correspondence between the distribution of debris flows and various variables (e.g., stream power index, topographic position index, normalized difference vegetation index, distance to stream, flow accumulation, slope and soil weathering index, aspect, elevation) suggesting a causal effect. For example, debris flows were found in areas of high slope, low distance to low stream orders and low vegetation index. To evaluate the extent to which these factors control landslide distribution, we constructed and applied: (1) a stepwise input selection by testing all input combinations to make the final model more compact and effective, (2) a statistic-based binary logistic regression (BLR) model, and (3) a mathematical-based artificial neural network (ANN) model. Only 80% (8267 locations) of the data was used for the construction of each of the models and the remaining samples (2067 locations) were used for the accuracy assessment purposes. Results

  1. Interest communities and flow roles in directed networks: the Twitter network of the UK riots.

    PubMed

    Beguerisse-Díaz, Mariano; Garduño-Hernández, Guillermo; Vangelov, Borislav; Yaliraki, Sophia N; Barahona, Mauricio

    2014-12-01

    Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e. groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer and topic. The study of flows also allows us to generate an interest distance, which affords a personalized view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterized by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks. PMID:25297320

  2. Interest communities and flow roles in directed networks: the Twitter network of the UK riots

    PubMed Central

    Beguerisse-Díaz, Mariano; Garduño-Hernández, Guillermo; Vangelov, Borislav; Yaliraki, Sophia N.; Barahona, Mauricio

    2014-01-01

    Directionality is a crucial ingredient in many complex networks in which information, energy or influence are transmitted. In such directed networks, analysing flows (and not only the strength of connections) is crucial to reveal important features of the network that might go undetected if the orientation of connections is ignored. We showcase here a flow-based approach for community detection through the study of the network of the most influential Twitter users during the 2011 riots in England. Firstly, we use directed Markov Stability to extract descriptions of the network at different levels of coarseness in terms of interest communities, i.e. groups of nodes within which flows of information are contained and reinforced. Such interest communities reveal user groupings according to location, profession, employer and topic. The study of flows also allows us to generate an interest distance, which affords a personalized view of the attention in the network as viewed from the vantage point of any given user. Secondly, we analyse the profiles of incoming and outgoing long-range flows with a combined approach of role-based similarity and the novel relaxed minimum spanning tree algorithm to reveal that the users in the network can be classified into five roles. These flow roles go beyond the standard leader/follower dichotomy and differ from classifications based on regular/structural equivalence. We then show that the interest communities fall into distinct informational organigrams characterized by a different mix of user roles reflecting the quality of dialogue within them. Our generic framework can be used to provide insight into how flows are generated, distributed, preserved and consumed in directed networks. PMID:25297320

  3. Design and performance evaluation of an OpenFlow-based control plane for software-defined elastic optical networks with direct-detection optical OFDM (DDO-OFDM) transmission.

    PubMed

    Liu, Lei; Peng, Wei-Ren; Casellas, Ramon; Tsuritani, Takehiro; Morita, Itsuro; Martínez, Ricardo; Muñoz, Raül; Yoo, S J B

    2014-01-13

    Optical Orthogonal Frequency Division Multiplexing (O-OFDM), which transmits high speed optical signals using multiple spectrally overlapped lower-speed subcarriers, is a promising candidate for supporting future elastic optical networks. In contrast to previous works which focus on Coherent Optical OFDM (CO-OFDM), in this paper, we consider the direct-detection optical OFDM (DDO-OFDM) as the transport technique, which leads to simpler hardware and software realizations, potentially offering a low-cost solution for elastic optical networks, especially in metro networks, and short or medium distance core networks. Based on this network scenario, we design and deploy a software-defined networking (SDN) control plane enabled by extending OpenFlow, detailing the network architecture, the routing and spectrum assignment algorithm, OpenFlow protocol extensions and the experimental validation. To the best of our knowledge, it is the first time that an OpenFlow-based control plane is reported and its performance is quantitatively measured in an elastic optical network with DDO-OFDM transmission. PMID:24514962

  4. An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks.

    PubMed

    Huff, Emily Silver; Leahy, Jessica E; Hiebeler, David; Weiskittel, Aaron R; Noblet, Caroline L

    2015-01-01

    Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner's management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of 'harvest readiness' and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

  5. An Agent-Based Model of Private Woodland Owner Management Behavior Using Social Interactions, Information Flow, and Peer-To-Peer Networks

    PubMed Central

    Huff, Emily Silver; Leahy, Jessica E.; Hiebeler, David; Weiskittel, Aaron R.; Noblet, Caroline L.

    2015-01-01

    Privately owned woodlands are an important source of timber and ecosystem services in North America and worldwide. Impacts of management on these ecosystems and timber supply from these woodlands are difficult to estimate because complex behavioral theory informs the owner’s management decisions. The decision-making environment consists of exogenous market factors, internal cognitive processes, and social interactions with fellow landowners, foresters, and other rural community members. This study seeks to understand how social interactions, information flow, and peer-to-peer networks influence timber harvesting behavior using an agent-based model. This theoretical model includes forested polygons in various states of ‘harvest readiness’ and three types of agents: forest landowners, foresters, and peer leaders (individuals trained in conservation who use peer-to-peer networking). Agent rules, interactions, and characteristics were parameterized with values from existing literature and an empirical survey of forest landowner attitudes, intentions, and demographics. The model demonstrates that as trust in foresters and peer leaders increases, the percentage of the forest that is harvested sustainably increases. Furthermore, peer leaders can serve to increase landowner trust in foresters. Model output and equations will inform forest policy and extension/outreach efforts. The model also serves as an important testing ground for new theories of landowner decision making and behavior. PMID:26562429

  6. Gas-Dynamic Transients Flow Networks

    Energy Science and Technology Software Center (ESTSC)

    1987-09-01

    TVENT1P predicts flows and pressures in a ventilation system or other air pathway caused by pressure transients, such as a tornado. For an analytical model to simulate an actual system, it must have (1) the same arrangement of components in a network of flow paths; (2) the same friction characteristics; (3) the same boundary pressures; (4) the same capacitance; and (5) the same forces that drive the air. A specific set of components used formore » constructing the analytical model includes filters, dampers, ducts, blowers, rooms, or volume connected at nodal points to form networks. The effects of a number of similar components can be lumped into a single one. TVENT1P contains a material transport algorithm and features for turning blowers off and on, changing blower speeds, changing the resistance of dampers and filters, and providing a filter model to handle very high flows. These features make it possible to depict a sequence of events during a single run. Component properties are varied using time functions. The filter model is not used by the code unless it is specified by the user. The basic results of a TVENT1P solution are flows in branches and pressures at nodes. A postprocessor program, PLTTEX, is included to produce the plots specified in the TVENT1P input. PLTTEX uses the proprietary CA-DISSPLA graphics software.« less

  7. TCP flow control using link layer information in mobile networks

    NASA Astrophysics Data System (ADS)

    Koga, Hiroyuki; Kawahara, Kenji; Oie, Yuji

    2002-07-01

    Mobile Networks have been expanding and IMT-2000 further increases their available bandwidth over wireless links. However, TCP, which is a reliable end-to-end transport protocol, is tuned to perform well in wired networks where bit error rates are very low and packet loss occurs mostly because of congestion. Although a TCP sender can execute flow control to utilize as much available bandwidth as possible in wired networks, it cannot work well in wireless networks characterized by high bit error rates. In the next generation mobile systems, sophisticated error recovery technologies of FEC and ARQ are indeed employed over wireless links, i.e., over Layer 2, to avoid performance degradation of upper layers. However, multiple retransmissions by Layer 2 ARQ can adversely increase transmission delay of TCP segments, which will further make TCP unnecessarily increase RTO (Retransmission TimeOut). Furthermore, a link bandwidth assigned to TCP flows can change in response to changing air conditions to use wireless links efficiently. TCP thus has to adapt its transmission rate according to the changing available bandwidth. The major goal of this study is to develop a receiver-based effective TCP flow control without any modification on TCP senders, which are probably connected with wired networks. For this end, we propose a TCP flow control employing some Layer 2 information on a wireless link at the mobile station. Our performance evaluation of the proposed TCP shows that the receiver-based TCP flow control can moderate the performance degradation very well even if FER on Layer 2 is high.

  8. A study of two phase flow in fracture networks

    SciTech Connect

    Karasaki, K.; Pruess, K.; Vomvoris, S.; Segan, S.

    1994-12-31

    Accurate characterization of the two-phase flow behavior of the fractured rock mass is vital to the safety of a potential high level nuclear waste repository in the unsaturated, fractured welded tuff at Yucca Mountain, NV. A tool for studying the two-phase flow properties of a fracture networks was developed. It is based on a simple mechanistic model in which the capillary pressure of a fracture is a unique function of the aperture. Whether a particular fracture element is occupied by wetting fluid or non-wetting fluid is determined by allowability and accessibility criteria. Relative permeability characteristics of a simulated fracture network were investigated using the model. Different assumptions are examined regarding the interactions between phases. In all cases, strong phase interference was observed. Hysteresis effects and irreducible saturation were also explained based on the model.

  9. Employment Growth through Labor Flow Networks

    PubMed Central

    Guerrero, Omar A.; Axtell, Robert L.

    2013-01-01

    It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market. PMID:23658682

  10. Employment growth through labor flow networks.

    PubMed

    Guerrero, Omar A; Axtell, Robert L

    2013-01-01

    It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market. PMID:23658682

  11. Network-Based Management Procedures.

    ERIC Educational Resources Information Center

    Buckner, Allen L.

    Network-based management procedures serve as valuable aids in organizational management, achievement of objectives, problem solving, and decisionmaking. Network techniques especially applicable to educational management systems are the program evaluation and review technique (PERT) and the critical path method (CPM). Other network charting…

  12. Mapping information flow in sensorimotor networks.

    PubMed

    Lungarella, Max; Sporns, Olaf

    2006-10-27

    Biological organisms continuously select and sample information used by their neural structures for perception and action, and for creating coherent cognitive states guiding their autonomous behavior. Information processing, however, is not solely an internal function of the nervous system. Here we show, instead, how sensorimotor interaction and body morphology can induce statistical regularities and information structure in sensory inputs and within the neural control architecture, and how the flow of information between sensors, neural units, and effectors is actively shaped by the interaction with the environment. We analyze sensory and motor data collected from real and simulated robots and reveal the presence of information structure and directed information flow induced by dynamically coupled sensorimotor activity, including effects of motor outputs on sensory inputs. We find that information structure and information flow in sensorimotor networks (a) is spatially and temporally specific; (b) can be affected by learning, and (c) can be affected by changes in body morphology. Our results suggest a fundamental link between physical embeddedness and information, highlighting the effects of embodied interactions on internal (neural) information processing, and illuminating the role of various system components on the generation of behavior. PMID:17069456

  13. Directory Enabled Policy Based Networking

    SciTech Connect

    KELIIAA, CURTIS M.

    2001-10-01

    This report presents a discussion of directory-enabled policy-based networking with an emphasis on its role as the foundation for securely scalable enterprise networks. A directory service provides the object-oriented logical environment for interactive cyber-policy implementation. Cyber-policy implementation includes security, network management, operational process and quality of service policies. The leading network-technology vendors have invested in these technologies for secure universal connectivity that transverses Internet, extranet and intranet boundaries. Industry standards are established that provide the fundamental guidelines for directory deployment scalable to global networks. The integration of policy-based networking with directory-service technologies provides for intelligent management of the enterprise network environment as an end-to-end system of related clients, services and resources. This architecture allows logical policies to protect data, manage security and provision critical network services permitting a proactive defense-in-depth cyber-security posture. Enterprise networking imposes the consideration of supporting multiple computing platforms, sites and business-operation models. An industry-standards based approach combined with principled systems engineering in the deployment of these technologies allows these issues to be successfully addressed. This discussion is focused on a directory-based policy architecture for the heterogeneous enterprise network-computing environment and does not propose specific vendor solutions. This document is written to present practical design methodology and provide an understanding of the risks, complexities and most important, the benefits of directory-enabled policy-based networking.

  14. Random fracture networks: percolation, geometry and flow

    NASA Astrophysics Data System (ADS)

    Adler, P. M.; Thovert, J. F.; Mourzenko, V. V.

    2015-12-01

    This paper reviews some of the basic properties of fracture networks. Most of the data can only be derived numerically, and to be useful they need to be rationalized, i.e., a large set of numbers should be replaced by a simple formula which is easy to apply for estimating orders of magnitude. Three major tools are found useful in this rationalization effort. First, analytical results can usually be derived for infinite fractures, a limit which corresponds to large densities. Second, the excluded volume and the dimensionless density prove crucial to gather data obtained at intermediate densities. Finally, shape factors can be used to further reduce the influence of fracture shapes. Percolation of fracture networks is of primary importance since this characteristic controls transport properties such as permeability. Recent numerical studies for various types of fracture networks (isotropic, anisotropic, heterogeneous in space, polydisperse, mixture of shapes) are summarized; the percolation threshold rho is made dimensionless by means of the excluded volume. A general correlation for rho is proposed as a function of the gyration radius. The statistical characteristics of the blocks which are cut in the solid matrix by the network are presented, since they control transfers between the porous matrix and the fractures. Results on quantities such as the volume, surface and number of faces are given and semi empirical relations are proposed. The possible intersection of a percolating network and of a cubic cavity is also summarized. This might be of importance for the underground storage of wastes. An approximate reasoning based on the excluded volume of the percolating cluster and of the cubic cavity is proposed. Finally, consequences on the permeability of fracture networks are briefly addressed. An empirical formula which verifies some theoretical properties is proposed.

  15. Monitoring individual traffic flows within the ATLAS TDAQ network

    NASA Astrophysics Data System (ADS)

    Sjoen, R.; Stancu, S.; Ciobotaru, M.; Batraneanu, S. M.; Leahu, L.; Martin, B.; Al-Shabibi, A.

    2010-04-01

    The ATLAS data acquisition system consists of four different networks interconnecting up to 2000 processors using up to 200 edge switches and five multi-blade chassis devices. The architecture of the system has been described in [1] and its operational model in [2]. Classical, SNMP-based, network monitoring provides statistics on aggregate traffic, but for performance monitoring and troubleshooting purposes there was an imperative need to identify and quantify single traffic flows. sFlow [3] is an industry standard based on statistical sampling which attempts to provide a solution to this. Due to the size of the ATLAS network, the collection and analysis of the sFlow data from all devices generates a data handling problem of its own. This paper describes how this problem is addressed by making it possible to collect and store data either centrally or distributed according to need. The methods used to present the results in a relevant fashion for system analysts are discussed and we explore the possibilities and limitations of this diagnostic tool, giving an example of its use in solving system problems that arise during the ATLAS data taking.

  16. Flow networks: A characterization of geophysical fluid transport

    NASA Astrophysics Data System (ADS)

    Ser-Giacomi, Enrico; Rossi, Vincent; López, Cristóbal; Hernández-García, Emilio

    2015-03-01

    We represent transport between different regions of a fluid domain by flow networks, constructed from the discrete representation of the Perron-Frobenius or transfer operator associated to the fluid advection dynamics. The procedure is useful to analyze fluid dynamics in geophysical contexts, as illustrated by the construction of a flow network associated to the surface circulation in the Mediterranean sea. We use network-theory tools to analyze the flow network and gain insights into transport processes. In particular, we quantitatively relate dispersion and mixing characteristics, classically quantified by Lyapunov exponents, to the degree of the network nodes. A family of network entropies is defined from the network adjacency matrix and related to the statistics of stretching in the fluid, in particular, to the Lyapunov exponent field. Finally, we use a network community detection algorithm, Infomap, to partition the Mediterranean network into coherent regions, i.e., areas internally well mixed, but with little fluid interchange between them.

  17. A methodology for linking 2D overland flow models with the sewer network model SWMM 5.1 based on dynamic link libraries.

    PubMed

    Leandro, Jorge; Martins, Ricardo

    2016-01-01

    Pluvial flooding in urban areas is characterized by a gradually varying inundation process caused by surcharge of the sewer manholes. Therefore urban flood models need to simulate the interaction between the sewer network and the overland flow in order to accurately predict the flood inundation extents. In this work we present a methodology for linking 2D overland flow models with the storm sewer model SWMM 5. SWMM 5 is a well-known free open-source code originally developed in 1971. The latest major release saw its structure re-written in C ++ allowing it to be compiled as a command line executable or through a series of calls made to function inside a dynamic link library (DLL). The methodology developed herein is written inside the same DLL in C + +, and is able to simulate the bi-directional interaction between both models during simulation. Validation is done in a real case study with an existing urban flood coupled model. The novelty herein is that the new methodology can be added to SWMM without the need for editing SWMM's original code. Furthermore, it is directly applicable to other coupled overland flow models aiming to use SWMM 5 as the sewer network model. PMID:27332848

  18. Dynamics-based centrality for directed networks

    NASA Astrophysics Data System (ADS)

    Masuda, Naoki; Kori, Hiroshi

    2010-11-01

    Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

  19. Analysis of HRCT-derived xylem network reveals reverse flow in some vessels

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Flow in xylem vessels is modeled based on constructions of three dimensional xylem networks derived from High Resolution Computed Tomography (HRCT) images of grapevine (Vitis vinifera) stems. Flow in 6-14% of the vessels was found to be oriented in the opposite direction to the bulk flow under norma...

  20. Evolution of weighted complex bus transit networks with flow

    NASA Astrophysics Data System (ADS)

    Huang, Ailing; Xiong, Jie; Shen, Jinsheng; Guan, Wei

    2016-02-01

    Study on the intrinsic properties and evolutional mechanism of urban public transit networks (PTNs) has great significance for transit planning and control, particularly considering passengers’ dynamic behaviors. This paper presents an empirical analysis for exploring the complex properties of Beijing’s weighted bus transit network (BTN) based on passenger flow in L-space, and proposes a bi-level evolution model to simulate the development of transit routes from the view of complex network. The model is an iterative process that is driven by passengers’ travel demands and dual-controlled interest mechanism, which is composed of passengers’ spatio-temporal requirements and cost constraint of transit agencies. Also, the flow’s dynamic behaviors, including the evolutions of travel demand, sectional flow attracted by a new link and flow perturbation triggered in nearby routes, are taken into consideration in the evolutional process. We present the numerical experiment to validate the model, where the main parameters are estimated by using distribution functions that are deduced from real-world data. The results obtained have proven that our model can generate a BTN with complex properties, such as the scale-free behavior or small-world phenomenon, which shows an agreement with our empirical results. Our study’s results can be exploited to optimize the real BTN’s structure and improve the network’s robustness.

  1. CytoITMprobe: a network information flow plugin for Cytoscape

    PubMed Central

    2012-01-01

    Background Cytoscape is a well-developed flexible platform for visualization, integration and analysis of network data. Apart from the sophisticated graph layout and visualization routines, it hosts numerous user-developed plugins that significantly extend its core functionality. Earlier, we developed a network information flow framework and implemented it as a web application, called ITM Probe. Given a context consisting of one or more user-selected nodes, ITM Probe retrieves other network nodes most related to that context. It requires neither user restriction to subnetwork of interest nor additional and possibly noisy information. However, plugins for Cytoscape with these features do not yet exist. To provide the Cytoscape users the possibility of integrating ITM Probe into their workflows, we developed CytoITMprobe, a new Cytoscape plugin. Findings CytoITMprobe maintains all the desirable features of ITM Probe and adds additional flexibility not achievable through its web service version. It provides access to ITM Probe either through a web server or locally. The input, consisting of a Cytoscape network, together with the desired origins and/or destinations of information and a dissipation coefficient, is specified through a query form. The results are shown as a subnetwork of significant nodes and several summary tables. Users can control the composition and appearance of the subnetwork and interchange their ITM Probe results with other software tools through tab-delimited files. Conclusions The main strength of CytoITMprobe is its flexibility. It allows the user to specify as input any Cytoscape network, rather than being restricted to the pre-compiled protein-protein interaction networks available through the ITM Probe web service. Users may supply their own edge weights and directionalities. Consequently, as opposed to ITM Probe web service, CytoITMprobe can be applied to many other domains of network-based research beyond protein-networks. It also enables

  2. Laminar flow of two miscible fluids in a simple network

    NASA Astrophysics Data System (ADS)

    Karst, Casey M.; Storey, Brian D.; Geddes, John B.

    2013-03-01

    When a fluid comprised of multiple phases or constituents flows through a network, nonlinear phenomena such as multiple stable equilibrium states and spontaneous oscillations can occur. Such behavior has been observed or predicted in a number of networks including the flow of blood through the microcirculation, the flow of picoliter droplets through microfluidic devices, the flow of magma through lava tubes, and two-phase flow in refrigeration systems. While the existence of nonlinear phenomena in a network with many inter-connections containing fluids with complex rheology may seem unsurprising, this paper demonstrates that even simple networks containing Newtonian fluids in laminar flow can demonstrate multiple equilibria. The paper describes a theoretical and experimental investigation of the laminar flow of two miscible Newtonian fluids of different density and viscosity through a simple network. The fluids stratify due to gravity and remain as nearly distinct phases with some mixing occurring only by diffusion. This fluid system has the advantage that it is easily controlled and modeled, yet contains the key ingredients for network nonlinearities. Experiments and 3D simulations are first used to explore how phases distribute at a single T-junction. Once the phase separation at a single junction is known, a network model is developed which predicts multiple equilibria in the simplest of networks. The existence of multiple stable equilibria is confirmed experimentally and a criterion for existence is developed. The network results are generic and could be applied to or found in different physical systems.

  3. Dynamics of blood flow in a microfluidic ladder network

    NASA Astrophysics Data System (ADS)

    Maddala, Jeevan; Zilberman-Rudenko, Jevgenia; McCarty, Owen

    The dynamics of a complex mixture of cells and proteins, such as blood, in perturbed shear flow remains ill-defined. Microfluidics is a promising technology for improving the understanding of blood flow under complex conditions of shear; as found in stent implants and in tortuous blood vessels. We model the fluid dynamics of blood flow in a microfluidic ladder network with dimensions mimicking venules. Interaction of blood cells was modeled using multiagent framework, where cells of different diameters were treated as spheres. This model served as the basis for predicting transition regions, collision pathways, re-circulation zones and residence times of cells dependent on their diameters and device architecture. Based on these insights from the model, we were able to predict the clot formation configurations at various locations in the device. These predictions were supported by the experiments using whole blood. To facilitate platelet aggregation, the devices were coated with fibrillar collagen and tissue factor. Blood was perfused through the microfluidic device for 9 min at a physiologically relevant venous shear rate of 600 s-1. Using fluorescent microscopy, we observed flow transitions near the channel intersections and at the areas of blood flow obstruction, which promoted larger thrombus formation. This study of integrating model predictions with experimental design, aids in defining the dynamics of blood flow in microvasculature and in development of novel biomedical devices.

  4. Hierarchicality of trade flow networks reveals complexity of products.

    PubMed

    Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

    2014-01-01

    With globalization, countries are more connected than before by trading flows, which amounts to at least 36 trillion dollars today. Interestingly, around 30-60 percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent η can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely. PMID:24905753

  5. Hierarchicality of Trade Flow Networks Reveals Complexity of Products

    PubMed Central

    Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

    2014-01-01

    With globalization, countries are more connected than before by trading flows, which amounts to at least trillion dollars today. Interestingly, around percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely. PMID:24905753

  6. The simplicity of fractal-like flow networks for effective heat and mass transport

    SciTech Connect

    Pence, Deborah

    2010-05-15

    A variety of applications using disk-shaped fractal-like flow networks and the status of one and two-dimensional predictive models for these applications are summarized. Applications discussed include single-phase and two-phase heat sinks and heat exchangers, two-phase flow separators, desorbers, and passive micromixers. Advantages of using these fractal-like flow networks versus parallel-flow networks include lower pressure drop, lower maximum wall temperature, inlet plenum symmetry, alternate flow paths, and pressure recovery at the bifurcation. The compact nature of microscale fractal-like branching heat exchangers makes them ideal for modularity. Differences between fractal-like and constructal approaches applied to disk-shaped heat sink designs are highlighted, and the importance of including geometric constraints, including fabrication constraints, in flow network design optimization is discussed. Finally, a simple pencil and paper procedure for designing single-phase heat sinks with fractal-like flow networks based solely on geometric constraints is outlined. Benefit-to-cost ratios resulting from geometric-based designs are compared with those from flow networks determined using multivariable optimization. Results from the two network designs are within 11%. (author)

  7. Traffic flow on realistic road networks with adaptive traffic lights

    NASA Astrophysics Data System (ADS)

    de Gier, Jan; Garoni, Timothy M.; Rojas, Omar

    2011-04-01

    We present a model of traffic flow on generic urban road networks based on cellular automata. We apply this model to an existing road network in the Australian city of Melbourne, using empirical data as input. For comparison, we also apply this model to a square-grid network using hypothetical input data. On both networks we compare the effects of non-adaptive versus adaptive traffic lights, in which instantaneous traffic state information feeds back into the traffic signal schedule. We observe that not only do adaptive traffic lights result in better averages of network observables, they also lead to significantly smaller fluctuations in these observables. We furthermore compare two different systems of adaptive traffic signals, one which is informed by the traffic state on both upstream and downstream links and one which is informed by upstream links only. We find that, in general, both the mean and the fluctuation of the travel time are smallest when using the joint upstream-downstream control strategy.

  8. Identifying Modular Flows on Multilayer Networks Reveals Highly Overlapping Organization in Interconnected Systems

    NASA Astrophysics Data System (ADS)

    De Domenico, Manlio; Lancichinetti, Andrea; Arenas, Alex; Rosvall, Martin

    2015-01-01

    To comprehend interconnected systems across the social and natural sciences, researchers have developed many powerful methods to identify functional modules. For example, with interaction data aggregated into a single network layer, flow-based methods have proven useful for identifying modular dynamics in weighted and directed networks that capture constraints on flow processes. However, many interconnected systems consist of agents or components that exhibit multiple layers of interactions, possibly from several different processes. Inevitably, representing this intricate network of networks as a single aggregated network leads to information loss and may obscure the actual organization. Here, we propose a method based on a compression of network flows that can identify modular flows both within and across layers in nonaggregated multilayer networks. Our numerical experiments on synthetic multilayer networks, with some layers originating from the same interaction process, show that the analysis fails in aggregated networks or when treating the layers separately, whereas the multilayer method can accurately identify modules across layers that originate from the same interaction process. We capitalize on our findings and reveal the community structure of two multilayer collaboration networks with topics as layers: scientists affiliated with the Pierre Auger Observatory and scientists publishing works on networks on the arXiv. Compared to conventional aggregated methods, the multilayer method uncovers connected topics and reveals smaller modules with more overlap that better capture the actual organization.

  9. Comparative analysis of food webs based on flow networks: effects of nutrient supply on structure and function of coastal plankton communities

    NASA Astrophysics Data System (ADS)

    Olsen, Yngvar; Reinertsen, Helge; Vadstein, Olav; Andersen, Tom; Gismervik, Ingrid; Duarte, Carlos; Agusti, Susana; Stibor, Herwig; Sommer, Ulrich; Lignell, Risto; Tamminen, Timo; Lancelot, Christiane; Rousseau, Veronique; Hoell, Espen; Sanderud, Knut Arvid

    2001-12-01

    The objective of COMWEB was to develop efficient analytical, numerical and experimental methods for assessing and predicting the effects of nutrient (N, P, Si) supply on the stability and persistence of pelagic food web structure and function in coastal waters. The experimental comparative work included a geographic gradient covering Baltic, Mediterranean, and NE Atlantic waters and a NE Atlantic gradient in state of eutrophication. COMWEB has been an experimental approach to coastal eutrophication, studying effects of enhanced nutrient supply on components and flows of the entire lower pelagic food web. Flow network representations of pelagic food webs has been a framework of data reduction and flows were established by sophisticated inverse modelling. Fundamental information on physiological properties of functional key species in the pelagic food web was used to constrain flow estimations. A main conclusion derived from the flow networks was that very little energy and materials were transferred from the microbial food web to the main food chain. The lower food web could therefore be described as two parallel food chains with relatively limited interaction between heterotrophic groups. Short-term effects of nutrient perturbations were examined in mesocosms along the geographic gradient. The response was comparable in all systems, with a stronger effect on the activity and biomass of autotrophic groups than those of heterotrophic ones. Mediterranean waters showed much lower autotrophic biomass response than Baltic and NE Atlantic waters, which responded almost equally. The response of primary production was, however, more comparable. High phytoplankton lysis rate explained this low accumulation of biomass in Mediterranean waters. The study of Atlantic coastal waters of different eutrophic states revealed that the ecological response was higher in the closed nutrient perturbed mesocosms than in open systems exposed for >4 summer months (summer/autumn season). The

  10. Flow focusing in unsaturated fracture networks: A numerical investigation

    SciTech Connect

    Zhang, Keni; Wu, Yu-Shu; Bodvarsson, G.S.; Liu, Hui-Hai

    2003-04-17

    A numerical modeling study is presented to investigate flow-focusing phenomena in a large-scale fracture network, constructed using field data collected from the unsaturated zone of Yucca Mountain, Nevada, the proposed repository site for high-level nuclear waste. The two-dimensional fracture network for an area of 100 m x 150 m contains more than 20,000 fractures. Steady-state unsaturated flow in the fracture network is investigated for different boundary conditions and rock properties. Simulation results indicate that flow paths are generally vertical, and that horizontal fractures mainly provide pathways between neighboring vertical paths. In addition to fracture properties, flow-focusing phenomena are also affected by rock-matrix permeability, with lower matrix permeability leading to a high degree of flow focusing. The simulation results further indicate that the average spacing between flow paths in a layered system tends to increase and flow tends to becomes more focused, with depth.

  11. Analyzing the International Exergy Flow Network of Ferrous Metal Ores

    PubMed Central

    Qi, Hai; An, Haizhong; Hao, Xiaoqing; Zhong, Weiqiong; Zhang, Yanbing

    2014-01-01

    This paper employs an un-weighted and weighted exergy network to study the properties of ferrous metal ores in countries worldwide and their evolution from 2002 to 2012. We find that there are few countries controlling most of the ferrous metal ore exports in terms of exergy and that the entire exergy flow network is becoming more heterogeneous though the addition of new nodes. The increasing of the average clustering coefficient indicates that the formation of an international exergy flow system and regional integration is improving. When we contrast the average out strength of exergy and the average out strength of currency, we find both similarities and differences. Prices are affected largely by human factors; thus, the growth rate of the average out strength of currency has fluctuated acutely in the eleven years from 2002 to 2012. Exergy is defined as the maximum work that can be extracted from a system and can reflect the true cost in the world, and this parameter fluctuates much less. Performing an analysis based on the two aspects of exergy and currency, we find that the network is becoming uneven. PMID:25188407

  12. Blood flow in microvascular networks: A study in nonlinear biology

    PubMed Central

    Geddes, John B.; Carr, Russell T.; Wu, Fan; Lao, Yingyi; Maher, Meaghan

    2010-01-01

    Plasma skimming and the Fahraeus–Lindqvist effect are well-known phenomena in blood rheology. By combining these peculiarities of blood flow in the microcirculation with simple topological models of microvascular networks, we have uncovered interesting nonlinear behavior regarding blood flow in networks. Nonlinearity manifests itself in the existence of multiple steady states. This is due to the nonlinear dependence of viscosity on blood cell concentration. Nonlinearity also appears in the form of spontaneous oscillations in limit cycles. These limit cycles arise from the fact that the physics of blood flow can be modeled in terms of state dependent delay equations with multiple interacting delay times. In this paper we extend our previous work on blood flow in a simple two node network and begin to explore how topological complexity influences the dynamics of network blood flow. In addition we present initial evidence that the nonlinear phenomena predicted by our model are observed experimentally. PMID:21198135

  13. Pressure-field extraction on unstructured flow data using a Voronoi tessellation-based networking algorithm: a proof-of-principle study

    NASA Astrophysics Data System (ADS)

    Neeteson, Nathan J.; Rival, David E.

    2015-02-01

    A novel technique is described for pressure extraction from Lagrangian particle-tracking data. The technique uses a Poisson solver to extract the pressure field on a network of data nodes, which is constructed using the Voronoi tessellation and the Delaunay triangulation. The technique is demonstrated on two cases: synthetic Lagrangian data generated for the analytical case of Hill's spherical vortex, and the flow in the wake behind a NACA 0012 which was impulsively accelerated to . The experimental data were collected using four-camera, three-dimensional particle-tracking velocimetry. For both the analytical case and the experimental case, the dependence of pressure-field error or sensitivity on the normalized spatial particle density was found to follow similar power-law relationships. It was shown that in order to resolve the salient flow structures from experimental data, the required particle density was an order of magnitude greater than for the analytical case. Furthermore, additional sub-structures continued to be identified in the experimental data as the particle density was increased. The increased density requirements of the experimental data were assumed to be due to a combination of phase-averaging error and the presence of turbulent coherent structures in the flow. Additionally, the computational requirements of the technique were assessed. It was found that in the current implementation, the computational requirements are slightly nonlinear with respect to the number of particles. However, the technique will remain feasible even as advancements in particle-tracking techniques in the future increase the density of Lagrangian data.

  14. Backbone of complex networks of corporations: the flow of control.

    PubMed

    Glattfelder, J B; Battiston, S

    2009-09-01

    We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here. PMID:19905177

  15. Backbone of complex networks of corporations: The flow of control

    NASA Astrophysics Data System (ADS)

    Glattfelder, J. B.; Battiston, S.

    2009-09-01

    We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us to address important questions in economics, namely, how control and wealth are structured and concentrated across national markets. We report on the first cross-country investigation of ownership networks, focusing on the stock markets of 48 countries around the world. On the one hand, our analysis confirms results expected on the basis of the literature on corporate control, namely, that in Anglo-Saxon countries control tends to be dispersed among numerous shareholders. On the other hand, it also reveals that in the same countries, control is found to be highly concentrated at the global level, namely, lying in the hands of very few important shareholders. Interestingly, the exact opposite is observed for European countries. These results have previously not been reported as they are not observable without the kind of network analysis developed here.

  16. Flow distributions and spatial correlations in human brain capillary networks

    NASA Astrophysics Data System (ADS)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  17. Multi-frequency complex network from time series for uncovering oil-water flow structure

    PubMed Central

    Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

    2015-01-01

    Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective. PMID:25649900

  18. Multi-frequency complex network from time series for uncovering oil-water flow structure

    NASA Astrophysics Data System (ADS)

    Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

    2015-02-01

    Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

  19. Advantages of IP over elastic optical networks using multi-flow transponders from cost and equipment count aspects.

    PubMed

    Tanaka, Takafumi; Hirano, Akira; Jinno, Masahiko

    2014-01-13

    To evaluate the cost efficiency of IP over elastic optical network architectures, we use a multi-layer network design scheme that covers network to node equipment level. An evaluation in a static traffic environment shows that the multi-flow optical transponder-based elastic optical network reduces total cost as well as equipment counts compared to other elastic network models based on fixed-rate, mixed-line-rate and bandwidth-variable transponders. PMID:24514966

  20. Cilia driven flow networks in the brain

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Faubel, Regina; Westendorf, Chrsitian; Eichele, Gregor; Bodenschatz, Eberhard

    Neurons exchange soluble substances via the cerebrospinal fluid (CSF) that fills the ventricular system. The walls of the ventricular cavities are covered with motile cilia that constantly beat and thereby induce a directional flow. We recently discovered that cilia in the third ventricle generate a complex flow pattern leading to partitioning of the ventricular volume and site-directed transport paths along the walls. Transient and daily recurrent alterations in the cilia beating direction lead to changes in the flow pattern. This has consequences for delivery of CSF components along the near wall flow. The contribution of this cilia-induced flow to overall CSF flow remains to be investigated. The state-of-art lattice Boltzmann method is adapted for studying the CFS flow. The 3D geometry of the third ventricle at high resolution was reconstructed. Simulation of CSF flow without cilia in this geometry confirmed that the previous idea about unidirectional flow does not explain how different components of CSF can be delivered to their various target sites. We study the contribution of the cilia-induced flow pattern to overall CSF flow and identify target areas for site-specific delivery of CSF-constituents with respect to the temporal changes.

  1. Polysulfide flow batteries enabled by percolating nanoscale conductor networks.

    PubMed

    Fan, Frank Y; Woodford, William H; Li, Zheng; Baram, Nir; Smith, Kyle C; Helal, Ahmed; McKinley, Gareth H; Carter, W Craig; Chiang, Yet-Ming

    2014-01-01

    A new approach to flow battery design is demonstrated wherein diffusion-limited aggregation of nanoscale conductor particles at ∼1 vol % concentration is used to impart mixed electronic-ionic conductivity to redox solutions, forming flow electrodes with embedded current collector networks that self-heal after shear. Lithium polysulfide flow cathodes of this architecture exhibit electrochemical activity that is distributed throughout the volume of flow electrodes rather than being confined to surfaces of stationary current collectors. The nanoscale network architecture enables cycling of polysulfide solutions deep into precipitation regimes that historically have shown poor capacity utilization and reversibility and may thereby enable new flow battery designs of higher energy density and lower system cost. Lithium polysulfide half-flow cells operating in both continuous and intermittent flow mode are demonstrated for the first time. PMID:24597525

  2. Forecasting flows in Apalachicola River using neural networks

    NASA Astrophysics Data System (ADS)

    Huang, Wenrui; Xu, Bing; Chan-Hilton, Amy

    2004-09-01

    Forecasting river flow is important to water resources management and planning. In this study, an artificial neural network (ANN) model was successfully developed to forecast river flow in Apalachicola River. The model used a feed-forward, back-propagation network structure with an optimized conjugated training algorithm. Using long-term observations of rainfall and river flow during 1939-2000, the ANN model was satisfactorily trained and verified. Model predictions of river flow match well with the observations. The correlation coefficients between forecasting and observation for daily, monthly, quarterly and yearly flow forecasting are 0.98, 0.95, 0.91 and 0.83, respectively. Results of the forecasted flow rates from the ANN model were compared with those from a traditional autoregressive integrated moving average (ARIMA) forecasting model. Results indicate that the ANN model provides better accuracy in forecasting river flow than does the ARIMA model.

  3. Cell motion, contractile networks, and the physics of interpenetrating reactive flow

    SciTech Connect

    Dembo, M.; Harlow, F.

    1986-07-01

    In this paper the authors propose a physical model of contractile biological polymer networks based on the notion of reactive interpenetrating flow. They show how their model leads to a mathematical formulation of the dynamical laws governing the behavior of contractile networks. They also develop estimates of the various parameters that appear in their equations, and discuss some elementary predictions of the model concerning the general scaling principles that pertain to the motions of contractile networks.

  4. Cell motion, contractile networks, and the physics of interpenetrating reactive flow.

    PubMed Central

    Dembo, M; Harlow, F

    1986-01-01

    In this paper we propose a physical model of contractile biological polymer networks based on the notion of reactive interpenetrating flow. We show how our model leads to a mathematical formulation of the dynamical laws governing the behavior of contractile networks. We also develop estimates of the various parameters that appear in our equations, and we discuss some elementary predictions of the model concerning the general scaling principles that pertain to the motions of contractile networks. PMID:3730497

  5. Ramification of Channel Networks Incised by Groundwater Flow

    NASA Astrophysics Data System (ADS)

    Yi, R. S.; Seybold, H. F.; Petroff, A. P.; Devauchelle, O.; Rothman, D.

    2011-12-01

    The geometry of channel networks has been a source of fascination since at least Leonardo da Vinci's time. Yet a comprehensive understanding of ramification---the mechanism of branching by which a stream network acquires its geometric complexity---remains elusive. To investigate the mechanisms of ramification and network growth, we consider channel growth driven by groundwater flow as a model system, analogous to a medical scientist's laboratory rat. We test our theoretical predictions through analysis of a particularly compelling example found on the Florida Panhandle north of Bristol. As our ultimate goal is to understand ramification and growth dynamics of the entire network, we build a computational model based on the following growth hypothesis: Channels grow in the direction that captures the maximum water flux. When there are two such directions, tips bifurcate. The direction of growth can be determined from the expansion of the ground water field around each tip, where each coefficient in this expansion has a physical interpretation. The first coefficient in the expansion determines the ground water discharge, leading to a straight growth of the channel. The second term describes the asymmetry in the water field leading to a bending of the stream in the direction of maximal water flux. The ratio between the first and the third coefficient determines a critical distance rc over which the tip feels inhomogeneities in the ground water table. This initiates then the splitting of the tip. In order to test our growth hypothesis and to determine rc, we grow the Florida network backward. At each time step we calculate the solution of the ground water field and determine the appropriate expansion coefficients around each tip. Comparing this simulation result to the predicted values provides us with a stringent measure for rc and the significance of our growth hypothesis.

  6. Overland flow erosion inferred from Martian channel network geometry

    NASA Astrophysics Data System (ADS)

    Seybold, Hansjörg; Kirchner, James

    2016-04-01

    The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian drainage networks, and new studies suggest that Mars once had large volumes of surface water. But how this water flowed, and how it could have carved the channels, remains unclear. Simple scaling arguments show that networks formed by similar mechanisms should have similar branching angles on Earth and Mars, suggesting that Earth analogues can be informative here. A recent analysis of high-resolution data for the continental United States shows that climate leaves a characteristic imprint in the branching geometry of stream networks. Networks growing in humid regions have an average branching angle of α = 2π/5 = 72° [1], which is characteristic of network growth by groundwater sapping [2]. Networks in arid regions, where overland flow erosion is more dominant, show much smaller branching angles. Here we show that the channel networks on Mars have branching angles that resemble those created by surficial flows on Earth. This result implies that the growth of Martian channel networks was dominated by near-surface flow, and suggests that deeper infiltration was inhibited, potentially by permafrost or by impermeable weathered soils. [1] Climate's Watermark in the Geometry of River Networks, Seybold et al.; under review [2] Ramification of stream networks, Devauchelle et al.; PNAS (2012)

  7. Urban traffic-network performance: flow theory and simulation experiments

    SciTech Connect

    Williams, J.C.

    1986-01-01

    Performance models for urban street networks were developed to describe the response of a traffic network to given travel-demand levels. The three basic traffic flow variables, speed, flow, and concentration, are defined at the network level, and three model systems are proposed. Each system consists of a series of interrelated, consistent functions between the three basic traffic-flow variables as well as the fraction of stopped vehicles in the network. These models are subsequently compared with the results of microscopic simulation of a small test network. The sensitivity of one of the model systems to a variety of network features was also explored. Three categories of features were considered, with the specific features tested listed in parentheses: network topology (block length and street width), traffic control (traffic signal coordination), and traffic characteristics (level of inter-vehicular interaction). Finally, a fundamental issue concerning the estimation of two network-level parameters (from a nonlinear relation in the two-fluid theory) was examined. The principal concern was that of comparability of these parameters when estimated with information from a single vehicle (or small group of vehicles), as done in conjunction with previous field studies, and when estimated with network-level information (i.e., all the vehicles), as is possible with simulation.

  8. Understanding Urban Traffic Flow Characteristics from the Network Centrality Perspective at Different Granularities

    NASA Astrophysics Data System (ADS)

    Zhao, P. X.; Zhao, S. M.

    2016-06-01

    In this study, we analyze urban traffic flow using taxi trajectory data to understand the characteristics of traffic flow from the network centrality perspective at point (intersection), line (road), and area (community) granularities. The entire analysis process comprises three steps. The first step utilizes the taxi trajectory data to evaluate traffic flow at different granularities. Second, the centrality indices are calculated based on research units at different granularities. Third, correlation analysis between the centrality indices and corresponding urban traffic flow is performed. Experimental results indicate that urbaxperimental results indicate that urbaxperimental results indicate that urban traffic flow is relatively influenced by the road network structure. However, urban traffic flow also depends on the research unit size. Traditional centralities and traffic flow exhibit a low correlation at point granularity but exhibit a high correlation at line and area granularities. Furthermore, the conclusions of this study reflect the universality of the modifiable areal unit problem.

  9. Base flow and ground water in upper Sweetwater Valley, Tennessee

    USGS Publications Warehouse

    Evaldi, R.D.; Lewis, J.G.

    1983-01-01

    Base flow measurements showed interbasin transfer of water among sub-basins of upper Sweetwater Valley. In general, topographically higher sub-basins have deficient surface outflow unless significant spring flow occurs in the basin. Topographically lower areas adjacent to the main channel of Sweetwater Creek generally have surplus flow. Major flow surpluses were associated with areas in which the majority of flow originated at a spring. Unusual outflow was related to geology to hypothesize a ground-water flow network. Areas of ground-water flow up-gradient of large springs were hypothesized as likely areas for significant ground-water reservoirs. A water budget study indicated that during dry years approximately three-fourths of the annual flow to Sweetwater Creek may be derived from ground-water sources. Streamflow records were analyzed to estimate the frequency of low-flow of Sweetwater Creek. (USGS)

  10. Optimal active power dispatch by network flow approach

    SciTech Connect

    Carvalho, M.F. ); Soares, S.; Ohishi, T. )

    1988-11-01

    In this paper the optimal active power dispatch problem is formulated as a nonlinear capacitated network flow problem with additional linear constraints. Transmission flow limits and both Kirchhoff's laws are taken into account. The problem is solved by a Generalized Upper Bounding technique that takes advantage of the network flow structure of the problem. The new approach has potential applications on power systems problems such as economic dispatch, load supplying capability, minimum load shedding, and generation-transmission reliability. The paper also reviews the use of transportation models for power system analysis. A detailed illustrative example is presented.

