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Sample records for network capsnet collects

  1. The Canadian Pediatric Surgery Network (CAPSNet): Lessons Learned from a National Registry Devoted to the Study of Congenital Diaphragmatic Hernia and Gastroschisis.

    Science.gov (United States)

    Butler, Alison E; Puligandla, Pramod S; Skarsgard, Erik D

    2015-12-01

    The Canadian Pediatric Surgery Network (CAPSNet) was created in 2005 by a geographically representative, multidisciplinary group of clinicians and researchers with the intent of establishing a national research registry for gastroschisis (GS) and congenital diaphragmatic hernia (CDH). Since then, CAPSNet has used this registry and its 16-center network to make contributions to the knowledge base informing best practices for GS and CDH care. More recently, CAPSNet has expanded its focus to include quality assurance and improvement at each of its sites, by issuing a benchmarked outcomes "report card" with its annual report. Finally, a major objective of CAPSNet has been to establish and adopt standardized, evidence-based practice guidelines for GS and CDH across all Canadian perinatal centers. Georg Thieme Verlag KG Stuttgart · New York.

  2. Collective network routing

    Science.gov (United States)

    Hoenicke, Dirk

    2014-12-02

    Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

  3. Collective network for computer structures

    Science.gov (United States)

    Blumrich, Matthias A [Ridgefield, CT; Coteus, Paul W [Yorktown Heights, NY; Chen, Dong [Croton On Hudson, NY; Gara, Alan [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Hoenicke, Dirk [Ossining, NY; Takken, Todd E [Brewster, NY; Steinmacher-Burow, Burkhard D [Wernau, DE; Vranas, Pavlos M [Bedford Hills, NY

    2011-08-16

    A system and method for enabling high-speed, low-latency global collective communications among interconnected processing nodes. The global collective network optimally enables collective reduction operations to be performed during parallel algorithm operations executing in a computer structure having a plurality of the interconnected processing nodes. Router devices ate included that interconnect the nodes of the network via links to facilitate performance of low-latency global processing operations at nodes of the virtual network and class structures. The global collective network may be configured to provide global barrier and interrupt functionality in asynchronous or synchronized manner. When implemented in a massively-parallel supercomputing structure, the global collective network is physically and logically partitionable according to needs of a processing algorithm.

  4. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  5. Collective fluctuations in networks of noisy components

    International Nuclear Information System (INIS)

    Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi

    2010-01-01

    Collective dynamics result from interactions among noisy dynamical components. Examples include heartbeats, circadian rhythms and various pattern formations. Because of noise in each component, collective dynamics inevitably involve fluctuations, which may crucially affect the functioning of the system. However, the relation between the fluctuations in isolated individual components and those in collective dynamics is not clear. Here, we study a linear dynamical system of networked components subjected to independent Gaussian noise and analytically show that the connectivity of networks determines the intensity of fluctuations in the collective dynamics. Remarkably, in general directed networks including scale-free networks, the fluctuations decrease more slowly with system size than the standard law stated by the central limit theorem. They even remain finite for a large system size when global directionality of the network exists. Moreover, such non-trivial behavior appears even in undirected networks when nonlinear dynamical systems are considered. We demonstrate it with a coupled oscillator system.

  6. Collective intelligent wireless sensor networks

    NARCIS (Netherlands)

    Mihaylov, M.; Nowe, A.; Tuyls, K.P.; Nijholt, A.; Pantic, M.

    2008-01-01

    In this paper we apply the COllective INtelligence (COIN) framework ofWolpert et al. toWireless Sensor Networks (WSNs) with the aim to increase the autonomous lifetime of the network in a decentralized manner. COIN describes how selfish agents can learn to optimize their own performance, so that the

  7. Collective stochastic coherence in recurrent neuronal networks

    Science.gov (United States)

    Sancristóbal, Belén; Rebollo, Beatriz; Boada, Pol; Sanchez-Vives, Maria V.; Garcia-Ojalvo, Jordi

    2016-09-01

    Recurrent networks of dynamic elements frequently exhibit emergent collective oscillations, which can show substantial regularity even when the individual elements are considerably noisy. How noise-induced dynamics at the local level coexists with regular oscillations at the global level is still unclear. Here we show that a combination of stochastic recurrence-based initiation with deterministic refractoriness in an excitable network can reconcile these two features, leading to maximum collective coherence for an intermediate noise level. We report this behaviour in the slow oscillation regime exhibited by a cerebral cortex network under dynamical conditions resembling slow-wave sleep and anaesthesia. Computational analysis of a biologically realistic network model reveals that an intermediate level of background noise leads to quasi-regular dynamics. We verify this prediction experimentally in cortical slices subject to varying amounts of extracellular potassium, which modulates neuronal excitability and thus synaptic noise. The model also predicts that this effectively regular state should exhibit noise-induced memory of the spatial propagation profile of the collective oscillations, which is also verified experimentally. Taken together, these results allow us to construe the high regularity observed experimentally in the brain as an instance of collective stochastic coherence.