  11. Stability and dynamical properties of material flow systems on random networks

    NASA Astrophysics Data System (ADS)

    Anand, K.; Galla, T.

    2009-04-01

    The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

  12. Confidence intervals in Flow Forecasting by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Panagoulia, Dionysia; Tsekouras, George

    2014-05-01

    One of the major inadequacies in implementation of Artificial Neural Networks (ANNs) for flow forecasting is the development of confidence intervals, because the relevant estimation cannot be implemented directly, contrasted to the classical forecasting methods. The variation in the ANN output is a measure of uncertainty in the model predictions based on the training data set. Different methods for uncertainty analysis, such as bootstrap, Bayesian, Monte Carlo, have already proposed for hydrologic and geophysical models, while methods for confidence intervals, such as error output, re-sampling, multi-linear regression adapted to ANN have been used for power load forecasting [1-2]. The aim of this paper is to present the re-sampling method for ANN prediction models and to develop this for flow forecasting of the next day. The re-sampling method is based on the ascending sorting of the errors between real and predicted values for all input vectors. The cumulative sample distribution function of the prediction errors is calculated and the confidence intervals are estimated by keeping the intermediate value, rejecting the extreme values according to the desired confidence levels, and holding the intervals symmetrical in probability. For application of the confidence intervals issue, input vectors are used from the Mesochora catchment in western-central Greece. The ANN's training algorithm is the stochastic training back-propagation process with decreasing functions of learning rate and momentum term, for which an optimization process is conducted regarding the crucial parameters values, such as the number of neurons, the kind of activation functions, the initial values and time parameters of learning rate and momentum term etc. Input variables are historical data of previous days, such as flows, nonlinearly weather related temperatures and nonlinearly weather related rainfalls based on correlation analysis between the under prediction flow and each implicit input

  13. Exact Convex Relaxation of Optimal Power Flow in Radial Networks

    SciTech Connect

    Gan, LW; Li, N; Topcu, U; Low, SH

    2015-01-01

    The optimal power flow (OPF) problem determines a network operating point that minimizes a certain objective such as generation cost or power loss. It is nonconvex. We prove that a global optimum of OPF can be obtained by solving a second-order cone program, under a mild condition after shrinking the OPF feasible set slightly, for radial power networks. The condition can be checked a priori, and holds for the IEEE 13, 34, 37, 123-bus networks and two real-world networks.

  14. Analysis of HRCT-derived xylem network reveals reverse flow in some vessels.

    PubMed

    Lee, Eric F; Matthews, Mark A; McElrone, Andrew J; Phillips, Ronald J; Shackel, Kenneth A; Brodersen, Craig R

    2013-09-21

    Long distance water and nutrient transport in plants is dependent on the proper functioning of xylem networks, a series of interconnected pipe-like cells that are vulnerable to hydraulic dysfunction as a result of drought-induced embolism and/or xylem-dwelling pathogens. Here, flow in xylem vessels was modeled to determine the role of vessel connectivity by using three dimensional xylem networks derived from High Resolution Computed Tomography (HRCT) images of grapevine (Vitis vinifera cv. 'Chardonnay') stems. Flow in 4-27% of the vessel segments (i.e. any section of vessel elements between connection points associated with intervessel pits) was found to be oriented in the direction opposite to the bulk flow under normal transpiration conditions. In order for the flow in a segment to be in the reverse direction, specific requirements were determined for the location of connections, distribution of vessel endings, diameters of the connected vessels, and the conductivity of the connections. Increasing connectivity and decreasing vessel length yielded increasing numbers of reverse flow segments until a maximum value was reached, after which more interconnected networks and smaller average vessel lengths yielded a decrease in the number of reverse flow segments. Xylem vessel relays also encouraged the formation of reverse flow segments. Based on the calculated flow rates in the xylem network, the downward spread of Xylella fastidiosa bacteria in grape stems was modeled, and reverse flow was shown to be an additional mechanism for the movement of bacteria to the trunk of grapevine. PMID:23743143

  15. Efficient community detection of network flows for varying Markov times and bipartite networks

    NASA Astrophysics Data System (ADS)

    Kheirkhahzadeh, Masoumeh; Lancichinetti, Andrea; Rosvall, Martin

    2016-03-01

    Community detection of network flows conventionally assumes one-step dynamics on the links. For sparse networks and interest in large-scale structures, longer timescales may be more appropriate. Oppositely, for large networks and interest in small-scale structures, shorter timescales may be better. However, current methods for analyzing networks at different timescales require expensive and often infeasible network reconstructions. To overcome this problem, we introduce a method that takes advantage of the inner workings of the map equation and evades the reconstruction step. This makes it possible to efficiently analyze large networks at different Markov times with no extra overhead cost. The method also evades the costly unipartite projection for identifying flow modules in bipartite networks.

  16. Extracting directed information flow networks: An application to genetics and semantics

    NASA Astrophysics Data System (ADS)

    Masucci, A. P.; Kalampokis, A.; Eguíluz, V. M.; Hernández-García, E.

    2011-02-01

    We introduce a general method to infer the directional information flow between populations whose elements are described by n-dimensional vectors of symbolic attributes. The method is based on the Jensen-Shannon divergence and on the Shannon entropy and has a wide range of application. We show here the results of two applications: first we extract the network of genetic flow between meadows of the seagrass Poseidonia oceanica, where the meadow elements are specified by sets of microsatellite markers, and then we extract the semantic flow network from a set of Wikipedia pages, showing the semantic channels between different areas of knowledge.

  17. Neural network approach to classification of traffic flow states

    SciTech Connect

    Yang, H.; Qiao, F.

    1998-11-01

    The classification of traffic flow states in China has traditionally been based on the Highway Capacity Manual, published in the United States. Because traffic conditions are generally different from country to country, though, it is important to develop a practical and useful classification method applicable to Chinese highway traffic. In view of the difficulty and complexity of a mathematical and physical realization, modern pattern recognition methods are considered practical in fulfilling this goal. This study applies a self-organizing neural network pattern recognition method to classify highway traffic states into some distinctive cluster centers. A small scale test with actual data is conducted, and the method is found to be potentially applicable in practice.

  18. River flow mass exponents with fractal channel networks and rainfall

    USGS Publications Warehouse

    Troutman, B.M.; Over, T.M.

    2001-01-01

    An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. ?? 2001 Elsevier Science Ltd. All rights reserved.

  19. Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects

    NASA Astrophysics Data System (ADS)

    de la Mata, Tamara; Llano, Carlos

    2013-07-01

    Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.

  20. Host Event Based Network Monitoring

    SciTech Connect

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  1. Building the Material Flow Networks of Aluminum in the 2007 U.S. Economy.

    PubMed

    Chen, Wei-Qiang; Graedel, T E; Nuss, Philip; Ohno, Hajime

    2016-04-01

    Based on the combination of the U.S. economic input-output table and the stocks and flows framework for characterizing anthropogenic metal cycles, this study presents a methodology for building material flow networks of bulk metals in the U.S. economy and applies it to aluminum. The results, which we term the Input-Output Material Flow Networks (IO-MFNs), achieve a complete picture of aluminum flow in the entire U.S. economy and for any chosen industrial sector (illustrated for the Automobile Manufacturing sector). The results are compared with information from our former study on U.S. aluminum stocks and flows to demonstrate the robustness and value of this new methodology. We find that the IO-MFN approach has the following advantages: (1) it helps to uncover the network of material flows in the manufacturing stage in the life cycle of metals; (2) it provides a method that may be less time-consuming but more complete and accurate in estimating new scrap generation, process loss, domestic final demand, and trade of final products of metals, than existing material flow analysis approaches; and, most importantly, (3) it enables the analysis of the material flows of metals in the U.S. economy from a network perspective, rather than merely that of a life cycle chain. PMID:26926828

  2. Loan and nonloan flows in the Australian interbank network

    NASA Astrophysics Data System (ADS)

    Sokolov, Andrey; Webster, Rachel; Melatos, Andrew; Kieu, Tien

    2012-05-01

    High-value transactions between banks in Australia are settled in the Reserve Bank Information and Transfer System (RITS) administered by the Reserve Bank of Australia. RITS operates on a real-time gross settlement (RTGS) basis and settles payments and transfers sourced from the SWIFT payment delivery system, the Austraclear securities settlement system, and the interbank transactions entered directly into RITS. In this paper, we analyse a dataset received from the Reserve Bank of Australia that includes all interbank transactions settled in RITS on an RTGS basis during five consecutive weekdays from 19 February 2007 inclusive, a week of relatively quiescent market conditions. The source, destination, and value of each transaction are known, which allows us to separate overnight loans from other transactions (nonloans) and reconstruct monetary flows between banks for every day in our sample. We conduct a novel analysis of the flow stability and examine the connection between loan and nonloan flows. Our aim is to understand the underlying causal mechanism connecting loan and nonloan flows. We find that the imbalances in the banks' exchange settlement funds resulting from the daily flows of nonloan transactions are almost exactly counterbalanced by the flows of overnight loans. The correlation coefficient between loan and nonloan imbalances is about -0.9 on most days. Some flows that persist over two consecutive days can be highly variable, but overall the flows are moderately stable in value. The nonloan network is characterised by a large fraction of persistent flows, whereas only half of the flows persist over any two consecutive days in the loan network. Moreover, we observe an unusual degree of coherence between persistent loan flow values on Tuesday and Wednesday. We probe static topological properties of the Australian interbank network and find them consistent with those observed in other countries.

  3. Network fingerprint: a knowledge-based characterization of biomedical networks

    PubMed Central

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  4. Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management.

    EPA Science Inventory

    Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing in...

  5. Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management

    EPA Science Inventory

    Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing i...

  6. The stationary flow in a heterogeneous compliant vessel network

    NASA Astrophysics Data System (ADS)

    Filoche, Marcel; Florens, Magali

    2011-09-01

    We introduce a mathematical model of the hydrodynamic transport into systems consisting in a network of connected flexible pipes. In each pipe of the network, the flow is assumed to be steady and one-dimensional. The fluid-structure interaction is described through tube laws which relate the pipe diameter to the pressure difference across the pipe wall. We show that the resulting one-dimensional differential equation describing the flow in the pipe can be exactly integrated if one is able to estimate averages of the Reynolds number along the pipe. The differential equation is then transformed into a non linear scalar equation relating pressures at both ends of the pipe and the flow rate in the pipe. These equations are coupled throughout the network with mass conservation equations for the flow and zero pressure losses at the branching points of the network. This allows us to derive a general model for the computation of the flow into very large inhomogeneous networks consisting of several thousands of flexible pipes. This model is then applied to perform numerical simulations of the human lung airway system at exhalation. The topology of the system and the tube laws are taken from morphometric and physiological data in the literature. We find good qualitative and quantitative agreement between the simulation results and flow-volume loops measured in real patients. In particular, expiratory flow limitation which is an essential characteristic of forced expiration is found to be well reproduced by our simulations. Finally, a mathematical model of a pathology (Chronic Obstructive Pulmonary Disease) is introduced which allows us to quantitatively assess the influence of a moderate or severe alteration of the airway compliances.

  7. Executable Code Recognition in Network Flows Using Instruction Transition Probabilities

    NASA Astrophysics Data System (ADS)

    Kim, Ikkyun; Kang, Koohong; Choi, Yangseo; Kim, Daewon; Oh, Jintae; Jang, Jongsoo; Han, Kijun

    The ability to recognize quickly inside network flows to be executable is prerequisite for malware detection. For this purpose, we introduce an instruction transition probability matrix (ITPX) which is comprised of the IA-32 instruction sets and reveals the characteristics of executable code's instruction transition patterns. And then, we propose a simple algorithm to detect executable code inside network flows using a reference ITPX which is learned from the known Windows Portable Executable files. We have tested the algorithm with more than thousands of executable and non-executable codes. The results show that it is very promising enough to use in real world.

  8. Field-effect Flow Control in Polymer Microchannel Networks

    NASA Technical Reports Server (NTRS)

    Sniadecki, Nathan; Lee, Cheng S.; Beamesderfer, Mike; DeVoe, Don L.

    2003-01-01

    A new Bio-MEMS electroosmotic flow (EOF) modulator for plastic microchannel networks has been developed. The EOF modulator uses field-effect flow control (FEFC) to adjust the zeta potential at the Parylene C microchannel wall. By setting a differential EOF pumping rate in two of the three microchannels at a T-intersection with EOF modulators, the induced pressure at the intersection generated pumping in the third, field-free microchannel. The EOF modulators are able to change the magnitude and direction of the pressure pumping by inducing either a negative or positive pressure at the intersection. The flow velocity is tracked by neutralized fluorescent microbeads in the microchannels. The proof-of-concept of the EOF modulator described here may be applied to complex plastic ,microchannel networks where individual microchannel flow rates are addressable by localized induced-pressure pumping.

  9. Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

    PubMed

    Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

    2013-06-01

    Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

  10. A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks

    PubMed Central

    Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

    2015-01-01

    This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

  11. A Scheme to Optimize Flow Routing and Polling Switch Selection of Software Defined Networks.

    PubMed

    Chen, Huan; Li, Lemin; Ren, Jing; Wang, Yang; Zhao, Yangming; Wang, Xiong; Wang, Sheng; Xu, Shizhong

    2015-01-01

    This paper aims at minimizing the communication cost for collecting flow information in Software Defined Networks (SDN). Since flow-based information collecting method requires too much communication cost, and switch-based method proposed recently cannot benefit from controlling flow routing, jointly optimize flow routing and polling switch selection is proposed to reduce the communication cost. To this end, joint optimization problem is formulated as an Integer Linear Programming (ILP) model firstly. Since the ILP model is intractable in large size network, we also design an optimal algorithm for the multi-rooted tree topology and an efficient heuristic algorithm for general topology. According to extensive simulations, it is found that our method can save up to 55.76% communication cost compared with the state-of-the-art switch-based scheme. PMID:26690571

  12. Betweenness centrality and its applications from modeling traffic flows to network community detection

    NASA Astrophysics Data System (ADS)

    Ren, Yihui

    As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the

  13. Resistive Network Optimal Power Flow: Uniqueness and Algorithms

    SciTech Connect

    Tan, CW; Cai, DWH; Lou, X

    2015-01-01

    The optimal power flow (OPF) problem minimizes the power loss in an electrical network by optimizing the voltage and power delivered at the network buses, and is a nonconvex problem that is generally hard to solve. By leveraging a recent development on the zero duality gap of OPF, we propose a second-order cone programming convex relaxation of the resistive network OPF, and study the uniqueness of the optimal solution using differential topology, especially the Poincare-Hopf Index Theorem. We characterize the global uniqueness for different network topologies, e.g., line, radial, and mesh networks. This serves as a starting point to design distributed local algorithms with global behaviors that have low complexity, are computationally fast, and can run under synchronous and asynchronous settings in practical power grids.

  14. Altered Cerebral Blood Flow Covariance Network in Schizophrenia

    PubMed Central

    Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui

    2016-01-01

    Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia. PMID:27445677

  15. Altered Cerebral Blood Flow Covariance Network in Schizophrenia.

    PubMed

    Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui

    2016-01-01

    Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia. PMID:27445677

  16. On Tree-Based Phylogenetic Networks.

    PubMed

    Zhang, Louxin

    2016-07-01

    A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model. PMID:27228397

  17. Lagrangian Flow networks: a new way to characterize transport and connectivity in geophysical flows

    NASA Astrophysics Data System (ADS)

    Ser-Giacomi, Enrico; Hernandez-Garcia, Emilio; Lopez, Cristobal; Rossi, Vincent; Vasile, Ruggero

    2015-04-01

    Water and air transport are among the basic processes shaping the climate of our planet. Heat and salinity fluxes change sea water density, and thus drive the global thermohaline circulation. Atmospheric winds force the ocean motion, and also transport moisture, heat or chemicals, impacting the regional climate. We describe transport among different regions of the ocean or the atmosphere by flow networks, giving a discrete and robust representation of the fluid advection dynamics. We use network-theory tools to gain insights into transport problem. Local and global features of the networks are extracted from many numerical experiments to give a time averaged description of the system. Classical concepts like dispersion, mixing and connectivity are finally related to a set of network-like objects contributing to build a "dictionary" between network measures and physical quantities in geophysical flows.

  18. Toward an optimal design principle in symmetric and asymmetric tree flow networks.

    PubMed

    Miguel, Antonio F

    2016-01-21

    Fluid flow in tree-shaped networks plays an important role in both natural and engineered systems. This paper focuses on laminar flows of Newtonian and non-Newtonian power law fluids in symmetric and asymmetric bifurcating trees. Based on the constructal law, we predict the tree-shaped architecture that provides greater access to the flow subjected to the total network volume constraint. The relationships between the sizes of parent and daughter tubes are presented both for symmetric and asymmetric branching tubes. We also approach the wall-shear stresses and the flow resistance in terms of first tube size, degree of asymmetry between daughter branches, and rheological behavior of the fluid. The influence of tubes obstructing the fluid flow is also accounted for. The predictions obtained by our theory-driven approach find clear support in the findings of previous experimental studies. PMID:26555845

  19. Methods to improve neural network performance in daily flows prediction

    NASA Astrophysics Data System (ADS)

    Wu, C. L.; Chau, K. W.; Li, Y. S.

    2009-06-01

    SummaryIn this paper, three data-preprocessing techniques, moving average (MA), singular spectrum analysis (SSA), and wavelet multi-resolution analysis (WMRA), were coupled with artificial neural network (ANN) to improve the estimate of daily flows. Six models, including the original ANN model without data preprocessing, were set up and evaluated. Five new models were ANN-MA, ANN-SSA1, ANN-SSA2, ANN-WMRA1, and ANN-WMRA2. The ANN-MA was derived from the raw ANN model combined with the MA. The ANN-SSA1, ANN-SSA2, ANN-WMRA1 and ANN-WMRA2 were generated by using the original ANN model coupled with SSA and WMRA in terms of two different means. Two daily flow series from different watersheds in China (Lushui and Daning) were used in six models for three prediction horizons (i.e., 1-, 2-, and 3-day-ahead forecast). The poor performance on ANN forecast models was mainly due to the existence of the lagged prediction. The ANN-MA, among six models, performed best and eradicated the lag effect. The performances from the ANN-SSA1 and ANN-SSA2 were similar, and the performances from the ANN-WMRA1 and ANN-WMRA2 were also similar. However, the models based on the SSA presented better performance than the models based on the WMRA at all forecast horizons, which meant that the SSA is more effective than the WMRA in improving the ANN performance in the current study. Based on an overall consideration including the model performance and the complexity of modeling, the ANN-MA model was optimal, then the ANN model coupled with SSA, and finally the ANN model coupled with WMRA.

  20. Location-Based Services in Vehicular Networks

    ERIC Educational Resources Information Center

    Wu, Di

    2013-01-01

    Location-based services have been identified as a promising communication paradigm in highly mobile and dynamic vehicular networks. However, existing mobile ad hoc networking cannot be directly applied to vehicular networking due to differences in traffic conditions, mobility models and network topologies. On the other hand, hybrid architectures…

  1. Integrated OpenFlow-GMPLS control plane: an overlay model for software defined packet over optical networks.

    PubMed

    Azodolmolky, Siamak; Nejabati, Reza; Escalona, Eduard; Jayakumar, Ramanujam; Efstathiou, Nikolaos; Simeonidou, Dimitra

    2011-12-12

    Bandwidth demands resulting from generated traffics by emerging applications, when aggregated at the edge of the networks for transport over core networks can only be met with high-capacity WDM circuit switched optical networks. An efficient end-to-end delivery of packet streams in terms of network control, operation and management is one of the key challenges for the network operators. Therefore, a unified control and management plane for both packet and optical circuit switch domains is a good candidate to address this need. In this paper a novel software-defined packet over optical networks solution based on the integration of OpenFlow and GMPLS control plane is experimentally demonstrated. The proposed architecture, experimental setup, and average flow setup time for different optical flows are reported. The performance of the extended OpenFlow controller is also presented and discussed. PMID:22274052

  2. A stable approach for coupling multidimensional cardiovascular and pulmonary networks based on a novel pressure-flow rate or pressure-only Neumann boundary condition formulation.

    PubMed

    Ismail, M; Gravemeier, V; Comerford, A; Wall, W A

    2014-04-01

    In many biomedical flow problems, reversed flows along with standard treatment of Neumann boundary conditions can cause instabilities. We have developed a method that resolves these instabilities in a consistent way while maintaining correct pressure and flow rate values. We also are able to remove the necessary prescription of both pressure and velocities/flow rates to problems where only pressure is known. In addition, the method is extended to coupled 3D/reduced-D fluid and fluid-structure interaction models. Numerical examples mainly focus on using Neumann boundary condition in cardiovascular and pulmonary systems, particularly, coupled with 3D-1D and 3D-0D models. Inflow pressure, traction, and impedance boundary conditions are first tested on idealized tubes for various Womersley numbers. Both pressure and flow rate are shown to match the analytical solutions for these examples. Our method is then tested on a coupled 1D-3D-1D artery example, demonstrating the power and simplicity of extending this method toward fluid-structure interaction. Finally, the proposed method is investigated for a coupled 3D-0D patient-specific full lung model during spontaneous breathing. All coupled 3D/reduced-D results show a perfect matching of pressure and flow rate between 3D and corresponding reduced-D boundaries. The methods are straight-forward to implement in contrast to using Lagrange multipliers as previously proposed in other studies. PMID:24243701

  3. Flow and Transport Phenomena in Two-Dimensional Fracture Networks.

    NASA Astrophysics Data System (ADS)

    Rodriguez, Adolfo Antonio

    1995-01-01

    This dissertation presents a comprehensive study of two-dimensional fracture networks; it addresses three different aspects: geometry, fluid-flow and diffusion solute transport. The first subject consists in the description of the topological structure of the network. This is done by creating matrix representations for different topological operators which are then used to describe the geometry of the system. A series of systematic procedures were developed to determine the most important geometrical features of the fracture network including connectivity and backbone. The second point of study was subdivided in two parts: steady-state and transient phenomena. The steady -state hydraulic response of the network was investigated by generalizing the topological formulations of electrical networks. These formulations (which were originally developed by classical authors like Kirchhoff and Weyl) give a convenient mean for expressing the mass balance condition at the nodes. The analogy between electrical conduction and steady-state fluid flow is not exact thus, some additional concepts need to be introduced (like the node-rate-injection vector). Results for this part of the work include detailed vector field diagrams that represent the flow pattern across the network. In order to solve the transient fluid-flow problem, some additional considerations needed to be made. The idea is to start with the one-dimensional partial differential equation that governs the transient fluid flow across a single fracture (diffusion equation). The Laplace transform is then applied to eliminate time, the mass balance condition at each node is expressed in terms of the Laplace transform variables. Once the results are found, the inverse Laplace transforms were obtained via a numerical algorithm (Stephest algorithm). With the introduction of two new topological operators (closely related to the boundary operator), it was possible to express the linear set of mass balance equations in a form

  4. Bicriteria Network Optimization Problem using Priority-based Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Gen, Mitsuo; Lin, Lin; Cheng, Runwei

    Network optimization is being an increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. In many applications, however, there are several criteria associated with traversing each edge of a network. For example, cost and flow measures are both important in the networks. As a result, there has been recent interest in solving Bicriteria Network Optimization Problem. The Bicriteria Network Optimization Problem is known a NP-hard. The efficient set of paths may be very large, possibly exponential in size. Thus the computational effort required to solve it can increase exponentially with the problem size in the worst case. In this paper, we propose a genetic algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including maximum flow (MXF) model and minimum cost flow (MCF) model. The objective is to find the set of Pareto optimal solutions that give possible maximum flow with minimum cost. This paper also combines Adaptive Weight Approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. Computer simulations show the several numerical experiments by using some difficult-to-solve network design problems, and show the effectiveness of the proposed method.

  5. Knowledge-Based Network Operations

    NASA Astrophysics Data System (ADS)

    Wu, Chuan-lin; Hung, Chaw-Kwei; Stedry, Steven P.; McClure, James P.; Yeh, Show-Way

    1988-03-01

    An expert system is being implemented for enhancing operability of the Ground Communication Facility (GCF) of Jet Propulsion Laboratory's (JPL) Deep Space Network (DSN). The DSN is a tracking network for all of JPL's spacecraft plus a subset of spacecrafts launched by other NASA centers. A GCF upgrade task is set to replace the current GCF aging system with new, modern equipments which are capable of using knowledge-based monitor and control approach. The expert system, implemented in terms of KEE and SUN workstation, is used for performing network fault management, configuration management, and performance management in real-time. Monitor data are collected from each processor and DSCC's in every five seconds. In addition to serving as input parameters of the expert system, extracted management information is used to update a management information database. For the monitor and control purpose, software of each processor is divided into layers following the OSI standard. Each layer is modeled as a finite state machine. A System Management Application Process (SMAP) is implemented at application layer, which coordinates layer managers of the same processor and communicates with peer SMAPs of other processors. The expert system will be tuned by augmenting the production rules as the operation is going on, and its performance will be measured.

  6. Dynamic QoS Provisioning for Ethernet-based Networks

    NASA Astrophysics Data System (ADS)

    Angelopoulos, J.; Kanonakis, K.; Leligou, H. C.; Orfanoudakis, Th.; Katsigiannis, M.

    2008-11-01

    The evolution towards packet-based access networks and the importance of quality of experience brings the need for access networks that support the offer of a wide range of multimedia services not currently available to the desired extent. Legacy networks based on circuit switching used explicit signalling that travelled to all nodes along the path to book resources before the launce of the media stream. This approach does not scale well and is not in line with the philosophy of packet networks. Still, the need to reserve resources in advance remains since real-time services have limited if any means of adjusting their rates to the prevailing network conditions and to preserve customer satisfaction the traditional preventive approach that needs accurate estimates of resource needs for the duration of the session is the only option. The paper describes a possible CAC solution based on measuring flows and enriches the network with implicit admission control (without obviating explicit control if available) and can manage resource allocation to protect quality-demanding services from degradation. The basis is a flow measurement system, which will estimate the traffic load produced by the flow and activate admission control. However, because in most cases these initial indication may well be misleading, it will be cross checked against a database of previously recorded flows per customer interface which can provide long term data on the flows leaving only a few cases that have to be corrected on the fly. The overall product is a self-learning autonomic system that supports QoS in the access network for services that do not communicate with the network layer such as, for example, peer-to-peer real-time multimedia applications.

  7. Quantification of Blood Flow and Topology in Developing Vascular Networks

    PubMed Central

    Kloosterman, Astrid; Hierck, Beerend; Westerweel, Jerry; Poelma, Christian

    2014-01-01

    Since fluid dynamics plays a critical role in vascular remodeling, quantification of the hemodynamics is crucial to gain more insight into this complex process. Better understanding of vascular development can improve prediction of the process, and may eventually even be used to influence the vascular structure. In this study, a methodology to quantify hemodynamics and network structure of developing vascular networks is described. The hemodynamic parameters and topology are derived from detailed local blood flow velocities, obtained by in vivo micro-PIV measurements. The use of such detailed flow measurements is shown to be essential, as blood vessels with a similar diameter can have a large variation in flow rate. Measurements are performed in the yolk sacs of seven chicken embryos at two developmental stages between HH 13+ and 17+. A large range of flow velocities (1 µm/s to 1 mm/s) is measured in blood vessels with diameters in the range of 25–500 µm. The quality of the data sets is investigated by verifying the flow balances in the branching points. This shows that the quality of the data sets of the seven embryos is comparable for all stages observed, and the data is suitable for further analysis with known accuracy. When comparing two subsequently characterized networks of the same embryo, vascular remodeling is observed in all seven networks. However, the character of remodeling in the seven embryos differs and can be non-intuitive, which confirms the necessity of quantification. To illustrate the potential of the data, we present a preliminary quantitative study of key network topology parameters and we compare these with theoretical design rules. PMID:24823933

  8. Flow based vs. demand based energy-water modelling

    NASA Astrophysics Data System (ADS)

    Rozos, Evangelos; Nikolopoulos, Dionysis; Efstratiadis, Andreas; Koukouvinos, Antonios; Makropoulos, Christos

    2015-04-01

    The water flow in hydro-power generation systems is often used downstream to cover other type of demands like irrigation and water supply. However, the typical case is that the energy demand (operation of hydro-power plant) and the water demand do not coincide. Furthermore, the water inflow into a reservoir is a stochastic process. Things become more complicated if renewable resources (wind-turbines or photovoltaic panels) are included into the system. For this reason, the assessment and optimization of the operation of hydro-power systems are challenging tasks that require computer modelling. This modelling should not only simulate the water budget of the reservoirs and the energy production/consumption (pumped-storage), but should also take into account the constraints imposed by the natural or artificial water network using a flow routing algorithm. HYDRONOMEAS, for example, uses an elegant mathematical approach (digraph) to calculate the flow in a water network based on: the demands (input timeseries), the water availability (simulated) and the capacity of the transmission components (properties of channels, rivers, pipes, etc.). The input timeseries of demand should be estimated by another model and linked to the corresponding network nodes. A model that could be used to estimate these timeseries is UWOT. UWOT is a bottom up urban water cycle model that simulates the generation, aggregation and routing of water demand signals. In this study, we explore the potentials of UWOT in simulating the operation of complex hydrosystems that include energy generation. The evident advantage of this approach is the use of a single model instead of one for estimation of demands and another for the system simulation. An application of UWOT in a large scale system is attempted in mainland Greece in an area extending over 130×170 km². The challenges, the peculiarities and the advantages of this approach are examined and critically discussed.

  9. A semi-analytical model for the flow behavior of naturally fractured formations with multi-scale fracture networks

    NASA Astrophysics Data System (ADS)

    Jia, Pin; Cheng, Linsong; Huang, Shijun; Wu, Yonghui

    2016-06-01

    This paper presents a semi-analytical model for the flow behavior of naturally fractured formations with multi-scale fracture networks. The model dynamically couples an analytical dual-porosity model with a numerical discrete fracture model. The small-scale fractures with the matrix are idealized as a dual-porosity continuum and an analytical flow solution is derived based on source functions in Laplace domain. The large-scale fractures are represented explicitly as the major fluid conduits and the flow is numerically modeled, also in Laplace domain. This approach allows us to include finer details of the fracture network characteristics while keeping the computational work manageable. For example, the large-scale fracture network may have complex geometry and varying conductivity, and the computations can be done at predetermined, discrete times, without any grids in the dual-porosity continuum. The validation of the semi-analytical model is demonstrated in comparison to the solution of ECLIPSE reservoir simulator. The simulation is fast, gridless and enables rapid model setup. On the basis of the model, we provide detailed analysis of the flow behavior of a horizontal production well in fractured reservoir with multi-scale fracture networks. The study has shown that the system may exhibit six flow regimes: large-scale fracture network linear flow, bilinear flow, small-scale fracture network linear flow, pseudosteady-state flow, interporosity flow and pseudoradial flow. During the first four flow periods, the large-scale fracture network behaves as if it only drains in the small-scale fracture network; that is, the effect of the matrix is negligibly small. The characteristics of the bilinear flow and the small-scale fracture network linear flow are predominantly determined by the dimensionless large-scale fracture conductivity. And low dimensionless fracture conductivity will generate large pressure drops in the large-scale fractures surrounding the wellbore. With

  10. Minimum cost maximum flow algorithm for upstream bandwidth allocation in OFDMA passive optical networks

    NASA Astrophysics Data System (ADS)

    Wu, Yating; Kuang, Bin; Wang, Tao; Zhang, Qianwu; Wang, Min

    2015-12-01

    This paper presents a minimum cost maximum flow (MCMF) based upstream bandwidth allocation algorithm, which supports differentiated QoS for orthogonal frequency division multiple access passive optical networks (OFDMA-PONs). We define a utility function as the metric to characterize the satisfaction degree of an ONU on the obtained bandwidth. The bandwidth allocation problem is then formulated as maximizing the sum of the weighted total utility functions of all ONUs. By constructing a flow network graph, we obtain the optimized bandwidth allocation using the MCMF algorithm. Simulation results show that the proposed scheme improves the performance in terms of mean packet delay, packet loss ratio and throughput.

  11. The prescribed output pattern regulates the modular structure of flow networks

    NASA Astrophysics Data System (ADS)

    Beber, Moritz Emanuel; Armbruster, Dieter; Hütt, Marc-Thorsten

    2013-11-01

    Modules are common functional and structural properties of many social, technical and biological networks. Especially for biological systems it is important to understand how modularity is related to function and how modularity evolves. It is known that time-varying or spatially organized goals can lead to modularity in a simulated evolution of signaling networks. Here, we study a minimal model of material flow in networks. We discuss the relation between the shared use of nodes, i.e., the cooperativity of modules, and the orthogonality of a prescribed output pattern. We study the persistence of cooperativity through an evolution of robustness against local damages. We expect the results to be valid for a large class of flow-based biological and technical networks.

  12. Availability Improvement of Layer 2 Seamless Networks Using OpenFlow

    PubMed Central

    Molina, Elias; Jacob, Eduardo; Matias, Jon; Moreira, Naiara; Astarloa, Armando

    2015-01-01

    The network robustness and reliability are strongly influenced by the implementation of redundancy and its ability of reacting to changes. In situations where packet loss or maximum latency requirements are critical, replication of resources and information may become the optimal technique. To this end, the IEC 62439-3 Parallel Redundancy Protocol (PRP) provides seamless recovery in layer 2 networks by delegating the redundancy management to the end-nodes. In this paper, we present a combination of the Software-Defined Networking (SDN) approach and PRP topologies to establish a higher level of redundancy and thereby, through several active paths provisioned via the OpenFlow protocol, the global reliability is increased, as well as data flows are managed efficiently. Hence, the experiments with multiple failure scenarios, which have been run over the Mininet network emulator, show the improvement in the availability and responsiveness over other traditional technologies based on a single active path. PMID:25759861

  13. The prescribed output pattern regulates the modular structure of flow networks

    NASA Astrophysics Data System (ADS)

    Emanuel Beber, Moritz; Armbruster, Dieter; Hütt, Marc-Thorsten

    2013-11-01

    Modules are common functional and structural properties of many social, technical and biological networks. Especially for biological systems it is important to understand how modularity is related to function and how modularity evolves. It is known that time-varying or spatially organized goals can lead to modularity in a simulated evolution of signaling networks. Here, we study a minimal model of material flow in networks. We discuss the relation between the shared use of nodes, i.e., the cooperativity of modules, and the orthogonality of a prescribed output pattern. We study the persistence of cooperativity through an evolution of robustness against local damages. We expect the results to be valid for a large class of flow-based biological and technical networks. Supplementary material in the form of one pdf file available from the Journal web page at http://dx.doi.org/10.1140/epjb/e2013-40672-3

  14. Availability improvement of layer 2 seamless networks using OpenFlow.

    PubMed

    Molina, Elias; Jacob, Eduardo; Matias, Jon; Moreira, Naiara; Astarloa, Armando

    2015-01-01

    The network robustness and reliability are strongly influenced by the implementation of redundancy and its ability of reacting to changes. In situations where packet loss or maximum latency requirements are critical, replication of resources and information may become the optimal technique. To this end, the IEC 62439-3 Parallel Redundancy Protocol (PRP) provides seamless recovery in layer 2 networks by delegating the redundancy management to the end-nodes. In this paper, we present a combination of the Software-Defined Networking (SDN) approach and PRP topologies to establish a higher level of redundancy and thereby, through several active paths provisioned via the OpenFlow protocol, the global reliability is increased, as well as data flows are managed efficiently. Hence, the experiments with multiple failure scenarios, which have been run over the Mininet network emulator, show the improvement in the availability and responsiveness over other traditional technologies based on a single active path. PMID:25759861

  15. An Amorphous Network Model for Capillary Flow and Dispersion in a Partially Saturated Porous Medium

    NASA Astrophysics Data System (ADS)

    Simmons, C. S.; Rockhold, M. L.

    2013-12-01

    Network models of capillary flow are commonly used to represent conduction of fluids at pore scales. Typically, a flow system is described by a regular geometric lattice of interconnected tubes. Tubes constitute the pore throats, while connection junctions (nodes) are pore bodies. Such conceptualization of the geometry, however, is questionable for the pore scale, where irregularity clearly prevails, although prior published models using a regular lattice have demonstrated successful descriptions of the flow in the bulk medium. Here a network is allowed to be amorphous, and is not subject to any particular lattice structure. Few network flow models have treated partially saturated or even multiphase conditions. The research trend is toward using capillary tubes with triangular or square cross sections that have corners and always retain some fluid by capillarity when drained. In contrast, this model uses only circular capillaries, whose filled state is controlled by a capillary pressure rule for the junctions. The rule determines which capillary participate in the flow under an imposed matric potential gradient during steady flow conditions. Poiseuille's Law and Laplace equation are used to describe flow and water retention in the capillary units of the model. A modified conjugate gradient solution for steady flow that tracks which capillary in an amorphous network contribute to fluid conduction was devised for partially saturated conditions. The model thus retains the features of classical capillary models for determining hydraulic flow properties under unsaturated conditions based on distribution of non-interacting tubes, but now accounts for flow exchange at junctions. Continuity of the flow balance at every junction is solved simultaneously. The effective water retention relationship and unsaturated permeability are evaluated for an extensive enough network to represent a small bulk sample of porous medium. The model is applied for both a hypothetically

  16. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

    PubMed Central

    Cheung, Kit; Schultz, Simon R.; Luk, Wayne

    2016-01-01

    NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

  17. NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors.

    PubMed

    Cheung, Kit; Schultz, Simon R; Luk, Wayne

    2015-01-01

    NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation. PMID:26834542

  18. Tracking Inter-Regional Carbon Flows: A Hybrid Network Model.

    PubMed

    Chen, Shaoqing; Chen, Bin

    2016-05-01

    The mitigation of anthropogenic carbon emissions has moved beyond the local scale because they diffuse across boundaries, and the consumption that triggers emissions has become regional and global. A precondition of effective mitigation is to explicitly assess inter-regional transfer of emissions. This study presents a hybrid network model to track inter-regional carbon flows by combining network analysis and input-output analysis. The direct, embodied, and controlled emissions associated with regions are quantified for assessing various types of carbon flow. The network-oriented metrics called "controlled emissions" is proposed to cover the amount of carbon emissions that can be mitigated within a region by adjusting its consumption. The case study of the Jing-Jin-Ji Area suggests that CO2 emissions embodied in products are only partially controlled by a region from a network perspective. Controlled carbon accounted for about 70% of the total embodied carbon flows, while household consumption only controlled about 25% of Beijing's emissions, much lower than its proportion of total embodied carbon. In addition to quantifying emissions, the model can pinpoint the dominant processes and sectors of emissions transfer across regions. This technique is promising for searching efficient pathways of coordinated emissions control across various regions connected by trade. PMID:27063784

  19. Network Flow Simulation of Fluid Transients in Rocket Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Bandyopadhyay, Alak; Hamill, Brian; Ramachandran, Narayanan; Majumdar, Alok

    2011-01-01

    Fluid transients, also known as water hammer, can have a significant impact on the design and operation of both spacecraft and launch vehicle propulsion systems. These transients often occur at system activation and shutdown. The pressure rise due to sudden opening and closing of valves of propulsion feed lines can cause serious damage during activation and shutdown of propulsion systems. During activation (valve opening) and shutdown (valve closing), pressure surges must be predicted accurately to ensure structural integrity of the propulsion system fluid network. In the current work, a network flow simulation software (Generalized Fluid System Simulation Program) based on Finite Volume Method has been used to predict the pressure surges in the feed line due to both valve closing and valve opening using two separate geometrical configurations. The valve opening pressure surge results are compared with experimental data available in the literature and the numerical results compared very well within reasonable accuracy (< 5%) for a wide range of inlet-to-initial pressure ratios. A Fast Fourier Transform is preformed on the pressure oscillations to predict the various modal frequencies of the pressure wave. The shutdown problem, i.e. valve closing problem, the simulation results are compared with the results of Method of Characteristics. Most rocket engines experience a longitudinal acceleration, known as "pogo" during the later stage of engine burn. In the shutdown example problem, an accumulator has been used in the feed system to demonstrate the "pogo" mitigation effects in the feed system of propellant. The simulation results using GFSSP compared very well with the results of Method of Characteristics.

  20. Block-based neural networks.

    PubMed

    Moon, S W; Kong, S G

    2001-01-01

    This paper presents a novel block-based neural network (BBNN) model and the optimization of its structure and weights based on a genetic algorithm. The architecture of the BBNN consists of a 2D array of fundamental blocks with four variable input/output nodes and connection weights. Each block can have one of four different internal configurations depending on the structure settings, The BBNN model includes some restrictions such as 2D array and integer weights in order to allow easier implementation with reconfigurable hardware such as field programmable logic arrays (FPGA). The structure and weights of the BBNN are encoded with bit strings which correspond to the configuration bits of FPGA. The configuration bits are optimized globally using a genetic algorithm with 2D encoding and modified genetic operators. Simulations show that the optimized BBNN can solve engineering problems such as pattern classification and mobile robot control. PMID:18244385

  1. Growth-induced mass flows in fungal networks

    PubMed Central

    Heaton, Luke L. M.; López, Eduardo; Maini, Philip K.; Fricker, Mark D.; Jones, Nick S.

    2010-01-01

    Cord-forming fungi form extensive networks that continuously adapt to maintain an efficient transport system. As osmotically driven water uptake is often distal from the tips, and aqueous fluids are incompressible, we propose that growth induces mass flows across the mycelium, whether or not there are intrahyphal concentration gradients. We imaged the temporal evolution of networks formed by Phanerochaete velutina, and at each stage calculated the unique set of currents that account for the observed changes in cord volume, while minimizing the work required to overcome viscous drag. Predicted speeds were in reasonable agreement with experimental data, and the pressure gradients needed to produce these flows are small. Furthermore, cords that were predicted to carry fast-moving or large currents were significantly more likely to increase in size than cords with slow-moving or small currents. The incompressibility of the fluids within fungi means there is a rapid global response to local fluid movements. Hence velocity of fluid flow is a local signal that conveys quasi-global information about the role of a cord within the mycelium. We suggest that fluid incompressibility and the coupling of growth and mass flow are critical physical features that enable the development of efficient, adaptive biological transport networks. PMID:20538649

  2. Flow distribution in parallel microfluidic networks and its effect on concentration gradient.

    PubMed

    Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N

    2015-09-01

    The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow

  3. A Network Coding Based Routing Protocol for Underwater Sensor Networks

    PubMed Central

    Wu, Huayang; Chen, Min; Guan, Xin

    2012-01-01

    Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime. PMID:22666045

  4. Modeling dynamic functional information flows on large-scale brain networks.

    PubMed

    Lv, Peili; Guo, Lei; Hu, Xintao; Li, Xiang; Jin, Changfeng; Han, Junwei; Li, Lingjiang; Liu, Tianming

    2013-01-01

    Growing evidence from the functional neuroimaging field suggests that human brain functions are realized via dynamic functional interactions on large-scale structural networks. Even in resting state, functional brain networks exhibit remarkable temporal dynamics. However, it has been rarely explored to computationally model such dynamic functional information flows on large-scale brain networks. In this paper, we present a novel computational framework to explore this problem using multimodal resting state fMRI (R-fMRI) and diffusion tensor imaging (DTI) data. Basically, recent literature reports including our own studies have demonstrated that the resting state brain networks dynamically undergo a set of distinct brain states. Within each quasi-stable state, functional information flows from one set of structural brain nodes to other sets of nodes, which is analogous to the message package routing on the Internet from the source node to the destination. Therefore, based on the large-scale structural brain networks constructed from DTI data, we employ a dynamic programming strategy to infer functional information transition routines on structural networks, based on which hub routers that most frequently participate in these routines are identified. It is interesting that a majority of those hub routers are located within the default mode network (DMN), revealing a possible mechanism of the critical functional hub roles played by the DMN in resting state. Also, application of this framework on a post trauma stress disorder (PTSD) dataset demonstrated interesting difference in hub router distributions between PTSD patients and healthy controls. PMID:24579202

  5. Overall Ventilation System Flow Network Calculation for Site Recommendation

    SciTech Connect

    Jeff J. Steinhoff

    2001-08-02

    The scope of this calculation is to determine ventilation system resistances, pressure drops, airflows, and operating cost estimates for the Site Recommendation (SR) design as detailed in the ''Site Recommendation Subsurface Layout'' (BSC (Bechtel SAIC Company) 2001a). The statutory limit for emplacement of waste in Yucca Mountain is 70,000 metric tons of uranium (MTU) and is considered the base case for this report. The objective is to determine the overall repository system ventilation flow network for the monitoring phase during normal operations and to provide a basis for the system description document design descriptions. Any values derived from this calculation will not be used to support construction, fabrication, or procurement. The work scope is identified in the ''Technical Work Plan for Subsurface Design Section FY01 Work Activities'' (CRWMS M&O 2001, pp. 6 and 13). In accordance with the technical work plan this calculation was prepared in accordance with AP-3.12Q, ''Calculations'' and other procedures invoked by AP-3.12Q. It also incorporates the procedure AP-SI1.Q, ''Software Management''.

  6. Self-control of traffic lights and vehicle flows in urban road networks

    NASA Astrophysics Data System (ADS)

    Lämmer, Stefan; Helbing, Dirk

    2008-04-01

    Based on fluid-dynamic and many-particle (car-following) simulations of traffic flows in (urban) networks, we study the problem of coordinating incompatible traffic flows at intersections. Inspired by the observation of self-organized oscillations of pedestrian flows at bottlenecks, we propose a self-organization approach to traffic light control. The problem can be treated as a multi-agent problem with interactions between vehicles and traffic lights. Specifically, our approach assumes a priority-based control of traffic lights by the vehicle flows themselves, taking into account short-sighted anticipation of vehicle flows and platoons. The considered local interactions lead to emergent coordination patterns such as 'green waves' and achieve an efficient, decentralized traffic light control. While the proposed self-control adapts flexibly to local flow conditions and often leads to non-cyclical switching patterns with changing service sequences of different traffic flows, an almost periodic service may evolve under certain conditions and suggests the existence of a spontaneous synchronization of traffic lights despite the varying delays due to variable vehicle queues and travel times. The self-organized traffic light control is based on an optimization and a stabilization rule, each of which performs poorly at high utilizations of the road network, while their proper combination reaches a superior performance. The result is a considerable reduction not only in the average travel times, but also of their variation. Similar control approaches could be applied to the coordination of logistic and production processes.

  7. An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

    PubMed Central

    Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.

    2013-01-01

    The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

  8. An open-access modeled passenger flow matrix for the global air network in 2010.

    PubMed

    Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J

    2013-01-01

    The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

  9. Wet Channel Network Extraction based on LiDAR Data

    NASA Astrophysics Data System (ADS)

    Hooshyar, M.; Kim, S.; Wang, D.; Medeiros, S. C.

    2015-12-01

    The temporal dynamics of stream network is vitally important for understanding hydrologic processes including groundwater interactions and hydrograph recessions. However, observations are limited on flowing channel heads, which are usually located in headwater catchments and under canopy. Near infrared LiDAR data provides an opportunity to map the flowing channel network owing to the fine spatial resolution, canopy penetration, and strong absorption of the light energy by the water surface. A systematic method is developed herein to map flowing channel networks based on the signal intensity of ground LiDAR return, which is lower on water surfaces than on dry surfaces. Based on the selected sample sites where the wetness conditions are known, the signal intensities of ground returns are extracted from the LiDAR point data. The frequency distributions of wet surface and dry surface returns are constructed. With the aid of LiDAR-based ground elevation, the signal intensity thresholds are identified for mapping flowing channels. The developed method is applied to Lake Tahoe area based on eight LiDAR snapshots during recession periods in five watersheds. A power-law relationship between streamflow and flowing channel length during the recession period is derived based on the result.

  10. Prediction of friction factor of pure water flowing inside vertical smooth and microfin tubes by using artificial neural networks

    NASA Astrophysics Data System (ADS)

    Çebi, A.; Akdoğan, E.; Celen, A.; Dalkilic, A. S.

    2016-06-01

    An artificial neural network (ANN) model of friction factor in smooth and microfin tubes under heating, cooling and isothermal conditions was developed in this study. Data used in ANN was taken from a vertically positioned heat exchanger experimental setup. Multi-layered feed-forward neural network with backpropagation algorithm, radial basis function networks and hybrid PSO-neural network algorithm were applied to the database. Inputs were the ratio of cross sectional flow area to hydraulic diameter, experimental condition number depending on isothermal, heating, or cooling conditions and mass flow rate while the friction factor was the output of the constructed system. It was observed that such neural network based system could effectively predict the friction factor values of the flows regardless of their tube types. A dependency analysis to determine the strongest parameter that affected the network and database was also performed and tube geometry was found to be the strongest parameter of all as a result of analysis.

  11. Visualization and Measurement of Flow in Two-Dimensional Paper Networks

    PubMed Central

    Kauffman, Peter; Fu, Elain; Lutz, Barry; Yager, Paul

    2016-01-01

    The two-dimensional paper network (2DPN) is a versatile new microfluidic format for performing complex chemical processes. For chemical detection, for example, 2DPNs have the potential to exceed the capabilities and performance of existing paper-based lateral flow devices at a comparable cost and ease of use. To design such 2DPNs, it is necessary to predict 2D flow patterns and velocities within them, but because of the scattering of the paper matrix, conventional particle imaging velocimetry is not practical. In this note, we demonstrate two methods for visualization of flow in 2DPNs that are inexpensive, easy to implement, and quantifiable. PMID:20676410

  12. Multiscale fracture network characterization and impact on flow: A case study on the Latemar carbonate platform

    NASA Astrophysics Data System (ADS)

    Hardebol, N. J.; Maier, C.; Nick, H.; Geiger, S.; Bertotti, G.; Boro, H.

    2015-12-01

    A fracture network arrangement is quantified across an isolated carbonate platform from outcrop and aerial imagery to address its impact on fluid flow. The network is described in terms of fracture density, orientation, and length distribution parameters. Of particular interest is the role of fracture cross connections and abutments on the effective permeability. Hence, the flow simulations explicitly account for network topology by adopting Discrete-Fracture-and-Matrix description. The interior of the Latemar carbonate platform (Dolomites, Italy) is taken as outcrop analogue for subsurface reservoirs of isolated carbonate build-ups that exhibit a fracture-dominated permeability. New is our dual strategy to describe the fracture network both as deterministic- and stochastic-based inputs for flow simulations. The fracture geometries are captured explicitly and form a multiscale data set by integration of interpretations from outcrops, airborne imagery, and lidar. The deterministic network descriptions form the basis for descriptive rules that are diagnostic of the complex natural fracture arrangement. The fracture networks exhibit a variable degree of multitier hierarchies with smaller-sized fractures abutting against larger fractures under both right and oblique angles. The influence of network topology on connectivity is quantified using Discrete-Fracture-Single phase fluid flow simulations. The simulation results show that the effective permeability for the fracture and matrix ensemble can be 50 to 400 times higher than the matrix permeability of 1.0 · 10-14 m2. The permeability enhancement is strongly controlled by the connectivity of the fracture network. Therefore, the degree of intersecting and abutting fractures should be captured from outcrops with accuracy to be of value as analogue.

  13. Power flow tracing in a simplified highly renewable European electricity network

    NASA Astrophysics Data System (ADS)

    Tranberg, Bo; Thomsen, Anders B.; Rodriguez, Rolando A.; Andresen, Gorm B.; Schäfer, Mirko; Greiner, Martin

    2015-10-01

    The increasing transmission capacity needs in a future energy system raise the question of how associated costs should be allocated to the users of a strengthened power grid. In contrast to straightforward oversimplified methods, a flow tracing based approach provides a fair and consistent nodal usage and thus cost assignment of transmission investments. This technique follows the power flow through the network and assigns the link capacity usage to the respective sources or sinks using a diffusion-like process, thus taking into account the underlying network structure and injection pattern. As a showcase, we apply power flow tracing to a simplified model of the European electricity grid with a high share of renewable wind and solar power generation, based on long-term weather and load data with an hourly temporal resolution.

  14. Computer-Based Information Networks: Selected Examples.

    ERIC Educational Resources Information Center

    Hardesty, Larry

    The history, purpose, and operation of six computer-based information networks are described in general and nontechnical terms. In the introduction the many definitions of an information network are explored. Ohio College Library Center's network (OCLC) is the first example. OCLC began in 1963, and since early 1973 has been extending its services…

  15. Flux flow pinning and resistive behavior in superconducting networks

    SciTech Connect

    Teitel, S.

    1990-10-01

    We have studied the behavior of superconducting networks in terms of XY and Coulomb gas models. The dynamics of frustrated Josephson junction arrays has been simulated, with a view toward understanding the effects of vortex correlations on flux flow resistance. Randomness has been introduced, and its effects on the superconducting transition, and vortex mobility, have been studied. A three dimensional network has been simulated to study the effects of vortex line entanglement in high temperature superconductors. Preliminary calculations are in progress. The two dimensional classical Coulomb gas where charges map onto vortices in the superconducting network, has been simulated. The melting transitions of ordered charge (vortex) lattices have been studied, and we find clear evidence that these transitions do not have the critical behavior expected from standard symmetry analysis.

  16. Towards effective flow simulations in realistic discrete fracture networks

    NASA Astrophysics Data System (ADS)

    Berrone, Stefano; Pieraccini, Sandra; Scialò, Stefano

    2016-04-01

    We focus on the simulation of underground flow in fractured media, modeled by means of Discrete Fracture Networks. Focusing on a new recent numerical approach proposed by the authors for tackling the problem avoiding mesh generation problems, we further improve the new family of methods making a step further towards effective simulations of large, multi-scale, heterogeneous networks. Namely, we tackle the imposition of Dirichlet boundary conditions in weak form, in such a way that geometrical complexity of the DFN is not an issue; we effectively solve DFN problems with fracture transmissivities spanning many orders of magnitude and approaching zero; furthermore, we address several numerical issues for improving the numerical solution also in quite challenging networks.

  17. Selective pumping in a network: A novel bioinspired flow transport paradigm

    NASA Astrophysics Data System (ADS)

    Aboelkassem, Yasser; Staples, Anne

    2012-11-01

    We present a new paradigm for selectively pumping and controlling fluids at the microscale in a complex network of channels, which we call ``selective pumping in a network.'' The approach is inspired by internal flow distributions induced by rhythmic wall contraction phenomena in insect tracheal networks. The selective pumping concept presented enables fluids to be transported, controlled and directed into specific branches in networks while avoiding other possible branching routes, without the use of any mechanical valves. The results presented here might help guide efforts to fabricate novel microfluidic devices with improved efficiency for mixing purposes and targeted drug delivery applications. In this study, both theoretical analysis and Stokeslets-meshfree computational methods are used to solve for the 2D viscous flow transport in an insect-like tracheal network of channels with prescribed moving wall contractions. The derived theoretical analysis is based on both lubrication theory and quasi-steady approximations at low Reynolds numbers. The meshfree numerical method is based on the method of fundamental solutions (MFS) that uses a set of singularized force elements ``Stokeslets'' to induce the flow motions. Moreover, the passive particle tracking simulation.

  18. Catchment organisation, free energy dynamics and network control on critical zone water flows

    NASA Astrophysics Data System (ADS)

    Zehe, E.; Ehret, U.; Kleidon, A.; Jackisch, C.; Scherer, U.; Blume, T.

    2012-04-01

    as that these flow structures organize and dominate flows of water, dissolved matter and sediments during rainfall driven conditions at various scales: - Surface connected vertical flow structures of anecic worm burrows or soil cracks organize and dominated vertical flows at the plot scale - this is usually referred to as preferential flow; - Rill networks at the soil surface organise and dominate hillslope scale overland flow response and sediment yields; - Subsurface pipe networks at the bedrock interface organize and dominate hillslope scale lateral subsurface water and tracer flows; - The river net organizes and dominates flows of water, dissolved matter and sediments to the catchment outlet and finally across continental gradients to the sea. Fundamental progress with respect to the parameterization of hydrological models, subscale flow networks and to understand the adaptation of hydro-geo ecosystems to change could be achieved by discovering principles that govern the organization of catchments flow networks in particular at least during steady state conditions. This insight has inspired various scientists to suggest principles for organization of ecosystems, landscapes and flow networks; as Bejans constructural law, Minimum Energy Expenditure , Maximum Entropy Production. In line with these studies we suggest that a thermodynamic/energetic treatment of the catchment is might be a key for understanding the underlying principles that govern organisation of flow and transport. Our approach is to employ a) physically based hydrological model that address at least all the relevant hydrological processes in the critical zone in a coupled way, behavioural representations of the observed organisation of flow structures and textural elements, that are consistent with observations in two well investigated research catchments and have been tested against distributed observations of soil moisture and catchment scale discharge; to simulate the full concert of hydrological

  19. Gene flow networks among American Aedes aegypti populations

    PubMed Central

    Gonçalves da Silva, Anders; Cunha, Ivana C L; Santos, Walter S; Luz, Sérgio L B; Ribolla, Paulo E M; Abad-Franch, Fernando

    2012-01-01

    The mosquito Aedes aegypti, the dengue virus vector, has spread throughout the tropics in historical times. While this suggests man-mediated dispersal, estimating contemporary connectivity among populations has remained elusive. Here, we use a large mtDNA dataset and a Bayesian coalescent framework to test a set of hypotheses about gene flow among American Ae. aegypti populations. We assessed gene flow patterns at the continental and subregional (Amazon basin) scales. For the Americas, our data favor a stepping-stone model in which gene flow is higher among adjacent populations but in which, at the same time, North American and southeastern Brazilian populations are directly connected, likely via sea trade. Within Amazonia, the model with highest support suggests extensive gene flow among major cities; Manaus, located at the center of the subregional transport network, emerges as a potentially important connecting hub. Our results suggest substantial connectivity across Ae. aegypti populations in the Americas. As long-distance active dispersal has not been observed in this species, our data support man-mediated dispersal as a major determinant of the genetic structure of American Ae. aegypti populations. The inferred topology of interpopulation connectivity can inform network models of Ae. aegypti and dengue spread. PMID:23144654

  20. TVENT1P. Gas-Dynamic Transients Flow Networks

    SciTech Connect

    Eyberger, L.

    1987-09-01

    TVENT1P predicts flows and pressures in a ventilation system or other air pathway caused by pressure transients, such as a tornado. For an analytical model to simulate an actual system, it must have (1) the same arrangement of components in a network of flow paths; (2) the same friction characteristics; (3) the same boundary pressures; (4) the same capacitance; and (5) the same forces that drive the air. A specific set of components used for constructing the analytical model includes filters, dampers, ducts, blowers, rooms, or volume connected at nodal points to form networks. The effects of a number of similar components can be lumped into a single one. TVENT1P contains a material transport algorithm and features for turning blowers off and on, changing blower speeds, changing the resistance of dampers and filters, and providing a filter model to handle very high flows. These features make it possible to depict a sequence of events during a single run. Component properties are varied using time functions. The filter model is not used by the code unless it is specified by the user. The basic results of a TVENT1P solution are flows in branches and pressures at nodes. A postprocessor program, PLTTEX, is included to produce the plots specified in the TVENT1P input. PLTTEX uses the proprietary CA-DISSPLA graphics software.

  1. Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

    PubMed

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

    2016-01-01

    It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence. PMID:27239189

  2. Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks

    PubMed Central

    Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

    2016-01-01

    It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a “signature” of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence. PMID:27239189

  3. Measuring information flow in cellular networks by the systems biology method through microarray data

    PubMed Central

    Chen, Bor-Sen; Li, Cheng-Wei

    2015-01-01

    In general, it is very difficult to measure the information flow in a cellular network directly. In this study, based on an information flow model and microarray data, we measured the information flow in cellular networks indirectly by using a systems biology method. First, we used a recursive least square parameter estimation algorithm to identify the system parameters of coupling signal transduction pathways and the cellular gene regulatory network (GRN). Then, based on the identified parameters and systems theory, we estimated the signal transductivities of the coupling signal transduction pathways from the extracellular signals to each downstream protein and the information transductivities of the GRN between transcription factors in response to environmental events. According to the proposed method, the information flow, which is characterized by signal transductivity in coupling signaling pathways and information transductivity in the GRN, can be estimated by microarray temporal data or microarray sample data. It can also be estimated by other high-throughput data such as next-generation sequencing or proteomic data. Finally, the information flows of the signal transduction pathways and the GRN in leukemia cancer cells and non-leukemia normal cells were also measured to analyze the systematic dysfunction in this cancer from microarray sample data. The results show that the signal transductivities of signal transduction pathways change substantially from normal cells to leukemia cancer cells. PMID:26082788

  4. Structural efficiency of percolated landscapes in flow networks.

    PubMed

    Serrano, M Angeles; De Los Rios, Paolo

    2008-01-01

    The large-scale structure of complex systems is intimately related to their functionality and evolution. In particular, global transport processes in flow networks rely on the presence of directed pathways from input to output nodes and edges, which organize in macroscopic connected components. However, the precise relation between such structures and functional or evolutionary aspects remains to be understood. Here, we investigate which are the constraints that the global structure of directed networks imposes on transport phenomena. We define quantitatively under minimal assumptions the structural efficiency of networks to determine how robust communication between the core and the peripheral components through interface edges could be. Furthermore, we assess that optimal topologies in terms of access to the core should look like "hairy balls" so to minimize bottleneck effects and the sensitivity to failures. We illustrate our investigation with the analysis of three real networks with very different purposes and shaped by very different dynamics and time-scales-the Internet customer-provider set of relationships, the nervous system of the worm Caenorhabditis elegans, and the metabolism of the bacterium Escherichia coli. Our findings prove that different global connectivity structures result in different levels of structural efficiency. In particular, biological networks seem to be close to the optimal layout. PMID:18985157

  5. Network Medicine: A Network-based Approach to Human Diseases

    NASA Astrophysics Data System (ADS)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  6. Reputation-based collaborative network biology.

    PubMed

    Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Fields, R Brett; Hayes, William; Hoeng, Julia; Park, Jennifer S; Peitsch, Manuel C

    2015-01-01

    A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities. PMID:25592588

  7. Image-Based Flow Modeling

    NASA Astrophysics Data System (ADS)

    Dillard, Seth; Mousel, John; Buchholz, James; Udaykumar, H. S.

    2009-11-01

    A preliminary method has been developed to model complex moving boundaries interacting with fluids in two dimensions using video files. Image segmentation techniques are employed to generate sharp object interfaces which are cast as level sets embedded in a Cartesian flow domain. In this way, boundary evolution is effected directly through imagery rather than by way of functional approximation. Videos of an American eel swimming in a water tunnel apparatus and a guinea pig duodenum undergoing peristaltic contractions in vitro serve as external and internal flow examples, which are evaluated for wake structure and mixing efficacy, respectively.

  8. Experimental demonstration of OpenFlow-enabled media ecosystem architecture for high-end applications over metro and core networks.

    PubMed

    Ntofon, Okung-Dike; Channegowda, Mayur P; Efstathiou, Nikolaos; Rashidi Fard, Mehdi; Nejabati, Reza; Hunter, David K; Simeonidou, Dimitra

    2013-02-25

    In this paper, a novel Software-Defined Networking (SDN) architecture is proposed for high-end Ultra High Definition (UHD) media applications. UHD media applications require huge amounts of bandwidth that can only be met with high-capacity optical networks. In addition, there are requirements for control frameworks capable of delivering effective application performance with efficient network utilization. A novel SDN-based Controller that tightly integrates application-awareness with network control and management is proposed for such applications. An OpenFlow-enabled test-bed demonstrator is reported with performance evaluations of advanced online and offline media- and network-aware schedulers. PMID:23482015

  9. Deterministic and stochastic algorithms for resolving the flow fields in ducts and networks using energy minimization

    NASA Astrophysics Data System (ADS)

    Sochi, Taha

    2016-09-01

    Several deterministic and stochastic multi-variable global optimization algorithms (Conjugate Gradient, Nelder-Mead, Quasi-Newton and global) are investigated in conjunction with energy minimization principle to resolve the pressure and volumetric flow rate fields in single ducts and networks of interconnected ducts. The algorithms are tested with seven types of fluid: Newtonian, power law, Bingham, Herschel-Bulkley, Ellis, Ree-Eyring and Casson. The results obtained from all those algorithms for all these types of fluid agree very well with the analytically derived solutions as obtained from the traditional methods which are based on the conservation principles and fluid constitutive relations. The results confirm and generalize the findings of our previous investigations that the energy minimization principle is at the heart of the flow dynamics systems. The investigation also enriches the methods of computational fluid dynamics for solving the flow fields in tubes and networks for various types of Newtonian and non-Newtonian fluids.

  10. Modeling Crustal-Scale Hydrothermal Flows through a Seamount Network

    NASA Astrophysics Data System (ADS)

    Lauer, R. M.; Fisher, A. T.; Winslow, D. M.

    2014-12-01

    The current study represents the first efforts to model 3D hydrothermal circulation in fast-spreading oceanic crust, using a network of outcrops patterned after a region of the Cocos plate offshore Costa Rica, where heat extraction is exceptionally high, resulting in heat flow values ~30% of those predicted by conductive lithospheric cooling models. Previous studies of this region attribute the heat deficit to vigorous hydrothermal circulation through basaltic basement outcrops that provide a hydraulic connection between the igneous oceanic crust and the seafloor, resulting in efficient mining of heat by large-scale lateral fluid flow. Seafloor bathymetry indicates that outcrops in this region are spaced 20-50-km apart, although there are likely additional unmapped structures that facilitate recharge and discharge of hydrothermal fluids. The modeled outcrop network consists of 20-km and 40-km square grids, with outcrops located at the corners. We vary the number, size, permeability, and orientation of the outcrops to consider what combination of these parameters achieve the observed pattern and/or quantity of heat loss. Additionally, we consider the effect of aquifer permeability and thickness on the modeled heat flow distribution. Model results suggest that extremely high aquifer permeability is required to match the observed heat loss and low heat flow, together with a heterogeneous outcrop permeability distribution. In particular, we find that an aquifer permeability of 10-9 m2 is required to achieve the measured heat flow distribution in this region, which estimates a mean value of 29 ±13 mW/m2 in areas of flat lying basement, overlain by 400-500-m of sediment. In addition to high aquifer permeability, heterogeneous outcrop permeability is required to initiate the hydraulic connection between outcrops, with higher permeability outcrops acting as recharge sites, and lower permeability outcrops as discharge sites.

  11. Knowledge-based flow field zoning

    NASA Technical Reports Server (NTRS)

    Andrews, Alison E.

    1988-01-01

    Automation flow field zoning in two dimensions is an important step towards easing the three-dimensional grid generation bottleneck in computational fluid dynamics. A knowledge based approach works well, but certain aspects of flow field zoning make the use of such an approach challenging. A knowledge based flow field zoner, called EZGrid, was implemented and tested on representative two-dimensional aerodynamic configurations. Results are shown which illustrate the way in which EZGrid incorporates the effects of physics, shape description, position, and user bias in a flow field zoning.

  12. A University-Based Electronic Publishing Network.

    ERIC Educational Resources Information Center

    Yavarkovsky, Jerome

    1990-01-01

    Based on a presentation at the Coalition for Networked Information (CNI), this article discusses a university-based computer network that would support electronic publishing. Highlights include the influence on libraries and librarians; technical and operational standards; economic factors; and institutional planning. Six sidebars address other…

  13. Content-Based Networking: DTN, AMS, Sharednet

    NASA Technical Reports Server (NTRS)

    Burleigh, Scott

    2006-01-01

    A detailed viewgraph presentation on DTN, AMS, and Sharednet content-based networking is shown. The contents include: 1) DARPA Content-Based Networking Summary of Requirements; 2) Concept; 3) Key Features of AMS; 4) Overview of Sharednet; 5) SharedNet Deployment History; 6) SharedNet AMS DTN; 7) Detailed Structure; and 8) Bottom line.

  14. Network Anomaly Detection Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  15. Applications of flow-networks to opinion-dynamics

    NASA Astrophysics Data System (ADS)

    Tupikina, Liubov; Kurths, Jürgen

    2015-04-01

    Networks were successfully applied to describe complex systems, such as brain, climate, processes in society. Recently a socio-physical problem of opinion-dynamics was studied using network techniques. We present the toy-model of opinion-formation based on the physical model of advection-diffusion. We consider spreading of the opinion on the fixed subject, assuming that opinion on society is binary: if person has opinion then the state of the node in the society-network equals 1, if the person doesn't have opinion state of the node equals 0. Opinion can be spread from one person to another if they know each other, or in the network-terminology, if the nodes are connected. We include into the system governed by advection-diffusion equation the external field to model such effects as for instance influence from media. The assumptions for our model can be formulated as the following: 1.the node-states are influenced by the network structure in such a way, that opinion can be spread only between adjacent nodes (the advective term of the opinion-dynamics), 2.the network evolution can have two scenarios: -network topology is not changing with time; -additional links can appear or disappear each time-step with fixed probability which requires adaptive networks properties. Considering these assumptions for our system we obtain the system of equations describing our model-dynamics which corresponds well to other socio-physics models, for instance, the model of the social cohesion and the famous voter-model. We investigate the behavior of the suggested model studying "waiting time" of the system, time to get to the stable state, stability of the model regimes for different values of model parameters and network topology.

  16. Influence of membrane structure on the operating current densities of non-aqueous redox flow batteries: Organic-inorganic composite membranes based on a semi-interpenetrating polymer network

    NASA Astrophysics Data System (ADS)

    Shin, Sung-Hee; Kim, Yekyung; Yun, Sung-Hyun; Maurya, Sandip; Moon, Seung-Hyeon

    2015-11-01

    We develop three types of organic-inorganic composite membranes based on a semi-interpenetrating polymer network (SIPN) to explore the effects of membrane structure on the possible operating current densities of a non-aqueous redox flow battery (RFB) system. Poly(vinylidene fluoride) (PVdF) is selected as a supporting polymer matrix for improving the chemical and thermal stability of the organic-inorganic composite membranes. We also introduce silica nanoparticles (5 wt% of PVdF) into the membranes to ensure the low crossover of active species. The fabrication of SIPN through the addition of glycidyl methacrylate, 4-vinylpyridine, or N-vinylcarbazole enables control of the membrane structure. Depending on monomer type, the membrane structure is determined to be either aliphatic or aromatic in terms of chemical properties and either dense or porous in terms of physical properties. These chemical and physical structures affect the electrochemical properties that correspond to charge/discharge performance and to the range of possible operating current densities. An important requirement is to examine charge/discharge performance at the possible range of operating current densities by using various membrane structures. This requirement is discussed in relation to a proposed design strategy for non-aqueous RFB membranes.

  17. Parallel CFD design on network-based computer

    NASA Technical Reports Server (NTRS)

    Cheung, Samson

    1995-01-01

    Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

  18. CFD Optimization on Network-Based Parallel Computer System

    NASA Technical Reports Server (NTRS)

    Cheung, Samson H.; Holst, Terry L. (Technical Monitor)

    1994-01-01

    Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

  19. Flow Effects on the Controlled Growth of Nanostructured Networks at Microcapillary Walls for Applications in Continuous Flow Reactions.

    PubMed

    Wang, Gang; Yuan, Cansheng; Fu, Boyi; He, Luye; Reichmanis, Elsa; Wang, Hongzhi; Zhang, Qinghong; Li, Yaogang

    2015-09-30

    Low-cost microfluidic devices are desirable for many chemical processes; however, access to robust, inert, and appropriately structured materials for the inner channel wall is severely limited. Here, the shear force within confined microchannels was tuned through control of reactant solution fluid-flow and shown to dramatically impact nano- through microstructure growth. Combined use of experimental results and simulations allowed controlled growth of 3D networked Zn(OH)F nanostructures with uniform pore distributions and large fluid contact areas on inner microchannel walls. These attributes facilitated subsequent preparation of uniformly distributed Pd and PdPt networks with high structural and chemical stability using a facile, in situ conversion method. The advantageous properties of the microchannel based catalytic system were demonstrated using microwave-assisted continuous-flow coupling as a representative reaction. High conversion rates and good recyclability were obtained. Controlling materials nanostructure via fluid-flow-enhanced growth affords a general strategy to optimize the structure of an inner microchannel wall for desired attributes. The approach provides a promising pathway toward versatile, high-performance, and low-cost microfluidic devices for continuous-flow chemical processes. PMID:26352859

  20. Visualizing the flow of evidence in network meta-analysis and characterizing mixed treatment comparisons.

    PubMed

    König, Jochem; Krahn, Ulrike; Binder, Harald

    2013-12-30

    Network meta-analysis techniques allow for pooling evidence from different studies with only partially overlapping designs for getting a broader basis for decision support. The results are network-based effect estimates that take indirect evidence into account for all pairs of treatments. The results critically depend on homogeneity and consistency assumptions, which are sometimes difficult to investigate. To support such evaluation, we propose a display of the flow of evidence and introduce new measures that characterize the structure of a mixed treatment comparison. Specifically, a linear fixed effects model for network meta-analysis is considered, where the network estimates for two treatments are linear combinations of direct effect estimates comparing these or other treatments. The linear coefficients can be seen as the generalization of weights known from classical meta-analysis. We summarize properties of these coefficients and display them as a weighted directed acyclic graph, representing the flow of evidence. Furthermore, measures are introduced that quantify the direct evidence proportion, the mean path length, and the minimal parallelism of mixed treatment comparisons. The graphical display and the measures are illustrated for two published network meta-analyses. In these applications, the proposed methods are seen to render transparent the process of data pooling in mixed treatment comparisons. They can be expected to be more generally useful for guiding and facilitating the validity assessment in network meta-analysis. PMID:24123165

  1. Transfer entropy in magnetoencephalographic data: quantifying information flow in cortical and cerebellar networks.

    PubMed

    Wibral, Michael; Rahm, Benjamin; Rieder, Maria; Lindner, Michael; Vicente, Raul; Kaiser, Jochen

    2011-03-01

    The analysis of cortical and subcortical networks requires the identification of their nodes, and of the topology and dynamics of their interactions. Exploratory tools for the identification of nodes are available, e.g. magnetoencephalography (MEG) in combination with beamformer source analysis. Competing network topologies and interaction models can be investigated using dynamic causal modelling. However, we lack a method for the exploratory investigation of network topologies to choose from the very large number of possible network graphs. Ideally, this method should not require a pre-specified model of the interaction. Transfer entropy--an information theoretic implementation of Wiener-type causality--is a method for the investigation of causal interactions (or information flow) that is independent of a pre-specified interaction model. We analysed MEG data from an auditory short-term memory experiment to assess whether the reconfiguration of networks implied in this task can be detected using transfer entropy. Transfer entropy analysis of MEG source-level signals detected changes in the network between the different task types. These changes prominently involved the left temporal pole and cerebellum--structures that have previously been implied in auditory short-term or working memory. Thus, the analysis of information flow with transfer entropy at the source-level may be used to derive hypotheses for further model-based testing. PMID:21115029

  2. Stochastic resonance for information flows on hierarchical networks

    NASA Astrophysics Data System (ADS)

    Czaplicka, Agnieszka; Hołyst, Janusz A.; Sloot, Peter M. A.

    2013-09-01

    A simple model of information flows represented by package delivery on networks with hierarchical structures is considered. The packages should be transferred from one network node to another and the delivery process is influenced by two types of noise. The first type of noise is related to a partially false knowledge of network topology (topological noise), i.e. membership of nodes in communities in a shipping algorithm include a number of errors corresponding to a random rewiring of a fraction of network links. The second type of noise (dynamical noise) is related to a diffusive part in packet dynamics, i.e. package paths do not follow from completely deterministic rules. In the case of a pure topological noise and in the case of combination of both types of noises, we observe a resonance-like phenomenon for communication efficiency. The system performance measured as a fraction of packages that are delivered in a certain time period or as an inverse of time of a package delivery is maximal for intermediate levels of noise. This effect resembles the phenomenon of stochastic resonance that exists in many complex systems where a noise can enhance the information transfer.

  3. Program for Analyzing Flows in a Complex Network

    NASA Technical Reports Server (NTRS)

    Majumdar, Alok Kumar

    2006-01-01

    Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.

  4. Value flow mapping: Using networks to inform stakeholder analysis

    NASA Astrophysics Data System (ADS)

    Cameron, Bruce G.; Crawley, Edward F.; Loureiro, Geilson; Rebentisch, Eric S.

    2008-02-01

    Stakeholder theory has garnered significant interest from the corporate community, but has proved difficult to apply to large government programs. A detailed value flow exercise was conducted to identify the value delivery mechanisms among stakeholders for the current Vision for Space Exploration. We propose a method for capturing stakeholder needs that explicitly recognizes the outcomes required of the value creating organization. The captured stakeholder needs are then translated into input-output models for each stakeholder, which are then aggregated into a network model. Analysis of this network suggests that benefits are infrequently linked to the root provider of value. Furthermore, it is noted that requirements should not only be written to influence the organization's outputs, but also to influence the propagation of benefit further along the value chain. A number of future applications of this model to systems architecture and requirement analysis are discussed.

  5. Application Oriented Flow Routing Algorithm for VoIP Overlay Networks

    NASA Astrophysics Data System (ADS)

    Wipusitwarakun, Komwut; Chimmanee, Sanon

    Overlay networks which are dynamically created over underlying IP networks are becoming widely used for delivering multimedia contents since they can provide several additional user-definable services. Multiple overlay paths between a source-destination overlay node pair are designed to improve service robustness against failures and bandwidth fluctuation of the underlying networks. Multimedia traffic can be distributed over those multiple paths in order to maximize paths' utilization and to increase application throughputs. Most of flow-based routing algorithms consider only common metrics such as paths' bandwidth or delay, which may be effective for data applications but not for real-time applications such as Voice over IP (VoIP), in which different levels of such performance metrics may give the same level of the performance experienced by end users. This paper focuses on such VoIP overlay networks and proposes a novel alternative path based flow routing algorithm using an application-specific traffic metric, i.e. “VoIP Path Capacity (VPCap), ” to calculate the maximum number of QoS satisfied VoIP flows which may be distributed over each available overlay path at a moment. The simulation results proved that more QoS-satisfied VoIP sessions can be established over the same multiple overlay paths, comparing to traditional approaches.

  6. Suspended sediment dynamics in a tidal channel network under peak river flow

    NASA Astrophysics Data System (ADS)

    Achete, Fernanda Minikowski; van der Wegen, Mick; Roelvink, Dano; Jaffe, Bruce

    2016-05-01

    Peak river flows transport fine sediment, nutrients, and contaminants that may deposit in the estuary. This study explores the importance of peak river flows on sediment dynamics with special emphasis on channel network configurations. The Sacramento-San Joaquin Delta, which is connected to San Francisco Bay (California, USA), motivates this study and is used as a validation case. Besides data analysis of observations, we applied a calibrated process-based model (D-Flow FM) to explore and analyze high-resolution (˜100 m, ˜1 h) dynamics. Peak river flows supply the vast majority of sediment into the system. Data analysis of six peak flows (between 2012 and 2014) shows that on average, 40 % of the input sediment in the system is trapped and that trapping efficiency depends on timing and magnitude of river flows. The model has 90 % accuracy reproducing these trapping efficiencies. Modeled deposition patterns develop as the result of peak river flows after which, during low river flow conditions, tidal currents are not able to significantly redistribute deposited sediment. Deposition is quite local and mainly takes place at a deep junction. Tidal movement is important for sediment resuspension, but river induced, tide residual currents are responsible for redistributing the sediment towards the river banks and to the bay. We applied the same forcing for four different channel configurations ranging from a full delta network to a schematization of the main river. A higher degree of network schematization leads to higher peak-sediment export downstream to the bay. However, the area of sedimentation is similar for all the configurations because it is mostly driven by geometry and bathymetry.

  7. Network modeling for reverse flows of end-of-life vehicles

    SciTech Connect

    Ene, Seval; Öztürk, Nursel

    2015-04-15

    Highlights: • We developed a network model for reverse flows of end-of-life vehicles. • The model considers all recovery operations for end-of-life vehicles. • A scenario-based model is used for uncertainty to improve real case applications. • The model is adequate to real case applications for end-of-life vehicles recovery. • Considerable insights are gained from the model by sensitivity analyses. - Abstract: Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is a need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles’ recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment.

  8. Inference of Gene Regulatory Network Based on Local Bayesian Networks

    PubMed Central

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Chen, Luonan

    2016-01-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  9. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    PubMed

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  10. Irreversibility and complex network behavior of stream flow fluctuations

    NASA Astrophysics Data System (ADS)

    Serinaldi, Francesco; Kilsby, Chris G.

    2016-05-01

    Exploiting the duality between time series and networks, directed horizontal visibility graphs (DHVGs) are used to perform an unprecedented analysis of the dynamics of stream flow fluctuations with focus on time irreversibility and long range dependence. The analysis relies on a large quality-controlled data set consisting of 699 daily time series recorded in the continental United States (CONUS) that are not affected by human activity and primarily reflects meteorological conditions. DHVGs allow a clear visualization and quantification of time irreversibility of flow dynamics, which can be interpreted as a signature of nonlinearity, and long range dependence resulting from the interaction of atmospheric, surface and underground processes acting at multiple spatio-temporal scales. Irreversibility is explored by mapping the time series into ingoing, outgoing, and undirected graphs and comparing the corresponding degree distributions. Using surrogate data preserving up to the second order linear temporal dependence properties of the observed series, DHVGs highlight the additional complexity introduced by nonlinearity into flow fluctuation dynamics. We show that the degree distributions do not decay exponentially as expected, but tend to follow a subexponential behavior, even though sampling uncertainty does not allow a clear distinction between apparent or true power law decay. These results confirm that the complexity of stream flow dynamics goes beyond a linear representation involving for instance the combination of linear processes with short and long range dependence, and requires modeling strategies accounting for temporal asymmetry and nonlinearity.

  11. FLOWNET: A Computer Program for Calculating Secondary Flow Conditions in a Network of Turbomachinery

    NASA Technical Reports Server (NTRS)

    Rose, J. R.

    1978-01-01

    The program requires the network parameters, the flow component parameters, the reservoir conditions, and the gas properties as input. It will then calculate all unknown pressures and the mass flow rate in each flow component in the network. The program can treat networks containing up to fifty flow components and twenty-five unknown network pressures. The types of flow components that can be treated are face seals, narrow slots, and pipes. The program is written in both structured FORTRAN (SFTRAN) and FORTRAN 4. The program must be run in an interactive (conversational) mode.

  12. Reciprocating flow-based centrifugal microfluidics mixer

    NASA Astrophysics Data System (ADS)

    Noroozi, Zahra; Kido, Horacio; Micic, Miodrag; Pan, Hansheng; Bartolome, Christian; Princevac, Marko; Zoval, Jim; Madou, Marc

    2009-07-01

    Proper mixing of reagents is of paramount importance for an efficient chemical reaction. While on a large scale there are many good solutions for quantitative mixing of reagents, as of today, efficient and inexpensive fluid mixing in the nanoliter and microliter volume range is still a challenge. Complete, i.e., quantitative mixing is of special importance in any small-scale analytical application because the scarcity of analytes and the low volume of the reagents demand efficient utilization of all available reaction components. In this paper we demonstrate the design and fabrication of a novel centrifugal force-based unit for fast mixing of fluids in the nanoliter to microliter volume range. The device consists of a number of chambers (including two loading chambers, one pressure chamber, and one mixing chamber) that are connected through a network of microchannels, and is made by bonding a slab of polydimethylsiloxane (PDMS) to a glass slide. The PDMS slab was cast using a SU-8 master mold fabricated by a two-level photolithography process. This microfluidic mixer exploits centrifugal force and pneumatic pressure to reciprocate the flow of fluid samples in order to minimize the amount of sample and the time of mixing. The process of mixing was monitored by utilizing the planar laser induced fluorescence (PLIF) technique. A time series of high resolution images of the mixing chamber were analyzed for the spatial distribution of light intensities as the two fluids (suspension of red fluorescent particles and water) mixed. Histograms of the fluorescent emissions within the mixing chamber during different stages of the mixing process were created to quantify the level of mixing of the mixing fluids. The results suggest that quantitative mixing was achieved in less than 3 min. This device can be employed as a stand alone mixing unit or may be integrated into a disk-based microfluidic system where, in addition to mixing, several other sample preparation steps may be

  13. Predicting Flow Breakdown Probability and Duration in Stochastic Network Models: Impact on Travel Time Reliability

    SciTech Connect

    Dong, Jing; Mahmassani, Hani S.

    2011-01-01

    This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.

  14. Traffic flow collection wireless sensor network node for intersection light control

    NASA Astrophysics Data System (ADS)

    Li, Xu; Li, Xue

    2011-10-01

    Wireless sensor network (WSN) is expected to be deployed in intersection to monitor the traffic flow continuously, and the monitoring datum can be used as the foundation of traffic light control. In this paper, a WSN based on ZigBee protocol for monitoring traffic flow is proposed. Structure, hardware and work flow of WSN nodes are designed. CC2431 from Texas Instrument is chosen as the main computational and transmission unit, and CC2591 as the amplification unit. The stability experiment and the actual environment experiment are carried out in the last of the paper. The results of experiments show that WSN has the ability to collect traffic flow information quickly and transmit the datum to the processing center in real time.

  15. Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks

    PubMed Central

    Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

    2014-01-01

    Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway. PMID:25544838

  16. Neural network based architectures for aerospace applications

    NASA Technical Reports Server (NTRS)

    Ricart, Richard

    1987-01-01

    A brief history of the field of neural networks research is given and some simple concepts are described. In addition, some neural network based avionics research and development programs are reviewed. The need for the United States Air Force and NASA to assume a leadership role in supporting this technology is stressed.

  17. Network-Based Classrooms: Promises and Realities.

    ERIC Educational Resources Information Center

    Bruce, Bertram C., Ed.; And Others

    Exploring how new technologies and new pedagogies transform and are transformed by existing institutions, this book presents 14 essays that discuss network-based classrooms in which students use communications software on computer networks to converse in writing. The first part of the book discusses general themes and issues of the ENFI…

  18. A New Multiscale Flow Network Generation Scheme for Land Surface Models

    SciTech Connect

    Guo, Jianzhong; Liang, Xu; Leung, Lai R.

    2004-12-11

    This paper presents a new approach of generating flow networks for land surface models that are applied at different spatial scales based on fine-resolution digital elevation model (DEM). Without losing computational efficiency, the new multi-scale approach has the following advantages compared to existing methods: (1) it allows surface and subsurface runoff from a land surface model grid to exit through multiple directions simultaneously rather than through only one of the eight directions as in many other methods; (2) it guarantees that the newly generated river network is closer to the real river network; and (3) it introduces the concept of elastic coefficient to determine hydrological features such as river slope and length for more accurate flow routing across different spatial scales. The new flow network generation scheme has been applied to the Blue River watershed in Oklahoma at different spatial resolutions using a kinematic wave routing method. Comparisons of the routed streamflows at the watershed outlet associated with different spatial scales show clear advantages of the new approach over the widely used eight directions (D8) method, especially at the coarser spatial resolution. This method is particularly suitable for macroscale hydrologic models and climate models where the accuracy of river routing can be severely limited by the coarse spatial resolution.

  19. Regional low-flow frequency analysis using single and ensemble artificial neural networks

    NASA Astrophysics Data System (ADS)

    Ouarda, T. B. M. J.; Shu, C.

    2009-11-01

    In this paper, artificial neural networks (ANNs) are introduced to obtain improved regional low-flow estimates at ungauged sites. A multilayer perceptron (MLP) network is used to identify the functional relationship between low-flow quantiles and the physiographic variables. Each ANN is trained using the Levenberg-Marquardt algorithm. To improve the generalization ability of a single ANN, several ANNs trained for the same task are used as an ensemble. The bootstrap aggregation (or bagging) approach is used to generate individual networks in the ensemble. The stacked generalization (or stacking) technique is adopted to combine the member networks of an ANN ensemble. The proposed approaches are applied to selected catchments in the province of Quebec, Canada, to obtain estimates for several representative low-flow quantiles of summer and winter seasons. The jackknife validation procedure is used to evaluate the performance of the proposed models. The ANN-based approaches are compared with the traditional parametric regression models. The results indicate that both the single and ensemble ANN models provide superior estimates than the traditional regression models. The ANN ensemble approaches provide better generalization ability than the single ANN models.

  20. Multi-flow virtual concatenation triggered by path cascading degree in Flexi-Grid optical networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Zhang, Jie; Zhao, Yongli; Wang, Shouyu; Gu, Wanyi; Han, Jianrui; Lin, Yi; Lee, Young

    2013-12-01

    The Flexi-Grid optical networks can elastically allocate spectrum tailored for various bandwidth requirements. In the flexible architecture, routing and spectrum allocation (RSA) is the key problem is to assign spectral resources to accommodate traffic demands. However, spectrum continuity and contiguity constraints in Flexi-Grid optical networks may cause the network fragmentation issue and lead to poor spectrum utilization. In this paper, different from defragmentation methods, we propose multi-flow virtual concatenation (MFVC) in Flexi-Grid optical networks. MFVC can utilize spectral fragments effectively and decrease blocking probability without influencing the already existing active services or wasting additional spectrum resources. We also analyze the feasibility of MFVC and present a MFVC-enabled transponder and control model implementation. For estimating the distribution and size of available fragments on a path in advance, a split-multi-flow RSA heuristic algorithm (SMF) is proposed by introducing path cascading degree (PCD) based triggered mechanism according to the proposed model. Additionally, resource assignment scheme, guard band size, maximum number of split-flow and differential delay constraint are also considered into MFVC and the performances of the proposed algorithm can be demonstrated to improve the spectral utilization and greatly decrease blocking probability through extensive simulations.

  1. A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions

    NASA Technical Reports Server (NTRS)

    Lee, Douglas W.; Patek, Stephen D.; Alexandrov, Natalia; Bass, Ellen J.; Kincaid, Rex K.

    2010-01-01

    This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports.