  8. Control of collective network chaos.

    Science.gov (United States)

    Wagemakers, Alexandre; Barreto, Ernest; Sanjuán, Miguel A F; So, Paul

    2014-06-01

    Under certain conditions, the collective behavior of a large globally-coupled heterogeneous network of coupled oscillators, as quantified by the macroscopic mean field or order parameter, can exhibit low-dimensional chaotic behavior. Recent advances describe how a small set of "reduced" ordinary differential equations can be derived that captures this mean field behavior. Here, we show that chaos control algorithms designed using the reduced equations can be successfully applied to imperfect realizations of the full network. To systematically study the effectiveness of this technique, we measure the quality of control as we relax conditions that are required for the strict accuracy of the reduced equations, and hence, the controller. Although the effects are network-dependent, we show that the method is effective for surprisingly small networks, for modest departures from global coupling, and even with mild inaccuracy in the estimate of network heterogeneity.

  9. Optimal stabilization of Boolean networks through collective influence

    Science.gov (United States)

    Wang, Jiannan; Pei, Sen; Wei, Wei; Feng, Xiangnan; Zheng, Zhiming

    2018-03-01

    Boolean networks have attracted much attention due to their wide applications in describing dynamics of biological systems. During past decades, much effort has been invested in unveiling how network structure and update rules affect the stability of Boolean networks. In this paper, we aim to identify and control a minimal set of influential nodes that is capable of stabilizing an unstable Boolean network. For locally treelike Boolean networks with biased truth tables, we propose a greedy algorithm to identify influential nodes in Boolean networks by minimizing the largest eigenvalue of a modified nonbacktracking matrix. We test the performance of the proposed collective influence algorithm on four different networks. Results show that the collective influence algorithm can stabilize each network with a smaller set of nodes compared with other heuristic algorithms. Our work provides a new insight into the mechanism that determines the stability of Boolean networks, which may find applications in identifying virulence genes that lead to serious diseases.

  10. Global action networks: agents for collective action

    NARCIS (Netherlands)

    Glasbergen, P.

    2010-01-01

    Global action networks (GANs) are civil society initiated multi-stakeholder arrangements that aim to fulfill a leadership role for systemic change in global governance for sustainable development. The paper develops a network approach to study some of these GANs as motivators of global collective

  11. Collective frequency variation in network synchronization and reverse PageRank.

    Science.gov (United States)

    Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

    2016-04-01

    A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

  12. Collective frequency variation in network synchronization and reverse PageRank

    Science.gov (United States)

    Skardal, Per Sebastian; Taylor, Dane; Sun, Jie; Arenas, Alex

    2016-04-01

    A wide range of natural and engineered phenomena rely on large networks of interacting units to reach a dynamical consensus state where the system collectively operates. Here we study the dynamics of self-organizing systems and show that for generic directed networks the collective frequency of the ensemble is not the same as the mean of the individuals' natural frequencies. Specifically, we show that the collective frequency equals a weighted average of the natural frequencies, where the weights are given by an outflow centrality measure that is equivalent to a reverse PageRank centrality. Our findings uncover an intricate dependence of the collective frequency on both the structural directedness and dynamical heterogeneity of the network, and also reveal an unexplored connection between synchronization and PageRank, which opens the possibility of applying PageRank optimization to synchronization. Finally, we demonstrate the presence of collective frequency variation in real-world networks by considering the UK and Scandinavian power grids.

  13. Collective Dynamics in Physical and Social Networks

    Science.gov (United States)

    Isakov, Alexander

    We study four systems where individual units come together to display a range of collective behavior. First, we consider a physical system of phase oscillators on a network that expands the Kuramoto model to include oscillator-network interactions and the presence of noise: using a Hebbian-like learning rule, oscillators that synchronize in turn strengthen their connections to each other. We find that the average degree of connectivity strongly affects rates of flipping between aligned and anti-aligned states, and that this result persists to the case of complex networks. Turning to a fully multi-player, multi-strategy evolutionary dynamics model of cooperating bacteria that change who they give resources to and take resources from, we find several regimes that give rise to high levels of collective structure in the resulting networks. In this setting, we also explore the conditions in which an intervention that affects cooperation itself (e.g. "seeding the network with defectors") can lead to wiping out an infection. We find a non-monotonic connection between the percent of disabled cooperation and cure rate, suggesting that in some regimes a limited perturbation can lead to total population collapse. At a larger scale, we study how the locomotor system recovers after amputation in fruit flies. Through experiment and a theoretical model of multi-legged motion controlled by neural oscillators, we find that proprioception plays a role in the ability of flies to control leg forces appropriately to recover from a large initial turning bias induced by the injury. Finally, at the human scale, we consider a social network in a traditional society in Africa to understand how social ties lead to group formation for collective action (stealth raids). We identify critical and distinct roles for both leadership (important for catalyzing a group) and friendship (important for final composition). We conclude with prospects for future work.

  14. High-speed and high-fidelity system and method for collecting network traffic

    Science.gov (United States)

    Weigle, Eric H [Los Alamos, NM

    2010-08-24

    A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

  15. A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

    Science.gov (United States)

    Mao, Yuxin; Wei, Guiyi

    2010-01-01

    The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose. PMID:22163424

  16. A feedback-based secure path approach for wireless sensor network data collection.

    Science.gov (United States)

    Mao, Yuxin; Wei, Guiyi

    2010-01-01

    The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

  17. A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

    Directory of Open Access Journals (Sweden)

    Guiyi Wei

    2010-10-01

    Full Text Available The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

  18. Google Correlations: New approaches to collecting data for statistical network analysis

    Science.gov (United States)

    Mahdavi, Paasha

    This thesis introduces a new method for data collection on political elite networks using non-obtrusive web-based techniques. One possible indicator of elite connectivity is the frequency with which individuals appear at the same political events. Using a Google search scraping algorithm (Lee 2010) to capture how often pairs of individuals appear in the same news articles reporting on these events, I construct network matrices for a given list of individuals that I identify as elites using a variety of criteria. To assess cross-validity and conceptual accuracy, I compare data from this method to previously collected data on the network connectedness of three separate populations. I then supply an application of the Google method to collect network data on the Nigerian oil elite in 2012. Conducting a network analysis, I show that appointments to the Nigerian National Petroleum Corporation board of directors are made on the basis of political connectivity and not necessarily on technical experience or merit. These findings lend support to hypotheses that leaders use patronage appointments to lucrative bureaucratic positions in order to satisfy political elites. Given that many political theories on elite behavior aim to understand individual- and group-level interactions, the potential applicability of network data using the proposed technique is very large, especially in situations where collecting network data intrusively is costly or prohibitive.

  19. Planning logistics network for recyclables collection

    Directory of Open Access Journals (Sweden)

    Ratković Branislava

    2014-01-01

    Full Text Available Rapid urbanization, intensified industrialization, rise of income, and a more sophisticated form of consumerism are leading to an increase in the amount and toxicity of waste all over the world. Whether reused, recycled, incinerated or put into landfill sites, the management of household and industrial waste yield financial and environmental costs. This paper presents a modeling approach that can be used for designing one part of recycling logistics network through defining optimal locations of collection points, and possible optimal scheduling of vehicles for collecting recyclables. [Projekat Ministarstva nauke Republike Srbije, br. TR36005

  20. Networking Alone? Digital Communications and Collective Action in Vietnam

    Directory of Open Access Journals (Sweden)

    Sandra Kurfürst

    2015-01-01

    Full Text Available This article explores the potential for the formation of collective action in Vietnam. Referring to land and labour protests, bauxite mining, anti-China demonstrations, as well as the revision of the 1992 Constitution, the article examines the social movement repertoires diverse groups have adopted to reach their objectives. Drawing on social movement theory and communication power, this contribution shows that apart from access to the technology, citizens’ opportunities to participate in digital networks as well as access to the default communication network of the state are necessary prerequisites in order to attain public attention and possibly to achieve social change. Moreover, this article shows that existing power differentials in Vietnam are reproduced in digital space. It concludes that for different collective behaviours to result in a social movement, it is essential to “switch” and to connect the different networks. For the moment, the call to protect Vietnam’s sovereignty offers common ground for collective action.

  1. Novel Framework for Data Collection in Wireless Sensor Networks Using Flying Sensors

    DEFF Research Database (Denmark)

    Mathur, Prateek; Nielsen, Rasmus Hjorth; Prasad, Neeli R.

    2014-01-01

    This paper proposes a novel framework for data collection from a sensor network using flying sensor nodes. Efficient data communication within the network is a necessity as sensor nodes are usually energy constrained. The proposed framework utilizes the various entities forming the network...... for a different utility compared to their usual role in sensor networks. Use of flying sensor nodes is usually considered for conventional purpose of sensing and monitoring. Flying sensing nodes are usually utilized collectively in the form of an aerial sensor network, they are not expected to function as a data...... collection entity, as proposed in this framework. Similarly, cluster heads (CHs) are usually expected to transfer the aggregated data to an adjoining CH or to the base station (BS) directly. In the proposed framework the CH transfers data directly to the flying sensor node, averting the need for energy...