  2. Directedness of Information Flow in Mobile Phone Communication Networks

    PubMed Central

    Peruani, Fernando; Tabourier, Lionel

    2011-01-01

    Without having direct access to the information that is being exchanged, traces of information flow can be obtained by looking at temporal sequences of user interactions. These sequences can be represented as causality trees whose statistics result from a complex interplay between the topology of the underlying (social) network and the time correlations among the communications. Here, we study causality trees in mobile-phone data, which can be represented as a dynamical directed network. This representation of the data reveals the existence of super-spreaders and super-receivers. We show that the tree statistics, respectively the information spreading process, are extremely sensitive to the in-out degree correlation exhibited by the users. We also learn that a given information, e.g., a rumor, would require users to retransmit it for more than 30 hours in order to cover a macroscopic fraction of the system. Our analysis indicates that topological node-node correlations of the underlying social network, while allowing the existence of information loops, they also promote information spreading. Temporal correlations, and therefore causality effects, are only visible as local phenomena and during short time scales. Consequently, the very idea that there is (intentional) information spreading beyond a small vecinity is called into question. These results are obtained through a combination of theory and data analysis techniques. PMID:22216128

  3. Network-Based Electronic Serials.

    ERIC Educational Resources Information Center

    Bailey, Charles W., Jr.

    1992-01-01

    Discusses electronic serials that are available on noncommercial international computer networks such as BITNET and Internet. Issues affecting libraries are discussed, including access and ownership; computer conferences are considered; examples of electronic newsletters and electronic journals are described; and the possible future of electronic…

  4. Granular flows on a dissipative base.

    PubMed

    Louge, Michel Y; Valance, Alexandre; Lancelot, Paul; Delannay, Renaud; Artières, Olivier

    2015-08-01

    We study inclined channel flows of sand over a sensor-enabled composite geotextile fabric base that dissipates granular fluctuation energy. We record strain of the fabric along the flow direction with imbedded fiber-optic Bragg gratings, flow velocity on the surface by correlating grain position in successive images, flow thickness with the streamwise shift of an oblique laser light sheet, velocity depth profile through a transparent side wall using a high-speed camera, and overall discharge rate. These independent measurements at inclinations between 33∘ and 37∘ above the angle of repose at 32.1±0.8∘ are consistent with a mass flow rate scaling as the 3/2 power of the flow depth, which is markedly different than flows on a rigid bumpy boundary. However, this power changes to 5/2 when flows are forced on the sand bed below its angle of repose. Strain measurements imply that the mean solid volume fraction in the flowing layer above the angle of repose is 0.268±0.033, independent of discharge rate or inclination. PMID:26382391

  5. Granular flows on a dissipative base

    NASA Astrophysics Data System (ADS)

    Louge, Michel Y.; Valance, Alexandre; Lancelot, Paul; Delannay, Renaud; Artières, Olivier

    2015-08-01

    We study inclined channel flows of sand over a sensor-enabled composite geotextile fabric base that dissipates granular fluctuation energy. We record strain of the fabric along the flow direction with imbedded fiber-optic Bragg gratings, flow velocity on the surface by correlating grain position in successive images, flow thickness with the streamwise shift of an oblique laser light sheet, velocity depth profile through a transparent side wall using a high-speed camera, and overall discharge rate. These independent measurements at inclinations between 33∘ and 37∘ above the angle of repose at 32.1 ±0 .8∘ are consistent with a mass flow rate scaling as the 3 /2 power of the flow depth, which is markedly different than flows on a rigid bumpy boundary. However, this power changes to 5 /2 when flows are forced on the sand bed below its angle of repose. Strain measurements imply that the mean solid volume fraction in the flowing layer above the angle of repose is 0.268 ±0.033 , independent of discharge rate or inclination.

  6. Traffic Flow Density Distribution Based on FEM

    NASA Astrophysics Data System (ADS)

    Ma, Jing; Cui, Jianming

    In analysis of normal traffic flow, it usually uses the static or dynamic model to numerical analyze based on fluid mechanics. However, in such handling process, the problem of massive modeling and data handling exist, and the accuracy is not high. Finite Element Method (FEM) is a production which is developed from the combination of a modern mathematics, mathematics and computer technology, and it has been widely applied in various domain such as engineering. Based on existing theory of traffic flow, ITS and the development of FEM, a simulation theory of the FEM that solves the problems existing in traffic flow is put forward. Based on this theory, using the existing Finite Element Analysis (FEA) software, the traffic flow is simulated analyzed with fluid mechanics and the dynamics. Massive data processing problem of manually modeling and numerical analysis is solved, and the authenticity of simulation is enhanced.

  7. Catchment organisation, free energy dynamics and network control on critical zone water flows

    NASA Astrophysics Data System (ADS)

    Zehe, E.; Ehret, U.; Kleidon, A.; Jackisch, C.; Scherer, U.; Blume, T.

    2012-04-01

    as that these flow structures organize and dominate flows of water, dissolved matter and sediments during rainfall driven conditions at various scales: - Surface connected vertical flow structures of anecic worm burrows or soil cracks organize and dominated vertical flows at the plot scale - this is usually referred to as preferential flow; - Rill networks at the soil surface organise and dominate hillslope scale overland flow response and sediment yields; - Subsurface pipe networks at the bedrock interface organize and dominate hillslope scale lateral subsurface water and tracer flows; - The river net organizes and dominates flows of water, dissolved matter and sediments to the catchment outlet and finally across continental gradients to the sea. Fundamental progress with respect to the parameterization of hydrological models, subscale flow networks and to understand the adaptation of hydro-geo ecosystems to change could be achieved by discovering principles that govern the organization of catchments flow networks in particular at least during steady state conditions. This insight has inspired various scientists to suggest principles for organization of ecosystems, landscapes and flow networks; as Bejans constructural law, Minimum Energy Expenditure , Maximum Entropy Production. In line with these studies we suggest that a thermodynamic/energetic treatment of the catchment is might be a key for understanding the underlying principles that govern organisation of flow and transport. Our approach is to employ a) physically based hydrological model that address at least all the relevant hydrological processes in the critical zone in a coupled way, behavioural representations of the observed organisation of flow structures and textural elements, that are consistent with observations in two well investigated research catchments and have been tested against distributed observations of soil moisture and catchment scale discharge; to simulate the full concert of hydrological

  8. Numerical Modeling of Interstitial Fluid Flow Coupled with Blood Flow through a Remodeled Solid Tumor Microvascular Network.

    PubMed

    Soltani, M; Chen, P

    2013-01-01

    Modeling of interstitial fluid flow involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. To date, majority of microvascular flow modeling has been done at different levels and scales mostly on simple tumor shapes with their capillaries. However, with our proposed numerical model, more complex and realistic tumor shapes and capillary networks can be studied. Both blood flow through a capillary network, which is induced by a solid tumor, and fluid flow in tumor's surrounding tissue are formulated. First, governing equations of angiogenesis are implemented to specify the different domains for the network and interstitium. Then, governing equations for flow modeling are introduced for different domains. The conservation laws for mass and momentum (including continuity equation, Darcy's law for tissue, and simplified Navier-Stokes equation for blood flow through capillaries) are used for simulating interstitial and intravascular flows and Starling's law is used for closing this system of equations and coupling the intravascular and extravascular flows. This is the first study of flow modeling in solid tumors to naturalistically couple intravascular and extravascular flow through a network. This network is generated by sprouting angiogenesis and consisting of one parent vessel connected to the network while taking into account the non-continuous behavior of blood, adaptability of capillary diameter to hemodynamics and metabolic stimuli, non-Newtonian blood flow, and phase separation of blood flow in capillary bifurcation. The incorporation of the outlined components beyond the previous models provides a more realistic prediction of interstitial fluid flow pattern in solid tumors and surrounding tissues. Results predict higher interstitial pressure, almost two times, for realistic model compared to the simplified model. PMID:23840579

  9. Numerical Modeling of Interstitial Fluid Flow Coupled with Blood Flow through a Remodeled Solid Tumor Microvascular Network

    PubMed Central

    Soltani, M.; Chen, P.

    2013-01-01

    Modeling of interstitial fluid flow involves processes such as fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. To date, majority of microvascular flow modeling has been done at different levels and scales mostly on simple tumor shapes with their capillaries. However, with our proposed numerical model, more complex and realistic tumor shapes and capillary networks can be studied. Both blood flow through a capillary network, which is induced by a solid tumor, and fluid flow in tumor’s surrounding tissue are formulated. First, governing equations of angiogenesis are implemented to specify the different domains for the network and interstitium. Then, governing equations for flow modeling are introduced for different domains. The conservation laws for mass and momentum (including continuity equation, Darcy’s law for tissue, and simplified Navier–Stokes equation for blood flow through capillaries) are used for simulating interstitial and intravascular flows and Starling’s law is used for closing this system of equations and coupling the intravascular and extravascular flows. This is the first study of flow modeling in solid tumors to naturalistically couple intravascular and extravascular flow through a network. This network is generated by sprouting angiogenesis and consisting of one parent vessel connected to the network while taking into account the non-continuous behavior of blood, adaptability of capillary diameter to hemodynamics and metabolic stimuli, non-Newtonian blood flow, and phase separation of blood flow in capillary bifurcation. The incorporation of the outlined components beyond the previous models provides a more realistic prediction of interstitial fluid flow pattern in solid tumors and surrounding tissues. Results predict higher interstitial pressure, almost two times, for realistic model compared to the simplified model. PMID:23840579

  10. RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

    SciTech Connect

    Balasundaram, Balabhaskar; Butenko, Sergiy; Boginski, Vladimir; Uryasev, Stan

    2013-12-25

    The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need

  11. Sediment transport mechanisms through the sustainable vegetated flow networks

    NASA Astrophysics Data System (ADS)

    Allen, Deonie; Haynes, Heather; Arthur, Scott

    2016-04-01

    Understanding the pollution treatment efficiency of a sustainable urban drainage (SuDS) asset or network requires the influx, transport, detention and discharge of the pollutant within the system. To date event specific monitoring of sediment (primarily total suspended solids) concentrations in the inflow and discharge from SuDS have been monitored. Long term analysis of where the sediment is transported to and the residency time of this pollutant within the SuDS asset or network have not been unraveled due to the difficulty in monitoring specific sediment particulate movement. Using REO tracing methodology, sediment particulate movement has become possible. In tracing sediment movement from an urban surface the internal residency and transportation of this sediment has illustrated SuDS asset differences in multi-event detention. Of key importance is the finding that sediment remains within the SuDS asset for extended periods of time, but that the location sediment detention changes. Thus, over multiple rainfall-runoff events sediment is seen to move through the SuDS assets and network proving the assumption that detained sediment is permanent and stationary to be inaccurate. Furthermore, mass balance analysis of SuDS sediment indicates that there is notable re-suspension and ongoing release of sediment from the SuDS over time and cumulative rainfall-runoff events. Continued monitoring of sediment deposition and concentration in suspension illustrates that sediment detention within SuDS decreases over time/multiple events, without stabilizing within a 12 month period. Repeated experiments show a consistent pattern of detention and release for the three SuDS networks monitored in Scotland. Through consideration of both rainfall and flow factors the drivers of sediment transport within the monitored SuDS have been identified. Within the limitation of this field study the key drivers to SuDS sediment detention efficiency (or transport of sediment through the system

  12. Embedded GIS based on the convergenced network

    NASA Astrophysics Data System (ADS)

    Chen, Zhaiwei; Qi, Qingwen

    2007-06-01

    With the development of modern information technology, Telecommunication network, Computer network and TVBroadcast network are converging rapidly. And the three networks form the base of the modern information industry. Although this convergence is considered a support of all services, their convergence doesn't indicate that physical networks will integrate completely. No one of these networks can take the place of others. In fact, this concept inclines to the convergence of services and the infiltration of function among these three networks. This paper give a deep analysis about the characteristic of GIS in this convergenced environment, and discuss the difference compared with traditional WebGIS. Suppose iTV is the terminal service platform of the three networks' fusion, this paper make a discussion about frame and modules of this kind of GIS. The key techology about iTV-GIS includes embedded operation system, middleware and so on. Set-top box as the most important device to run iTV-GIS program has its particularity. A development phase in virtual mechine before hardware importing is necessary. Then a antetype design of iTV-GIS is given as an example at the end of this paper. This research is just a beginning for developmeing GIS on the platform of the three networks' convergence. The subjects mentoined in this paper is just one implement on iTV virual platform, but wish such attempt will bring GIS to a new circumstance, and supply some material for the research later.

  13. Optimal structure of tree-like branching networks for fluid flow

    NASA Astrophysics Data System (ADS)

    Kou, Jianlong; Chen, Yanyan; Zhou, Xiaoyan; Lu, Hangjun; Wu, Fengmin; Fan, Jintu

    2014-01-01

    Tree-like branching networks are very common flow or transportation systems from natural evolution. In this study, the optimal structures of tree-like branching networks for minimum flow resistance are analyzed for both laminar and turbulent flow in both smooth and rough pipes. It is found that the dimensionless effective flow resistance under the volume constraint for different flows is sensitive to the geometrical parameters of the structure. The flow resistance of the tree-like branching networks reaches a minimum when the diameter ratio β∗ satisfies β∗=Nk, where, N is the bifurcation number N=2,3,4,… and k is a constant. For laminar flow, k=-1/3, which is in agreement with the existing Murray’s law; for turbulent flow in smooth pipes, k=-3/7; for turbulent flow in rough pipes, k=-7/17. These results serve as design guidelines of efficient transport and flow systems.

  14. Speed limit and ramp meter control for traffic flow networks

    NASA Astrophysics Data System (ADS)

    Goatin, Paola; Göttlich, Simone; Kolb, Oliver

    2016-07-01

    The control of traffic flow can be related to different applications. In this work, a method to manage variable speed limits combined with coordinated ramp metering within the framework of the Lighthill-Whitham-Richards (LWR) network model is introduced. Following a 'first-discretize-then-optimize' approach, the first order optimality system is derived and the switch of speeds at certain fixed points in time is explained, together with the boundary control for the ramp metering. Sequential quadratic programming methods are used to solve the control problem numerically. For application purposes, experimental setups are presented wherein variable speed limits are used as a traffic guidance system to avoid traffic jams on highway interchanges and on-ramps.

  15. Probabilistic constrained load flow based on sensitivity analysis

    SciTech Connect

    Karakatsanis, T.S.; Hatziargyriou, N.D. )

    1994-11-01

    This paper presents a method for network constrained setting of control variables based on probabilistic load flow analysis. The method determines operating constraint violations for a whole planning period together with the probability of each violation. An iterative algorithm is subsequently employed providing adjustments of the control variables based on sensitivity analysis of the constrained variables with respect to the control variables. The method is applied to the IEEE 14 busbar system and to a realistic model of the Hellenic Interconnected system indicating its suitability for short-term operational planning applications.

  16. A new approach to blood flow simulation in vascular networks.

    PubMed

    Tamaddon, Houman; Behnia, Mehrdad; Behnia, Masud; Kritharides, Leonard

    2016-01-01

    A proper analysis of blood flow is contingent upon accurate modelling of the branching pattern and vascular geometry of the network of interest. It is challenging to reconstruct the entire vascular network of any organ experimentally, in particular the pulmonary vasculature, because of its very high number of vessels, complexity of the branching pattern and poor accessibility in vivo. The objective of our research is to develop an innovative approach for the reconstruction of the full pulmonary vascular tree from available morphometric data. Our method consists of the use of morphometric data on those parts of the pulmonary vascular tree that are too small to reconstruct by medical imaging methods. This method is a three-step technique that reconstructs the entire pulmonary arterial tree down to the capillary bed. Vessels greater than 2 mm are reconstructed from direct volume and surface analysis using contrast-enhanced computed tomography. Vessels smaller than 2 mm are reconstructed from available morphometric and distensibility data and rearranged by applying Murray's laws. Implementation of morphometric data to reconstruct the branching pattern and applying Murray's laws to every vessel bifurcation simultaneously leads to an accurate vascular tree reconstruction. The reconstruction algorithm generates full arterial tree topography down to the first capillary bifurcation. Geometry of each order of the vascular tree is generated separately to minimize the construction and simulation time. The node-to-node connectivity along with the diameter and length of every vessel segment is established and order numbers, according to the diameter-defined Strahler system, are assigned. In conclusion, the present model provides a morphological foundation for future analysis of blood flow in the pulmonary circulation. PMID:26195135

  17. NASDA knowledge-based network planning system

    NASA Technical Reports Server (NTRS)

    Yamaya, K.; Fujiwara, M.; Kosugi, S.; Yambe, M.; Ohmori, M.

    1993-01-01

    One of the SODS (space operation and data system) sub-systems, NP (network planning) was the first expert system used by NASDA (national space development agency of Japan) for tracking and control of satellite. The major responsibilities of the NP system are: first, the allocation of network and satellite control resources and, second, the generation of the network operation plan data (NOP) used in automated control of the stations and control center facilities. Up to now, the first task of network resource scheduling was done by network operators. NP system automatically generates schedules using its knowledge base, which contains information on satellite orbits, station availability, which computer is dedicated to which satellite, and how many stations must be available for a particular satellite pass or a certain time period. The NP system is introduced.

  18. Network based sky Brightness Monitor

    NASA Astrophysics Data System (ADS)

    McKenna, Dan; Pulvermacher, R.; Davis, D. R.

    2009-01-01

    We have developed and are currently testing an autonomous 2 channel photometer designed to measure the night sky brightness in the visual wavelengths over a multi-year campaign. The photometer uses a robust silicon sensor filtered with Hoya CM500 glass. The Sky brightness is measured every minute at two elevation angles typically zenith and 20 degrees to monitor brightness and transparency. The Sky Brightness monitor consists of two units, the remote photometer and a network interface. Currently these devices use 2.4 Ghz transceivers with a free space range of 100 meters. The remote unit is battery powered with day time recharging using a solar panel. Data received by the network interface transmits data via standard POP Email protocol. A second version is under development for radio sensitive areas using an optical fiber for data transmission. We will present the current comparison with the National Park Service sky monitoring camera. We will also discuss the calibration methods used for standardization and temperature compensation. This system is expected to be deployed in the next year and be operated by the International Dark Sky Association SKYMONITOR project.

  19. Parallel Computation of Unsteady Flows on a Network of Workstations

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Parallel computation of unsteady flows requires significant computational resources. The utilization of a network of workstations seems an efficient solution to the problem where large problems can be treated at a reasonable cost. This approach requires the solution of several problems: 1) the partitioning and distribution of the problem over a network of workstation, 2) efficient communication tools, 3) managing the system efficiently for a given problem. Of course, there is the question of the efficiency of any given numerical algorithm to such a computing system. NPARC code was chosen as a sample for the application. For the explicit version of the NPARC code both two- and three-dimensional problems were studied. Again both steady and unsteady problems were investigated. The issues studied as a part of the research program were: 1) how to distribute the data between the workstations, 2) how to compute and how to communicate at each node efficiently, 3) how to balance the load distribution. In the following, a summary of these activities is presented. Details of the work have been presented and published as referenced.

  20. In vivo measurement of blood flow in the vitelline network

    NASA Astrophysics Data System (ADS)

    Poelma, Christian; Vennemann, Peter; Lindken, Ralph; Westerweel, Jerry

    2007-11-01

    The growth and adaptation of blood vessels is studied in vivo in the so-called vitelline network of a chick embryo. The vitelline network, a system of extra-embryonic blood vessels that transports nutrients from the yolk sac to the chick embryo, is an easily accessible model system for the study of human cardiovascular development and functioning. We present measurements obtained by means of scanning microscopic Particle Image Velocimetry. Using phase-locking, we can reconstruct the full three-dimensional flow as a function of the cardiac cycle. Typical reconstructed volumes are 0.4x0.5x0.2 mm^3 with a spatial resolution (i.e. vector spacing) of 6 μm. These hemodynamic measurements allow a study of the coupling between form and functioning of the blood vessels. Special attention is given to the local wall shear stress (WSS), an important physiological parameter that is thought to determine - to great extent - the adaptation of the vessels to changing conditions. The WSS can be estimated directly from the velocity gradient at the wall or from a fit to the blood velocity profile. The former method slightly underestimates the WSS (most likely due to lack of resolution) but is significantly easier to apply in the complex geometries under consideration.

  1. Base flow in the Great Lakes Basin

    USGS Publications Warehouse

    Neff, B.P.; Day, S.M.; Piggott, A.R.; Fuller, L.M.

    2005-01-01

    Hydrograph separations were performed using the PART, HYSEP 1, 2, and 3, BFLOW and UKIH methods on 104,293 years of daily streamflow records from 3,936 streamflow-gaging stations in Ontario, Canada and the eight Great Lakes States of Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Pennsylvania, and Wisconsin to estimate base-flow index (BFI) and base flow. BFI ranged an average of 0.24 BFI depending on which hydrograph-separation method was used. BFI data from 959 selected streamflow-gaging stations with a combined 28,784 years of daily streamflow data were used to relate BFI to surficial geology and the proportion of surface water within the gaged watersheds. This relation was then used to derive estimates of BFI throughout the Great Lakes, Ottawa River, and upper St. Lawrence River Basins at a scale of 8-digit hydrologic unit code (HUC) watersheds for the U.S. and tertiary watersheds in Canada. This process was repeated for each of the six hydrograph-separation methods used. When applied to gaged watersheds, model results predicted observed base flow within 0.2 BFI up to 94 percent of the time. Estimates of long-term (length of streamflow record) average annual streamflow in each HUC and tertiary watershed were calculated and used to determine average annual base flow from BFI estimates. Possibilities for future study based on results from this study include long-term trend analysis of base flow and improving the scale at which base-flow estimates can be made.

  2. Characterization of fracture networks for fluid flow analysis

    SciTech Connect

    Long, J.C.S.; Billaux, D.; Hestir, K.; Majer, E.L.; Peterson, J.; Karasaki, K.; Nihei, K.; Gentier, S.; Cox, L.

    1989-06-01

    The analysis of fluid flow through fractured rocks is difficult because the only way to assign hydraulic parameters to fractures is to perform hydraulic tests. However, the interpretation of such tests, or ''inversion'' of the data, requires at least that we know the geometric pattern formed by the fractures. Combining a statistical approach with geophysical data may be extremely helpful in defining the fracture geometry. Cross-hole geophysics, either seismic or radar, can provide tomograms which are pixel maps of the velocity or attenuation anomalies in the rock. These anomalies are often due to fracture zones. Therefore, tomograms can be used to identify fracture zones and provide information about the structure within the fracture zones. This structural information can be used as the basis for simulating the degree of fracturing within the zones. Well tests can then be used to further refine the model. Because the fracture network is only partially connected, the resulting geometry of the flow paths may have fractal properties. We are studying the behavior of well tests under such geometry. Through understanding of this behavior, it may be possible to use inverse techniques to refine the a priori assignment of fractures and their conductances such that we obtain the best fit to a series of well test results simultaneously. The methodology described here is under development and currently being applied to several field sites. 4 refs., 14 figs.

  3. Influence of perched groundwater on base flow

    USGS Publications Warehouse

    Niswonger, R.G.; Fogg, G.E.

    2008-01-01

    Analysis with a three-dimensional variably saturated groundwater flow model provides a basic understanding of the interplay between streams and perched groundwater. A simplified, layered model of heterogeneity was used to explore these relationships. Base flow contribution from perched groundwater was evaluated with regard to varying hydrogeologic conditions, including the size and location of the fine-sediment unit and the hydraulic conductivity of the fine-sediment unit and surrounding coarser sediment. Simulated base flow was sustained by perched groundwater with a maximum monthly discharge in excess of 15 L/s (0.6 feet3/s) over the length of the 2000-m stream reach. Generally, the rate of perched-groundwater discharge to the stream was proportional to the hydraulic conductivity of sediment surrounding the stream, whereas the duration of discharge was proportional to the hydraulic conductivity of the fine-sediment unit. Other aspects of the perched aquifer affected base flow, such as the depth of stream penetration and the size of the fine-sediment unit. Greater stream penetration decreased the maximum base flow contribution but increased the duration of contribution. Perched groundwater provided water for riparian vegetation at the demand rate but reduced the duration of perched-groundwater discharge nearly 75%. Copyright 2008 by the American Geophysical Union.

  4. Identifying Network Public Opinion Leaders Based on Markov Logic Networks

    PubMed Central

    Zhang, Weizhe; Li, Xiaoqiang; He, Hui; Wang, Xing

    2014-01-01

    Public opinion emergencies have important effect on social activities. Recognition of special communities like opinion leaders can contribute to a comprehensive understanding of the development trend of public opinion. In this paper, a network opinion leader recognition method based on relational data was put forward, and an opinion leader recognition system integrating public opinion data acquisition module, data characteristic selection, and fusion module as well as opinion leader discovery module based on Markov Logic Networks was designed. The designed opinion leader recognition system not only can overcome the incomplete data acquisition and isolated task of traditional methods, but also can recognize opinion leaders comprehensively with considerations to multiple problems by using the relational model. Experimental results demonstrated that, compared with the traditional methods, the proposed method can provide a more accurate opinion leader recognition and has good noise immunity. PMID:24977188

  5. Web100-based Network Diagnostic Tool

    Energy Science and Technology Software Center (ESTSC)

    2003-03-20

    NDT is a client/server based network diagnostic tool developed to aid in finding network performance and configuration problems. The tool measures data transfer rates between two internet hosts (client and server). It also gathers detailed TCP statistical variable counters supplied by the Web100 modified server and uses these TCP variables to compute the theoretical performance rate between the two internet hosts. It then compares these analytical results with the measured results to determine if performancemore » or configuration problems exist and translates these results into plain text messages to aid users and network operators in resolving reported problems.« less

  6. Three Dimensional Flow, Transport and Geomechanical Simulations in Discrete Fracture Network Under Condition of Uncertainty

    NASA Astrophysics Data System (ADS)

    Ryerson, F. J.; Ezzedine, S. M.; Glascoe, L. G.; Antoun, T. H.

    2011-12-01

    Fractures and fracture networks are the principle pathways for migration of water, heat and mass in enhanced geothermal systems, oil and gas reservoirs, CO2 leakage from saline aquifers, and radioactive and toxic industrial wastes from underground storage repositories. A major issue to overcome when characterizing a fractured reservoir is that of data limitation due to accessibility and affordability. Moreover, the ability to map discontinuities in the rock with available geological and geophysical tools tends to decrease particularly as the scale of the discontinuity goes down. Data collected are often reduced to probability distribution functions for predictive modeling and simulation in a stochastic framework such as stochastic discrete fracture network. Stochastic discrete fracture network models enable probabilistic assessment of flow, transport and geomechanical phenomena that are not adequately captured using continuum models. Despite the fundamental uncertainties inherited within the probabilistic reduction of the sparse data collected, very little work has been conducted on quantifying uncertainty on the reduced probabilistic distribution functions. In the current study, we investigate the impact of parameter uncertainties of the distribution functions that characterize discrete fracture networks on the flow, heat and mass transport and geomechanics. Numerical results of first, second and third moments, normalized to a base case scenario, are presented and compared to theoretical results extended from percolation theory. (Prepared by LLNL under Contract DE-AC52-07NA27344)

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  8. Leo satellite-based telecommunication network concepts

    NASA Technical Reports Server (NTRS)

    Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

    1991-01-01

    Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

  9. Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch.

    PubMed

    Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

    2016-01-01

    Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

  10. Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch

    PubMed Central

    Huang, Tao; Yan, Siyu; Yang, Fan; Pan, Tian; Liu, Jiang

    2016-01-01

    Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. PMID:26797616

  11. Artificial Neural Network Modeling to Evaluate the Dynamic Flow Stress of 7050 Aluminum Alloy

    NASA Astrophysics Data System (ADS)

    Quan, Guo-zheng; Wang, Tong; Li, Yong-le; Zhan, Zong-yang; Xia, Yu-feng

    2016-02-01

    The flow stress data have been obtained by a set of isothermal hot compression tests, which were carried out in the temperature range of 573-723 K and strain rates of 0.01, 0.1, 1, and 10 s-1 with a reduction of 60% on a Gleeble-1500 thermo-mechanical simulator. On the basis of the experimental data, constitutive equation and an artificial neural network model were developed for the analysis and simulation of the flow behavior of the 7050 aluminum alloy. After training with standard back-propagation learning algorithm, the artificial neural network model has the ability to present the intrinsic relationship between the flow stress and the processing variables. In the present model, the temperature, strain, and strain rate were chosen as inputs, and the flow stress was chosen as output. By comparing the values of correlation coefficient and average absolute relative error, the prediction accuracy of the model and the improved Arrhenius-type model can be evaluated. The results indicated that the well-trained artificial neural network model is more accurate than the improved Arrhenius-type model in predicting the hot compressive behavior of the as-extruded 7050 aluminum alloy. Based on the predicted stress data and experimental stress data, the 3D continuous stress-strain maps at different strains, temperatures, and strain rates were plotted subsequently. Besides, the flow stress values at arbitrary temperature, strain rate, and strain are explicit on the 3D continuous stress-strain maps, which would be beneficial to articulate working processes more validly.

  12. Elements of Network-Based Assessment

    ERIC Educational Resources Information Center

    Gibson, David

    2007-01-01

    Elements of network-based assessment systems are envisioned based on recent advances in knowledge and practice in learning theory, assessment design and delivery, and semantic web interoperability. The architecture takes advantage of the meditating role of technology as well as recent models of assessment systems. This overview of the elements…

  13. Riparian indicators of flow frequency in a tropical montane stream network

    NASA Astrophysics Data System (ADS)

    Pike, Andrew S.; Scatena, Frederick N.

    2010-03-01

    SummaryMany field indicators have been used to approximate the magnitude and frequency of flows in a variety of streams and rivers, yet due to a scarcity of long-term flow records in tropical mountain streams, little to no work has been done to establish such relationships between field features and the flow regime in these environments. Furthermore, the transition between the active channel of a river and the adjacent flood zone (i.e. bankfull) is an important geomorphologic and ecological boundary, but is rarely identifiable in steep mountain channels that lack alluvial flood plains. This study (a) quantifies relationships between field indicators and flow frequency in alluvial and steepland channels in a tropical mountain stream network and (b) identifies a reference active channel boundary in these channels, based on statistically defined combinations of riparian features, that corresponds to the same flow frequency of the bankfull stage and the effective discharge in adjacent alluvial channels. The relative elevation of transitions in riparian vegetation, soil, and substrate characteristics were first surveyed at nine stream gages in and around the Luquillo Experimental Forest in Northeastern Puerto Rico. The corresponding discharge, flow frequency, and recurrence intervals associated with these features was then determined from long-term 15-min discharge records and a partial duration series analysis. Survey data indicate that mosses and short grasses dominate at a stage often inundated by sub-effective flows. Herbaceous vegetation is associated with intermediate discharges that correspond to the threshold for sediment mobilization. Near-channel woody shrubs and trees establish at elevations along the channel margin inundated by a less frequent discharge that is coincident with the effective discharge of bed load sediment transport. Our data demonstrate that in alluvial channels in the study, both the bankfull stage (as marked by a flood plain) and the

  14. Blood flow distribution in an anatomically detailed arterial network model: criteria and algorithms.

    PubMed

    Blanco, Pablo J; Watanabe, Sansuke M; Dari, Enzo A; Passos, Marco Aurélio R F; Feijóo, Raúl A

    2014-11-01

    Development of blood flow distribution criteria is a mandatory step toward developing computational models and numerical simulations of the systemic circulation. In the present work, we (i) present a systematic approach based on anatomical and physiological considerations to distribute the blood flow in a 1D anatomically detailed model of the arterial network and (ii) develop a numerical procedure to calibrate resistive parameters in terminal models in order to effectively satisfy such flow distribution. For the first goal, we merge data collected from the specialized medical literature with anatomical concepts such as vascular territories to determine blood flow supply to specific (encephalon, kidneys, etc.) and distributed (muscles, skin, etc.) organs. Overall, 28 entities representing the main specific organs are accounted for in the detailed description of the arterial topology that we use as model substrate. In turn, 116 vascular territories are considered as the basic blocks that compose the distributed organs throughout the whole body. For the second goal, Windkessel models are used to represent the peripheral beds, and the values of the resistive parameters are computed applying a Newton method to a parameter identification problem to guarantee the supply of the correct flow fraction to each terminal location according to the given criteria. Finally, it is shown that, by means of the criteria developed, and for a rather standard set of model parameters, the model predicts physiologically realistic pressure and flow waveforms. PMID:24682727

  15. Optimizing neural networks for river flow forecasting - Evolutionary Computation methods versus the Levenberg-Marquardt approach

    NASA Astrophysics Data System (ADS)

    Piotrowski, Adam P.; Napiorkowski, Jarosław J.

    2011-09-01

    SummaryAlthough neural networks have been widely applied to various hydrological problems, including river flow forecasting, for at least 15 years, they have usually been trained by means of gradient-based algorithms. Recently nature inspired Evolutionary Computation algorithms have rapidly developed as optimization methods able to cope not only with non-differentiable functions but also with a great number of local minima. Some of proposed Evolutionary Computation algorithms have been tested for neural networks training, but publications which compare their performance with gradient-based training methods are rare and present contradictory conclusions. The main goal of the present study is to verify the applicability of a number of recently developed Evolutionary Computation optimization methods, mostly from the Differential Evolution family, to multi-layer perceptron neural networks training for daily rainfall-runoff forecasting. In the present paper eight Evolutionary Computation methods, namely the first version of Differential Evolution (DE), Distributed DE with Explorative-Exploitative Population Families, Self-Adaptive DE, DE with Global and Local Neighbors, Grouping DE, JADE, Comprehensive Learning Particle Swarm Optimization and Efficient Population Utilization Strategy Particle Swarm Optimization are tested against the Levenberg-Marquardt algorithm - probably the most efficient in terms of speed and success rate among gradient-based methods. The Annapolis River catchment was selected as the area of this study due to its specific climatic conditions, characterized by significant seasonal changes in runoff, rapid floods, dry summers, severe winters with snowfall, snow melting, frequent freeze and thaw, and presence of river ice - conditions which make flow forecasting more troublesome. The overall performance of the Levenberg-Marquardt algorithm and the DE with Global and Local Neighbors method for neural networks training turns out to be superior to other

  16. Bus-based park-and-ride system: a stochastic model on multimodal network with congestion pricing schemes

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyuan; Meng, Qiang

    2014-05-01

    This paper focuses on modelling the network flow equilibrium problem on a multimodal transport network with bus-based park-and-ride (P&R) system and congestion pricing charges. The multimodal network has three travel modes: auto mode, transit mode and P&R mode. A continuously distributed value-of-time is assumed to convert toll charges and transit fares to time unit, and the users' route choice behaviour is assumed to follow the probit-based stochastic user equilibrium principle with elastic demand. These two assumptions have caused randomness to the users' generalised travel times on the multimodal network. A comprehensive network framework is first defined for the flow equilibrium problem with consideration of interactions between auto flows and transit (bus) flows. Then, a fixed-point model with unique solution is proposed for the equilibrium flows, which can be solved by a convergent cost averaging method. Finally, the proposed methodology is tested by a network example.

  17. Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks.

    PubMed

    Natale, Fabrizio; Savini, Lara; Giovannini, Armando; Calistri, Paolo; Candeloro, Luca; Fiore, Gianluca

    2011-02-01

    A new method for the calculation of a centrality measure (Disease Flow Centrality, DFC), which takes into account temporal dynamics of livestock movement networks, is proposed. The method is based on a network traversal algorithm which represents an epidemic process more realistically compared with traditional graph traversal algorithms used in the calculation of centrality measures on static networks. The new approach was tested on networks generated from all the registered movements of cattle in Italy in the years 2007, 2008 and 2009 and the results were compared to those obtained by classical centrality measures. The results show that DFC values often differ substantially from those of other centrality measures and that these DFC values tend to be more unstable in time. The DFC offers several advantages for assessing risk and vulnerability of specific holdings and of an entire network, using recent movement data from national livestock databases. Some examples also indicate how the basic approach in the DFC calculation could be expanded into a more complex epidemic model by incorporating weights and how it could be combined with a geo-spatial perspective. PMID:21159393

  18. Base pressure in laminar supersonic flow.

    NASA Technical Reports Server (NTRS)

    Messiter, A. F.; Hough, G. R.; Feo, A.

    1973-01-01

    An asymptotic description is proposed for supersonic laminar flow over a wedge or a backward-facing step, for large Reynolds number and for a base or step height which is small compared with the boundary-layer length. The analysis is carried out for adiabatic wall conditions and a viscosity coefficient proportional to temperature. In a particular limit corresponding to a very thick boundary layer, a similarity law is obtained for the base pressure. For a thinner boundary layer an asymptotic form for the base pressure is obtained which shows the dependence on the parameters explicitly and which permits good agreement with experiment. This latter result is based on an inviscid-flow approximation for the corner expansion and for reattachment with viscous forces important primarily in a thin sublayer about the dividing streamline. A prediction of the pressure distribution at reattachment is given and the result is compared with experimental pressure distributions.

  19. Combining neural networks and genetic algorithms for hydrological flow forecasting

    NASA Astrophysics Data System (ADS)

    Neruda, Roman; Srejber, Jan; Neruda, Martin; Pascenko, Petr

    2010-05-01

    We present a neural network approach to rainfall-runoff modeling for small size river basins based on several time series of hourly measured data. Different neural networks are considered for short time runoff predictions (from one to six hours lead time) based on runoff and rainfall data observed in previous time steps. Correlation analysis shows that runoff data, short time rainfall history, and aggregated API values are the most significant data for the prediction. Neural models of multilayer perceptron and radial basis function networks with different numbers of units are used and compared with more traditional linear time series predictors. Out of possible 48 hours of relevant history of all the input variables, the most important ones are selected by means of input filters created by a genetic algorithm. The genetic algorithm works with population of binary encoded vectors defining input selection patterns. Standard genetic operators of two-point crossover, random bit-flipping mutation, and tournament selection were used. The evaluation of objective function of each individual consists of several rounds of building and testing a particular neural network model. The whole procedure is rather computational exacting (taking hours to days on a desktop PC), thus a high-performance mainframe computer has been used for our experiments. Results based on two years worth data from the Ploucnice river in Northern Bohemia suggest that main problems connected with this approach to modeling are ovetraining that can lead to poor generalization, and relatively small number of extreme events which makes it difficult for a model to predict the amplitude of the event. Thus, experiments with both absolute and relative runoff predictions were carried out. In general it can be concluded that the neural models show about 5 per cent improvement in terms of efficiency coefficient over liner models. Multilayer perceptrons with one hidden layer trained by back propagation algorithm and

  20. Analysis of the Complex Fracture Flow in Multiple Fractured Horizontal Wells with the Fractal Tree-Like Network Models

    NASA Astrophysics Data System (ADS)

    Wang, Wendong; Su, Yuliang; Zhang, Xiao; Sheng, Guanglong; Ren, Long

    2015-03-01

    This paper formulates a fractal-tree network model to address the challenging problem of characterizing the hydraulic fracture network in unconventional reservoirs. It has been proved that the seepage flow in tight/shale oil reservoirs is much more complicated to the conventional formation. To further understand the flow mechanisms in such a complex system, a semi-analytical model considering "branch network fractures" was established stage by stage using point source method and superposition principle. Fractal method was employed to generate and represent induced fracture network around bi-wing fractures. In addition, based on the new established model and solution, deterministic fractal-tree-like fracture network patterns and heterogeneity were carefully investigated and compared with the simulation model. Results show that the fractal dimension for the fracture network has significant effect on the connectivity of the stimulated reservoir. The proposed fractal model may capture the characteristics of the heterogeneous complex fracture network and help in understanding the flow and transport mechanisms of multiple fractured horizontal wells.

  1. Autonomous robot behavior based on neural networks

    NASA Astrophysics Data System (ADS)

    Grolinger, Katarina; Jerbic, Bojan; Vranjes, Bozo

    1997-04-01

    The purpose of autonomous robot is to solve various tasks while adapting its behavior to the variable environment, expecting it is able to navigate much like a human would, including handling uncertain and unexpected obstacles. To achieve this the robot has to be able to find solution to unknown situations, to learn experienced knowledge, that means action procedure together with corresponding knowledge on the work space structure, and to recognize working environment. The planning of the intelligent robot behavior presented in this paper implements the reinforcement learning based on strategic and random attempts for finding solution and neural network approach for memorizing and recognizing work space structure (structural assignment problem). Some of the well known neural networks based on unsupervised learning are considered with regard to the structural assignment problem. The adaptive fuzzy shadowed neural network is developed. It has the additional shadowed hidden layer, specific learning rule and initialization phase. The developed neural network combines advantages of networks based on the Adaptive Resonance Theory and using shadowed hidden layer provides ability to recognize lightly translated or rotated obstacles in any direction.

  2. MEMS Based Flow Sensors and Their Application on Flow Imaging

    NASA Astrophysics Data System (ADS)

    Yang, Yingchen; Chen, Nannan; Engel, Jonathan; Tucker, Craig; Pandya, Saunvit; Liu, Chang

    2006-11-01

    We report characterization and application of recently developed, MEMS based, out-of-plane hot-wire anemometer (HWA) sensor and bio-inspired artificial hair cell (AHC) sensor. Sensitivities of 0.2mm/s for HWA and 0.1mm/s for AHC have been achieved in water flows, comparing with 1mm/s of a conventional HWA. In contrast to its high sensitivity, the AHC sensor can survive 55 bending of its hair, making it very robust. After calibration, both HWA and AHC sensors were employed for dipole field and wake measurements. The dipole field was generated by a vibrating sphere in a large water tank; the measurement results match very well with the analytical model. The wake was created by a circular cylinder in a water channel; the RMS velocity distributions replicate the main features of a typical wake accurately. The two types of sensors were also applied in array format to mimic a fish lateral line for imaging hydrodynamic events. Multi-modal sensors capable of simultaneous measurement of flow velocity, shear stress, pressure and temperature are under development.

  3. Bipolar Membranes for Acid Base Flow Batteries

    NASA Astrophysics Data System (ADS)

    Anthamatten, Mitchell; Roddecha, Supacharee; Jorne, Jacob; Coughlan, Anna

    2011-03-01

    Rechargeable batteries can provide grid-scale electricity storage to match power generation with consumption and promote renewable energy sources. Flow batteries offer modular and flexible design, low cost per kWh and high efficiencies. A novel flow battery concept will be presented based on acid-base neutralization where protons (H+) and hydroxyl (OH-) ions react electrochemically to produce water. The large free energy of this highly reversible reaction can be stored chemically, and, upon discharge, can be harvested as usable electricity. The acid-base flow battery concept avoids the use of a sluggish oxygen electrode and utilizes the highly reversible hydrogen electrode, thus eliminating the need for expensive noble metal catalysts. The proposed flow battery is a hybrid of a battery and a fuel cell---hydrogen gas storing chemical energy is produced at one electrode and is immediately consumed at the other electrode. The two electrodes are exposed to low and high pH solutions, and these solutions are separated by a hybrid membrane containing a hybrid cation and anion exchange membrane (CEM/AEM). Membrane design will be discussed, along with ion-transport data for synthesized membranes.

  4. Adaptive Evolutionary Programming Incorporating Neural Network for Transient Stability Constrained Optimal Power Flow

    NASA Astrophysics Data System (ADS)

    Tangpatiphan, Kritsana; Yokoyama, Akihiko

    This paper presents an adaptive evolutionary programming incorporating neural network for solving transient stability constrained optimal power flow (TSCOPF). The proposed AEP method is an evolutionary programming (EP)-based algorithm, which adjusts its population size automatically during an optimization process. The artificial neural network, which classifies the AEP individual based on its stability degrees, is embedded into the search template to reduce the computational load caused by transient stability constraints. The fuel cost minimization is selected as the objective function of TSCOPF. The proposed method is tested on the IEEE 30-bus system with two types of the fuel cost functions, i.e. the conventional quadratic function and the quadratic function superimposed by sine component to model the cost curves without and with valve-point loading effect respectively. The numerical examples show that AEP is more effective than conventional EP in terms of computational speed, and when the neural network is incorporated into AEP, it can significantly reduce the computational time of TSCOPF. A study of the architecture of the neural network is also conducted and discussed. In addition, the effectiveness of the proposed method for solving TSCOPF with the consideration of multiple contingencies is manifested.

  5. Incorporation of Condensation Heat Transfer in a Flow Network Code

    NASA Technical Reports Server (NTRS)

    Anthony, Miranda; Majumdar, Alok

    2002-01-01

    Pure water is distilled from waste water in the International Space Station. The distillation assembly consists of an evaporator, a compressor and a condenser. Vapor is periodically purged from the condenser to avoid vapor accumulation. Purged vapor is condensed in a tube by coolant water prior to entering the purge pump. The paper presents a condensation model of purged vapor in a tube. This model is based on the Finite Volume Method. In the Finite Volume Method, the flow domain is discretized into multiple control volumes and a simultaneous analysis is performed.

  6. Overlapping Community Detection based on Network Decomposition

    NASA Astrophysics Data System (ADS)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  7. Overlapping Community Detection based on Network Decomposition

    PubMed Central

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  8. Overlapping Community Detection based on Network Decomposition.