  2. Government information collections in the networked environment new issues and models

    CERN Document Server

    Cheverie, Joan F

    2013-01-01

    This insightful book explores the challenging issues related to effective access to government information.Amidst all the chaos of today's dynamic information transition period, the only constants related to government information are change and inconsistency, yet with Government Information Collections in the Networked Environment: New Issues and Models, you will defeat the challenging issues and take advantage of the opportunities that networked government information collections have to offer. This valuable book gives you a fresh opportunity to rethink collecting activities and to

  3. Applications of deep convolutional neural networks to digitized natural history collections

    Directory of Open Access Journals (Sweden)

    Eric Schuettpelz

    2017-11-01

    Full Text Available Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

  4. Applications of deep convolutional neural networks to digitized natural history collections.

    Science.gov (United States)

    Schuettpelz, Eric; Frandsen, Paul B; Dikow, Rebecca B; Brown, Abel; Orli, Sylvia; Peters, Melinda; Metallo, Adam; Funk, Vicki A; Dorr, Laurence J

    2017-01-01

    Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.

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

    Science.gov (United States)

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

    2018-04-01

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

  6. Forecasting Zakat collection using artificial neural network

    Science.gov (United States)

    Sy Ahmad Ubaidillah, Sh. Hafizah; Sallehuddin, Roselina

    2013-04-01

    'Zakat', "that which purifies" or "alms", is the giving of a fixed portion of one's wealth to charity, generally to the poor and needy. It is one of the five pillars of Islam, and must be paid by all practicing Muslims who have the financial means (nisab). 'Nisab' is the minimum level to determine whether there is a 'zakat' to be paid on the assets. Today, in most Muslim countries, 'zakat' is collected through a decentralized and voluntary system. Under this voluntary system, 'zakat' committees are established, which are tasked with the collection and distribution of 'zakat' funds. 'Zakat' promotes a more equitable redistribution of wealth, and fosters a sense of solidarity amongst members of the 'Ummah'. The Malaysian government has established a 'zakat' center at every state to facilitate the management of 'zakat'. The center has to have a good 'zakat' management system to effectively execute its functions especially in the collection and distribution of 'zakat'. Therefore, a good forecasting model is needed. The purpose of this study is to develop a forecasting model for Pusat Zakat Pahang (PZP) to predict the total amount of collection from 'zakat' of assets more precisely. In this study, two different Artificial Neural Network (ANN) models using two different learning algorithms are developed; Back Propagation (BP) and Levenberg-Marquardt (LM). Both models are developed and compared in terms of their accuracy performance. The best model is determined based on the lowest mean square error and the highest correlations values. Based on the results obtained from the study, BP neural network is recommended as the forecasting model to forecast the collection from 'zakat' of assets for PZP.

  7. Prioritized Degree Distribution in Wireless Sensor Networks with a Network Coded Data Collection Method

    Science.gov (United States)

    Wan, Jan; Xiong, Naixue; Zhang, Wei; Zhang, Qinchao; Wan, Zheng

    2012-01-01

    The reliability of wireless sensor networks (WSNs) can be greatly affected by failures of sensor nodes due to energy exhaustion or the influence of brutal external environment conditions. Such failures seriously affect the data persistence and collection efficiency. Strategies based on network coding technology for WSNs such as LTCDS can improve the data persistence without mass redundancy. However, due to the bad intermediate performance of LTCDS, a serious ‘cliff effect’ may appear during the decoding period, and source data are hard to recover from sink nodes before sufficient encoded packets are collected. In this paper, the influence of coding degree distribution strategy on the ‘cliff effect’ is observed and the prioritized data storage and dissemination algorithm PLTD-ALPHA is presented to achieve better data persistence and recovering performance. With PLTD-ALPHA, the data in sensor network nodes present a trend that their degree distribution increases along with the degree level predefined, and the persistent data packets can be submitted to the sink node according to its degree in order. Finally, the performance of PLTD-ALPHA is evaluated and experiment results show that PLTD-ALPHA can greatly improve the data collection performance and decoding efficiency, while data persistence is not notably affected. PMID:23235451

  8. Prioritized degree distribution in wireless sensor networks with a network coded data collection method.

    Science.gov (United States)