    PubMed

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  9. Robustness in clustering-based weighted inter-connected networks

    NASA Astrophysics Data System (ADS)

    Qiu, Yuzhuo; Yağan, Osman

    2014-04-01

    We study the robustness of symmetrically coupled and clustering-based weighted heterogeneous inter-connected networks with respect to load-failure-induced cascades. This is done under the assumption that the flow dynamics are governed by global redistribution of loads based on weighted betweenness centrality. Our results indicate that no weighting bias should be assigned to inter-links when calculating shortest path between node pairs under the clustering-based weighting scheme; i.e., inter-links shall be treated no differently than intra-links. In contrast with local load redistribution cases, we show that increasing connectivity is preferred for the robustness against global load redistribution-based cascading failures in clustering-based weighted inter-connected networks. Furthermore, comparisons among weighting schemes reveal that, both the clustering-based and degree-based schemes outperform the random one in the sense of requiring lower initial and total investments required to ensure robustness. We also find that clustering-based scheme outperforms degree-based one in terms of requiring lower initial investments. Except in a limited range where weighting is heavily suppressed, clustering-based scheme is shown to outperform degree-based one in terms of total investments. Finally, when there exists a hard investment budget constraint, clustering-based weighting scheme would be a better choice against a two-nodes-induced failure than the degree-based weighting, and the clustering-based scheme is more stable than degree-based scheme against one-or-two-nodes-induced failure. We expect our findings to be significantly useful in designing real-world weighted inter-connected networks that are robust against load-failure-induced cascades.

  10. Spatiotemporal properties of intracellular calcium signaling in osteocytic and osteoblastic cell networks under fluid flow.

    PubMed

    Jing, Da; Lu, X Lucas; Luo, Erping; Sajda, Paul; Leong, Pui L; Guo, X Edward

    2013-04-01

    Mechanical stimuli can trigger intracellular calcium (Ca(2+)) responses in osteocytes and osteoblasts. Successful construction of bone cell networks necessitates more elaborate and systematic analysis for the spatiotemporal properties of Ca(2+) signaling in the networks. In the present study, an unsupervised algorithm based on independent component analysis (ICA) was employed to extract the Ca(2+) signals of bone cells in the network. We demonstrated that the ICA-based technology could yield higher signal fidelity than the manual region of interest (ROI) method. Second, the spatiotemporal properties of Ca(2+) signaling in osteocyte-like MLO-Y4 and osteoblast-like MC3T3-E1 cell networks under laminar and steady fluid flow stimulation were systematically analyzed and compared. MLO-Y4 cells exhibited much more active Ca(2+) transients than MC3T3-E1 cells, evidenced by more Ca(2+) peaks, less time to the 1st peak and less time between the 1st and 2nd peaks. With respect to temporal properties, MLO-Y4 cells demonstrated higher spike rate and Ca(2+) oscillating frequency. The spatial intercellular synchronous activities of Ca(2+) signaling in MLO-Y4 cell networks were higher than those in MC3T3-E1 cell networks and also negatively correlated with the intercellular distance, revealing faster Ca(2+) wave propagation in MLO-Y4 cell networks. Our findings show that the unsupervised ICA-based technique results in more sensitive and quantitative signal extraction than traditional ROI analysis, with the potential to be widely employed in Ca(2+) signaling extraction in the cell networks. The present study also revealed a dramatic spatiotemporal difference in Ca(2+) signaling for osteocytic and osteoblastic cell networks in processing the mechanical stimulus. The higher intracellular Ca(2+) oscillatory behaviors and intercellular coordination of MLO-Y4 cells provided further evidences that osteocytes may behave as the major mechanical sensor in bone modeling and remodeling

  11. Flow simulation and erosion assessment in a ditch network of a drained peatland forest catchment in Eastern Finland

    NASA Astrophysics Data System (ADS)

    Haahti, Kersti; Koivusalo, Harri; Younis, Bassam; Stenberg, Leena

    2014-05-01

    One third of the land area in Finland is covered by peatlands and today 4.5 million ha of peatlands are drained for forestry purposes. In order to sustain forest productivity, ditch networks are maintained annually on an area of approximately 60 000 ha. The suspended solid (SS) load from drained peatland forest sites after ditch network maintenance causes one of the largest strains on the water system by forestry in Finland. Understanding the hydraulic processes in newly maintained ditch networks is necessary for quantifying the SS load generation and transport in the source areas. In this study we developed a hydraulic unsteady-flow model to predict the behavior of flow in a drainage network in a boreal forested peatland site. The input to this model was in the form of a discharge hydrograph that was produced by a hydrological model (FEMMA). The simulations were performed using the algorithm of Zhu et al. (2011) for unsteady flows in a network of channels. In this iterative procedure, the Saint-Venant equations that govern the flow in each of the network channels were solved separately, and the flow depths at the junction-points were corrected using the method of characteristics. The algorithm was programmed using the numeric computing environment MATLAB by MathWorks. Based on the hydraulic conditions produced by the model, erosion risk within the network was evaluated. The model was applied to a peatland catchment drained for forestry in Koivupuro in Eastern Finland (63°53' N, 28°40' E). In August 2011, most of the Koivupuro catchment ditch network was maintained creating simultaneously a smaller nested catchment (area 5.2 ha) which was the focus of this study. The ditch network consisted of 15 branches, altogether 1.6 km in length, and 8 junctions. The model performance was evaluated against flow depth measurements at 5 locations in the network. The simulations in the small ditches of Koivupuro with mostly very low flow rate (< 0.05 m3/s) introduced its

  12. Micro/Nano-pore Network Analysis of Gas Flow in Shale Matrix

    PubMed Central

    Zhang, Pengwei; Hu, Liming; Meegoda, Jay N.; Gao, Shengyan

    2015-01-01

    The gas flow in shale matrix is of great research interests for optimized shale gas extraction. The gas flow in the nano-scale pore may fall in flow regimes such as viscous flow, slip flow and Knudsen diffusion. A 3-dimensional nano-scale pore network model was developed to simulate dynamic gas flow, and to describe the transient properties of flow regimes. The proposed pore network model accounts for the various size distributions and low connectivity of shale pores. The pore size, pore throat size and coordination number obey normal distribution, and the average values can be obtained from shale reservoir data. The gas flow regimes were simulated using an extracted pore network backbone. The numerical results show that apparent permeability is strongly dependent on pore pressure in the reservoir and pore throat size, which is overestimated by low-pressure laboratory tests. With the decrease of reservoir pressure, viscous flow is weakening, then slip flow and Knudsen diffusion are gradually becoming dominant flow regimes. The fingering phenomenon can be predicted by micro/nano-pore network for gas flow, which provides an effective way to capture heterogeneity of shale gas reservoir. PMID:26310236

  13. The Flow of International Students from a Macro Perspective: A Network Analysis

    ERIC Educational Resources Information Center

    Barnett, George A.; Lee, Moosung; Jiang, Ke; Park, Han Woo

    2016-01-01

    This paper provides a network analysis of the international flow of students among 210 countries and the factors determining the structure of this flow. Among these factors, bilateral hyperlink connections between countries and the number of telephone minutes (communication variables) are the most important predictors of the flow's structure,…

  14. Micro/Nano-pore Network Analysis of Gas Flow in Shale Matrix

    NASA Astrophysics Data System (ADS)

    Zhang, Pengwei; Hu, Liming; Meegoda, Jay N.; Gao, Shengyan

    2015-08-01

    The gas flow in shale matrix is of great research interests for optimized shale gas extraction. The gas flow in the nano-scale pore may fall in flow regimes such as viscous flow, slip flow and Knudsen diffusion. A 3-dimensional nano-scale pore network model was developed to simulate dynamic gas flow, and to describe the transient properties of flow regimes. The proposed pore network model accounts for the various size distributions and low connectivity of shale pores. The pore size, pore throat size and coordination number obey normal distribution, and the average values can be obtained from shale reservoir data. The gas flow regimes were simulated using an extracted pore network backbone. The numerical results show that apparent permeability is strongly dependent on pore pressure in the reservoir and pore throat size, which is overestimated by low-pressure laboratory tests. With the decrease of reservoir pressure, viscous flow is weakening, then slip flow and Knudsen diffusion are gradually becoming dominant flow regimes. The fingering phenomenon can be predicted by micro/nano-pore network for gas flow, which provides an effective way to capture heterogeneity of shale gas reservoir.

  15. Micro/Nano-pore Network Analysis of Gas Flow in Shale Matrix.

    PubMed

    Zhang, Pengwei; Hu, Liming; Meegoda, Jay N; Gao, Shengyan

    2015-01-01

    The gas flow in shale matrix is of great research interests for optimized shale gas extraction. The gas flow in the nano-scale pore may fall in flow regimes such as viscous flow, slip flow and Knudsen diffusion. A 3-dimensional nano-scale pore network model was developed to simulate dynamic gas flow, and to describe the transient properties of flow regimes. The proposed pore network model accounts for the various size distributions and low connectivity of shale pores. The pore size, pore throat size and coordination number obey normal distribution, and the average values can be obtained from shale reservoir data. The gas flow regimes were simulated using an extracted pore network backbone. The numerical results show that apparent permeability is strongly dependent on pore pressure in the reservoir and pore throat size, which is overestimated by low-pressure laboratory tests. With the decrease of reservoir pressure, viscous flow is weakening, then slip flow and Knudsen diffusion are gradually becoming dominant flow regimes. The fingering phenomenon can be predicted by micro/nano-pore network for gas flow, which provides an effective way to capture heterogeneity of shale gas reservoir. PMID:26310236

  16. Motion detection based on recurrent network dynamics

    PubMed Central

    Joukes, Jeroen; Hartmann, Till S.; Krekelberg, Bart

    2014-01-01

    The detection of visual motion requires temporal delays to compare current with earlier visual input. Models of motion detection assume that these delays reside in separate classes of slow and fast thalamic cells, or slow and fast synaptic transmission. We used a data-driven modeling approach to generate a model that instead uses recurrent network dynamics with a single, fixed temporal integration window to implement the velocity computation. This model successfully reproduced the temporal response dynamics of a population of motion sensitive neurons in macaque middle temporal area (MT) and its constituent parts matched many of the properties found in the motion processing pathway (e.g., Gabor-like receptive fields (RFs), simple and complex cells, spatially asymmetric excitation and inhibition). Reverse correlation analysis revealed that a simplified network based on first and second order space-time correlations of the recurrent model behaved much like a feedforward motion energy (ME) model. The feedforward model, however, failed to capture the full speed tuning and direction selectivity properties based on higher than second order space-time correlations typically found in MT. These findings support the idea that recurrent network connectivity can create temporal delays to compute velocity. Moreover, the model explains why the motion detection system often behaves like a feedforward ME network, even though the anatomical evidence strongly suggests that this network should be dominated by recurrent feedback. PMID:25565992

  17. Network based high performance concurrent computing

    SciTech Connect

    Sunderam, V.S.

    1991-01-01

    The overall objectives of this project are to investigate research issues pertaining to programming tools and efficiency issues in network based concurrent computing systems. The basis for these efforts is the PVM project that evolved during my visits to Oak Ridge Laboratories under the DOE Faculty Research Participation program; I continue to collaborate with researchers at Oak Ridge on some portions of the project.

  18. Dissecting a Network-Based Education System

    ERIC Educational Resources Information Center

    Davis, Tiffany; Yoo, Seong-Moo; Pan, Wendi

    2005-01-01

    The Alabama Learning Exchange (ALEX; www.alex.state.al.us) is a network-based education system designed and implemented to help improve education in Alabama. It accomplishes this goal by providing a single location for the state's K-12 educators to find information that will help improve their classroom effectiveness. The ALEX system includes…

  19. The implementation of a standards based heterogeneous network

    SciTech Connect

    Eldridge, J.M.; Tolendino, L.F.

    1991-08-05

    Computer networks, supporting an organization's activities, are prevalent and very important to the organization's mission. Implementing a heterogenous organizational network allows the staff to select the computing environment that best supports their job requirements. This paper outlines the lessons learned implementing a heterogenous computer network based on networking standards such as TCP/IP and Ethernet. Such a network is a viable alternative to a proprietary, vendor supported network and can provide all the functionality customers expect in a computer network. 2 figs.

  20. Bubble Eliminator Based on Centrifugal Flow

    NASA Technical Reports Server (NTRS)

    Gonda, Steve R.; Tsao, Yow-Min D.; Lee, Wenshan

    2004-01-01

    The fluid bubble eliminator (FBE) is a device that removes gas bubbles from a flowing liquid. The FBE contains no moving parts and does not require any power input beyond that needed to pump the liquid. In the FBE, the buoyant force for separating the gas from the liquid is provided by a radial pressure gradient associated with a centrifugal flow of the liquid and any entrained bubbles. A device based on a similar principle is described in Centrifugal Adsorption Cartridge System (MSC- 22863), which appears on page 48 of this issue. The FBE was originally intended for use in filtering bubbles out of a liquid flowing relatively slowly in a bioreactor system in microgravity. Versions that operate in normal Earth gravitation at greater flow speeds may also be feasible. The FBE (see figure) is constructed as a cartridge that includes two concentric cylinders with flanges at the ends. The outer cylinder is an impermeable housing; the inner cylinder comprises a gas-permeable, liquid-impermeable membrane covering a perforated inner tube. Multiple spiral disks that collectively constitute a spiral ramp are mounted in the space between the inner and outer cylinders. The liquid enters the FBE through an end flange, flows in the annular space between the cylinders, and leaves through the opposite end flange. The spiral disks channel the liquid into a spiral flow, the circumferential component of which gives rise to the desired centrifugal effect. The resulting radial pressure gradient forces the bubbles radially inward; that is, toward the inner cylinder. At the inner cylinder, the gas-permeable, liquid-impermeable membrane allows the bubbles to enter the perforated inner tube while keeping the liquid in the space between the inner and outer cylinders. The gas thus collected can be vented via an endflange connection to the inner tube. The centripetal acceleration (and thus the radial pressure gradient) is approximately proportional to the square of the flow speed and

  1. Tests of peak flow scaling in simulated self-similar river networks

    USGS Publications Warehouse

    Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.

    2001-01-01

    The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

  2. Secured network sensor-based defense system

    NASA Astrophysics Data System (ADS)

    Wei, Sixiao; Shen, Dan; Ge, Linqiang; Yu, Wei; Blasch, Erik P.; Pham, Khanh D.; Chen, Genshe

    2015-05-01

    Network sensor-based defense (NSD) systems have been widely used to defend against cyber threats. Nonetheless, if the adversary finds ways to identify the location of monitor sensors, the effectiveness of NSD systems can be reduced. In this paper, we propose both temporal and spatial perturbation based defense mechanisms to secure NSD systems and make the monitor sensor invisible to the adversary. The temporal-perturbation based defense manipulates the timing information of published data so that the probability of successfully recognizing monitor sensors can be reduced. The spatial-perturbation based defense dynamically redeploys monitor sensors in the network so that the adversary cannot obtain the complete information to recognize all of the monitor sensors. We carried out experiments using real-world traffic traces to evaluate the effectiveness of our proposed defense mechanisms. Our data shows that our proposed defense mechanisms can reduce the attack accuracy of recognizing detection sensors.

  3. Constrained optimisation in granular network flows: Games with a loaded dice

    NASA Astrophysics Data System (ADS)

    Lin, Qun; Tordesillas, Antoinette

    2013-06-01

    Flows in real world networks are rarely the outcome of unconditional random allocations as, say, the roll of a dice. Think, for example, of force transmission through a contact network in a quasistatically deforming granular material. Forces `flow' through this network in a highly conditional manner. How much force is transmitted between two contacting particles is always conditional not only on all the other forces acting between the particles in question but also on those acting on the other particles in the system. Broadly, we are interested in the nature and extent to which flows through a contact network favour certain pathways over others, and how the mechanisms that govern such biased flows for a given imposed loading history determine the future evolution of the contact network. Our first step is to solve a selection of fundamental combinatorial optimisation problems on the contact network from the perspective of force transmission. Here we report on solutions to the Maximum Flow Minimum Cost Problem for a weighted contact network where the weights assigned to the links of the contact network are varied according to their contact types. We found that those pathways through which the maximum flow of force is transmitted, in the direction of the maximum principal stress, at minimum cost - pass through the great majority of the force chains. Although the majority of the contacts in these pathways are elastic, the plastic contacts bear an undue influence on the minimum cost.

  4. A New Multi-Scale Flow Network Generation Scheme for Land Surface Models

    SciTech Connect

    Guo, Jianzhong; Liang, Xu; Leung, Lai-Yung R.

    2004-12-11

    This paper presents a new approach of generating flow networks for land surface models that are applied at different spatial scales based on a fine-resolution digital elevation model (DEM). Without losing computational efficiency, the new multi-scale approach has the advantages that (1) it allows surface and subsurface runoff in a land surface model grid to exit through multiple directions simultaneously rather than through only one of the eight directions as in many other methods; and (2) it introduces the concept of elastic coefficient to determine hydrological features, such as river slope and length for more accurate flow routing across different spatial scales. The new flow network generation scheme has been applied to the Blue River watershed in Oklahoma at different spatial resolutions used in conjunction with a kinematic wave routing method. Comparisons of the routed streamflows at the watershed outlet show clear advantages of the new approach over the widely used eight directions (D8) method, especially at coarser spatial resolution. This method is particularly suitable for macroscale hydrologic models and climate models where the accuracy of river routing can be severely limited by the coarse spatial resolution.

  5. A Comprehensive Flow, Heat and Mass Transport Uncertainty Quantification in Discrete Fracture Network Systems

    NASA Astrophysics Data System (ADS)

    Ezzedine, S. M.

    2010-12-01

    Fractures and fracture networks are the principle pathways for migration of water, heat and mass in enhanced geothermal systems, oil and gas reservoirs, CO2 leakage from saline aquifers, and radioactive and toxic industrial wastes from underground storage repositories. A major issue to overcome when characterizing a fractured reservoir is that of data limitation due to accessibility and affordability. Moreover, the ability to map discontinuities in the rock with available geological and geophysical tools tends to decrease particularly as the scale of the discontinuity goes down. Geological characterization data include measurements of fracture density, orientation, extent, and aperture, and are based on analysis of outcrops, borehole optical and acoustic televiewer logs, aerial photographs, and core samples among others. All of these measurements are taken at the field scale through a very sparse limited number of deep boreholes. These types of data are often reduced to probability distributions function for predictive modeling and simulation in a stochastic framework such as stochastic discrete fracture network. Stochastic discrete fracture network models enable, through Monte Carlo realizations and simulations, for probabilistic assessment of flow and transport phenomena that are not adequately captured using continuum models. Despite the fundamental uncertainties inherited within the probabilistic reduction of the sparse data collected, very little work has been conducted on quantifying uncertainty on the reduced probabilistic distribution functions. In the current study, using nested Monte Carlo simulations, we present the impact of parameter uncertainties of the distribution functions that characterize discrete fracture networks on the flow, heat and mass transport. Numerical results of first, second and third moments, normalized to a base case scenario, are presented and compared to theoretical results extended from percolation theory.

  6. Report of the European Myeloma Network on multiparametric flow cytometry in multiple myeloma and related disorders.

    PubMed

    Rawstron, Andy C; Orfao, Alberto; Beksac, Meral; Bezdickova, Ludmila; Brooimans, Rik A; Bumbea, Horia; Dalva, Klara; Fuhler, Gwenny; Gratama, Jan; Hose, Dirk; Kovarova, Lucie; Lioznov, Michael; Mateo, Gema; Morilla, Ricardo; Mylin, Anne K; Omedé, Paola; Pellat-Deceunynck, Catherine; Perez Andres, Martin; Petrucci, Maria; Ruggeri, Marina; Rymkiewicz, Grzegorz; Schmitz, Alexander; Schreder, Martin; Seynaeve, Carine; Spacek, Martin; de Tute, Ruth M; Van Valckenborgh, Els; Weston-Bell, Nicky; Owen, Roger G; San Miguel, Jesús F; Sonneveld, Pieter; Johnsen, Hans E

    2008-03-01

    The European Myeloma Network (EMN) organized two flow cytometry workshops. The first aimed to identify specific indications for flow cytometry in patients with monoclonal gammopathies, and consensus technical approaches through a questionnaire-based review of current practice in participating laboratories. The second aimed to resolve outstanding technical issues and develop a consensus approach to analysis of plasma cells. The primary clinical applications identified were: differential diagnosis of neoplastic plasma cell disorders from reactive plasmacytosis; identifying risk of progression in patients with MGUS and detecting minimal residual disease. A range of technical recommendations were identified, including: 1) CD38, CD138 and CD45 should all be included in at least one tube for plasma cell identification and enumeration. The primary gate should be based on CD38 vs. CD138 expression; 2) after treatment, clonality assessment is only likely to be informative when combined with immunophenotype to detect abnormal cells. Flow cytometry is suitable for demonstrating a stringent complete remission; 3) for detection of abnormal plasma cells, a minimal panel should include CD19 and CD56. A preferred panel would also include CD20, CD117, CD28 and CD27; 4) discrepancies between the percentage of plasma cells detected by flow cytometry and morphology are primarily related to sample quality and it is, therefore, important to determine that marrow elements are present in follow-up samples, particularly normal plasma cells in MRD negative cases. PMID:18268286

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

    PubMed

    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. PMID:20866710

  8. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

    Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

  9. Neural networks application to divergence-based passive ranging

    NASA Technical Reports Server (NTRS)

    Barniv, Yair

    1992-01-01

    The purpose of this report is to summarize the state of knowledge and outline the planned work in divergence-based/neural networks approach to the problem of passive ranging derived from optical flow. Work in this and closely related areas is reviewed in order to provide the necessary background for further developments. New ideas about devising a monocular passive-ranging system are then introduced. It is shown that image-plan divergence is independent of image-plan location with respect to the focus of expansion and of camera maneuvers because it directly measures the object's expansion which, in turn, is related to the time-to-collision. Thus, a divergence-based method has the potential of providing a reliable range complementing other monocular passive-ranging methods which encounter difficulties in image areas close to the focus of expansion. Image-plan divergence can be thought of as some spatial/temporal pattern. A neural network realization was chosen for this task because neural networks have generally performed well in various other pattern recognition applications. The main goal of this work is to teach a neural network to derive the divergence from the imagery.

  10. Schwarz-Based Algorithms for Compressible Flows

    NASA Technical Reports Server (NTRS)

    Tidriri, M. D.

    1996-01-01

    We investigate in this paper the application of Schwarz-based algorithms to compressible flows. First we study the combination of these methods with defect-correction procedures. We then study the effect on the Schwarz-based methods of replacing the explicit treatment of the boundary conditions by an implicit one. In the last part of this paper we study the combination of these methods with Newton-Krylov matrix-free methods. Numerical experiments that show the performance of our approaches are then presented.

  11. Timescale analysis of rule-based biochemical reaction networks

    PubMed Central

    Klinke, David J.; Finley, Stacey D.

    2012-01-01

    The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed upon reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of Interleukin-12 (IL-12) signaling in näive CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based upon the available data. The analysis correctly predicted that reactions associated with JAK2 and TYK2 binding to their corresponding receptor exist at a pseudo-equilibrium. In contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. PMID:21954150

  12. Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

    NASA Astrophysics Data System (ADS)

    Islam, Mujahidul

    from the vast network. A path tracing methodology is developed to identify the power lines that are vulnerable to an unscheduled flow effect in the sub-transmission network. It is much harder to aggregate power system network sensitivity information or data from measuring load flow physically than to simulate in software. System dynamics is one of the key factors to determine an appropriate dynamic control mechanism at an optimum network location. Once a model of deterministic but variable power generator is used, the simulation can be meaningful in justifying this claim. The method used to model the variable generator is named the two-components phase distortion model. The model was validated from the high resolution data collected from three pilot photovoltaic sites in Florida - two in the city of St. Petersburg and one in the city of Tampa. The high resolution data was correlated with weather radar closest to the sites during the design stage of the model. Technically the deterministic model cannot replicate a stochastic model which is more realistically applicable for solar isolation and involves a Markov chain. The author justified the proposition based on the fact that for analysis of the response functions of different systems, the excitation function should be common for comparison. Moreover, there could be many possible simulation scenarios but fewer worst cases. Almost all commercial systems are protected against potential faults and contingencies to a certain extent. Hence, the proposed model for worst case studies was designed within a reasonable limit. The simulation includes steady state and transient mode using multiple software modules including MatlabRTM, PSCADRTM and Paladin Design BaseRTM. It is shown that by identifying vulnerable or sensitive branches in the network, the control mechanisms can be coordinated reliably. In the long run this can save money by preventing unscheduled power flow in the network and eventually stabilizing the energy market.

  13. Calcium response in osteocytic networks under steady and oscillatory fluid flow.

    PubMed

    Lu, X Lucas; Huo, Bo; Park, Miri; Guo, X Edward

    2012-09-01

    The fluid flow in the lacunar-canalicular system of bone is an essential mechanical stimulation on the osteocyte networks. Due to the complexity of human physical activities, the fluid shear stress on osteocyte bodies and processes consists of both steady and oscillatory components. In this study, we investigated and compared the intracellular calcium ([Ca(2+)](i)) responses of osteocytic networks under steady and oscillatory fluid flows. An in vitro osteocytic network was built with MLO-Y4 osteocyte-like cells using micro-patterning techniques to simulate the in vivo orderly organization of osteocyte networks. Sinusoidal oscillating fluid flow or unidirectional steady flow was applied on the cell surface with 2Pa peak shear stress. It was found that the osteocytic networks were significantly more responsive to steady flow than to oscillatory flow. The osteocytes can release more calcium peaks with higher magnitudes at a faster speed under steady flow stimulation. The [Ca(2+)](i) signaling transients under the steady and oscillatory flows have significantly different spatiotemporal characters, but a similar responsive percentage of cells. Further signaling pathway studies using inhibitors showed that endoplasmic reticulum (ER) calcium store, extracellular calcium source, ATP, PGE(2) and NO related pathways play similar roles in the [Ca(2+)](i) signaling of osteocytes under either steady or oscillating flow. The spatiotemporal characteristics of [Ca(2+)](i) transients under oscillating fluid flow are affected more profoundly by pharmacological treatments than under the steady flow. Our findings support the hypothesis that the [Ca(2+)](i) responses of osteocytic networks are significantly dependent on the profiles of fluid flow. PMID:22750013

  14. Convolutional Neural Network Based dem Super Resolution

    NASA Astrophysics Data System (ADS)

    Chen, Zixuan; Wang, Xuewen; Xu, Zekai; Hou, Wenguang

    2016-06-01

    DEM super resolution is proposed in our previous publication to improve the resolution for a DEM on basis of some learning examples. Meanwhile, the nonlocal algorithm is introduced to deal with it and lots of experiments show that the strategy is feasible. In our publication, the learning examples are defined as the partial original DEM and their related high measurements due to this way can avoid the incompatibility between the data to be processed and the learning examples. To further extent the applications of this new strategy, the learning examples should be diverse and easy to obtain. Yet, it may cause the problem of incompatibility and unrobustness. To overcome it, we intend to investigate a convolutional neural network based method. The input of the convolutional neural network is a low resolution DEM and the output is expected to be its high resolution one. A three layers model will be adopted. The first layer is used to detect some features from the input, the second integrates the detected features to some compressed ones and the final step transforms the compressed features as a new DEM. According to this designed structure, some learning DEMs will be taken to train it. Specifically, the designed network will be optimized by minimizing the error of the output and its expected high resolution DEM. In practical applications, a testing DEM will be input to the convolutional neural network and a super resolution will be obtained. Many experiments show that the CNN based method can obtain better reconstructions than many classic interpolation methods.

  15. Dissolved Nutrient Retention Dynamics in River Networks: A Modeling Investigation of Transient Flow and Scale Effects

    SciTech Connect

    Ye, Sheng; Covino, Timothy P.; Sivapalan, Murugesu; Basu, Nandita; Li, Hongyi; Wang, Shaowen

    2012-06-30

    In this paper, we use a dynamic network flow model, coupled with a transient storage zone biogeochemical model, to simulate dissolved nutrient removal processes at the channel network scale. We have explored several scenarios in respect of the combination of rainfall variability, and the biological and geomorphic characteristics of the catchment, to understand the dominant controls on removal and delivery of dissolved nutrients (e.g., nitrate). These model-based theoretical analyses suggested that while nutrient removal efficiency is lower during flood events compared to during baseflow periods, flood events contribute significantly to bulk nutrient removal, whereas bulk removal during baseflow periods is less. This is due to the fact that nutrient supply is larger during flood events; this trend is even stronger in large rivers. However, the efficiency of removal during both periods decreases in larger rivers, however, due to (i) increasing flow velocities and thus decreasing residence time, and (ii) increasing flow depth, and thus decreasing nutrient uptake rates. Besides nutrient removal processes can be divided into two parts: in the main channel and in the hyporheic transient storage zone. When assessing their relative contributions the size of the transient storage zone is a dominant control, followed by uptake rates in the main channel and in the transient storage zone. Increasing size of the transient storage zone with downstream distance affects the relative contributions to nutrient removal of the water column and the transient storage zone, which also impacts the way nutrient removal rates scale with increasing size of rivers. Intra-annual hydrologic variability has a significant impact on removal rates at all scales: the more variable the streamflow is, compared to mean discharge, the less nutrient is removed in the channel network. A scale-independent first order uptake coefficient, ke, estimated from model simulations, is highly dependent on the

  16. Network-based modular latent structure analysis

    PubMed Central

    2014-01-01

    Background High-throughput expression data, such as gene expression and metabolomics data, exhibit modular structures. Groups of features in each module follow a latent factor model, while between modules, the latent factors are quasi-independent. Recovering the latent factors can shed light on the hidden regulation patterns of the expression. The difficulty in detecting such modules and recovering the latent factors lies in the high dimensionality of the data, and the lack of knowledge in module membership. Methods Here we describe a method based on community detection in the co-expression network. It consists of inference-based network construction, module detection, and interacting latent factor detection from modules. Results In simulations, the method outperformed projection-based modular latent factor discovery when the input signals were not Gaussian. We also demonstrate the method's value in real data analysis. Conclusions The new method nMLSA (network-based modular latent structure analysis) is effective in detecting latent structures, and is easy to extend to non-linear cases. The method is available as R code at http://web1.sph.emory.edu/users/tyu8/nMLSA/. PMID:25435002

  17. Nanoparticle-based lateral flow biosensors.

    PubMed

    Quesada-González, Daniel; Merkoçi, Arben

    2015-11-15

    Lateral flow biosensors (LFBs) are paper-based devices which permit the performance of low-cost and fast diagnostics with good robustness, specificity, sensitivity and low limits of detection. The use of nanoparticles (NPs) as labels play an important role in the design and fabrication of a lateral flow strip (LFS). The choice of NPs and the corresponding detection method directly affect the performance of these devices. This review discusses aspects related to the application of different nanomaterials (e.g. gold nanoparticles, carbon nanotubes, quantum dots, up-converting phosphor technologies, and latex beads, between others) in LFBs. Moreover, different detection methods (colorimetric, fluorescent, electrochemical, magnetic, etc.) and signal enhancement strategies (affording secondary reactions or modifying the architecture of the LFS) as well as the use of devices such as smartphones to mediate the response of LFSs will be analyzed. PMID:26043315

  18. Microfluidics based phantoms of superficial vascular network

    PubMed Central

    Luu, Long; Roman, Patrick A.; Mathews, Scott A.; Ramella-Roman, Jessica C.

    2012-01-01

    Several new bio-photonic techniques aim to measure flow in the human vasculature non-destructively. Some of these tools, such as laser speckle imaging or Doppler optical coherence tomography, are now reaching the clinical stage. Therefore appropriate calibration and validation techniques dedicated to these particular measurements are therefore of paramount importance. In this paper we introduce a fast prototyping technique based on laser micromachining for the fabrication of dynamic flow phantoms. Micro-channels smaller than 20 µm in width can be formed in a variety of materials such as epoxies, plastics, and household tape. Vasculature geometries can be easily and quickly modified to accommodate a particular experimental scenario. PMID:22741081

  19. Network-based recommendation algorithms: A review

    NASA Astrophysics Data System (ADS)

    Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš

    2016-06-01

    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

  20. Gas/liquid flow measurement using coriolis-based flow meters

    SciTech Connect

    Liu, K.T.; Nguyen, T.V.

    1991-07-09

    This patent describes a method of determining total mass flow rate and phase distribution of individual components in a flowing gas/liquid stream. It comprises flowing at least a first gas/liquid stream through a Coriolis-based flow meter, the first gas/liquid stream having a first known total mass flow rate and component phase distribution; obtaining a first apparent total mass flow rate output and a first apparent density output from the Coriolis- based mass flow meter; correlating the first known total mass flow rate and phase distribution with the first apparent mass flow rate output and the first apparent density output obtained from the Coriolis-based mass flow meter to determine a set of correlation equations; flowing a second gas/liquid stream through the Coriolis-based mass flow meter; obtaining a second apparent mass flow rate output and a second apparent density output from the Coriolis-based mass flow meter; calculating a total mass flow rate and a component phase distribution of the second gas/liquid stream based on the correlation equations and the second apparent mass flow rate output and the second apparent density output.

  1. Price-Based Information Routing in Complex Satellite Networks for

    NASA Astrophysics Data System (ADS)

    Hussein, I.; Su, J.; Wang, Y.; Wyglinski, A.

    Future space-based situational awareness and space surveillance systems are envisioned to include a large array of satellites that seek to cooperatively achieve full awareness over given space and terrestrial domains. Given the complexity of the communication network architecture of such a system, in this paper we build on the system architecture that was proposed by the presenting author in the 2008 AMOS conference and propose an efficient, adaptable and scalable price-based routing and bandwidth allocation algorithm for the generation, routing and delivery of surveillance information in distributed wireless satellite networks. Due to the potentially large deployments of these satellites, the access points employed in a centralized network control scheme would easily be overwhelmed due to lack of spectral bandwidth, synchronization issues, and multiple access coordination. Alternatively, decentralized schemes could facilitate the flow and transference of information between data gatherers and data collectors via mechanisms such as (multi-hop) routing, allocation of spectral bandwidths per relaying node, and coordination between adjacent nodes. Although there are numerous techniques and concepts focusing on the network operations, control, and management of sensor networks, existing solution approaches require the use of information for routing, allocation, and decision-making that may not be readily available to the satellites in a timely fashion. This is especially true in the literature on price-based routing, where the approach is almost always game theoretic or relies on optimization techniques. Instead of seeking such techniques, in this paper we present algorithms that will (1) be energy-aware, (2) be highly adaptable and responsive to demands and seek delivery of information to desired nodes despite the fact that the source and destination are not globally known, (3) be secure, (4) be efficient in allocating bandwidth, (5) be decentralized and allow for

  2. The effect of structural and rheological properties on blood flow distributions in capillary networks

    NASA Astrophysics Data System (ADS)

    Goldman, Daniel

    2001-11-01

    In various tissues microvascular structure, both geometric and topological, has been shown to be an important determinant of microcirculatory hemodynamics. In addition, blood rheology affects flow and hematocrit distributions in the microcirculation. Here we study steady-state hemodynamics in capillary networks modeled on the three-dimensional structure of the hamster cheek pouch retractor muscle. Capillary diameter is fixed while other structural properties are varied and an ensemble of similar random networks is generated for each parameter set. Using an experimentally derived two-phase continuum model for the flow of blood plasma and red cells, we investigate the effects of network size and topology on blood flow distributions and their variability. We also use typical capillary network structures to examine the importance of rheological effects under varying conditions. Our results indicate the relative importance of microvascular structure and blood rheology in determining the hemodynamic properties of capillary networks in striated muscle.

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

    PubMed

    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

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

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

    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.

  6. Finite element generation of arbitrary 3-D fracture networks for flow analysis in complicated discrete fracture networks

    NASA Astrophysics Data System (ADS)

    Zhang, Qi-Hua

    2015-10-01

    Finite element generation of complicated fracture networks is the core issue and source of technical difficulty in three-dimensional (3-D) discrete fracture network (DFN) flow models. Due to the randomness and uncertainty in the configuration of a DFN, the intersection lines (traces) are arbitrarily distributed in each face (fracture and other surfaces). Hence, subdivision of the fractures is an issue relating to subdivision of two-dimensional (2-D) domains with arbitrarily-distributed constraints. When the DFN configuration is very complicated, the well-known approaches (e.g. Voronoi Delaunay-based methods and advancing-front techniques) cannot operate properly. This paper proposes an algorithm to implement end-to-end connection between traces to subdivide 2-D domains into closed loops. The compositions of the vertices in the common edges between adjacent loops (which may belong to a single fracture or two connected fractures) are thus ensured to be topologically identical. The paper then proposes an approach for triangulating arbitrary loops which does not add any nodes to ensure consistency of the meshes at the common edges. In addition, several techniques relating to tolerance control and improving code robustness are discussed. Finally, the equivalent permeability of the rock mass is calculated for some very complicated DFNs (the DFN may contain 1272 fractures, 633 connected fractures, and 16,270 closed loops). The results are compared with other approaches to demonstrate the veracity and efficiency of the approach proposed in this paper.

  7. Network-Based Protein Biomarker Discovery Platforms

    PubMed Central

    Kim, Minhyung

    2016-01-01

    The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms. PMID:27103885

  8. Community detection based on network communicability

    NASA Astrophysics Data System (ADS)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  9. Flow Forecasting via Artificial Neural Networks - A Study for Input Variables conditioned on atmospheric circulation

    NASA Astrophysics Data System (ADS)

    Panagoulia, D.; Trichakis, I.; Tsekouras, G. J.

    2012-04-01

    The paper compares the performance of different structures of Artificial Neural Networks (ANNs) for flow forecasting of the next day in the Mesochora catchment in Northwestern Greece with respect to different input variables. The input variables are historical data of previous days, such as: (a) flows, (b) temperatures conditioned on atmospheric circulation, and (c) rainfalls conditioned on atmospheric circulation too. The training algorithm is the stochastic training back-propagation process with decreasing functions of learning rate and momentum term, for which a calibration process is conducted regarding the crucial parameters values, such as the number of neurons, the kind of activation functions, the initial values and time parameters of learning rate and momentum term etc. The performance of each structure has been evaluated by different criterions, such as (i) the root mean square error (RMSE), (ii) the correlation index (R), (iii) the mean absolute percentage error (MAPE), (iv) the mean percentage error (MPE), (v) the mean percentage error (ME), (vi) the percentage volume in errors (VE), (vii) the percentage error in peak (MF), (viii) the normalized mean bias error (NMBE), (ix) the normalized root mean bias error (NRMSE), (x) the Nash-Sutcliffe model efficiency coefficient (E), (xi) the modified Nash-Sutcliffe model efficiency coefficient (E1), (xii) the threshold statistics (TSp%) for a level of absolute relative error of p% (=1%, 2%, 5%, 25%, 50% and 100%). Here, the calibration process has been based on the voting analysis of the (i) to (xi) criterions. The time period of long-term falling flow (1972-77) is divided in two sets: one for ANN training with the 80% of data and the other for ANN parameters' calibration with the 20% data. The test set for the final verification of behaviour of ANN structures encompasses the following long-term time period with falling flow (1987-92). From the aforementioned analysis the nonlinear behaviour between forecasted

  10. Inferring network flows from incomplete information with application to natural gas flows. [State-to-state natural gas flows in 1974-77

    SciTech Connect

    Hooker, J.N.

    1980-02-01

    A method is detailed for estimating flows along arcs (edges or links) of a network, such as a transportation network, when the total outflow and total inflow at each node (vertex) are known. It proves the optimality of a greedy method of choosing flows for independent estimation so as to determine the other flows, and does so by exploiting an underlying matroid structure. The resulting problem is formulated both as a linear program and a multi-commodity flow problem, and sensitivity analysis is performed. The technique is applied to the estimation of US state-to-state natural gas flows in the years 1974 to 1977, and numerical results are presented; 1974 and 1975 results are checked against actual data. The potential application of the same technique to the estimation of disaggregate data (of any kind), when aggregate and some disaggregate data are known, is pointed out.

  11. Flow cytometry-based apoptosis detection

    PubMed Central

    Wlodkowic, Donald; Skommer, Joanna; Darzynkiewicz, Zbigniew

    2013-01-01

    An apoptosing cell demonstrates multitude of characteristic morphological and biochemical features, which vary depending on the stimuli and cell type. The gross majority of classical apoptotic hallmarks can be rapidly examined by flow and image cytometry. Cytometry thus became a technology of choice in diverse studies of cellular demise. A large variety of cytometric methods designed to identify apoptotic cells and probe mechanisms associated with this mode of cell demise have been developed during the past two decades. In the present chapter we outline a handful of commonly used methods that are based on the assessment of: mitochondrial transmembrane potential, activation of caspases, plasma membrane alterations and DNA fragmentation. PMID:19609746

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  13. Hardness Analysis and Empirical Studies of the Relations among Robustness, Topology and Flow in Dynamic Networks

    PubMed Central

    Zhou, Xing; Peng, Wei; Xu, Zhen; Yang, Bo

    2015-01-01

    Network robustness is the ability of a network to maintain performance after disruption, thus it is an important index for network designers to refer to. Every actual network has its own topology structure, flow magnitude (scale) and flow distribution. How the robustness relates to these factors still remains unresolved. To analyze the relations, we first established a robustness problem model, studied the hardness of a special case of the model, and generated a lot of representative network instances. We conducted experiments on these instances, deleting 5% to 50% edges on each instance and found that the robustness of a network has an approximate linearity to its structural entropy and flow entropy, when the correlation coefficient between the structure and flow is fixed. We also found that robustness is unlikely to have a relation to the flow scale and edge scale in our model. The empirical studies thus can provide a way of quickly estimating the robustness of real-world networks by using the regression coefficients we obtained during the experiments. We conducted computation on a real-world dataset and got favorable results, which exhibited the effectiveness of the estimation. PMID:26695517

  14. Dynamic schedule-based assignment model for urban rail transit network with capacity constraints.

    PubMed

    Han, Baoming; Zhou, Weiteng; Li, Dewei; Yin, Haodong

    2015-01-01

    There is a great need for estimation of passenger flow temporal and spatial distribution in urban rail transit network. The literature review indicates that passenger flow assignment models considering capacity constraints with overload delay factor for in-vehicle crowding are limited in schedule-based network. This paper proposes a stochastic user equilibrium model for solving the assignment problem in a schedule-based rail transit network with considering capacity constraint. As splitting the origin-destination demands into the developed schedule expanded network with time-space paths, the model transformed into a dynamic schedule-based assignment model. The stochastic user equilibrium conditions can be equivalent to the equilibrium passenger overload delay with crowding penalty in the transit network. The proposal model can estimate the path choice probability according to the equilibrium condition when passengers minimize their perceptive cost in a schedule-based network. Numerical example in Beijing urban rail transit (BURT) network is used to demonstrate the performance of the model and estimate the passenger flow temporal and spatial distribution more reasonably and dynamically with train capacity constraints. PMID:25918747

  15. A multiclass vehicular dynamic traffic flow model for main roads and dedicated lanes/roads of multimodal transport network

    SciTech Connect

    Sossoe, K.S.; Lebacque, J-P.

    2015-03-10

    We present in this paper a model of vehicular traffic flow for a multimodal transportation road network. We introduce the notion of class of vehicles to refer to vehicles of different transport modes. Our model describes the traffic on highways (which may contain several lanes) and network transit for pubic transportation. The model is drafted with Eulerian and Lagrangian coordinates and uses a Logit model to describe the traffic assignment of our multiclass vehicular flow description on shared roads. The paper also discusses traffic streams on dedicated lanes for specific class of vehicles with event-based traffic laws. An Euler-Lagrangian-remap scheme is introduced to numerically approximate the model’s flow equations.

  16. Application Guide for AFINCH (Analysis of Flows in Networks of Channels) Described by NHDPlus

    USGS Publications Warehouse

    Holtschlag, David J.

    2009-01-01

    AFINCH (Analysis of Flows in Networks of CHannels) is a computer application that can be used to generate a time series of monthly flows at stream segments (flowlines) and water yields for catchments defined in the National Hydrography Dataset Plus (NHDPlus) value-added attribute system. AFINCH provides a basis for integrating monthly flow data from streamgages, water-use data, monthly climatic data, and land-cover characteristics to estimate natural monthly water yields from catchments by user-defined regression equations. Images of monthly water yields for active streamgages are generated in AFINCH and provide a basis for detecting anomalies in water yields, which may be associated with undocumented flow diversions or augmentations. Water yields are multiplied by the drainage areas of the corresponding catchments to estimate monthly flows. Flows from catchments are accumulated downstream through the streamflow network described by the stream segments. For stream segments where streamgages are active, ratios of measured to accumulated flows are computed. These ratios are applied to upstream water yields to proportionally adjust estimated flows to match measured flows. Flow is conserved through the NHDPlus network. A time series of monthly flows can be generated for stream segments that average about 1-mile long, or monthly water yields from catchments that average about 1 square mile. Estimated monthly flows can be displayed within AFINCH, examined for nonstationarity, and tested for monotonic trends. Monthly flows also can be used to estimate flow-duration characteristics at stream segments. AFINCH generates output files of monthly flows and water yields that are compatible with ArcMap, a geographical information system analysis and display environment. Chloropleth maps of monthly water yield and flow can be generated and analyzed within ArcMap by joining NHDPlus data structures with AFINCH output. Matlab code for the AFINCH application is presented.