    Wan, Jan; Xiong, Naixue; Zhang, Wei; Zhang, Qinchao; Wan, Zheng

    2012-12-12

    The reliability of wireless sensor networks (WSNs) can be greatly affected by failures of sensor nodes due to energy exhaustion or the influence of brutal external environment conditions. Such failures seriously affect the data persistence and collection efficiency. Strategies based on network coding technology for WSNs such as LTCDS can improve the data persistence without mass redundancy. However, due to the bad intermediate performance of LTCDS, a serious 'cliff effect' may appear during the decoding period, and source data are hard to recover from sink nodes before sufficient encoded packets are collected. In this paper, the influence of coding degree distribution strategy on the 'cliff effect' is observed and the prioritized data storage and dissemination algorithm PLTD-ALPHA is presented to achieve better data persistence and recovering performance. With PLTD-ALPHA, the data in sensor network nodes present a trend that their degree distribution increases along with the degree level predefined, and the persistent data packets can be submitted to the sink node according to its degree in order. Finally, the performance of PLTD-ALPHA is evaluated and experiment results show that PLTD-ALPHA can greatly improve the data collection performance and decoding efficiency, while data persistence is not notably affected.

  9. Data Collection using Miniature Aerial Vehicles in Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Mathur, Prateek; Nielsen, Rasmus Hjorth; Prasad, Neeli R.

    2016-01-01

    Energy constraints of sensor nodes in wireless sensor networks (WSNs) is a major challenge and minimising the overall data transmitted across a network using data aggregation, distributed source coding, and compressive sensing have been proposed as mechanisms for energy saving. Similarly, use...... of mobile nodes capable of relocating within the network has been widely explored for energy saving. In this paper, we propose a novel method for using miniature aerial vehicles (MAVs) for data collection instead of actively sensing from a deployed network. The proposed mechanism is referred as Data...

  10. Collective Competence and Social Capital Analysis in Collaborative Networks

    Directory of Open Access Journals (Sweden)

    Janaina Macke

    2010-06-01

    Full Text Available The present paper addresses the issue of collective competence and social capital analysis for collaborative networks. The objective of the project is to understand how collaborative networks can be influenced considering the perspective of social capital and core competences. In this model we defend the emphasis on endogenous resources, once the technology is, in a general way, accessible to most of the companies and, therefore will not be a long term competitive advantage. The model shows that collaborative networks will be more competitive and successful if they invest in to core elements that are: organizational culture and people. Therefore, the model contributes for the researches in socio-organizational filed and provides a tool to evaluate collaborative networks.

  11. Branch-Based Centralized Data Collection for Smart Grids Using Wireless Sensor Networks

    OpenAIRE

    Kwangsoo Kim; Seong-il Jin

    2015-01-01

    A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network co...

  12. The United States Culture Collection Network (USCCN): Enhancing Microbial Genomics Research through Living Microbe Culture Collections

    Science.gov (United States)

    Boundy-Mills, Kyria; Hess, Matthias; Bennett, A. Rick; Ryan, Matthew; Kang, Seogchan; Nobles, David; Eisen, Jonathan A.; Inderbitzin, Patrik; Sitepu, Irnayuli R.; Torok, Tamas; Brown, Daniel R.; Cho, Juliana; Wertz, John E.; Mukherjee, Supratim; Cady, Sherry L.

    2015-01-01

    The mission of the United States Culture Collection Network (USCCN; http://usccn.org) is “to facilitate the safe and responsible utilization of microbial resources for research, education, industry, medicine, and agriculture for the betterment of human kind.” Microbial culture collections are a key component of life science research, biotechnology, and emerging global biobased economies. Representatives and users of several microbial culture collections from the United States and Europe gathered at the University of California, Davis, to discuss how collections of microorganisms can better serve users and stakeholders and to showcase existing resources available in public culture collections. PMID:26092453

  13. CPAC: Energy-Efficient Data Collection through Adaptive Selection of Compression Algorithms for Sensor Networks

    Science.gov (United States)

    Lee, HyungJune; Kim, HyunSeok; Chang, Ik Joon

    2014-01-01

    We propose a technique to optimize the energy efficiency of data collection in sensor networks by exploiting a selective data compression. To achieve such an aim, we need to make optimal decisions regarding two aspects: (1) which sensor nodes should execute compression; and (2) which compression algorithm should be used by the selected sensor nodes. We formulate this problem into binary integer programs, which provide an energy-optimal solution under the given latency constraint. Our simulation results show that the optimization algorithm significantly reduces the overall network-wide energy consumption for data collection. In the environment having a stationary sink from stationary sensor nodes, the optimized data collection shows 47% energy savings compared to the state-of-the-art collection protocol (CTP). More importantly, we demonstrate that our optimized data collection provides the best performance in an intermittent network under high interference. In such networks, we found that the selective compression for frequent packet retransmissions saves up to 55% energy compared to the best known protocol. PMID:24721763

  14. Droplet networks with incorporated protein diodes show collective properties

    Science.gov (United States)

    Maglia, Giovanni; Heron, Andrew J.; Hwang, William L.; Holden, Matthew A.; Mikhailova, Ellina; Li, Qiuhong; Cheley, Stephen; Bayley, Hagan

    2009-07-01

    Recently, we demonstrated that submicrolitre aqueous droplets submerged in an apolar liquid containing lipid can be tightly connected by means of lipid bilayers to form networks. Droplet interface bilayers have been used for rapid screening of membrane proteins and to form asymmetric bilayers with which to examine the fundamental properties of channels and pores. Networks, meanwhile, have been used to form microscale batteries and to detect light. Here, we develop an engineered protein pore with diode-like properties that can be incorporated into droplet interface bilayers in droplet networks to form devices with electrical properties including those of a current limiter, a half-wave rectifier and a full-wave rectifier. The droplet approach, which uses unsophisticated components (oil, lipid, salt water and a simple pore), can therefore be used to create multidroplet networks with collective properties that cannot be produced by droplet pairs.

  15. Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network

    Science.gov (United States)

    2015-12-24

    Optimal UAS Assignments and Trajectories for Persistent Surveillance and Data Collection from a Wireless Sensor Network DISSERTATION Nidal M. Jodeh...ASSIGNMENTS AND TRAJECTORIES FOR PERSISTENT SURVEILLANCE AND DATA COLLECTION FROM A WIRELESS SENSOR NETWORK DISSERTATION Presented to the Faculty...COLLECTION FROM A WIRELESS SENSOR NETWORK Nidal M. Jodeh, B.S., M.A.S., M.S. Lieutenant Colonel, USAF Committee Membership: Richard G. Cobb, PhD Chairman

  16. Collective Study On Security Threats In VOIP Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Zulkifl Hasan

    2017-01-01

    Full Text Available The Collective study will critically evaluate the voice over internet protocol VOIP Security threats issues amp challenges in the communication over the network the solution provided by different vendors. Authors will be discussing all security issues different protocols but main focus will be on SIP protocol its implementation and vendors VOIP security system.

  17. Data Collection Method for Mobile Control Sink Node in Wireless Sensor Network Based on Compressive Sensing

    Directory of Open Access Journals (Sweden)

    Ling Yongfa

    2016-01-01

    Full Text Available The paper proposes a mobile control sink node data collection method in the wireless sensor network based on compressive sensing. This method, with regular track, selects the optimal data collection points in the monitoring area via the disc method, calcu-lates the shortest path by using the quantum genetic algorithm, and hence determines the data collection route. Simulation results show that this method has higher network throughput and better energy efficiency, capable of collecting a huge amount of data with balanced energy consumption in the network.

  18. Collective multipartite Einstein-Podolsky-Rosen steering: more secure optical networks.

    Science.gov (United States)

    Wang, Meng; Gong, Qihuang; He, Qiongyi

    2014-12-01

    Collective multipartite Einstein-Podolsky-Rosen (EPR) steering is a type of quantum correlation shared among N parties, where the EPR paradox of one party can only be realized by performing local measurements on all the remaining N-1 parties. We formalize the collective tripartite steering in terms of local hidden state model and give the steering inequalities that act as signatures and suggest how to optimize collective tripartite steering in specific optical schemes. The special entangled states with property of collective multipartite steering may have potential applications in ultra-secure multiuser communication networks where the issue of trust is critical.

  19. Collective learning for the emergence of social norms in networked multiagent systems.

    Science.gov (United States)

    Yu, Chao; Zhang, Minjie; Ren, Fenghui

    2014-12-01

    Social norms such as social rules and conventions play a pivotal role in sustaining system order by regulating and controlling individual behaviors toward a global consensus in large-scale distributed systems. Systematic studies of efficient mechanisms that can facilitate the emergence of social norms enable us to build and design robust distributed systems, such as electronic institutions and norm-governed sensor networks. This paper studies the emergence of social norms via learning from repeated local interactions in networked multiagent systems. A collective learning framework, which imitates the opinion aggregation process in human decision making, is proposed to study the impact of agent local collective behaviors on the emergence of social norms in a number of different situations. In the framework, each agent interacts repeatedly with all of its neighbors. At each step, an agent first takes a best-response action toward each of its neighbors and then combines all of these actions into a final action using ensemble learning methods. Extensive experiments are carried out to evaluate the framework with respect to different network topologies, learning strategies, numbers of actions, influences of nonlearning agents, and so on. Experimental results reveal some significant insights into the manipulation and control of norm emergence in networked multiagent systems achieved through local collective behaviors.