  17. Critical hydraulic gradient for nonlinear flow through rock fracture networks: The roles of aperture, surface roughness, and number of intersections

    NASA Astrophysics Data System (ADS)

    Liu, Richeng; Li, Bo; Jiang, Yujing

    2016-02-01

    Transition of fluid flow from the linear to the nonlinear regime has been confirmed in single rock fractures when the Reynolds number (Re) exceeds some critical values, yet the criterion for such a transition in discrete fracture networks (DFNs) has received little attention. This study conducted flow tests on crossed fracture models with a single intersection and performed numerical simulations on fluid flow through DFNs of various geometric characteristics. The roles of aperture, surface roughness, and number of intersections of fractures on the variation of the critical hydraulic gradient (Jc) for the onset of nonlinear flow through DFNs were systematically investigated. The results showed that the relationship between hydraulic gradient (J) and flow rate can be well quantified by Forchheimer's law; when J drops below Jc, it reduces to the widely used cubic law, by diminishing the nonlinear term. Larger apertures, rougher fracture surfaces, and a greater number of intersections in a DFN would result in the onset of nonlinear flow at a lower Jc. Mathematical expressions of Jc and the coefficients involved in Forchheimer's law were developed based on multi-variable regressions of simulation results, which can help to choose proper governing equations when solving problems associated with fluid flow in fracture networks.

  18. An Adaptive Loss-Aware Flow Control Scheme for Delay-Sensitive Applications in OBS Networks

    NASA Astrophysics Data System (ADS)

    Jeong, Hongkyu; Choi, Jungyul; Mo, Jeonghoon; Kang, Minho

    Optical Burst Switching (OBS) is one of the most promising switching technologies for next generation optical networks. As delay-sensitive applications such as Voice-over-IP (VoIP) have recently become popular, OBS networks should guarantee stringent Quality of Service (QoS) requirements for such applications. Thus, this paper proposes an Adaptive Loss-aware Flow Control (ALFC) scheme, which adaptively decides on the burst offset time based on loss-rate information delivered from core nodes for assigning a high priority to delay-sensitive application traffic. The proposed ALFC scheme also controls the upper-bounds of the factors inducing delay and jitter for guaranteeing the delay and jitter requirements of delay-sensitive application traffic. Moreover, a piggybacking method used in the proposed scheme accelerates the guarantee of the loss, delay, and jitter requirements because the response time for flow control can be extremely reduced up to a quarter of the Round Trip Time (RTT) on average while minimizing the signaling overhead. Simulation results show that our mechanism can guarantee a 10-3 loss-rate under any traffic load while offering satisfactory levels of delay and jitter for delay-sensitive applications.

  19. Summer base-flow recession curves for Iowa streams

    USGS Publications Warehouse

    Saboe, C.W.

    1966-01-01

    Base-flow recession. curves for the summer months (June through September) were developed in this study for gaging stations on interior Iowa streams having five or more years of record. The tabulated data enables the user, starting with a known base flow at a gage, to estimate base flows for up to 20 days in the future. Rainfall during the period o£ the forecast will require that a new estimate be made after the stream again reaches base flow.

  20. Global migration topology analysis and modeling of bilateral flow network 2006–2010

    NASA Astrophysics Data System (ADS)

    Porat, I.; Benguigui, L.

    2016-07-01

    Migration is one of the most dramatic and vast human processes in modern times. Migration is defined as people that leave their home and home-land and move to a new country. In this research we address the pattern of this massive human movement with the tools of network theory. The undirected global flow migration network (2006–2010) was identified as an exclusive disassortative network which combines two types of defined groups of large- and small-degree (D) countries with betweeness (Be) of Be∼D 3. This structure was modeled and simulated with synthetic networks of similar characteristics as the global flow migration network, and the results suggest that small-degree nodes have the topology of random networks, but the dominant part of the large-degree hubs controls this topology and shapes the network into an ultra-small world. This exclusive topology and the difference of the global flow migration network from scale-free and from Erdös-Rényi networks may be a result of two defined and different topologies of large- and small-degree countries.

  1. An anti-attack model based on complex network theory in P2P networks

    NASA Astrophysics Data System (ADS)

    Peng, Hao; Lu, Songnian; Zhao, Dandan; Zhang, Aixin; Li, Jianhua

    2012-04-01

    Complex network theory is a useful way to study many real systems. In this paper, an anti-attack model based on complex network theory is introduced. The mechanism of this model is based on a dynamic compensation process and a reverse percolation process in P2P networks. The main purpose of the paper is: (i) a dynamic compensation process can turn an attacked P2P network into a power-law (PL) network with exponential cutoff; (ii) a local healing process can restore the maximum degree of peers in an attacked P2P network to a normal level; (iii) a restoring process based on reverse percolation theory connects the fragmentary peers of an attacked P2P network together into a giant connected component. In this way, the model based on complex network theory can be effectively utilized for anti-attack and protection purposes in P2P networks.

  2. File-Based Data Flow in the CMS Filter Farm

    SciTech Connect

    Andre, J.M.; et al.

    2015-12-23

    During the LHC Long Shutdown 1, the CMS Data Acquisition system underwent a partial redesign to replace obsolete network equipment, use more homogeneous switching technologies, and prepare the ground for future upgrades of the detector front-ends. The software and hardware infrastructure to provide input, execute the High Level Trigger (HLT) algorithms and deal with output data transport and storage has also been redesigned to be completely file- based. This approach provides additional decoupling between the HLT algorithms and the input and output data flow. All the metadata needed for bookkeeping of the data flow and the HLT process lifetimes are also generated in the form of small “documents” using the JSON encoding, by either services in the flow of the HLT execution (for rates etc.) or watchdog processes. These “files” can remain memory-resident or be written to disk if they are to be used in another part of the system (e.g. for aggregation of output data). We discuss how this redesign improves the robustness and flexibility of the CMS DAQ and the performance of the system currently being commissioned for the LHC Run 2.

  3. File-based data flow in the CMS Filter Farm

    NASA Astrophysics Data System (ADS)

    Andre, J.-M.; Andronidis, A.; Bawej, T.; Behrens, U.; Branson, J.; Chaze, O.; Cittolin, S.; Darlea, G.-L.; Deldicque, C.; Dobson, M.; Dupont, A.; Erhan, S.; Gigi, D.; Glege, F.; Gomez-Ceballos, G.; Hegeman, J.; Holzner, A.; Jimenez-Estupiñán, R.; Masetti, L.; Meijers, F.; Meschi, E.; Mommsen, R. K.; Morovic, S.; Nunez-Barranco-Fernandez, C.; O'Dell, V.; Orsini, L.; Paus, C.; Petrucci, A.; Pieri, M.; Racz, A.; Roberts, P.; Sakulin, H.; Schwick, C.; Stieger, B.; Sumorok, K.; Veverka, J.; Zaza, S.; Zejdl, P.

    2015-12-01

    During the LHC Long Shutdown 1, the CMS Data Acquisition system underwent a partial redesign to replace obsolete network equipment, use more homogeneous switching technologies, and prepare the ground for future upgrades of the detector front-ends. The software and hardware infrastructure to provide input, execute the High Level Trigger (HLT) algorithms and deal with output data transport and storage has also been redesigned to be completely file- based. This approach provides additional decoupling between the HLT algorithms and the input and output data flow. All the metadata needed for bookkeeping of the data flow and the HLT process lifetimes are also generated in the form of small “documents” using the JSON encoding, by either services in the flow of the HLT execution (for rates etc.) or watchdog processes. These “files” can remain memory-resident or be written to disk if they are to be used in another part of the system (e.g. for aggregation of output data). We discuss how this redesign improves the robustness and flexibility of the CMS DAQ and the performance of the system currently being commissioned for the LHC Run 2.

  4. Compact Interconnection Networks Based on Quantum Dots

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Toomarian, Nikzad; Modarress, Katayoon; Spotnitz, Matthew

    2003-01-01

    Architectures that would exploit the distinct characteristics of quantum-dot cellular automata (QCA) have been proposed for digital communication networks that connect advanced digital computing circuits. In comparison with networks of wires in conventional very-large-scale integrated (VLSI) circuitry, the networks according to the proposed architectures would be more compact. The proposed architectures would make it possible to implement complex interconnection schemes that are required for some advanced parallel-computing algorithms and that are difficult (and in many cases impractical) to implement in VLSI circuitry. The difficulty of implementation in VLSI and the major potential advantage afforded by QCA were described previously in Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), NASA Tech Briefs, Vol. 25, No. 10 (October 2001), page 42. To recapitulate: Wherever two wires in a conventional VLSI circuit cross each other and are required not to be in electrical contact with each other, there must be a layer of electrical insulation between them. This, in turn, makes it necessary to resort to a noncoplanar and possibly a multilayer design, which can be complex, expensive, and even impractical. As a result, much of the cost of designing VLSI circuits is associated with minimization of data routing and assignment of layers to minimize crossing of wires. Heretofore, these considerations have impeded the development of VLSI circuitry to implement complex, advanced interconnection schemes. On the other hand, with suitable design and under suitable operating conditions, QCA-based signal paths can be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes. The proposed architectures require two advances in QCA-based circuitry beyond basic QCA-based binary

  5. Vertex centrality as a measure of information flow in Italian Corporate Board Networks

    NASA Astrophysics Data System (ADS)

    Grassi, Rosanna

    2010-06-01

    The aim of this article is to investigate the governance models of companies listed on the Italian Stock Exchange by using a network approach, which describes the interlinks between boards of directors. Following mainstream literature, I construct a weighted graph representing the listed companies (vertices) and their relationships (weighted edges), the Corporate Board Network; I then apply three different vertex centrality measures: degree, betweenness and flow betweenness. What emerges from the network construction and by applying the degree centrality is a structure with a large number of connections but not particularly dense, where the presence of a small number of highly connected nodes (hubs) is evident. Then I focus on betweenness and flow betweenness; indeed I expect that these centrality measures may give a representation of the intensity of the relationship between companies, capturing the volume of information flowing from one vertex to another. Finally, I investigate the possible scale-free structure of the network.

  6. Impact of Geological Characterization Uncertainties on Subsurface Flow & Transport Using a Stochastic Discrete Fracture Network Approach

    NASA Astrophysics Data System (ADS)

    Ezzedine, S. M.

    2009-12-01

    Fractures and fracture networks are the principal pathways for transport of water and contaminants in groundwater systems, enhanced geothermal system fluids, migration of oil and gas, carbon dioxide leakage from carbon sequestration sites, and of radioactive and toxic industrial wastes from underground storage repositories. A major issue to overcome when characterizing a fractured reservoir is that of data limitation due to accessibility and affordability. Moreover, the ability to map discontinuities in the rock with available geological and geophysical tools tends to decrease particularly as the scale of the discontinuity goes down. Geological characterization data include measurements of fracture density, orientation, extent, and aperture, and are based on analysis of outcrops, borehole optical and acoustic televiewer logs, aerial photographs, and core samples, among other techniques. All of these measurements are taken at the field scale through a very sparse limited number of deep boreholes. These types of data are often reduced to probability distribution functions for predictive modeling and simulation in a stochastic framework such as a stochastic discrete fracture network. Stochastic discrete fracture network models enable, through Monte Carlo realizations and simulations, probabilistic assessment of flow and transport phenomena that are not adequately captured using continuum models. Despite the fundamental uncertainties inherited within the probabilistic reduction of the sparse data collected, very little work has been conducted on quantifying uncertainty on the reduced probabilistic distribution functions. In the current study, using nested Monte Carlo simulations, we present the impact of parameter uncertainties of the distribution functions of fracture density, orientation, aperture and size on the flow and transport using topological measures such as fracture connectivity, physical characteristics such as effective hydraulic conductivity tensors, and

  7. Selective pumping in a network: insect-style microscale flow transport.

    PubMed

    Aboelkassem, Yasser; Staples, Anne E

    2013-06-01

    A new paradigm for selective pumping of fluids in a complex network of channels in the microscale flow regime is presented. The model is inspired by internal flow distributions produced by the rhythmic wall contractions observed in many insect tracheal networks. The approach presented here is a natural extension of previous two-dimensional modeling of insect-inspired microscale flow transport in a single channel, and aims to manipulate fluids efficiently in microscale networks without the use of any mechanical valves. This selective pumping approach enables fluids to be transported, controlled and precisely directed into a specific branch in a network while avoiding other possible routes. In order to present a quantitative analysis of the selective pumping approach presented here, the velocity and pressure fields and the time-averaged net flow that are induced by prescribed wall contractions are calculated numerically using the method of fundamental solutions. More specifically, the Stokeslets-meshfree method is used in this study to solve the Stokes equations that govern the flow motions in a network with moving wall contractions. The results presented here might help in understanding some features of the insect respiratory system function and guide efforts to fabricate novel microfluidic devices for flow transport and mixing, and targeted drug delivery applications. PMID:23538838

  8. Detection of the dominant direction of information flow and feedback links in densely interconnected regulatory networks

    PubMed Central

    Ispolatov, Iaroslav; Maslov, Sergei

    2008-01-01

    Background Finding the dominant direction of flow of information in densely interconnected regulatory or signaling networks is required in many applications in computational biology and neuroscience. This is achieved by first identifying and removing links which close up feedback loops in the original network and hierarchically arranging nodes in the remaining network. In mathematical language this corresponds to a problem of making a graph acyclic by removing as few links as possible and thus altering the original graph in the least possible way. The exact solution of this problem requires enumeration of all cycles and combinations of removed links, which, as an NP-hard problem, is computationally prohibitive even for modest-size networks. Results We introduce and compare two approximate numerical algorithms for solving this problem: the probabilistic one based on a simulated annealing of the hierarchical layout of the network which minimizes the number of "backward" links going from lower to higher hierarchical levels, and the deterministic, "greedy" algorithm that sequentially cuts the links that participate in the largest number of feedback cycles. We find that the annealing algorithm outperforms the deterministic one in terms of speed, memory requirement, and the actual number of removed links. To further improve a visual perception of the layout produced by the annealing algorithm, we perform an additional minimization of the length of hierarchical links while keeping the number of anti-hierarchical links at their minimum. The annealing algorithm is then tested on several examples of regulatory and signaling networks/pathways operating in human cells. Conclusion The proposed annealing algorithm is powerful enough to performs often optimal layouts of protein networks in whole organisms, consisting of around ~104 nodes and ~105 links, while the applicability of the greedy algorithm is limited to individual pathways with ~100 vertices. The considered examples

  9. Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management.

    PubMed

    Kreakie, B J; Hychka, K C; Belaire, J A; Minor, E; Walker, H A

    2016-02-01

    Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution's web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google's "relatedness" operator that identifies pages "similar" to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago (n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined. PMID:26503113

  10. Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management

    NASA Astrophysics Data System (ADS)

    Kreakie, B. J.; Hychka, K. C.; Belaire, J. A.; Minor, E.; Walker, H. A.

    2016-02-01

    Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing internet-based social networks, and use an existing traditional (survey-based) case study to illustrate in a familiar context the deviations in methods and results. Internet-based approaches to SNA offer a means to overcome institutional hurdles to conducting survey-based SNA, provide unique insight into an institution's web presences, allow for easy snowballing (iterative process that incorporates new nodes in the network), and afford monitoring of social networks through time. The internet-based approaches differ in link definition: hyperlink is based on links on a website that redirect to a different website and relatedness links are based on a Google's "relatedness" operator that identifies pages "similar" to a URL. All networks were initiated with the same start nodes [members of a conservation alliance for the Calumet region around Chicago ( n = 130)], but the resulting networks vary drastically from one another. Interpretation of the resulting networks is highly contingent upon how the links were defined.

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

    SciTech Connect

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

    2012-07-01

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

  12. Curation-Based Network Marketing: Strategies for Network Growth and Electronic Word-of-Mouth Diffusion

    ERIC Educational Resources Information Center

    Church, Earnie Mitchell, Jr.

    2013-01-01

    In the last couple of years, a new aspect of online social networking has emerged, in which the strength of social network connections is based not on social ties but mutually shared interests. This dissertation studies these "curation-based" online social networks (CBN) and their suitability for the diffusion of electronic word-of-mouth…

  13. Rapid flow-based peptide synthesis.

    PubMed

    Simon, Mark D; Heider, Patrick L; Adamo, Andrea; Vinogradov, Alexander A; Mong, Surin K; Li, Xiyuan; Berger, Tatiana; Policarpo, Rocco L; Zhang, Chi; Zou, Yekui; Liao, Xiaoli; Spokoyny, Alexander M; Jensen, Klavs F; Pentelute, Bradley L

    2014-03-21

    A flow-based solid-phase peptide synthesis methodology that enables the incorporation of an amino acid residue every 1.8 min under automatic control or every 3 min under manual control is described. This is accomplished by passing a stream of reagent through a heat exchanger into a low volume, low backpressure reaction vessel, and through a UV detector. These features enable continuous delivery of heated solvents and reagents to the solid support at high flow rate, thereby maintaining maximal concentration of reagents in the reaction vessel, quickly exchanging reagents, and eliminating the need to rapidly heat reagents after they have been added to the vessel. The UV detector enables continuous monitoring of the process. To demonstrate the broad applicability and reliability of this method, it was employed in the total synthesis of a small protein, as well as dozens of peptides. The quality of the material obtained with this method is comparable to that for traditional batch methods, and, in all cases, the desired material was readily purifiable by RP-HPLC. The application of this method to the synthesis of the 113-residue Bacillus amyloliquefaciens RNase and the 130-residue DARPin pE59 is described in the accompanying manuscript. PMID:24616230

  14. Effect of Fluid Friction on Interstitial Fluid Flow Coupled with Blood Flow through Solid Tumor Microvascular Network

    PubMed Central

    Sefidgar, Mostafa; Soltani, M.; Bazmara, Hossein

    2015-01-01

    A solid tumor is investigated as porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multiscale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. The mathematical method involves processes such as blood flow through vessels and solute and fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model predicts. PMID:25960764

  15. Tracing the Flow of Perceptual Features in an Algorithmic Brain Network

    PubMed Central

    Ince, Robin A. A.; van Rijsbergen, Nicola J.; Thut, Gregor; Rousselet, Guillaume A.; Gross, Joachim; Panzeri, Stefano; Schyns, Philippe G.

    2015-01-01

    The model of the brain as an information processing machine is a profound hypothesis in which neuroscience, psychology and theory of computation are now deeply rooted. Modern neuroscience aims to model the brain as a network of densely interconnected functional nodes. However, to model the dynamic information processing mechanisms of perception and cognition, it is imperative to understand brain networks at an algorithmic level–i.e. as the information flow that network nodes code and communicate. Here, using innovative methods (Directed Feature Information), we reconstructed examples of possible algorithmic brain networks that code and communicate the specific features underlying two distinct perceptions of the same ambiguous picture. In each observer, we identified a network architecture comprising one occipito-temporal hub where the features underlying both perceptual decisions dynamically converge. Our focus on detailed information flow represents an important step towards a new brain algorithmics to model the mechanisms of perception and cognition. PMID:26635299

  16. Optimal halftoning for network-based imaging

    NASA Astrophysics Data System (ADS)

    Ostromoukhov, Victor

    2000-12-01

    In this contribution, we introduce a multiple depth progressive representation for network-based still and moving images. A simple quantization algorithm associated with this representation provides optimal image quality. By optimum, we mean the best possible visual quality for a given value of information under real life constraints such as physical, psychological , or legal constraints. A special variant of the algorithm, multi-depth coherent error diffusion, addresses a specific problem of temporal coherence between frames in moving images. The output produced with our algorithm is visually pleasant because its Fourier spectrum is close to the 'blue noise'.

  17. Email user ranking based on email networks

    NASA Astrophysics Data System (ADS)

    Tran, Quang Anh; Vu, Minh Tuan; Frater, Michael; Jiang, Frank

    2012-09-01

    In this paper, four spam-filtering approaches based on the mail networks: Clustering, Extended Clustering Coefficient, PageRank Algorithm and Weighted PageRank Algorithm are analyzed. We also propose a couple of fully worked-out datasets against which the experimental comparisons with the respect to the accuracy of email user ranking and spam filtering are conducted. The results indicate that PageRank algorithm and Extended Clustering Coefficient approaches are better than others. The rate of true detection is over 99.5% while the failed alarm remains below 0.5%.

  18. A microfluidic device for simultaneous measurement of viscosity and flow rate of blood in a complex fluidic network

    PubMed Central

    Jun Kang, Yang; Yeom, Eunseop; Lee, Sang-Joon

    2013-01-01

    Blood viscosity has been considered as one of important biophysical parameters for effectively monitoring variations in physiological and pathological conditions of circulatory disorders. Standard previous methods make it difficult to evaluate variations of blood viscosity under cardiopulmonary bypass procedures or hemodialysis. In this study, we proposed a unique microfluidic device for simultaneously measuring viscosity and flow rate of whole blood circulating in a complex fluidic network including a rat, a reservoir, a pinch valve, and a peristaltic pump. To demonstrate the proposed method, a twin-shaped microfluidic device, which is composed of two half-circular chambers, two side channels with multiple indicating channels, and one bridge channel, was carefully designed. Based on the microfluidic device, three sequential flow controls were applied to identify viscosity and flow rate of blood, with label-free and sensorless detection. The half-circular chamber was employed to achieve mechanical membrane compliance for flow stabilization in the microfluidic device. To quantify the effect of flow stabilization on flow fluctuations, a formula of pulsation index (PI) was analytically derived using a discrete fluidic circuit model. Using the PI formula, the time constant contributed by the half-circular chamber is estimated to be 8 s. Furthermore, flow fluctuations resulting from the peristaltic pumps are completely removed, especially under periodic flow conditions within short periods (T < 10 s). For performance demonstrations, the proposed method was applied to evaluate blood viscosity with respect to varying flow rate conditions [(a) known blood flow rate via a syringe pump, (b) unknown blood flow rate via a peristaltic pump]. As a result, the flow rate and viscosity of blood can be simultaneously measured with satisfactory accuracy. In addition, the proposed method was successfully applied to identify the viscosity of rat blood, which circulates in a

  19. Neural network modeling for regional hazard assessment of debris flow in Lake Qionghai Watershed, China

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Guo, H. C.; Zou, R.; Wang, L. J.

    2006-04-01

    This paper presents a neural network (NN) based model to assess the regional hazard degree of debris flows in Lake Qionghai Watershed, China. The NN model was used as an alternative for the more conventional linear model MFCAM (multi-factor composite assessment model) in order to effectively handle the nonlinearity and uncertainty inherent in the debris flow hazard analysis. The NN model was configured using a three layer structure with eight input nodes and one output node, and the number of nodes in the hidden layer was determined through an iterative process of varying the number of nodes in the hidden layer until an optimal performance was achieved. The eight variables used to represent the eight input nodes include density of debris flow gully, degree of weathering of rocks, active fault density, area percentage of slope land greater than 25° of the total land (APL25), frequency of flooding hazards, average covariance of monthly precipitation by 10 years (ACMP10), average days with rainfall >25 mm by 10 years (25D10Y), and percentage of cultivated land with slope land greater than 25° of the total cultivated land (PCL25). The output node represents the hazard-degree ranks (HDR). The model was trained with the 35 sets of data obtained from previous researches reported in literatures, and an explicit uncertainty analysis was undertaken to address the uncertainty in model training and prediction. Before the NN model is extrapolated to Lake Qionghai Watershed, a validation case, different from the above data, is conducted. In addition, the performances of the NN model and the MFCAM were compared. The NN model predicted that the HDRs of the five sub-watersheds in the Lake Qionghai Watershed were IV, IV, III, III, and IV V, indicating that the study area covers normal hazard and severe hazard areas. Based on the NN model results, debris flow management and economic development strategies in the study are proposed for each sub-watershed.

  20. Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

    PubMed

    Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo

    2014-04-21

    Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment. PMID:24787842

  1. Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

    NASA Astrophysics Data System (ADS)

    Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming

    With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.

  2. Poisson type models and descriptive statistics of computer network information flows

    SciTech Connect

    Downing, D.; Fedorov, V.; Dunigan, T.; Batsell, S.

    1997-08-01

    Many contemporary publications on network traffic gravitate to ideas of self-similarity and long-range dependence. The corresponding elegant and parsimonious mathematical techniques proved to be efficient for the description of a wide class of aggregated processes. Sharing the enthusiasm about the above ideas the authors also believe that whenever it is possible any problem must be considered at the most basic level in an attempt to understand the driving forces of the processes under analysis. Consequently the authors try to show that some behavioral patterns of descriptive statistics which are typical for long-memory processes (a particular case of long-range dependence) can also be explained in the framework of the traditional Poisson process paradigm. Applying the concepts of inhomogeneity, compoundness and double stochasticity they propose a simple and intuitively transparent approach of explaining the expected shape of the observed histograms of counts and the expected behavior of the sample covariance functions. Matching the images of these two descriptive statistics allows them to infer the presence of trends or double stochasticity in analyzed time series. They considered only statistics which are based on counts. A similar approach may be applied to waiting or inter-arrival time sequences and will be discussed in other publications. They hope that combining the reported results with the statistical methods based on aggregated models may lead to computationally affordable on-line techniques of compact and visualized data analysis of network flows.

  3. Network model of bilateral power markets based on complex networks

    NASA Astrophysics Data System (ADS)

    Wu, Yang; Liu, Junyong; Li, Furong; Yan, Zhanxin; Zhang, Li

    2014-06-01

    The bilateral power transaction (BPT) mode becomes a typical market organization with the restructuring of electric power industry, the proper model which could capture its characteristics is in urgent need. However, the model is lacking because of this market organization's complexity. As a promising approach to modeling complex systems, complex networks could provide a sound theoretical framework for developing proper simulation model. In this paper, a complex network model of the BPT market is proposed. In this model, price advantage mechanism is a precondition. Unlike other general commodity transactions, both of the financial layer and the physical layer are considered in the model. Through simulation analysis, the feasibility and validity of the model are verified. At same time, some typical statistical features of BPT network are identified. Namely, the degree distribution follows the power law, the clustering coefficient is low and the average path length is a bit long. Moreover, the topological stability of the BPT network is tested. The results show that the network displays a topological robustness to random market member's failures while it is fragile against deliberate attacks, and the network could resist cascading failure to some extent. These features are helpful for making decisions and risk management in BPT markets.

  4. The General-Use Nodal Network Solver (GUNNS) Modeling Package for Space Vehicle Flow System Simulation

    NASA Technical Reports Server (NTRS)

    Harvey, Jason; Moore, Michael

    2013-01-01

    The General-Use Nodal Network Solver (GUNNS) is a modeling software package that combines nodal analysis and the hydraulic-electric analogy to simulate fluid, electrical, and thermal flow systems. GUNNS is developed by L-3 Communications under the TS21 (Training Systems for the 21st Century) project for NASA Johnson Space Center (JSC), primarily for use in space vehicle training simulators at JSC. It has sufficient compactness and fidelity to model the fluid, electrical, and thermal aspects of space vehicles in real-time simulations running on commodity workstations, for vehicle crew and flight controller training. It has a reusable and flexible component and system design, and a Graphical User Interface (GUI), providing capability for rapid GUI-based simulator development, ease of maintenance, and associated cost savings. GUNNS is optimized for NASA's Trick simulation environment, but can be run independently of Trick.

  5. Fast surface design based on sketched networks

    NASA Astrophysics Data System (ADS)

    van Dijk, Casper G. C.

    1992-11-01

    Computer aided design of freeformed surfaces is strongly biased towards input and optimization of surfaces. Input modules are based on digitizing drawings or placing and manipulating spline control vertices. Design, especially during the idea generation (or conceptual) design phase, is poorly supported. We present a system based on direct manipulation of shaded images of the surfaces. The designer sketches profiles on a tablet. The profiles are positioned in object space with a spaceball (6D joystick). A network of crossing curves is built interactively. The system constructs patches over this network in realtime. The designer can correct a profile by sketching. The affected surfaces are updated immediately. Patches are defined by the curves and estimated cross-boundary derivatives. They connect with G1 continuity. Our prototype surface modeler avoids the need for exact dimensions and precise coordinates, as seen in traditional systems. Instead, it supports fast, intuitive generation and evaluation of surfaces. We discuss a comparison with other systems regarding the time needed to model shapes, and some opinions of professional industrial designers.

  6. UPM: unified policy-based network management

    NASA Astrophysics Data System (ADS)

    Law, Eddie; Saxena, Achint

    2001-07-01

    Besides providing network management to the Internet, it has become essential to offer different Quality of Service (QoS) to users. Policy-based management provides control on network routers to achieve this goal. The Internet Engineering Task Force (IETF) has proposed a two-tier architecture whose implementation is based on the Common Open Policy Service (COPS) protocol and Lightweight Directory Access Protocol (LDAP). However, there are several limitations to this design such as scalability and cross-vendor hardware compatibility. To address these issues, we present a functionally enhanced multi-tier policy management architecture design in this paper. Several extensions are introduced thereby adding flexibility and scalability. In particular, an intermediate entity between the policy server and policy rule database called the Policy Enforcement Agent (PEA) is introduced. By keeping internal data in a common format, using a standard protocol, and by interpreting and translating request and decision messages from multi-vendor hardware, this agent allows a dynamic Unified Information Model throughout the architecture. We have tailor-made this unique information system to save policy rules in the directory server and allow executions of policy rules with dynamic addition of new equipment during run-time.

  7. Paper-based synthetic gene networks.

    PubMed

    Pardee, Keith; Green, Alexander A; Ferrante, Tom; Cameron, D Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J

    2014-11-01

    Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides an alternate, versatile venue for synthetic biologists to operate and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze dried onto paper, enabling the inexpensive, sterile, and abiotic distribution of synthetic-biology-based technologies for the clinic, global health, industry, research, and education. For field use, we create circuits with colorimetric outputs for detection by eye and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small-molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167

  8. Paper-based Synthetic Gene Networks

    PubMed Central

    Pardee, Keith; Green, Alexander A.; Ferrante, Tom; Cameron, D. Ewen; DaleyKeyser, Ajay; Yin, Peng; Collins, James J.

    2014-01-01

    Synthetic gene networks have wide-ranging uses in reprogramming and rewiring organisms. To date, there has not been a way to harness the vast potential of these networks beyond the constraints of a laboratory or in vivo environment. Here, we present an in vitro paper-based platform that provides a new venue for synthetic biologists to operate, and a much-needed medium for the safe deployment of engineered gene circuits beyond the lab. Commercially available cell-free systems are freeze-dried onto paper, enabling the inexpensive, sterile and abiotic distribution of synthetic biology-based technologies for the clinic, global health, industry, research and education. For field use, we create circuits with colorimetric outputs for detection by eye, and fabricate a low-cost, electronic optical interface. We demonstrate this technology with small molecule and RNA actuation of genetic switches, rapid prototyping of complex gene circuits, and programmable in vitro diagnostics, including glucose sensors and strain-specific Ebola virus sensors. PMID:25417167

  9. Contraction driven flow in the extended vein networks of Physarum polycephalum

    NASA Astrophysics Data System (ADS)

    Alim, Karen; Amselem, Gabriel; Peaudecerf, Francois; Pringle, Anne; Brenner, Michael P.

    2011-11-01

    The true slime mold Physarum polycephalum is a basal organism that forms an extended network of veins to forage for food. P. polycephalum is renown for its adaptive changes of vein structure and morphology in response to food sources. These rearrangements presumably occur to establish an efficient transport and mixing of resources throughout the networks thus presenting a prototype to design transport networks under the constraints of laminar flow. The physical flows of cytoplasmic fluid enclosed by the veins exhibit an oscillatory flow termed ``shuttle streaming.'' The flow exceed by far the volume required for growth at the margins suggesting that the additional energy cost for generating the flow is spent for efficient and/or targeted redistribution of resources. We show that the viscous shuttle flow is driven by the radial contractions of the veins that accompany the streaming. We present a model for the fluid flow and resource dispersion arising due to radial contractions. The transport and mixing properties of the flow are discussed.

  10. The Blow Up Method for Brakke Flows: Networks Near Triple Junctions

    NASA Astrophysics Data System (ADS)

    Tonegawa, Yoshihiro; Wickramasekera, Neshan

    2016-09-01

    We introduce a parabolic blow-up method to study the asymptotic behavior of a Brakke flow of planar networks (that is a 1-dimensional Brakke flow in a two dimensional region) weakly close in a space-time region to a static multiplicity 1 triple junction J. We show that such a network flow is regular in a smaller space-time region, in the sense that it consists of three curves coming smoothly together at a single point at 120{^{circ}} angles, staying smoothly close to J and moving smoothly. Using this result and White's stratification theorem, we deduce that whenever a Brakke flow of networks in a space-time region {{mathcal {R}}} has no static tangent flow with density {{≥q}2}, there exists a closed subset {{Σ subset {mathcal {R}}}} of parabolic Hausdorff dimension at most 1 such that the flow is classical in {{mathcal {R}}backslashΣ}, that is near every point in {{mathcal {R}}backslashΣ}, the flow, if non-empty, consists of either an embedded curve moving smoothly or three embedded curves meeting smoothly at a single point at 120{^{circ}} angles and moving smoothly. In particular, such a flow is classical at all times except for a closed set of times of ordinary Hausdorff dimension at most {1/2}.

  11. Mesh deformation based on artificial neural networks

    NASA Astrophysics Data System (ADS)

    Stadler, Domen; Kosel, Franc; Čelič, Damjan; Lipej, Andrej

    2011-09-01

    In the article a new mesh deformation algorithm based on artificial neural networks is introduced. This method is a point-to-point method, meaning that it does not use connectivity information for calculation of the mesh deformation. Two already known point-to-point methods, based on interpolation techniques, are also presented. In contrast to the two known interpolation methods, the new method does not require a summation over all boundary nodes for one displacement calculation. The consequence of this fact is a shorter computational time of mesh deformation, which is proven by different deformation tests. The quality of the deformed meshes with all three deformation methods was also compared. Finally, the generated and the deformed three-dimensional meshes were used in the computational fluid dynamics numerical analysis of a Francis water turbine. A comparison of the analysis results was made to prove the applicability of the new method in every day computation.

  12. Control theoretical analysis of a window-based flow control mechanism for TCP connections with different propagation delays

    NASA Astrophysics Data System (ADS)

    Ohsaki, Hiroyuki; Takagaki, Keiichi; Murata, Masayuki

    2001-07-01

    A feedback-based congestion control mechanism is essential to realize an efficient best-effort service in high-speed networks. A window-based flow control mechanism called TCP (Transmission Control Protocol), which a sort of feedback-based congestion control mechanism, has been widely used in the current Internet. Recently-proposed TCP Vegas is another version of TCP mechanism, and can achieve better performance than the current TCP Reno. In our previous works, we have analyzed stability of a window-based flow control mechanism based on TCP Vegas in both homogeneous and heterogeneous networks. In this paper, using our analytic results, we invesitigate how the dynamics of the window-based flow control mechanism based on TCP Vegas is affected by the difference in propagation delays of TCP connections. We also investigate the effect of various system parameters on transient performance of the window-based flow control mechanism.

  13. Intelligent Sensing and Classification in DSR-Based Ad Hoc Networks

    NASA Astrophysics Data System (ADS)

    Dempsey, Tae; Sahin, Gokhan; Morton, Yu T. (Jade

    Wireless ad hoc networks have fundamentally altered today's battlefield, with applications ranging from unmanned air vehicles to randomly deployed sensor networks. Security and vulnerabilities in wireless ad hoc networks have been considered at different layers, and many attack strategies have been proposed, including denial of service (DoS) through the intelligent jamming of the most critical packet types of flows in a network. This paper investigates the effectiveness of intelligent jamming in wireless ad hoc networks using the Dynamic Source Routing (DSR) and TCP protocols and introduces an intelligent classifier to facilitate the jamming of such networks. Assuming encrypted packet headers and contents, our classifier is based solely on the observable characteristics of size, inter-arrival timing, and direction and classifies packets with up to 99.4% accuracy in our experiments.

  14. The International Postal Network and Other Global Flows as Proxies for National Wellbeing.

    PubMed

    Hristova, Desislava; Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

    2016-01-01

    The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals. PMID:27248142

  15. The International Postal Network and Other Global Flows as Proxies for National Wellbeing

    PubMed Central

    Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

    2016-01-01

    The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals. PMID:27248142

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

    PubMed

    Tupikina, Liubov; Molkenthin, Nora; López, Cristóbal; Hernández-García, Emilio; Marwan, Norbert; Kurths, Jürgen

    2016-01-01

    Complex network theory provides an elegant and powerful framework to statistically investigate different types of systems such as society, brain or the structure of local and long-range dynamical interrelationships in the climate system. Network links in climate networks typically imply information, mass or energy exchange. However, the specific connection between oceanic or atmospheric flows and the climate network's structure is still unclear. We propose a theoretical approach for verifying relations between the correlation matrix and the climate network measures, generalizing previous studies and overcoming the restriction to stationary flows. Our methods are developed for correlations of a scalar quantity (temperature, for example) which satisfies an advection-diffusion dynamics in the presence of forcing and dissipation. Our approach reveals that correlation networks are not sensitive to steady sources and sinks and the profound impact of the signal decay rate on the network topology. We illustrate our results with calculations of degree and clustering for a meandering flow resembling a geophysical ocean jet. PMID:27128846

  17. Rumor diffusion in an interests-based dynamic social network.

    PubMed

    Tang, Mingsheng; Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

    2013-01-01

    To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency. PMID:24453911

  18. Rumor Diffusion in an Interests-Based Dynamic Social Network

    PubMed Central

    Mao, Xinjun; Guessoum, Zahia; Zhou, Huiping

    2013-01-01

    To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1) positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2) with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3) a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4) a network with a smaller clustering coefficient has a larger efficiency. PMID:24453911

  19. Three Phase Probabilistic Load Flow in Radial Distribution Networks

    SciTech Connect

    Melhorn, Alexander C; Dimitrovski, Aleksandar D; Tomsovic, Kevin L

    2012-01-01

    Probabilistic load flow is a helpful tool in accounting for inconsistent or unknown loads and generation. This is especially true with the push for renewable generation and demand response. This paper proposes an improved version of the probabilistic load flow solution for balanced distribution systems and takes the next step by applying it to unbalanced three phase systems. It is validated by comparing the solutions to that obtained by Monte Carlo simulation. The proposed method provides an accurate and practical way for finding the solution to the stochastic problems occurring in power distribution system analysis today.

  20. Evolutionary systemic risk: Fisher information flow metric in financial network dynamics

    NASA Astrophysics Data System (ADS)

    Khashanah, Khaldoun; Yang, Hanchao

    2016-03-01

    Recently the topic of financial network dynamics has gained renewed interest from researchers in the field of empirical systemic risk measurements. We refer to this type of network analysis as information flow networks analysis (IFNA). This paper proposes a new method that applies Fisher information metric to the evolutionary dynamics of financial networks using IFNA. Our paper is the first to apply the Fisher information metric to a set of financial time series. We introduce Evolution Index (EI) as a measure of systemic risk in financial networks. It is shown, for concrete networks with actual data of several stock markets, that the EI can be implemented as a measure of fitness of the stock market and as a leading indicator of systemic risk.

  1. The influence of underlying topography on lava channel networks and flow behavior (Invited)

    NASA Astrophysics Data System (ADS)

    Dietterich, H. R.; Cashman, K. V.; Rust, A.

    2013-12-01

    New high resolution mapping of historical lava flows in Hawai';i reveals complex topographically controlled channel networks. Network morphologies range from distributary systems dominated by branching around local obstacles, to tributary systems constricted by topographic confinement. Because channel networks govern the distribution of lava within the flow, they can dramatically alter the effective volumetric flux, which affects both flow length and advance rate. The influence of flow bifurcations is evidenced by (1) channelized flows from Pu';u ';O';o episodes 1-20 at Kilauea Volcano, where flow front velocities decreased by approximately half each time a flow split, and (2) the length of confined flows, such as the Mauna Loa 1859 flow, which traveled twice as far as the distributary Mauna Loa 1984 flow, despite similar effusion rates and durations. To study the underlying controls on flow bifurcations, we have undertaken a series of analogue experiments with golden syrup (a Newtonian fluid) to better understand the physics of obstacle interaction and its influence on flow behavior and morphology. Controlling the effusion rate and surface slope, we extrude flows onto a surface with a cylindrical or V-shaped obstacle of variable angle. When the flow is sufficiently fast, a stationary wave forms upslope of the obstacle; if the stationary wave is sufficiently high, the flow can overtop, rather than split around, the obstacle. The stationary wave height increases with flow velocity and with the effective obstacle width. Evidence for stationary waves in Hawaiian lava flows comes from both photographs of active flows and waveforms frozen into solidified flows. We have also performed a preliminary set of similar experiments with molten basalt to identify the effect of cooling and investigate flow merging. In these experiments, a stationary wave develops upslope of the obstacle, which allows the surface to cool and thicken. After splitting, the syrup experiments show

  2. Influence of fracture scale heterogeneity on the flow properties of 3D Discrete Fracture Networks (DFN)

    NASA Astrophysics Data System (ADS)

    Meheust, Y.; De Dreuzy, J.; Pichot, G.

    2011-12-01

    Flow channeling and permeability scaling in fractured media have been classically addressed either at the fracture- or at the network- scales. In the latter case they are linked to the topological structure of the network, while at the fracture scale they are controlled by the variability of the local aperture distribution inside individual fractures. In this study we analyze these two combined effects, investigating how flow localization below the scale of individual fractures influences that at the network scale and the resulting medium permeability. This is done by use of a new highly-resolved 3D discrete fracture network model (DFN). The local apertures of individual fractures are distributed according to a truncated Gaussian law, and exhibit self-affine spatial correlations that are bounded by an upper cutoff scale Lc; Lc and the fracture closure, defined as the ratio of the aperture fluctuations at scale Lc to the mean aperture, are considered homogeneous over the DFN. The network topology is controlled by a homogeneous scalar fracture density and a power law fracture length distribution. We have varied these features to investigate a large variety of DFN topologies, from sparse networks with varying degrees of fracture interconnections, flow bottlenecks and dead-ends (Fig. 1a), to dense well-connected networks (Fig. 1b). We have also investigated a large range of fracture closures, performing extensive simulations of about 105 different DFN realizations. At the fracture scale, accounting for local aperture fluctuations leads to a monotical deviation (which can exceed 50%) of the equivalent fracture transmissivity from the parallel plate behavior. At the network scale we observe a complex interaction between flow channeling within fracture planes and flow localization in the network. This interaction is controlled by the location of fracture interactions with respect to that of low local transmissivity zones (particularly the closed zones), in the fracture

  3. DEM interpolation based on artificial neural networks

    NASA Astrophysics Data System (ADS)

    Jiao, Limin; Liu, Yaolin

    2005-10-01

    This paper proposed a systemic resolution scheme of Digital Elevation model (DEM) interpolation based on Artificial Neural Networks (ANNs). In this paper, we employ BP network to fit terrain surface, and then detect and eliminate the samples with gross errors. This paper uses Self-organizing Feature Map (SOFM) to cluster elevation samples. The study area is divided into many more homogenous tiles after clustering. BP model is employed to interpolate DEM in each cluster. Because error samples are eliminated and clusters are built, interpolation result is better. The case study indicates that ANN interpolation scheme is feasible. It also shows that ANN can get a more accurate result by comparing ANN with polynomial and spline interpolation. ANN interpolation doesn't need to determine the interpolation function beforehand, so manmade influence is lessened. The ANN interpolation is more automatic and intelligent. At the end of the paper, we propose the idea of constructing ANN surface model. This model can be used in multi-scale DEM visualization, and DEM generalization, etc.

  4. Network video transmission system based on SOPC

    NASA Astrophysics Data System (ADS)

    Zhang, Zhengbing; Deng, Huiping; Xia, Zhenhua

    2008-03-01

    Video systems have been widely used in many fields such as conferences, public security, military affairs and medical treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system. In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application program scheme is proposed.

  5. Graphene-based battery electrodes having continuous flow paths

    DOEpatents

    Zhang, Jiguang; Xiao, Jie; Liu, Jun; Xu, Wu; Li, Xiaolin; Wang, Deyu

    2014-05-24

    Some batteries can exhibit greatly improved performance by utilizing electrodes having randomly arranged graphene nanosheets forming a network of channels defining continuous flow paths through the electrode. The network of channels can provide a diffusion pathway for the liquid electrolyte and/or for reactant gases. Metal-air batteries can benefit from such electrodes. In particular Li-air batteries show extremely high capacities, wherein the network of channels allow oxygen to diffuse through the electrode and mesopores in the electrode can store discharge products.

  6. Analysis of the peak-flow gaging network in North Dakota

    USGS Publications Warehouse

    Williams-Sether, Tara

    1996-01-01

    A network analysis technique using generalized least-squares regression was used to evaluate the current (1993) peak-flow gaging network that provides regional peak-flow information for North Dakota. The analysis was conducted to evaluate the current (1993) network and to determine if reactivating discontinued gaging stations and adding new gaging stations on small drainage areas would improve regional peak-flow information. Peak flows having recurrence intervals of 15, 50, and 100 years and planning horizons of zero and 10 years for three hydrologic regions in North Dakota were used in the network analysis. Results of the network analysis indicate that the average sampling mean-square error could be reduced by about 10 percent for the 15-, 50-, and 100-year recurrence intervals by reactivating a minimum of two to five discontinued gaging stations in each hydrologic region. The reactivated discontinued gaging stations added to the current (1993) network should be located on streams having small drainage areas and steep main-channel slopes. For the 15-year recurrence interval and a 10-year planning horizon, adding a new gaging station at two new locations in each region instead of reactivating two discontinued gaging stations in each region would reduce the average sampling mean-square error by an average of about 13 percent in each region. The new gaging stations added to the current (1993) network should be located on streams having small drainage areas and mild or steep main-channel slopes in order to obtain improved regional peak-flow information.