  20. Citizen science networks in natural history and the collective validation of biodiversity data.

    Science.gov (United States)

    Turnhout, Esther; Lawrence, Anna; Turnhout, Sander

    2016-06-01

    Biodiversity data are in increasing demand to inform policy and management. A substantial portion of these data is generated in citizen science networks. To ensure the quality of biodiversity data, standards and criteria for validation have been put in place. We used interviews and document analysis from the United Kingdom and The Netherlands to examine how data validation serves as a point of connection between the diverse people and practices in natural history citizen science networks. We found that rather than a unidirectional imposition of standards, validation was performed collectively. Specifically, it was enacted in ongoing circulations of biodiversity records between recorders and validators as they jointly negotiated the biodiversity that was observed and the validity of the records. These collective validation practices contributed to the citizen science character or natural history networks and tied these networks together. However, when biodiversity records were included in biodiversity-information initiatives on different policy levels and scales, the circulation of records diminished. These initiatives took on a more extractive mode of data use. Validation ceased to be collective with important consequences for the natural history networks involved and citizen science more generally. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

  1. From social network (centralized vs. decentralized) to collective decision-making (unshared vs. shared consensus).

    Science.gov (United States)

    Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile

    2012-01-01

    Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones--star network vs. equal network--led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies.

  2. Joint Mobile Data Collection and Wireless Energy Transfer in Wireless Rechargeable Sensor Networks.

    Science.gov (United States)

    Zhong, Ping; Li, Ya-Ting; Liu, Wei-Rong; Duan, Gui-Hua; Chen, Ying-Wen; Xiong, Neal

    2017-08-16

    In wireless rechargeable sensor networks (WRSNs), there is a way to use mobile vehicles to charge node and collect data. It is a rational pattern to use two types of vehicles, one is for energy charging, and the other is for data collecting. These two types of vehicles, data collection vehicles (DCVs) and wireless charging vehicles (WCVs), are employed to achieve high efficiency in both data gathering and energy consumption. To handle the complex scheduling problem of multiple vehicles in large-scale networks, a twice-partition algorithm based on center points is proposed to divide the network into several parts. In addition, an anchor selection algorithm based on the tradeoff between neighbor amount and residual energy, named AS-NAE, is proposed to collect the zonal data. It can reduce the data transmission delay and the energy consumption for DCVs' movement in the zonal. Besides, we design an optimization function to achieve maximum data throughput by adjusting data rate and link rate of each node. Finally, the effectiveness of proposed algorithm is validated by numerical simulation results in WRSNs.

  3. Collecting Social Network Data from Mobile Phone SIM Cards

    Science.gov (United States)

    Peseckas, Ryan

    2016-01-01

    I used a subscriber identity module card reader to copy the lists of saved contacts from 170 mobile phones in Fiji. This approach has both advantages and disadvantages compared to other techniques for collecting telephone network data. Copying phone contacts avoids recall biases associated with survey-based name generators. It also obviates the…

  4. From social network (centralized vs. decentralized to collective decision-making (unshared vs. shared consensus.

    Directory of Open Access Journals (Sweden)

    Cédric Sueur

    Full Text Available Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones--star network vs. equal network--led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies.

  5. Collective Classification in Network Data

    OpenAIRE

    Sen, Prithviraj; Namata, Galileo; Bilgic, Mustafa; Getoor, Lise; University of Maryland; Galligher, Brian; Eliassi-Rad, Tina

    2008-01-01

    Many real-world applications produce networked data such as the world-wide web (hypertext documents connected via hyperlinks), social networks (for example, people connected by friendship links), communication networks (computers connected via communication links) and biological networks (for example, protein interaction networks). A recent focus in machine learning research has been to extend traditional machine learning classification techniques to classify nodes in such networks. In this a...

  6. Household food waste collection: Building service networks through neighborhood expansion.

    Science.gov (United States)

    Armington, William R; Chen, Roger B

    2018-04-17

    In this paper we develop a residential food waste collection analysis and modeling framework that captures transportation costs faced by service providers in their initial stages of service provision. With this framework and model, we gain insights into network transportation costs and investigate possible service expansion scenarios faced by these organizations. We solve a vehicle routing problem (VRP) formulated for the residential neighborhood context using a heuristic approach developed. The scenarios considered follow a narrative where service providers start with an initial neighborhood or community and expands to incorporate other communities and their households. The results indicate that increasing household participation, decreases the travel time and cost per household, up to a critical threshold, beyond which we see marginal time and cost improvements. Additionally, the results indicate different outcomes in expansion scenarios depending on the household density of incorporated neighborhoods. As household participation and density increases, the travel time per household in the network decreases. However, at approximately 10-20 households per km 2 , the decrease in travel time per household is marginal, suggesting a lowerbound household density threshold. Finally, we show in food waste collection, networks share common scaling effects with respect to travel time and costs, regardless of the number of nodes and links. Copyright © 2018 Elsevier Ltd. All rights reserved.