  7. Identification of surface flow paths, slopes, and channel networks from gridded elevation data

    NASA Astrophysics Data System (ADS)

    Orlandini, S.; Moretti, G.; Tarolli, P.; Dalla Fontana, G.

    2009-12-01

    Stream channels enhance the hydrological connectivity between land surface elements. The representation and prediction of stream channels in drainage basins has therefore been a perennial concern in geomorphology, with implications for understanding of drainage basin origin, scale and morphology, basin hydrology, and effects of natural and man-induced process changes. The channel (or stream) network is defined by channels with well-defined banks and sources. In theory, the channel network includes all the minor rills which are definite watercourses, even including all the ephemeral channels in the furthermost headwaters. In practice, the direct survey of all channels is normally a prohibitive task, and the detail with which the channel network is represented is dependent on the scale of the map used to trace the channels. In actual fact, the headward limits of the blue lines do not reflect any statistical characteristic of streamflow occurrence, but they are drawn to fit a rather personalized aesthetic. On the other hand, the explicit description of the mechanisms determining the channel heads is a nontrivial task since it requires complex fluvial and/or landsliding processes to be considered singly or in combination. However, the increasing availability of highly accurate digital elevation data derived from LiDAR surveys, reliable terrain analysis methods, and observations collected in the field or remotely, offers new potential for developing and/or evaluating prediction models for channel initiation. In addition to detailed models, simpler generalizations from field facts can be sought by incorporating the broad features of climate, topography, and geology. In the present study, methods for the determination of surface flow paths are briefly reviewed. Three methods for the prediction of channel networks are then evaluated by using gridded elevation data derived from high-precision LiDAR surveys, a reliable algorithm for the determination of surface flow paths

  8. Dynamic autonomous routing technology for IP-based satellite ad hoc networks

    NASA Astrophysics Data System (ADS)

    Wang, Xiaofei; Deng, Jing; Kostas, Theresa; Rajappan, Gowri

    2014-06-01

    IP-based routing for military LEO/MEO satellite ad hoc networks is very challenging due to network and traffic heterogeneity, network topology and traffic dynamics. In this paper, we describe a traffic priority-aware routing scheme for such networks, namely Dynamic Autonomous Routing Technology (DART) for satellite ad hoc networks. DART has a cross-layer design, and conducts routing and resource reservation concurrently for optimal performance in the fluid but predictable satellite ad hoc networks. DART ensures end-to-end data delivery with QoS assurances by only choosing routing paths that have sufficient resources, supporting different packet priority levels. In order to do so, DART incorporates several resource management and innovative routing mechanisms, which dynamically adapt to best fit the prevailing conditions. In particular, DART integrates a resource reservation mechanism to reserve network bandwidth resources; a proactive routing mechanism to set up non-overlapping spanning trees to segregate high priority traffic flows from lower priority flows so that the high priority flows do not face contention from low priority flows; a reactive routing mechanism to arbitrate resources between various traffic priorities when needed; a predictive routing mechanism to set up routes for scheduled missions and for anticipated topology changes for QoS assurance. We present simulation results showing the performance of DART. We have conducted these simulations using the Iridium constellation and trajectories as well as realistic military communications scenarios. The simulation results demonstrate DART's ability to discriminate between high-priority and low-priority traffic flows and ensure disparate QoS requirements of these traffic flows.

  9. Medical education practice-based research networks: Facilitating collaborative research

    PubMed Central

    Schwartz, Alan; Young, Robin; Hicks, Patricia J.; APPD LEARN, For

    2016-01-01

    Abstract Background: Research networks formalize and institutionalize multi-site collaborations by establishing an infrastructure that enables network members to participate in research, propose new studies, and exploit study data to move the field forward. Although practice-based clinical research networks are now widespread, medical education research networks are rapidly emerging. Aims: In this article, we offer a definition of the medical education practice-based research network, a brief description of networks in existence in July 2014 and their features, and a more detailed case study of the emergence and early growth of one such network, the Association of Pediatric Program Directors Longitudinal Educational Assessment Research Network (APPD LEARN). Methods: We searched for extant networks through peer-reviewed literature and the world-wide web. Results: We identified 15 research networks in medical education founded since 2002 with membership ranging from 8 to 120 programs. Most focus on graduate medical education in primary care or emergency medicine specialties. Conclusions: We offer four recommendations for the further development and spread of medical education research networks: increasing faculty development, obtaining central resources, studying networks themselves, and developing networks of networks. PMID:25319404

  10. Cluster and propensity based approximation of a network

    PubMed Central

    2013-01-01

    Background The models in this article generalize current models for both correlation networks and multigraph networks. Correlation networks are widely applied in genomics research. In contrast to general networks, it is straightforward to test the statistical significance of an edge in a correlation network. It is also easy to decompose the underlying correlation matrix and generate informative network statistics such as the module eigenvector. However, correlation networks only capture the connections between numeric variables. An open question is whether one can find suitable decompositions of the similarity measures employed in constructing general networks. Multigraph networks are attractive because they support likelihood based inference. Unfortunately, it is unclear how to adjust current statistical methods to detect the clusters inherent in many data sets. Results Here we present an intuitive and parsimonious parametrization of a general similarity measure such as a network adjacency matrix. The cluster and propensity based approximation (CPBA) of a network not only generalizes correlation network methods but also multigraph methods. In particular, it gives rise to a novel and more realistic multigraph model that accounts for clustering and provides likelihood based tests for assessing the significance of an edge after controlling for clustering. We present a novel Majorization-Minimization (MM) algorithm for estimating the parameters of the CPBA. To illustrate the practical utility of the CPBA of a network, we apply it to gene expression data and to a bi-partite network model for diseases and disease genes from the Online Mendelian Inheritance in Man (OMIM). Conclusions The CPBA of a network is theoretically appealing since a) it generalizes correlation and multigraph network methods, b) it improves likelihood based significance tests for edge counts, c) it directly models higher-order relationships between clusters, and d) it suggests novel clustering

  11. Quantifying the effects of tidal amplitude on river delta network flow partitioning

    NASA Astrophysics Data System (ADS)

    Hiatt, M. R.; Sendrowski, A.; Passalacqua, P.

    2014-12-01

    Deltas are generally classified as river-, tide-, or wave-dominated systems, but the influences of all environmental forces cannot be ignored when fully addressing the dynamics of the system. For example, in river-dominated deltas, river flow from the feeder channel acts as the primary driver of dynamics within the system by delivering water, sediment, and nutrients through the distributary channels, but tides and waves may affect their allocation within the network. There has been work on the asymmetry of environmental fluxes at bifurcations, but relatively few studies exist on the water partitioning at the network scale. Understanding the network and environmental effects on the flux of water, sediment, and nutrients would benefit delta restoration projects and management practices. In this study, we investigate the allocation of water flow among the five major distributary channels at Wax Lake Delta (WLD), a micro-tidal river-dominated delta in coastal Louisiana, and the effects of tidal amplitude on distributary channel discharges. We collect and compare discharge results from acoustic Doppler current profiler (ADCP) velocity transects between spring and neap tide and between falling and rising tide. The results show that discharges increased from spring to neap tide and from rising to falling tide. We investigate the spatial gradients of tidal influence within the network and validate hydraulic geometry relations for tidally influenced channels. Our results give insight into the control of network structure on flow partitioning and show the degree of tidal influence on channel flow in the river-dominated WLD.

  12. Cooperative UAV-Based Communications Backbone for Sensor Networks

    SciTech Connect

    Roberts, R S

    2001-10-07

    The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs are used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.

  13. Gas flow in plant microfluidic networks controlled by capillary valves.

    PubMed

    Capron, M; Tordjeman, Ph; Charru, F; Badel, E; Cochard, H

    2014-03-01

    The xylem vessels of trees constitute a model natural microfluidic system. In this work, we have studied the mechanism of air flow in the Populus xylem. The vessel microstructure was characterized by optical microscopy, transmission electronic microscopy (TEM), and atomic force microscopy (AFM) at different length scales. The xylem vessels have length ≈15 cm and diameter ≈20μm. Flow from one vessel to the next occurs through ∼102 pits, which are grouped together at the ends of the vessels. The pits contain a thin, porous pit membrane with a thickness of 310 nm. We have measured the Young's moduli of the vessel wall and of the pits (both water-saturated and after drying) by specific nanoindentation and nanoflexion experiments with AFM. We found that both the dried and water-saturated pit membranes have Young's modulus around 0.4 MPa, in agreement with values obtained by micromolding of pits deformed by an applied pressure difference. Air injection experiments reveal that air flows through the xylem vessels when the differential pressure across a sample is larger than a critical value ΔPc=1.8 MPa. In order to model the air flow rate for ΔP⩾ΔPc, we assumed the pit membrane to be a porous medium that is strained by the applied pressure difference. Water menisci in the pit pores play the role of capillary valves, which open at ΔP=ΔPc. From the point of view of the plant physiology, this work presents a basic understanding of the physics of bordered pits. PMID:24730949

  14. Gas flow in plant microfluidic networks controlled by capillary valves

    NASA Astrophysics Data System (ADS)

    Capron, M.; Tordjeman, Ph.; Charru, F.; Badel, E.; Cochard, H.

    2014-03-01

    The xylem vessels of trees constitute a model natural microfluidic system. In this work, we have studied the mechanism of air flow in the Populus xylem. The vessel microstructure was characterized by optical microscopy, transmission electronic microscopy (TEM), and atomic force microscopy (AFM) at different length scales. The xylem vessels have length ≈15 cm and diameter ≈20μm. Flow from one vessel to the next occurs through ˜102 pits, which are grouped together at the ends of the vessels. The pits contain a thin, porous pit membrane with a thickness of 310 nm. We have measured the Young's moduli of the vessel wall and of the pits (both water-saturated and after drying) by specific nanoindentation and nanoflexion experiments with AFM. We found that both the dried and water-saturated pit membranes have Young's modulus around 0.4 MPa, in agreement with values obtained by micromolding of pits deformed by an applied pressure difference. Air injection experiments reveal that air flows through the xylem vessels when the differential pressure across a sample is larger than a critical value ΔPc=1.8 MPa. In order to model the air flow rate for ΔP ⩾ΔPc, we assumed the pit membrane to be a porous medium that is strained by the applied pressure difference. Water menisci in the pit pores play the role of capillary valves, which open at ΔP =ΔPc. From the point of view of the plant physiology, this work presents a basic understanding of the physics of bordered pits.

  15. Data-Flow Based Model Analysis

    NASA Technical Reports Server (NTRS)

    Saad, Christian; Bauer, Bernhard

    2010-01-01

    The concept of (meta) modeling combines an intuitive way of formalizing the structure of an application domain with a high expressiveness that makes it suitable for a wide variety of use cases and has therefore become an integral part of many areas in computer science. While the definition of modeling languages through the use of meta models, e.g. in Unified Modeling Language (UML), is a well-understood process, their validation and the extraction of behavioral information is still a challenge. In this paper we present a novel approach for dynamic model analysis along with several fields of application. Examining the propagation of information along the edges and nodes of the model graph allows to extend and simplify the definition of semantic constraints in comparison to the capabilities offered by e.g. the Object Constraint Language. Performing a flow-based analysis also enables the simulation of dynamic behavior, thus providing an "abstract interpretation"-like analysis method for the modeling domain.

  16. Subsampling-based compression and flow visualization

    NASA Astrophysics Data System (ADS)

    Agranovsky, Alexy; Camp, David; Joy, Kenneth I.; Childs, Hank

    2015-01-01

    As computational capabilities increasingly outpace disk speeds on leading supercomputers, scientists will, in turn, be increasingly unable to save their simulation data at its native resolution. One solution to this problem is to compress these data sets as they are generated and visualize the compressed results afterwards. We explore this approach, specifically subsampling velocity data and the resulting errors for particle advection-based flow visualization. We compare three techniques: random selection of subsamples, selection at regular locations corresponding to multi-resolution reduction, and introduce a novel technique for informed selection of subsamples. Furthermore, we explore an adaptive system which exchanges the subsampling budget over parallel tasks, to ensure that subsampling occurs at the highest rate in the areas that need it most. We perform supercomputing runs to measure the effectiveness of the selection and adaptation techniques. Overall, we find that adaptation is very effective, and, among selection techniques, our informed selection provides the most accurate results, followed by the multi-resolution selection, and with the worst accuracy coming from random subsamples.

  17. Random network peristalsis in Physarum polycephalum organizes fluid flows across an individual.

    PubMed

    Alim, Karen; Amselem, Gabriel; Peaudecerf, François; Brenner, Michael P; Pringle, Anne

    2013-08-13

    Individuals can function as integrated organisms only when information and resources are shared across a body. Signals and substrates are commonly moved using fluids, often channeled through a network of tubes. Peristalsis is one mechanism for fluid transport and is caused by a wave of cross-sectional contractions along a tube. We extend the concept of peristalsis from the canonical case of one tube to a random network. Transport is maximized within the network when the wavelength of the peristaltic wave is of the order of the size of the network. The slime mold Physarum polycephalum grows as a random network of tubes, and our experiments confirm peristalsis is used by the slime mold to drive internal cytoplasmic flows. Comparisons of theoretically generated contraction patterns with the patterns exhibited by individuals of P. polycephalum demonstrate that individuals maximize internal flows by adapting patterns of contraction to size, thus optimizing transport throughout an organism. This control of fluid flow may be the key to coordinating growth and behavior, including the dynamic changes in network architecture seen over time in an individual. PMID:23898203

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

    PubMed Central

    Tupikina, Liubov; Molkenthin, Nora; López, Cristóbal; Hernández-García, Emilio; Marwan, Norbert; Kurths, Jürgen

    2016-01-01

    Complex network theory provides an elegant and powerful framework to statistically investigate different types of systems such as society, brain or the structure of local and long-range dynamical interrelationships in the climate system. Network links in climate networks typically imply information, mass or energy exchange. However, the specific connection between oceanic or atmospheric flows and the climate network’s structure is still unclear. We propose a theoretical approach for verifying relations between the correlation matrix and the climate network measures, generalizing previous studies and overcoming the restriction to stationary flows. Our methods are developed for correlations of a scalar quantity (temperature, for example) which satisfies an advection-diffusion dynamics in the presence of forcing and dissipation. Our approach reveals that correlation networks are not sensitive to steady sources and sinks and the profound impact of the signal decay rate on the network topology. We illustrate our results with calculations of degree and clustering for a meandering flow resembling a geophysical ocean jet. PMID:27128846

  19. Extraction of conjugate main-stream structures from a complex network flow.

    PubMed

    Tamura, Koutarou; Takayasu, Hideki; Takayasu, Misako

    2015-04-01

    We introduce a method to extract main-stream structures for a given complex network flow by trimming less effective links. As the resulting main streams generally have an almost loopless treelike structure, we can define the stream basin size for each node, which characterizes the importance of the node with regard to the flow. As a real-world example, we apply this method to an interfirm trading network, both for the money flow and its conjugate-the material or service flow-confirming that both basin size distributions follow a similar power law that differs significantly from the basin size distributions of rivers in nature. We theoretically analyze the process of trimming and derive a consistent statistical formulation between the original link number and the basin size. PMID:25974555

  20. Numerical Simulation of non-Newtonian Fluid Flows through Fracture Network

    NASA Astrophysics Data System (ADS)

    Dharmawan, I. A.; Ulhag, R. Z.; Endyana, C.; Aufaristama, M.

    2016-01-01

    We present a numerical simulation of non-Newtonian fluid flow in a twodimensional fracture network. The fracture is having constant mean aperture and bounded with Hurst exponent surfaces. The non-Newtonian rheology behaviour of the fluid is described using the Power-Law model. The lattice Boltzmann method is employed to calculate the solutions for non-Newtonian flow in finite Reynolds number. We use a constant force to drive the fluid within the fracture, while the bounceback rules and periodic boundary conditions are applied for the fluid-solid interaction and inflow outlflow boundary conditions, respectively. The validation study of the simulation is done via parallel plate flow simulation and the results demonstrated good agreement with the analytical solution. In addition, the fluid flow properties within the fracture network follow the relationships of power law fluid while the errors are becoming larger if the fluid more shear thinning.

  1. Modeling flow and sediment transport in a river system using an artificial neural network.

    PubMed

    Yitian, Li; Gu, Roy R

    2003-01-01

    A river system is a network of intertwining channels and tributaries, where interacting flow and sediment transport processes are complex and floods may frequently occur. In water resources management of a complex system of rivers, it is important that instream discharges and sediments being carried by streamflow are correctly predicted. In this study, a model for predicting flow and sediment transport in a river system is developed by incorporating flow and sediment mass conservation equations into an artificial neural network (ANN), using actual river network to design the ANN architecture, and expanding hydrological applications of the ANN modeling technique to sediment yield predictions. The ANN river system model is applied to modeling daily discharges and annual sediment discharges in the Jingjiang reach of the Yangtze River and Dongting Lake, China. By the comparison of calculated and observed data, it is demonstrated that the ANN technique is a powerful tool for real-time prediction of flow and sediment transport in a complex network of rivers. A significant advantage of applying the ANN technique to model flow and sediment phenomena is the minimum data requirements for topographical and morphometric information without significant loss of model accuracy. The methodology and results presented show that it is possible to integrate fundamental physical principles into a data-driven modeling technique and to use a natural system for ANN construction. This approach may increase model performance and interpretability while at the same time making the model more understandable to the engineering community. PMID:12447580

  2. Facilitating the Development of School-Based Learning Networks

    ERIC Educational Resources Information Center

    Kubiak, Chris; Bertram, Joan

    2010-01-01

    Purpose: This paper aims to contribute to the knowledge base on leading and facilitating the growth of school improvement networks by describing the activities and challenges faced by network leaders. Design/methodology/approach: A total of 19 co-leaders from 12 networks were interviewed using a semi-structured schedule about the growth of their…

  3. Survey-Based Measurement of Public Management and Policy Networks

    ERIC Educational Resources Information Center

    Henry, Adam Douglas; Lubell, Mark; McCoy, Michael

    2012-01-01

    Networks have become a central concept in the policy and public management literature; however, theoretical development is hindered by a lack of attention to the empirical properties of network measurement methods. This paper compares three survey-based methods for measuring organizational networks: the roster, the free-recall name generator, and…

  4. Recent Electrochemical and Optical Sensors in Flow-Based Analysis

    PubMed Central

    Chailapakul, Orawon; Ngamukot, Passapol; Yoosamran, Alongkorn; Siangproh, Weena; Wangfuengkanagul, Nattakarn

    2006-01-01

    Some recent analytical sensors based on electrochemical and optical detection coupled with different flow techniques have been chosen in this overview. A brief description of fundamental concepts and applications of each flow technique, such as flow injection analysis (FIA), sequential injection analysis (SIA), all injection analysis (AIA), batch injection analysis (BIA), multicommutated FIA (MCFIA), multisyringe FIA (MSFIA), and multipumped FIA (MPFIA) were reviewed.

  5. Flow batteries for microfluidic networks: configuring an electroosmotic pump for nonterminal positions.

    PubMed

    He, Chiyang; Lu, Joann J; Jia, Zhijian; Wang, Wei; Wang, Xiayan; Dasgupta, Purnendu K; Liu, Shaorong

    2011-04-01

    A micropump provides flow and pressure for a lab-on-chip device, just as a battery supplies current and voltage for an electronic system. Numerous micropumps have been developed, but none is as versatile as a battery. One cannot easily insert a micropump into a nonterminal position of a fluidic line without affecting the rest of the fluidic system, and one cannot simply connect several micropumps in series to enhance the pressure output, etc. In this work we develop a flow battery (or pressure power supply) to address this issue. A flow battery consists of a +EOP (in which the liquid flows in the same direction as the field gradient) and a -EOP (in which the liquid flows opposite to the electric field gradient), and the outlet of the +EOP is directly connected to the inlet of the -EOP. An external high voltage is applied to this outlet-inlet joint via a short gel-filled capillary that allows ions but not bulk liquid flow, while the +EOP's inlet and the -EOP's outlet (the flow battery's inlet and outlet) are grounded. This flow battery can be deployed anywhere in a fluidic network without electrically affecting the rest of the system. Several flow batteries can be connected in series to enhance the pressure output to drive HPLC separations. In a fluidic system powered by flow batteries, a hydraulic equivalent of Ohm's law can be applied to analyze system pressures and flow rates. PMID:21375230

  6. Networks.

    ERIC Educational Resources Information Center

    Maughan, George R.; Petitto, Karen R.; McLaughlin, Don

    2001-01-01

    Describes the connectivity features and options of modern campus communication and information system networks, including signal transmission (wire-based and wireless), signal switching, convergence of networks, and network assessment variables, to enable campus leaders to make sound future-oriented decisions. (EV)

  7. Connectivity of overland flow by drainage network expansion in a rain forest catchment

    NASA Astrophysics Data System (ADS)

    Zimmermann, Beate; Zimmermann, Alexander; Turner, Benjamin L.; Francke, Till; Elsenbeer, Helmut

    2014-02-01

    Soils in various places of the Panama Canal Watershed feature a low saturated hydraulic conductivity (Ks) at shallow depth, which promotes overland-flow generation and associated flashy catchment responses. In undisturbed forests of these areas, overland flow is concentrated in flow lines that extend the channel network and provide hydrological connectivity between hillslopes and streams. To understand the dynamics of overland-flow connectivity, as well as the impact of connectivity on catchment response, we studied an undisturbed headwater catchment by monitoring overland-flow occurrence in all flow lines and discharge, suspended sediment, and total phosphorus at the catchment outlet. We find that connectivity is strongly influenced by seasonal variation in antecedent wetness and can develop even under light rainfall conditions. Connectivity increased rapidly as rainfall frequency increased, eventually leading to full connectivity and surficial drainage of entire hillslopes. Connectivity was nonlinearly related to catchment response. However, additional information on factors such as overland-flow volume would be required to constrain relationships between connectivity, stormflow, and the export of suspended sediment and phosphorus. The effort to monitor those factors would be substantial, so we advocate applying the established links between rain event characteristics, drainage network expansion by flow lines, and catchment response for predictive modeling and catchment classification in forests of the Panama Canal Watershed and in similar regions elsewhere.

  8. Semantic segmentation based on neural network and Bayesian network

    NASA Astrophysics Data System (ADS)

    Ge, Wenying; Liu, Guoying

    2013-10-01

    It is rather difficult for low-level visual features to describe the need for specific applications of image understanding, which results in the inconsistency between vision information and application need. In this paper, a new model is proposed to reduce this gap by combining low-level visual features with semantic features. It uses the output of neural network as the semantic feature, which is accompanied with the priori label features to describe the image after making normalization. And then, the proposed method employs Potts to model the distribution of label priori, and utilizes the Bayesian network to classify images. Several experiments on both synthetic and real images have verified that this method can get more accurate segmentation.

  9. Physically-based interactive Schlieren flow visualization

    SciTech Connect

    Mccormick, Patrick S; Brownlee, Carson S; Pegoraro, Vincent; Shankar, Siddharth; Hansen, Charles D

    2009-01-01

    Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraphs and schlieren images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Results comparing this method to previous schlieren approximations are presented.

  10. Ionization based multi-directional flow sensor

    DOEpatents

    Chorpening, Benjamin T.; Casleton, Kent H.

    2009-04-28

    A method, system, and apparatus for conducting real-time monitoring of flow (airflow for example) in a system (a hybrid power generation system for example) is disclosed. The method, system and apparatus measure at least flow direction and velocity with minimal pressure drop and fast response. The apparatus comprises an ion source and a multi-directional collection device proximate the ion source. The ion source is configured to generate charged species (electrons and ions for example). The multi-directional collection source is configured to determine the direction and velocity of the flow in real-time.

  11. Evolution of RNA-Based Networks.

    PubMed

    Stadler, Peter F

    2016-01-01

    RNA molecules have served for decades as a paradigmatic example of molecular evolution that is tractable both in in vitro experiments and in detailed computer simulation. The adaptation of RNA sequences to external selection pressures is well studied and well understood. The de novo innovation or optimization of RNA aptamers and riboswitches in SELEX experiments serves as a case in point. Likewise, fitness landscapes building upon the efficiently computable RNA secondary structures have been a key toward understanding realistic fitness landscapes. Much less is known, however, on models in which multiple RNAs interact with each other, thus actively influencing the selection pressures acting on them. From a computational perspective, RNA-RNA interactions can be dealt with by same basic methods as the folding of a single RNA molecule, although many details become more complicated. RNA-RNA interactions are frequently employed in cellular regulation networks, e.g., as miRNA bases mRNA silencing or in the modulation of bacterial mRNAs by small, often highly structured sRNAs. In this chapter, we summarize the key features of networks of replicators. We highlight the differences between quasispecies-like models describing templates copied by an external replicase and hypercycle similar to autocatalytic replicators. Two aspects are of importance: the dynamics of selection within a population, usually described by conventional dynamical systems, and the evolution of replicating species in the space of chemical types. Product inhibition plays a key role in modulating selection dynamics from survival of the fittest to extinction of unfittest. The sequence evolution of replicators is rather well understood as approximate optimization in a fitness landscape for templates that is shaped by the sequence-structure map of RNA. Some of the properties of this map, in particular shape space covering and extensive neutral networks, give rise to evolutionary patterns such as drift

  12. The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin

    NASA Astrophysics Data System (ADS)

    Miller, Matthew P.; Buto, Susan G.; Susong, David D.; Rumsey, Christine A.

    2016-05-01

    The Colorado River has been identified as the most overallocated river in the world. Considering predicted future imbalances between water supply and demand and the growing recognition that base flow (a proxy for groundwater discharge to streams) is critical for sustaining flow in streams and rivers, there is a need to develop methods to better quantify present-day base flow across large regions. We adapted and applied the spatially referenced regression on watershed attributes (SPARROW) water quality model to assess the spatial distribution of base flow, the fraction of streamflow supported by base flow, and estimates of and potential processes contributing to the amount of base flow that is lost during in-stream transport in the Upper Colorado River Basin (UCRB). On average, 56% of the streamflow in the UCRB originated as base flow, and precipitation was identified as the dominant driver of spatial variability in base flow at the scale of the UCRB, with the majority of base flow discharge to streams occurring in upper elevation watersheds. The model estimates an average of 1.8 × 1010 m3/yr of base flow in the UCRB; greater than 80% of which is lost during in-stream transport to the Lower Colorado River Basin via processes including evapotranspiration and water diversion for irrigation. Our results indicate that surface waters in the Colorado River Basin are dependent on base flow, and that management approaches that consider groundwater and surface water as a joint resource will be needed to effectively manage current and future water resources in the Basin.

  13. Hierarchical coefficient of a multifractal based network

    NASA Astrophysics Data System (ADS)

    Moreira, Darlan A.; Lucena, Liacir dos Santos; Corso, Gilberto

    2014-02-01

    The hierarchical property for a general class of networks stands for a power-law relation between clustering coefficient, CC and connectivity k: CC∝kβ. This relation is empirically verified in several biologic and social networks, as well as in random and deterministic network models, in special for hierarchical networks. In this work we show that the hierarchical property is also present in a Lucena network. To create a Lucena network we use the dual of a multifractal lattice ML, the vertices are the sites of the ML and links are established between neighbouring lattices, therefore this network is space filling and planar. Besides a Lucena network shows a scale-free distribution of connectivity. We deduce a relation for the maximal local clustering coefficient CCimax of a vertex i in a planar graph. This condition expresses that the number of links among neighbour, N△, of a vertex i is equal to its connectivity ki, that means: N△=ki. The Lucena network fulfils the condition N△≃ki independent of ki and the anisotropy of ML. In addition, CCmax implies the threshold β=1 for the hierarchical property for any scale-free planar network.

  14. Ion channel networks in the control of cerebral blood flow.

    PubMed

    Longden, Thomas A; Hill-Eubanks, David C; Nelson, Mark T

    2016-03-01

    One hundred and twenty five years ago, Roy and Sherrington made the seminal observation that neuronal stimulation evokes an increase in cerebral blood flow.(1) Since this discovery, researchers have attempted to uncover how the cells of the neurovascular unit-neurons, astrocytes, vascular smooth muscle cells, vascular endothelial cells and pericytes-coordinate their activity to control this phenomenon. Recent work has revealed that ionic fluxes through a diverse array of ion channel species allow the cells of the neurovascular unit to engage in multicellular signaling processes that dictate local hemodynamics.In this review we center our discussion on two major themes: (1) the roles of ion channels in the dynamic modulation of parenchymal arteriole smooth muscle membrane potential, which is central to the control of arteriolar diameter and therefore must be harnessed to permit changes in downstream cerebral blood flow, and (2) the striking similarities in the ion channel complements employed in astrocytic endfeet and endothelial cells, enabling dual control of smooth muscle from either side of the blood-brain barrier. We conclude with a discussion of the emerging roles of pericyte and capillary endothelial cell ion channels in neurovascular coupling, which will provide fertile ground for future breakthroughs in the field. PMID:26661232

  15. Performance analysis of electronic code division multiple access based virtual private networks over passive optical networks

    NASA Astrophysics Data System (ADS)

    Nadarajah, Nishaanthan; Nirmalathas, Ampalavanapillai

    2008-03-01

    A solution for implementing multiple secure virtual private networks over a passive optical network using electronic code division multiple access is proposed and experimentally demonstrated. The multiple virtual private networking capability is experimentally demonstrated with 40 Mb/s data multiplexed with a 640 Mb/s electronic code that is unique to each of the virtual private networks in the passive optical network, and the transmission of the electronically coded data is carried out using Fabry-Perot laser diodes. A theoretical scalability analysis for electronic code division multiple access based virtual private networks over a passive optical network is also carried out to identify the performance limits of the scheme. Several sources of noise such as optical beat interference and multiple access interference that are present in the receiver are considered with different operating system parameters such as transmitted optical power, spectral width of the broadband optical source, and processing gain to study the scalability of the network.

  16. Flow distribution analysis on the cooling tube network of ITER thermal shield

    NASA Astrophysics Data System (ADS)

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O.; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-01

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  17. Flow distribution analysis on the cooling tube network of ITER thermal shield

    SciTech Connect

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-29

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  18. Network-based production quality control

    NASA Astrophysics Data System (ADS)

    Kwon, Yongjin; Tseng, Bill; Chiou, Richard

    2007-09-01

    This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.

  19. Automation of Network-Based Scientific Workflows

    SciTech Connect

    Altintas, I.; Barreto, R.; Blondin, J. M.; Cheng, Z.; Critchlow, T.; Khan, A.; Klasky, Scott A; Ligon, J.; Ludaescher, B.; Mouallem, P. A.; Parker, S.; Podhorszki, Norbert; Shoshani, A.; Silva, C.; Vouk, M. A.

    2007-01-01

    Comprehensive, end-to-end, data and workflow management solutions are needed to handle the increasing complexity of processes and data volumes associated with modern distributed scientific problem solving, such as ultra-scale simulations and high-throughput experiments. The key to the solution is an integrated network-based framework that is functional, dependable, fault-tolerant, and supports data and process provenance. Such a framework needs to make development and use of application workflows dramatically easier so that scientists' efforts can shift away from data management and utility software development to scientific research and discovery An integrated view of these activities is provided by the notion of scientific workflows - a series of structured activities and computations that arise in scientific problem-solving. An information technology framework that supports scientific workflows is the Ptolemy II based environment called Kepler. This paper discusses the issues associated with practical automation of scientific processes and workflows and illustrates this with workflows developed using the Kepler framework and tools.

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

    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.

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

    PubMed

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

    2016-01-01

    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. PMID:26833427

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

    PubMed Central

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

    2016-01-01

    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. PMID:26833427

  3. A neural networks-based hybrid routing protocol for wireless mesh networks.

    PubMed

    Kojić, Nenad; Reljin, Irini; Reljin, Branimir

    2012-01-01

    The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic-i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance. PMID:22969360

  4. A Neural Networks-Based Hybrid Routing Protocol for Wireless Mesh Networks

    PubMed Central

    Kojić, Nenad; Reljin, Irini; Reljin, Branimir

    2012-01-01

    The networking infrastructure of wireless mesh networks (WMNs) is decentralized and relatively simple, but they can display reliable functioning performance while having good redundancy. WMNs provide Internet access for fixed and mobile wireless devices. Both in urban and rural areas they provide users with high-bandwidth networks over a specific coverage area. The main problems affecting these networks are changes in network topology and link quality. In order to provide regular functioning, the routing protocol has the main influence in WMN implementations. In this paper we suggest a new routing protocol for WMN, based on good results of a proactive and reactive routing protocol, and for that reason it can be classified as a hybrid routing protocol. The proposed solution should avoid flooding and creating the new routing metric. We suggest the use of artificial logic—i.e., neural networks (NNs). This protocol is based on mobile agent technologies controlled by a Hopfield neural network. In addition to this, our new routing metric is based on multicriteria optimization in order to minimize delay and blocking probability (rejected packets or their retransmission). The routing protocol observes real network parameters and real network environments. As a result of artificial logic intelligence, the proposed routing protocol should maximize usage of network resources and optimize network performance. PMID:22969360

  5. Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks

    PubMed Central

    Castet, Jean-Francois; Saleh, Joseph H.

    2013-01-01

    This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the

  6. Neural network based system for equipment surveillance

    DOEpatents

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  7. Neural network based system for equipment surveillance

    DOEpatents

    Vilim, Richard B.; Gross, Kenneth C.; Wegerich, Stephan W.

    1998-01-01

    A method and system for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process.

  8. Flow of Emotional Messages in Artificial Social Networks

    NASA Astrophysics Data System (ADS)

    Chmiel, Anna; Hołyst, Janusz A.

    Models of message flows in an artificial group of users communicating via the Internet are introduced and investigated using numerical simulations. We assumed that messages possess an emotional character with a positive valence and that the willingness to send the next affective message to a given person increases with the number of messages received from this person. As a result, the weights of links between group members evolve over time. Memory effects are introduced, taking into account that the preferential selection of message receivers depends on the communication intensity during the recent period only. We also model the phenomenon of secondary social sharing when the reception of an emotional e-mail triggers the distribution of several emotional e-mails to other people.

  9. Identifying and Characterizing Key Nodes among Communities Based on Electrical-Circuit Networks

    PubMed Central

    Zhu, Fenghui; Wang, Wenxu; Di, Zengru; Fan, Ying

    2014-01-01

    Complex networks with community structures are ubiquitous in the real world. Despite many approaches developed for detecting communities, we continue to lack tools for identifying overlapping and bridging nodes that play crucial roles in the interactions and communications among communities in complex networks. Here we develop an algorithm based on the local flow conservation to effectively and efficiently identify and distinguish the two types of nodes. Our method is applicable in both undirected and directed networks without a priori knowledge of the community structure. Our method bypasses the extremely challenging problem of partitioning communities in the presence of overlapping nodes that may belong to multiple communities. Due to the fact that overlapping and bridging nodes are of paramount importance in maintaining the function of many social and biological networks, our tools open new avenues towards understanding and controlling real complex networks with communities accompanied with the key nodes. PMID:24897125

  10. Single image correlation for blood flow mapping in complex vessel networks

    NASA Astrophysics Data System (ADS)

    Chirico, Giuseppe; Sironi, Laura; Bouzin, Margaux; D'Alfonso, Laura; Collini, Maddalena; Ceffa, Nicolo'G.; Marquezin, Cassia

    2015-05-01

    Microcirculation plays a key role in the maintenance and hemodynamics of tissues and organs also due to its extensive interaction with the immune system. A critical limitation of state-of-the-art clinical techniques to characterize the blood flow is their lack of the spatial resolution required to scale down to individual capillaries. On the other hand the study of the blood flow through auto- or cross-correlation methods fail to correlate the flow speed values with the morphological details required to describe an intricate network of capillaries. Here we propose to use a newly developed technique (FLICS, FLow Image Correlation Spectroscopy) that, by employing a single raster-scanned xy-image acquired in vivo by confocal or multi-photon excitation fluorescence microscopy, allows the quantitative measurement of the blood flow velocity in the whole vessel pattern within the field of view, while simultaneously maintaining the morphological information on the immobile structures of the explored circulatory system. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The whole analytical dependence of the CCFs on the flow speed amplitude and the flow direction has been reported recently. We report here the derivation of approximated analytical relations that allows to use the CCF peak lag time and the corresponding CCF value, to directly estimate the flow speed amplitude and the flow direction. The validation has been performed on Zebrafish embryos for which the flow direction was changed systematically by rotating the embryos on the microscope stage. The results indicate that also from the CCF peak lag time it is possible to recover the flow speed amplitude within 13% of uncertainty (overestimation) in a wide range of angles between the flow and

  11. A Study of a Network-Flow Algorithm and a Noncorrecting Algorithm for Test Assembly.

    ERIC Educational Resources Information Center

    Armstrong, R. D.; And Others

    1996-01-01

    When the network-flow algorithm (NFA) and the average growth approximation algorithm (AGAA) were used for automated test assembly with American College Test and Armed Services Vocational Aptitude Battery item banks, results indicate that reasonable error in item parameters is not harmful for test assembly using NFA or AGAA. (SLD)

  12. Network flow model of force transmission in unbonded and bonded granular media.

    PubMed

    Tordesillas, Antoinette; Tobin, Steven T; Cil, Mehmet; Alshibli, Khalid; Behringer, Robert P

    2015-06-01

    An established aspect of force transmission in quasistatic deformation of granular media is the existence of a dual network of strongly versus weakly loaded particles. Despite significant interest, the regulation of strong and weak forces through the contact network remains poorly understood. We examine this aspect of force transmission using data on microstructural fabric from: (I) three-dimensional discrete element models of grain agglomerates of bonded subspheres constructed from in situ synchrotron microtomography images of silica sand grains under unconfined compression and (II) two-dimensional assemblies of unbonded photoelastic circular disks submitted to biaxial compression under constant volume. We model force transmission as a network flow and solve the maximum flow-minimum cost (MFMC) problem, the solution to which yields a percolating subnetwork of contacts that transmits the "maximum flow" (i.e., the highest units of force) at "least cost" (i.e., the dissipated energy from such transmission). We find the MFMC describes a two-tier hierarchical architecture. At the local level, it encapsulates intraconnections between particles in individual force chains and in their conjoined 3-cycles, with the most common configuration having at least one force chain contact experiencing frustrated rotation. At the global level, the MFMC encapsulates interconnections between force chains. The MFMC can be used to predict most of the force chain particles without need for any information on contact forces, thereby suggesting the network flow framework may have potential broad utility in the modeling of force transmission in unbonded and bonded granular media. PMID:26172702

  13. Network flow model of force transmission in unbonded and bonded granular media

    NASA Astrophysics Data System (ADS)

    Tordesillas, Antoinette; Tobin, Steven T.; Cil, Mehmet; Alshibli, Khalid; Behringer, Robert P.

    2015-06-01

    An established aspect of force transmission in quasistatic deformation of granular media is the existence of a dual network of strongly versus weakly loaded particles. Despite significant interest, the regulation of strong and weak forces through the contact network remains poorly understood. We examine this aspect of force transmission using data on microstructural fabric from: (I) three-dimensional discrete element models of grain agglomerates of bonded subspheres constructed from in situ synchrotron microtomography images of silica sand grains under unconfined compression and (II) two-dimensional assemblies of unbonded photoelastic circular disks submitted to biaxial compression under constant volume. We model force transmission as a network flow and solve the maximum flow-minimum cost (MFMC) problem, the solution to which yields a percolating subnetwork of contacts that transmits the "maximum flow" (i.e., the highest units of force) at "least cost" (i.e., the dissipated energy from such transmission). We find the MFMC describes a two-tier hierarchical architecture. At the local level, it encapsulates intraconnections between particles in individual force chains and in their conjoined 3-cycles, with the most common configuration having at least one force chain contact experiencing frustrated rotation. At the global level, the MFMC encapsulates interconnections between force chains. The MFMC can be used to predict most of the force chain particles without need for any information on contact forces, thereby suggesting the network flow framework may have potential broad utility in the modeling of force transmission in unbonded and bonded granular media.

  14. Higher Education and Global Talent Flows: Brain Drain, Overseas Chinese Intellectuals, and Diasporic Knowledge Networks

    ERIC Educational Resources Information Center

    Welch, Anthony R.; Zhen, Zhang

    2008-01-01

    In the global era, transnational flows of highly skilled individuals are increasing. In the much-touted global knowledge economy, the contribution of such diasporic individuals and the knowledge networks that they sustain are recognized as being of increasing importance. Brain circulation is of critical importance to the "giant periphery" of…

  15. Fuzzy neural network for flow estimation in sewer systems during wet weather.

    PubMed

    Shen, Jun; Shen, Wei; Chang, Jian; Gong, Ning

    2006-02-01

    Estimation of the water flow from rainfall intensity during storm events is important in hydrology, sewer system control, and environmental protection. The runoff-producing behavior of a sewer system changes from one storm event to another because rainfall loss depends not only on rainfall intensities, but also on the state of the soil and vegetation, the general condition of the climate, and so on. As such, it would be difficult to obtain a precise flowrate estimation without sufficient a priori knowledge of these factors. To establish a model for flow estimation, one can also use statistical methods, such as the neural network STORMNET, software developed at Lyonnaise des Eaux, France, analyzing the relation between rainfall intensity and flowrate data of the known storm events registered in the past for a given sewer system. In this study, the authors propose a fuzzy neural network to estimate the flowrate from rainfall intensity. The fuzzy neural network combines four STORMNETs and fuzzy deduction to better estimate the flowrates. This study's system for flow estimation can be calibrated automatically by using known storm events; no data regarding the physical characteristics of the drainage basins are required. Compared with the neural network STORMNET, this method reduces the mean square error of the flow estimates by approximately 20%. Experimental results are reported herein. PMID:16566517

  16. Modeling the Effect of Fluid Flow on a Growing Network of Fractures in a Porous Medium

    NASA Astrophysics Data System (ADS)

    Alhashim, Mohammed; Koch, Donald

    2015-11-01

    The injection of a viscous fluid at high pressure in a geological formation induces the fracturing of pre-existing joints. Assuming a constant solid-matrix stress field, a weak joint saturated with fluid is fractured when the fluid pressure exceeds a critical value that depends on the joint's orientation. In this work, the formation of a network of fractures in a porous medium is modeled. When the average length of the fractures is much smaller than the radius of a cluster of fractured joints, the fluid flow within the network can be described as Darcy flow in a permeable medium consisting of the fracture network. The permeability and porosity of the medium are functions of the number density of activated joints and consequently depend on the fluid pressure. We demonstrate conditions under which these relationships can be derived from percolation theory. Fluid may also be lost from the fracture network by flowing into the permeable rock matrix. The solution of the model shows that the cluster radius grows as a power law with time in two regimes: (1) an intermediate time regime when the network contains many fractures but fluid loss is negligible; and (2) a long time regime when fluid loss dominates. In both regimes, the power law exponent depends on the Euclidean dimension and the injection rate dependence on time.

  17. Network modeling for reverse flows of end-of-life vehicles.

    PubMed

    Ene, Seval; Öztürk, Nursel

    2015-04-01

    Product recovery operations are of critical importance for the automotive industry in complying with environmental regulations concerning end-of-life products management. Manufacturers must take responsibility for their products over the entire life cycle. In this context, there is a need for network design methods for effectively managing recovery operations and waste. The purpose of this study is to develop a mathematical programming model for managing reverse flows in end-of-life vehicles' recovery network. A reverse flow is the collection of used products from consumers and the transportation of these products for the purpose of recycling, reuse or disposal. The proposed model includes all operations in a product recovery and waste management network for used vehicles and reuse for vehicle parts such as collection, disassembly, refurbishing, processing (shredding), recycling, disposal and reuse of vehicle parts. The scope of the network model is to determine the numbers and locations of facilities in the network and the material flows between these facilities. The results show the performance of the model and its applicability for use in the planning of recovery operations in the automotive industry. The main objective of recovery and waste management is to maximize revenue and minimize pollution in end-of-life product operations. This study shows that with an accurate model, these activities may provide economic benefits and incentives in addition to protecting the environment. PMID:25659298

  18. The guitar chord-generating algorithm based on complex network

    NASA Astrophysics Data System (ADS)

    Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais

    2016-02-01

    This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.

  19. A case study of fluid flow in fractured rock mass based on 2-D DFN modeling

    NASA Astrophysics Data System (ADS)

    Han, Jisu; Noh, Young-Hwan; Um, Jeong-Gi; Choi, Yosoon

    2014-05-01

    A two dimensional steady-state fluid flow through fractured rock mass of an abandoned copper mine in Korea is addressed based on discrete fracture network modeling. An injection well and three observation wells were installed at the field site to monitor the variations of total heads induced by injection of fresh water. A series of packer tests were performed to estimate the rock mass permeability. First, the two dimensional stochastic fracture network model was built and validated for a granitic rock mass using the geometrical and statistical data obtained from surface exposures and borehole logs. This validated fracture network model was combined with the fracture data observed on boreholes to generate a stochastic-deterministic fracture network system. Estimated apertures for each of the fracture sets using permeability data obtained from borehole packer tests were discussed next. Finally, a systematic procedure for fluid flow modeling in fractured rock mass in two dimensional domain was presented to estimate the conductance, flow quantity and nodal head in 2-D conceptual linear pipe channel network. The results obtained in this study clearly show that fracture geometry parameters (orientation, density and size) play an important role in the hydraulic behavior of fractured rock masses.

  20. Factors influencing base flow in the Swiss Midlands - Can results from different base flow separation methods help to identify these factors?

    NASA Astrophysics Data System (ADS)

    Meyer, Raphael; Schädler, Bruno; Viviroli, Daniel; Weingartner, Rolf

    2010-05-01

    is generally accepted in the literature, secondly in land cover, and, especially for the Swiss Midlands, in aquifer area and aquifer volumes. In this contribution the results of the different methods are presented and conclusions as to control factors are drawn from the results. The data base for river flow analysis in the low flow range is ideal in Switzerland. There are long time series, a dense gauge network and a comprehensive knowledge about uncertainty of the runoff measurements during low flow. This allows, in addition to the obtained process understanding, a well-founded comparison between the methods applied, which is going to be presented as well. Demuth, S. (1993) Untersuchungen zum Niedrigwasser in West-Europa (European low flow study). Freiburger Schriften zur Hydrologie, Band 1, Freiburg, Germany. Institue of Hydrology (1980) Low Flows Studies Report, 3 volumes. Institute of Hydrology, Wallingford, UK. Kille, K. (1970) Das Verfahren MoMNQ, ein Beitrag zur Berechnung der mittleren langjährigen Grundwasserneubildung mit Hilfe der monatlichen Niedrigwasserabflüsse. Zeitschrift der deutschen Geologischen Gesellschaft, Sonderheft Hydrogeologie Hydrogeochemie, 89-95. Wittenberg, H. (1999) Baseflow recession and recharge as nonlinear storage processes. Hydrol. Process., 13, 715-726.

  1. Evidence That Calls-Based and Mobility Networks Are Isomorphic.

    PubMed

    Coscia, Michele; Hausmann, Ricardo

    2015-01-01

    Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable. PMID:26713730

  2. Evidence That Calls-Based and Mobility Networks Are Isomorphic

    PubMed Central

    Coscia, Michele; Hausmann, Ricardo

    2015-01-01

    Social relations involve both face-to-face interaction as well as telecommunications. We can observe the geography of phone calls and of the mobility of cell phones in space. These two phenomena can be described as networks of connections between different points in space. We use a dataset that includes billions of phone calls made in Colombia during a six-month period. We draw the two networks and find that the call-based network resembles a higher order aggregation of the mobility network and that both are isomorphic except for a higher spatial decay coefficient of the mobility network relative to the call-based network: when we discount distance effects on the call connections with the same decay observed for mobility connections, the two networks are virtually indistinguishable. PMID:26713730

  3. A network flow model for short-term hydro-dominated hydrothermal scheduling problems

    SciTech Connect

    Franco, P.E.C. ); Carvalho, M.F. ); Soares, S. )

    1994-05-01

    This paper is concerned with the Short-Term Hydrothermal Scheduling (STHS) of hydro-dominated power systems. The problem's formulation includes the representation of operational constraints such as the hydraulic coupling between hydro plants in cascade and the transmission limits in the electric network. In order to allow the problem's decomposition into hydraulic and electric subproblems, a linear-quadratic penalty approach is applied to enforce the coupling between hydro and electric variables. As a result, the problem's natural network flow structure is fully exploited through special-purposed network flow algorithms. The technique has been implemented in FORTRAN in a SUN SPARCstation IPX and tested in a 440 KV subsystem of the main interconnected Brazilian power system.

  4. Deformation of an Elastic beam due to Viscous Flow in an Embedded Channel Network

    NASA Astrophysics Data System (ADS)

    Matia, Yoav; Gat, Amir

    2015-11-01

    Elastic deformation due to embedded fluidic networks is currently studied in the context of soft-actuators and soft-robotic applications. In this work, we analyze the time dependent interaction between elastic deformation of a slender beam and viscous flow within a long serpentine channel, embedded in the elastic structure. The channel is positioned asymmetrically with regard to the midplane of the elastic beam, and thus pressure within the channel creates a local moment deforming the beam. We focus on creeping flows and small deformations of the elastic beam and obtain, in leading order, a convection-diffusion equation governing the pressure-field within the serpentine channel. The beam time-dependent deformation is then obtained as a function of the pressure-field and the geometry of the embedded network. This relation enables the design of complex time-dependent deformation patterns of beams with embedded channel networks. Our theoretical results were illustrated and verified by numerical computations.

  5. In Vivo Flow Mapping in Complex Vessel Networks by Single Image Correlation

    PubMed Central

    Sironi, Laura; Bouzin, Margaux; Inverso, Donato; D'Alfonso, Laura; Pozzi, Paolo; Cotelli, Franco; Guidotti, Luca G.; Iannacone, Matteo; Collini, Maddalena; Chirico, Giuseppe

    2014-01-01

    We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution. PMID:25475129

  6. In Vivo Flow Mapping in Complex Vessel Networks by Single Image Correlation

    NASA Astrophysics Data System (ADS)

    Sironi, Laura; Bouzin, Margaux; Inverso, Donato; D'Alfonso, Laura; Pozzi, Paolo; Cotelli, Franco; Guidotti, Luca G.; Iannacone, Matteo; Collini, Maddalena; Chirico, Giuseppe

    2014-12-01

    We describe a novel method (FLICS, FLow Image Correlation Spectroscopy) to extract flow speeds in complex vessel networks from a single raster-scanned optical xy-image, acquired in vivo by confocal or two-photon excitation microscopy. Fluorescent flowing objects produce diagonal lines in the raster-scanned image superimposed to static morphological details. The flow velocity is obtained by computing the Cross Correlation Function (CCF) of the intensity fluctuations detected in pairs of columns of the image. The analytical expression of the CCF has been derived by applying scanning fluorescence correlation concepts to drifting optically resolved objects and the theoretical framework has been validated in systems of increasing complexity. The power of the technique is revealed by its application to the intricate murine hepatic microcirculatory system where blood flow speed has been mapped simultaneously in several capillaries from a single xy-image and followed in time at high spatial and temporal resolution.

  7. Research on Individualized Product Requirement Expression Based on Semantic Network

    NASA Astrophysics Data System (ADS)

    Yang, Qin; Pan, Xiuqin; Wei, Daozhu; Wu, Ke

    In order to establish an effective platform for individualized product development, the individualized product requirement expression forms were put forward. The diversity Semantic Network of product knowledge representation was researched based on the dualistic semantic network, and the product requirement framework model was established. Thereby the validity, reliability and consistency of the requirement expression process were ensured. Finally an example of customer requirement expression model about differential mechanism based on semantic network was described to satisfy with the individualized product design system.

  8. On Determining if Tree-based Networks Contain Fixed Trees.

    PubMed

    Anaya, Maria; Anipchenko-Ulaj, Olga; Ashfaq, Aisha; Chiu, Joyce; Kaiser, Mahedi; Ohsawa, Max Shoji; Owen, Megan; Pavlechko, Ella; St John, Katherine; Suleria, Shivam; Thompson, Keith; Yap, Corrine

    2016-05-01

    We address an open question of Francis and Steel about phylogenetic networks and trees. They give a polynomial time algorithm to decide if a phylogenetic network, N, is tree-based and pose the problem: given a fixed tree T and network N, is N based on T? We show that it is [Formula: see text]-hard to decide, by reduction from 3-Dimensional Matching (3DM) and further that the problem is fixed-parameter tractable. PMID:27125655

  9. Development of microcontroller based water flow measurement

    NASA Astrophysics Data System (ADS)

    Munir, Muhammad Miftahul; Surachman, Arif; Fathonah, Indra Wahyudin; Billah, Muhammad Aziz; Khairurrijal, Mahfudz, Hernawan; Rimawan, Ririn; Lestari, Slamet

    2015-04-01

    A digital instrument for measuring water flow was developed using an AT89S52 microcontroller, DS1302 real time clock (RTC), and EEPROM for an external memory. The sensor used for probing the current was a propeller that will rotate if immersed in a water flow. After rotating one rotation, the sensor sends one pulse and the number of pulses are counted for a certain time of counting. The measurement data, i.e. the number of pulses per unit time, are converted into water flow velocity (m/s) through a mathematical formula. The microcontroller counts the pulse sent by the sensor and the number of counted pulses are stored into the EEPROM memory. The time interval for counting is provided by the RTC and can be set by the operator. The instrument was tested under various time intervals ranging from 10 to 40 seconds and several standard propellers owned by Experimental Station for Hydraulic Structure and Geotechnics (BHGK), Research Institute for Water Resources (Pusair). Using the same propellers and water flows, it was shown that water flow velocities obtained from the developed digital instrument and those found by the provided analog one are almost similar.

  10. A microfluidic platform with a flow-balanced fluidic network for osteoarthritis diagnosis

    NASA Astrophysics Data System (ADS)

    Kim, Kangil; Park, Yoo Min; Yoon, Hyun C.; Yang, Sang Sik

    2013-05-01

    Osteoarthritis (OA) is one of the most common human diseases, and the occurrence of OA is likely to increase with the increase of population ages. The diagnosis of OA is based on patientrelevant measures, structural measures, and measurement of biomarkers that are released through joint metabolism. Traditionally, radiography or magnetic resonance imaging (MRI) is used to diagnose OA and predict its course. However, diagnostic imaging in OA provides only indirect information on pathology and treatment response. A sensing of OA based on the detection of biomarkers insignificantly improves the accuracy and sensitivity of diagnosis and reduces the cost compared with that of radiography or MRI. In our former study, we proposed microfluidic platform to detect biomarker of OA. But the platform can detect only one biomarker because it has one microfluidic channel. In this report, we proposes microfluidic platform that can detect several biomarkers. The proposed platform has three layers. The bottom layer has gold patterns on a Si substrate for optical sensing. The middle layer and top layer were fabricated by polydimethysiloxane (PDMS) using soft-lithography. The middle layer has four channels connecting top layer to bottom layer. The top layer consists of one sample injection inlet, and four antibody injection inlets. To this end, we designed a flow-balanced microfluidic network using analogy between electric and hydraulic systems. Also, the designed microfluidic network was confirmed by finite element model (FEM) analysis using COMSOL FEMLAB. To verify the efficiency of fabricated platform, the optical sensing test was performed to detect biomarker of OA using fluorescence microscope. We used cartilage oligomeric matrix protein (COMP) as biomarker because it reflects specific changes in joint tissues. The platform successfully detected various concentration of COMP (0, 100, 500, 1000 ng/ml) at each chamber. The effectiveness of the microfluidic platform was verified

  11. Relating Diseases by Integrating Gene Associations and Information Flow through Protein Interaction Network

    PubMed Central

    Hamaneh, Mehdi Bagheri; Yu, Yi-Kuo

    2014-01-01

    Identifying similar diseases could potentially provide deeper understanding of their underlying causes, and may even hint at possible treatments. For this purpose, it is necessary to have a similarity measure that reflects the underpinning molecular interactions and biological pathways. We have thus devised a network-based measure that can partially fulfill this goal. Our method assigns weights to all proteins (and consequently their encoding genes) by using information flow from a disease to the protein interaction network and back. Similarity between two diseases is then defined as the cosine of the angle between their corresponding weight vectors. The proposed method also provides a way to suggest disease-pathway associations by using the weights assigned to the genes to perform enrichment analysis for each disease. By calculating pairwise similarities between 2534 diseases, we show that our disease similarity measure is strongly correlated with the probability of finding the diseases in the same disease family and, more importantly, sharing biological pathways. We have also compared our results to those of MimMiner, a text-mining method that assigns pairwise similarity scores to diseases. We find the results of the two methods to be complementary. It is also shown that clustering diseases based on their similarities and performing enrichment analysis for the cluster centers significantly increases the term association rate, suggesting that the cluster centers are better representatives for biological pathways than the diseases themselves. This lends support to the view that our similarity measure is a good indicator of relatedness of biological processes involved in causing the diseases. Although not needed for understanding this paper, the raw results are available for download for further study at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbpmn/DiseaseRelations/. PMID:25360770

  12. An efective fractal-tree closure model for simulating blood flow in large arterial networks

    PubMed Central

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em.

    2014-01-01

    The aim of the present work is to address the closure problem for hemodynamic simulations by developing a exible and effective model that accurately distributes flow in the downstream vasculature and can stably provide a physiological pressure out flow boundary condition. To achieve this goal, we model blood flow in the sub-pixel vasculature by using a non-linear 1D model in self-similar networks of compliant arteries that mimic the structure and hierarchy of vessels in the meso-vascular regime (radii 500 μm – 10 μm). We introduce a variable vessel length-to-radius ratio for small arteries and arterioles, while also addressing non-Newtonian blood rheology and arterial wall viscoelasticity effects in small arteries and arterioles. This methodology aims to overcome substantial cut-off radius sensitivities, typically arising in structured tree and linearized impedance models. The proposed model is not sensitive to out flow boundary conditions applied at the end points of the fractal network, and thus does not require calibration of resistance/capacitance parameters typically required for out flow conditions. The proposed model convergences to a periodic state in two cardiac cycles even when started from zero-flow initial conditions. The resulting fractal-trees typically consist of thousands to millions of arteries, posing the need for efficient parallel algorithms. To this end, we have scaled up a Discontinuous Galerkin solver that utilizes the MPI/OpenMP hybrid programming paradigm to thousands of computer cores, and can simulate blood flow in networks of millions of arterial segments at the rate of one cycle per 5 minutes. The proposed model has been extensively tested on a large and complex cranial network with 50 parent, patient-specific arteries and 21 outlets to which fractal trees where attached, resulting to a network of up to 4,392,484 vessels in total, and a detailed network of the arm with 276 parent arteries and 103 outlets (a total of 702,188 vessels

  13. DFNWorks. A discrete fracture network framework for modeling subsurface flow and transport

    DOE PAGESBeta

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-08-10

    DFNWorks is a parallalized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfnGen, which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs on the basis of site specific data with the LaGriT meshing toolbox to create a high-quality computational mesh representation, specifically a conforming Delaunay triangulation suitable for high performance computingmore » finite volume solvers, of the DFN in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans, which is an extension of the walkabout particle tracking method to determine pathlines through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.« less

  14. dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

    SciTech Connect

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  15. DFNWorks. A discrete fracture network framework for modeling subsurface flow and transport

    SciTech Connect

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-08-10

    DFNWorks is a parallalized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using dfnGen, which combines fram (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs on the basis of site specific data with the LaGriT meshing toolbox to create a high-quality computational mesh representation, specifically a conforming Delaunay triangulation suitable for high performance computing finite volume solvers, of the DFN in an intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code pflotran. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans, which is an extension of the walkabout particle tracking method to determine pathlines through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  16. Direction of information flow in large-scale resting-state networks is frequency-dependent.

    PubMed

    Hillebrand, Arjan; Tewarie, Prejaas; van Dellen, Edwin; Yu, Meichen; Carbo, Ellen W S; Douw, Linda; Gouw, Alida A; van Straaten, Elisabeth C W; Stam, Cornelis J

    2016-04-01

    Normal brain function requires interactions between spatially separated, and functionally specialized, macroscopic regions, yet the directionality of these interactions in large-scale functional networks is unknown. Magnetoencephalography was used to determine the directionality of these interactions, where directionality was inferred from time series of beamformer-reconstructed estimates of neuronal activation, using a recently proposed measure of phase transfer entropy. We observed well-organized posterior-to-anterior patterns of information flow in the higher-frequency bands (alpha1, alpha2, and beta band), dominated by regions in the visual cortex and posterior default mode network. Opposite patterns of anterior-to-posterior flow were found in the theta band, involving mainly regions in the frontal lobe that were sending information to a more distributed network. Many strong information senders in the theta band were also frequent receivers in the alpha2 band, and vice versa. Our results provide evidence that large-scale resting-state patterns of information flow in the human brain form frequency-dependent reentry loops that are dominated by flow from parieto-occipital cortex to integrative frontal areas in the higher-frequency bands, which is mirrored by a theta band anterior-to-posterior flow. PMID:27001844

  17. dfnWorks: A discrete fracture network framework for modeling subsurface flow and transport

    DOE PAGESBeta

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in anmore » intrinsically parallel fashion. Flow through the network is simulated in dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.« less

  18. Paper-based flow fractionation system for preconcentration and field-flow fractionation.

    NASA Astrophysics Data System (ADS)

    Hong, Seokbin; Kwak, Rhokyun; Kim, Wonjung

    2015-11-01

    We present a novel paper-based flow fractionation system for preconcentration and field-flow fractionation. The paper fluidic system consisting of a straight channel connected with expansion regions can generate a fluid flow with a constant flow rate for 10 min without any external pumping devices. The flow bifurcates with a fraction ratio of up to 30 depending on the control parameters of the channel geometry. Utilizing this simple paper-based bifurcation system, we developed a continuous-flow preconcentrator and a field-flow fractionator on a paper platform. Our experimental results show that the continuous-flow preconcentrator can produce a 33-fold enrichment of the ion concentration and that the flow fractionation system successfully separates the charged dyes. Our study suggests simple, cheap ways to construct preconcentration and field-flow fractionation systems for paper-based microfluidic diagnostic devices. This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (NRF-2015R1A2A2A04006181).

  19. Base-Flow Index Grid for the Conterminous United States

    USGS Publications Warehouse

    Wolock, David M.

    2003-01-01

    This 1-kilometer raster (grid) dataset for the conterminous United States was created by interpolating base-flow index (BFI) values estimated at U.S. Geological Survey (USGS) streamgages. Base flow is the component of streamflow that can be attributed to ground-water discharge into streams.

  20. Earthquake networks based on similar activity patterns.

    PubMed

    Tenenbaum, Joel N; Havlin, Shlomo; Stanley, H Eugene

    2012-10-01

    Earthquakes are a complex spatiotemporal phenomenon, the underlying mechanism for which is still not fully understood despite decades of research and analysis. We propose and develop a network approach to earthquake events. In this network, a node represents a spatial location while a link between two nodes represents similar activity patterns in the two different locations. The strength of a link is proportional to the strength of the cross correlation in activities of two nodes joined by the link. We apply our network approach to a Japanese earthquake catalog spanning the 14-year period 1985-1998. We find strong links representing large correlations between patterns in locations separated by more than 1000 kilometers, corroborating prior observations that earthquake interactions have no characteristic length scale. We find network characteristics not attributable to chance alone, including a large number of network links, high node assortativity, and strong stability over time. PMID:23214652

  1. Pattern recognition tool based on complex network-based approach

    NASA Astrophysics Data System (ADS)

    Casanova, Dalcimar; Backes, André Ricardo; Martinez Bruno, Odemir

    2013-02-01

    This work proposed a generalization of the method proposed by the authors: 'A complex network-based approach for boundary shape analysis'. Instead of modelling a contour into a graph and use complex networks rules to characterize it, here, we generalize the technique. This way, the work proposes a mathematical tool for characterization signals, curves and set of points. To evaluate the pattern description power of the proposal, an experiment of plat identification based on leaf veins image are conducted. Leaf vein is a taxon characteristic used to plant identification proposes, and one of its characteristics is that these structures are complex, and difficult to be represented as a signal or curves and this way to be analyzed in a classical pattern recognition approach. Here, we model the veins as a set of points and model as graphs. As features, we use the degree and joint degree measurements in a dynamic evolution. The results demonstrates that the technique has a good power of discrimination and can be used for plant identification, as well as other complex pattern recognition tasks.

  2. Extraction of conjugate main-stream structures from a complex network flow

    NASA Astrophysics Data System (ADS)

    Tamura, Koutarou; Takayasu, Hideki; Takayasu, Misako

    2015-04-01

    We introduce a method to extract main-stream structures for a given complex network flow by trimming less effective links. As the resulting main streams generally have an almost loopless treelike structure, we can define the stream basin size for each node, which characterizes the importance of the node with regard to the flow. As a real-world example, we apply this method to an interfirm trading network, both for the money flow and its conjugate—the material or service flow—confirming that both basin size distributions follow a similar power law that differs significantly from the basin size distributions of rivers in nature. We theoretically analyze the process of trimming and derive a consistent statistical formulation between the original link number and the basin size.

  3. Index : A Rule Based Expert System For Computer Network Maintenance

    NASA Astrophysics Data System (ADS)

    Chaganty, Srinivas; Pitchai, Anandhi; Morgan, Thomas W.

    1988-03-01

    Communications is an expert intensive discipline. The application of expert systems for maintenance of large and complex networks, mainly as an aid in trouble shooting, can simplify the task of network management. The important steps involved in troubleshooting are fault detection, fault reporting, fault interpretation and fault isolation. At present, Network Maintenance Facilities are capable of detecting and reporting the faults to network personnel. Fault interpretation refers to the next step in the process, which involves coming up with reasons for the failure. Fault interpretation can be characterized in two ways. First, it involves such a diversity of facts that it is difficult to predict. Secondly, it embodies a wealth of knowledge in the form of network management personnel. The application of expert systems in these interpretive tasks is an important step towards automation of network maintenance. In this paper, INDEX (Intelligent Network Diagnosis Expediter), a rule based production system for computer network alarm interpretation is described. It acts as an intelligent filter for people analyzing network alarms. INDEX analyzes the alarms in the network and identifies proper maintenance action to be taken.The important feature of this production system is that it is data driven. Working memory is the principal data repository of production systems and its contents represent the current state of the problem. Control is based upon which productions match the constantly changing working memory elements. Implementation of the prototype is in OPS83. Major issues in rule based system development such as rule base organization, implementation and efficiency are discussed.

  4. Base flow of streams on Long Island, New York

    USGS Publications Warehouse

    Reynolds, Richard J.

    1982-01-01

    On Long Island, base flow under nonurbanized conditions constitutes 90 to 95% of total stream discharge. Base-flow data from 19 continuously gaged streams are presented as monthly mean and annual mean discharge for water years 1960-75, which includes the 1962-66 drought. The data were derived by hydrograph-separation procedures that isolate mean daily base flow from mean daily discharge. A close empirical relationship between annual mean base flow and stream discharge at the 55-% duration point facilities estimation of average base flow and can be used in place of the more time-consuming hydrograph-separation technique. These data are needed in calibration of computer models that will be used to predict the effects of hydrologic stresses, such as sewering, on the Long Island ground-water system. (USGS)

  5. Improving Student Engagement Using Course-Based Social Networks

    ERIC Educational Resources Information Center

    Imlawi, Jehad Mohammad

    2013-01-01

    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  6. Place-Based Attributes Predict Community Membership in a Mobile Phone Communication Network

    PubMed Central

    Caughlin, T. Trevor; Ruktanonchai, Nick; Acevedo, Miguel A.; Lopiano, Kenneth K.; Prosper, Olivia; Eagle, Nathan; Tatem, Andrew J.

    2013-01-01

    Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes. PMID:23451034

  7. Place-based attributes predict community membership in a mobile phone communication network.

    PubMed

    Caughlin, T Trevor; Ruktanonchai, Nick; Acevedo, Miguel A; Lopiano, Kenneth K; Prosper, Olivia; Eagle, Nathan; Tatem, Andrew J

    2013-01-01

    Social networks can be organized into communities of closely connected nodes, a property known as modularity. Because diseases, information, and behaviors spread faster within communities than between communities, understanding modularity has broad implications for public policy, epidemiology and the social sciences. Explanations for community formation in social networks often incorporate the attributes of individual people, such as gender, ethnicity or shared activities. High modularity is also a property of large-scale social networks, where each node represents a population of individuals at a location, such as call flow between mobile phone towers. However, whether or not place-based attributes, including land cover and economic activity, can predict community membership for network nodes in large-scale networks remains unknown. We describe the pattern of modularity in a mobile phone communication network in the Dominican Republic, and use a linear discriminant analysis (LDA) to determine whether geographic context can explain community membership. Our results demonstrate that place-based attributes, including sugar cane production, urbanization, distance to the nearest airport, and wealth, correctly predicted community membership for over 70% of mobile phone towers. We observed a strongly positive correlation (r = 0.97) between the modularity score and the predictive ability of the LDA, suggesting that place-based attributes can accurately represent the processes driving modularity. In the absence of social network data, the methods we present can be used to predict community membership over large scales using solely place-based attributes. PMID:23451034

  8. Networks based on collisions among mobile agents

    NASA Astrophysics Data System (ADS)

    González, Marta C.; Lind, Pedro G.; Herrmann, Hans J.

    2006-12-01

    We investigate in detail a recent model of colliding mobile agents [M.C. González, P.G. Lind, H.J. Herrmann, Phys. Rev. Lett. 96 (2006) 088702. cond-mat/0602091], used as an alternative approach for constructing evolving networks of interactions formed by collisions governed by suitable dynamical rules. The system of mobile agents evolves towards a quasi-stationary state which is, apart from small fluctuations, well characterized by the density of the system and the residence time of the agents. The residence time defines a collision rate, and by varying this collision rate, the system percolates at a critical value, with the emergence of a giant cluster whose critical exponents are the ones of two-dimensional percolation. Further, the degree and clustering coefficient distributions, and the average path length, show that the network associated with such a system presents non-trivial features which, depending on the collision rules, enables one not only to recover the main properties of standard networks, such as exponential, random and scale-free networks, but also to obtain other topological structures. To illustrate, we show a specific example where the obtained structure has topological features which characterize the structure and evolution of social networks accurately in different contexts, ranging from networks of acquaintances to networks of sexual contacts.

  9. Neural Network Based Intelligent Sootblowing System

    SciTech Connect

    Mark Rhode

    2005-04-01

    , particulate matter is also a by-product of coal combustion. Modern day utility boilers are usually fitted with electrostatic precipitators to aid in the collection of particulate matter. Although extremely efficient, these devices are sensitive to rapid changes in inlet mass concentration as well as total mass loading. Traditionally, utility boilers are equipped with devices known as sootblowers, which use, steam, water or air to dislodge and clean the surfaces within the boiler and are operated based upon established rule or operator's judgment. Poor sootblowing regimes can influence particulate mass loading to the electrostatic precipitators. The project applied a neural network intelligent sootblowing system in conjunction with state-of-the-art controls and instruments to optimize the operation of a utility boiler and systematically control boiler slagging/fouling. This optimization process targeted reduction of NOx of 30%, improved efficiency of 2% and a reduction in opacity of 5%. The neural network system proved to be a non-invasive system which can readily be adapted to virtually any utility boiler. Specific conclusions from this neural network application are listed below. These conclusions should be used in conjunction with the specific details provided in the technical discussions of this report to develop a thorough understanding of the process.

  10. Image-Based Structural Modeling of the Cardiac Purkinje Network

    PubMed Central

    Liu, Benjamin R.; Cherry, Elizabeth M.

    2015-01-01

    The Purkinje network is a specialized conduction system within the heart that ensures the proper activation of the ventricles to produce effective contraction. Its role during ventricular arrhythmias is less clear, but some experimental studies have suggested that the Purkinje network may significantly affect the genesis and maintenance of ventricular arrhythmias. Despite its importance, few structural models of the Purkinje network have been developed, primarily because current physical limitations prevent examination of the intact Purkinje network. In previous modeling efforts Purkinje-like structures have been developed through either automated or hand-drawn procedures, but these networks have been created according to general principles rather than based on real networks. To allow for greater realism in Purkinje structural models, we present a method for creating three-dimensional Purkinje networks based directly on imaging data. Our approach uses Purkinje network structures extracted from photographs of dissected ventricles and projects these flat networks onto realistic endocardial surfaces. Using this method, we create models for the combined ventricle-Purkinje system that can fully activate the ventricles through a stimulus delivered to the Purkinje network and can produce simulated activation sequences that match experimental observations. The combined models have the potential to help elucidate Purkinje network contributions during ventricular arrhythmias. PMID:26583120

  11. Resiliency of EEG-Based Brain Functional Networks

    PubMed Central

    Jalili, Mahdi

    2015-01-01

    Applying tools available in network science and graph theory to study brain networks has opened a new era in understanding brain mechanisms. Brain functional networks extracted from EEG time series have been frequently studied in health and diseases. In this manuscript, we studied failure resiliency of EEG-based brain functional networks. The network structures were extracted by analysing EEG time series obtained from 30 healthy subjects in resting state eyes-closed conditions. As the network structure was extracted, we measured a number of metrics related to their resiliency. In general, the brain networks showed worse resilient behaviour as compared to corresponding random networks with the same degree sequences. Brain networks had higher vulnerability than the random ones (P < 0.05), indicating that their global efficiency (i.e., communicability between the regions) is more affected by removing the important nodes. Furthermore, the breakdown happened as a result of cascaded failures in brain networks was severer (i.e., less nodes survived) as compared to randomized versions (P < 0.05). These results suggest that real EEG-based networks have not been evolved to possess optimal resiliency against failures. PMID:26295341

  12. Single- and two-phase flow in microfluidic porous media analogs based on Voronoi tessellation

    SciTech Connect

    Wu, Mengjie; Xiao, Feng; Johnson-Paben, Rebecca; Retterer, Scott T; Yin, Xiaolong; Neeves, Keith B

    2012-01-01

    The objective of this study was to create a microfluidic model of complex porous media for studying single and multiphase flows. Most experimental porous media models consist of periodic geometries that lend themselves to comparison with well-developed theoretical predictions. However, most real porous media such as geological formations and biological tissues contain a degree of randomness and complexity that is not adequately represented in periodic geometries. To design an experimental tool to study these complex geometries, we created microfluidic models of random homogeneous and heterogeneous networks based on Voronoi tessellations. These networks consisted of approximately 600 grains separated by a highly connected network of channels with an overall porosity of 0.11 0.20. We found that introducing heterogeneities in the form of large cavities within the network changed the permeability in a way that cannot be predicted by the classical porosity-permeability relationship known as the Kozeny equation. The values of permeability found in experiments were in excellent agreement with those calculated from three-dimensional lattice Boltzmann simulations. In two-phase flow experiments of oil displacement with water we found that the surface energy of channel walls determined the pattern of water invasion, while the network topology determined the residual oil saturation. These results suggest that complex network topologies lead to fluid flow behavior that is difficult to predict based solely on porosity. The microfluidic models developed in this study using a novel geometry generation algorithm based on Voronoi tessellation are a new experimental tool for studying fluid and solute transport problems within complex porous media.

  13. Space-Based Voice over IP Networks

    NASA Technical Reports Server (NTRS)

    Nguyen, Sam P.; Okino, Clayton; Walsh, William; Clare, Loren

    2007-01-01

    In human space exploration missions (e.g. a return to the Moon and for future missions to Mars), there will be a need to provide voice communications services. In this work we focus on the performance of Voice over IP (VoIP) techniques applied to space networks, where long range latencies, simplex links, and significant bit error rates occur. Link layer and network layer overhead issues are examined. Finally, we provide some discussion on issues related to voice conferencing in the space network environment.

  14. Network simulation of steady-state two-phase flow in consolidated porous media

    SciTech Connect

    Constantinides, G.N.; Payatakes, A.C.

    1996-02-01

    Multiphase flow in porous media is a complex process encountered in many fields of practical engineering interest, such as oil recovery from reservoir rocks, aquifer pollution by liquid wastes and soil reconstitution, and agricultural irrigation. A computer-aided simulator of steady-state two-phase flow in consolidated porous media is developed. The porous medium is modeled as a 3-D pore network of suitably shaped and randomly sized unit cells of the constricted-tube type. The problem of two-phase flow is solved using the network approach. The wetting phase saturation, the viscosity ratio, the capillary number, and the probability of coalescence between two colliding ganglia are changed systematically, where as the geometrical and topological characteristics of the porous medium and wettability (dynamic contact angles) are kept constant. In the range of the parameter values investigated, the flow behavior observed is ganglion population dynamics (intrinsically unsteady, but giving a time-averaged steady state). The mean ganglion size and fraction of the nonwetting phase in the form of stranded ganglia are studied as functions of the main dimensionless parameters. Fractional flows and relative permeabilities are determined and correlated with flow phenomena at pore level. Effects of the wetting phase saturation, the viscosity ratio, the capillary number, and the coalescence factor on relative permeabilities are examined.

  15. Tuning-free controller to accurately regulate flow rates in a microfluidic network

    NASA Astrophysics Data System (ADS)

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-03-01

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework.

  16. Tuning-free controller to accurately regulate flow rates in a microfluidic network.

    PubMed

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-01-01

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework. PMID:26987587

  17. Tuning-free controller to accurately regulate flow rates in a microfluidic network

    PubMed Central

    Heo, Young Jin; Kang, Junsu; Kim, Min Jun; Chung, Wan Kyun

    2016-01-01

    We describe a control algorithm that can improve accuracy and stability of flow regulation in a microfluidic network that uses a conventional pressure pump system. The algorithm enables simultaneous and independent control of fluid flows in multiple micro-channels of a microfluidic network, but does not require any model parameters or tuning process. We investigate robustness and optimality of the proposed control algorithm and those are verified by simulations and experiments. In addition, the control algorithm is compared with a conventional PID controller to show that the proposed control algorithm resolves critical problems induced by the PID control. The capability of the control algorithm can be used not only in high-precision flow regulation in the presence of disturbance, but in some useful functions for lab-on-a-chip devices such as regulation of volumetric flow rate, interface position control of two laminar flows, valveless flow switching, droplet generation and particle manipulation. We demonstrate those functions and also suggest further potential biological applications which can be accomplished by the proposed control framework. PMID:26987587

  18. Effect of passive flow-control devices on turbulent low-speed base flow

    NASA Astrophysics Data System (ADS)

    Heidari-Miandoab, Farid

    Some configurations of blunt trailing-edge airfoils are known to have a lower pressure drag compared to sharp trailing-edge airfoils. However, this advantage in addition to the structural advantage of a thick trailing-edge airfoil is offset by its high base drag. At subsonic velocities, this is attributed to the low-pressure base flow dominated by a Karman vortex street. In the limiting case, the steady separated flow over a rearward-facing step is attained if the periodically shed vortices from a blunt trailing-edge are suppressed by the addition of a base spiltter-plate. Experimental studies in the Old Dominion University Low-Speed Closed-Circuit Wind Tunnel were conducted to examine the effect of several passive flow-control devices such as Wheeler doublets and wishbone vortex generators, longitudinal surface grooves, base cavities, and serrations on the characteristics of two- and three-dimensional base flows. Flow over flat-plate airfoil and rearward-facing step models was studied in the turbulent incompressible subsonic flow regime. Models with trailing-edge and step-sweep angles of 0, 30, and 45 degrees with respect to the crossflow direction were considered. Constant-temperature hot-wire anemometry, infrared surface thermography, and pitot-static probes were used to conduct flow measurements. The parameters measured included vortex shedding frequency, convective heat-transfer rates, base pressure, and flow reattachment distance. Surveys of mean velocity profiles in the wake were also conducted. Results have shown that most of the flow control devices tested increased the base pressure of the 2-D and 3-D flat-plate airfoils. Use of longitudinal surface grooves resulted in shorter flow reattachment distances and higher convective heat transfer rates downstream of the 2-D rearward-facing steps.

  19. Zone-Based Routing Protocol for Wireless Sensor Networks

    PubMed Central

    Venkateswarlu Kumaramangalam, Muni; Adiyapatham, Kandasamy; Kandasamy, Chandrasekaran

    2014-01-01

    Extensive research happening across the globe witnessed the importance of Wireless Sensor Network in the present day application world. In the recent past, various routing algorithms have been proposed to elevate WSN network lifetime. Clustering mechanism is highly successful in conserving energy resources for network activities and has become promising field for researches. However, the problem of unbalanced energy consumption is still open because the cluster head activities are tightly coupled with role and location of a particular node in the network. Several unequal clustering algorithms are proposed to solve this wireless sensor network multihop hot spot problem. Current unequal clustering mechanisms consider only intra- and intercluster communication cost. Proper organization of wireless sensor network into clusters enables efficient utilization of limited resources and enhances lifetime of deployed sensor nodes. This paper considers a novel network organization scheme, energy-efficient edge-based network partitioning scheme, to organize sensor nodes into clusters of equal size. Also, it proposes a cluster-based routing algorithm, called zone-based routing protocol (ZBRP), for elevating sensor network lifetime. Experimental results show that ZBRP out-performs interims of network lifetime and energy conservation with its uniform energy consumption among the cluster heads.

  20. Research of home networking system based on XML/BACnet

    NASA Astrophysics Data System (ADS)

    Wang, Zhongming

    2008-11-01

    To standardize home networking information and simplify its management, this paper form a universal information module of various devices in home networking by adopting XML technology and BACnet protocol(XML/BACnet). Then, a software architecture of home networking based on this module is designed, having the function like auto management and maintenance, safety, real-time and remote controlling. Consequently, a home networking system based on this architecture is completed. Tested and evaluated, this system is one easy-using, easy-realizing, nice real-time system with strong heterogeneity and stable safety system.

  1. Balance between noise and information flow maximizes set complexity of network dynamics.

    PubMed

    Mäki-Marttunen, Tuomo; Kesseli, Juha; Nykter, Matti

    2013-01-01

    Boolean networks have been used as a discrete model for several biological systems, including metabolic and genetic regulatory networks. Due to their simplicity they offer a firm foundation for generic studies of physical systems. In this work we show, using a measure of context-dependent information, set complexity, that prior to reaching an attractor, random Boolean networks pass through a transient state characterized by high complexity. We justify this finding with a use of another measure of complexity, namely, the statistical complexity. We show that the networks can be tuned to the regime of maximal complexity by adding a suitable amount of noise to the deterministic Boolean dynamics. In fact, we show that for networks with Poisson degree distributions, all networks ranging from subcritical to slightly supercritical can be tuned with noise to reach maximal set complexity in their dynamics. For networks with a fixed number of inputs this is true for near-to-critical networks. This increase in complexity is obtained at the expense of disruption in information flow. For a large ensemble of networks showing maximal complexity, there exists a balance between noise and contracting dynamics in the state space. In networks that are close to critical the intrinsic noise required for the tuning is smaller and thus also has the smallest effect in terms of the information processing in the system. Our results suggest that the maximization of complexity near to the state transition might be a more general phenomenon in physical systems, and that noise present in a system may in fact be useful in retaining the system in a state with high information content. PMID:23516395

  2. Cointegration-based financial networks study in Chinese stock market

    NASA Astrophysics Data System (ADS)

    Tu, Chengyi

    2014-05-01

    We propose a method based on cointegration instead of correlation to construct financial complex network in Chinese stock market. The network is obtained starting from the matrix of p-value calculated by Engle-Granger cointegration test between all pairs of stocks. Then some tools for filtering information in complex network are implemented to prune the complete graph described by the above matrix, such as setting a level of statistical significance as a threshold and Planar Maximally Filtered Graph. We also calculate Partial Correlation Planar Graph of these stocks to compare the above networks. Last, we analyze these directed, weighted and non-symmetric networks by using standard methods of network analysis, including degree centrality, PageRank, HITS, local clustering coefficient, K-shell and strongly and weakly connected components. The results shed a new light on the underlying mechanisms and driving forces in a financial market and deepen our understanding of financial complex network.

  3. Network Analysis of the Evolution of Traffic Flow with Speed Information

    NASA Astrophysics Data System (ADS)

    Li, Xin-Gang; Gao, Zi-You; Zheng, Jian-Feng; Jia, Bin

    In the cellular automata traffic flow model, the traffic state can be represented by the discrete speed value of vehicles, thus the traffic flow can be deemed as a discrete dynamical system. In the evolution process of traffic flow, complex networks are constructed by representing the traffic state as node and the evolution relationship in timescale as link. The emerging times of link is defined as its weight, then the node strength is equal to the emerging times of the corresponding traffic state. As a result, a weighted network is obtained. The dynamics of stop-and-go traffic are studied by investigating the statistical properties of the network. Simulation results show that scale-free behavior commonly exists in the evolution process of stop-and-go traffic. The degree distribution, node strength distribution and link weight distribution have the power law form. The node with high degree also has large strength. The structure of the network is not influenced by the randomization probability and density as long as the stop-and-go traffic is reproduced.

  4. Principal curves for lumen center extraction and flow channel width estimation in 3-D arterial networks: theory, algorithm, and validation.

    PubMed

    Wong, Wilbur C K; So, Ronald W K; Chung, Albert C S

    2012-04-01

    We present an energy-minimization-based framework for locating the centerline and estimating the width of tubelike objects from their structural network with a nonparametric model. The nonparametric representation promotes simple modeling of nested branches and n -way furcations, i.e., structures that abound in an arterial network, e.g., a cerebrovascular circulation. Our method is capable of extracting the entire vascular tree from an angiogram in a single execution with a proper initialization. A succinct initial model from the user with arterial network inlets, outlets, and branching points is sufficient for complex vasculature. The novel method is based upon the theory of principal curves. In this paper, theoretical extension to grayscale angiography is discussed, and an algorithm to find an arterial network as principal curves is also described. Quantitative validation on a number of simulated data sets, synthetic volumes of 19 BrainWeb vascular models, and 32 Rotterdam Coronary Artery volumes was conducted. We compared the algorithm to a state-of-the-art method and further tested it on two clinical data sets. Our algorithmic outputs-lumen centers and flow channel widths-are important to various medical and clinical applications, e.g., vasculature segmentation, registration and visualization, virtual angioscopy, and vascular atlas formation and population study. PMID:22167625

  5. Optimization on a Network-based Parallel Computer System for Supersonic Laminar Wing Design

    NASA Technical Reports Server (NTRS)

    Garcia, Joseph A.; Cheung, Samson; Holst, Terry L. (Technical Monitor)

    1995-01-01

    A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.

  6. DFNWORKS: A discrete fracture network framework for modeling subsurface flow and transport

    NASA Astrophysics Data System (ADS)

    Hyman, Jeffrey D.; Karra, Satish; Makedonska, Nataliia; Gable, Carl W.; Painter, Scott L.; Viswanathan, Hari S.

    2015-11-01

    DFNWORKS is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at Los Alamos National Laboratory over the past five years, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers. The networks are created and meshed using DFNGEN, which combines FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LAGRIT meshing toolbox to create a high-quality computational mesh representation. The representation produces a conforming Delaunay triangulation suitable for high performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated in DFNFLOW, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within DFNTRANS to determine pathlines and solute transport through the DFN. Example applications of this suite in the areas of nuclear waste repository science, hydraulic fracturing and CO2 sequestration are also included.

  7. No Snow No Flow: How Montane Stream Networks Respond to Drought

    NASA Astrophysics Data System (ADS)

    Grant, G.; Nolin, A. W.; Selker, J. S.; Lewis, S.; Hempel, L. A.; Jefferson, A.; Walter, C.; Roques, C.

    2015-12-01

    Hydrologic extremes, such as drought, offer an exceptional opportunity to explore how runoff generation mechanisms and stream networks respond to changing precipitation regimes. The winter of 2014-2015 was the warmest on record in western Oregon, US, with record low snowpacks, and was followed by an anomalously warm, dry spring, resulting in historically low streamflows. But a year like 2015 is more than an outlier meteorological year. It provides a unique opportunity to test fundamental hypotheses for how montane hydrologic systems will respond to anticipated changes in amount and timing of recharge. In particular, the volcanic Cascade Mountains represent a "landscape laboratory" comprised of two distinct runoff regimes: the surface-flow dominated Western Cascade watersheds, with flashy streamflow regimes, rapid baseflow recession, and very low summer flows; and (b) the spring-fed High Cascade watersheds, with a slow-responding streamflow regime, and a long and sustained baseflow recession that maintains late summer streamflow through deep-groundwater contributions to high volume, coldwater springs. We hypothesize that stream network response to the extremely low snowpack and recharge varies sharply in these two regions. In surface flow dominated streams, the location of channel heads can migrate downstream, contracting the network longitudinally; wetted channel width and depth contract laterally as summer recession proceeds and flows diminish. In contrast, in spring-fed streams, channel heads "jump" to the next downstream spring when upper basin spring flow diminishes to zero. Downstream of flowing springs, wetted channel width and depth contract laterally as flows recede. To test these hypotheses, we conducted a field campaign to measure changing discharge, hydraulic geometry, and channel head location in both types of watersheds throughout the summer and early fall. Multiple cross-section sites were established on 6 streams representing both flow regime types

  8. Experimental demonstration of elastic optical networks based on enhanced software defined networking (eSDN) for data center application.

    PubMed

    Zhang, Jie; Yang, Hui; Zhao, Yongli; Ji, Yuefeng; Li, Hui; Lin, Yi; Li, Gang; Han, Jianrui; Lee, Young; Ma, Teng

    2013-11-01

    Due to the high burstiness and high-bandwidth characteristics of the applications, data center interconnection by elastic optical networks have attracted much attention of network operators and service providers. Many data center applications require lower delay and higher availability with the end-to-end guaranteed quality of service. In this paper, we propose and implement a novel elastic optical network based on enhanced software defined networking (eSDN) architecture for data center application, by introducing a transport-aware cross stratum optimization (TA-CSO) strategy. eSDN can enable cross stratum optimization of application and elastic optical network stratum resources and provide the elastic physical layer parameter adjustment, e.g., modulation format and bandwidth. We have designed and verified experimentally software defined path provisioning on our testbed with four real OpenFlow-enabled elastic optical nodes for data center application. The