  7. 78 FR 3447 - Information Collection: Southern Alaska Sharing Network and Subsistence Study; Submitted for OMB...

    Science.gov (United States)

    2013-01-16

    ... local sharing networks that structure contemporary subsistence-cash economies using research methods... Collection: Southern Alaska Sharing Network and Subsistence Study; Submitted for OMB Review; Comment Request... conducting a survey on subsistence and sharing networks in coastal Alaska. This notice provides the public a...

  8. Saving energy for the data collection point in WBAN network

    Science.gov (United States)

    Nguyen-Duc, Toan; Kamioka, Eiji

    2017-11-01

    Wireless sensor networking (WSN) has been rapidly developed and become essential in various domains including health care systems. Such systems use WSN to collect real-time medical sensed data, aiming at improving the patient safety. For instance, patients suffered from adverse events, i.e., cardiac or respiratory arrests, are monitored so as to prevent them from getting harm. Sensors are placed on, in or near the patients' body to continuously collect sensing data such as the electrocardiograms, blood oxygenation, breathing, and heart rate. In this case, the sensors form a subcategory of WSN called wireless body area network (WBAN). In WBAN, sensing data are sent to one or more data collection points called personal server (PS). The role of PS is important since it forwards sensed data, to a medical server via a Bluetooth/WLAN connection in real time to support storage of information and real-time diagnosis, the device can also issue a notification of an emergency status. Since PS is a battery-based device, when its battery is empty, it will disconnect the sensed medical data with the rest network. To best of our knowledge, very few studies that focus on saving energy for the PS. To this end, this work investigates the trade-off between energy consumption for wireless communication and the amount of sensing data. An energy consumption model for wireless communication has been proposed based on direct measurement using real testbed. According to our findings, it is possible to save energy for the PS by selecting suitable wireless technology to be used based on the amount of data to be transmitted.

  9. Branch-Based Centralized Data Collection for Smart Grids Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kwangsoo Kim

    2015-05-01

    Full Text Available A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method.

  10. Branch-based centralized data collection for smart grids using wireless sensor networks.

    Science.gov (United States)

    Kim, Kwangsoo; Jin, Seong-il

    2015-05-21

    A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method.

  11. Uncovering collective listening habits and music genres in bipartite networks

    Science.gov (United States)

    Lambiotte, R.; Ausloos, M.

    2005-12-01

    In this paper, we analyze web-downloaded data on people sharing their music library, that we use as their individual musical signatures. The system is represented by a bipartite network, nodes being the music groups and the listeners. Music groups’ audience size behaves like a power law, but the individual music library size is an exponential with deviations at small values. In order to extract structures from the network, we focus on correlation matrices, that we filter by removing the least correlated links. This percolation idea-based method reveals the emergence of social communities and music genres, that are visualized by a branching representation. Evidence of collective listening habits that do not fit the neat usual genres defined by the music industry indicates an alternative way of classifying listeners and music groups. The structure of the network is also studied by a more refined method, based upon a random walk exploration of its properties. Finally, a personal identification-community imitation model for growing bipartite networks is outlined, following Potts ingredients. Simulation results do reproduce quite well the empirical data.

  12. On effective temperature in network models of collective behavior

    International Nuclear Information System (INIS)

    Porfiri, Maurizio; Ariel, Gil

    2016-01-01

    Collective behavior of self-propelled units is studied analytically within the Vectorial Network Model (VNM), a mean-field approximation of the well-known Vicsek model. We propose a dynamical systems framework to study the stochastic dynamics of the VNM in the presence of general additive noise. We establish that a single parameter, which is a linear function of the circular mean of the noise, controls the macroscopic phase of the system—ordered or disordered. By establishing a fluctuation–dissipation relation, we posit that this parameter can be regarded as an effective temperature of collective behavior. The exact critical temperature is obtained analytically for systems with small connectivity, equivalent to low-density ensembles of self-propelled units. Numerical simulations are conducted to demonstrate the applicability of this new notion of effective temperature to the Vicsek model. The identification of an effective temperature of collective behavior is an important step toward understanding order–disorder phase transitions, informing consistent coarse-graining techniques and explaining the physics underlying the emergence of collective phenomena.

  13. DC Collection Network Simulation for Offshore Wind Farms

    DEFF Research Database (Denmark)

    Vogel, Stephan; Rasmussen, Tonny Wederberg; El-Khatib, Walid Ziad

    2015-01-01

    The possibility to connect offshore wind turbines with a collection network based on Direct Current (DC), instead of Alternating Current (AC), gained attention in the scientific and industrial environment. There are many promising properties of DC components that could be beneficial such as......: smaller dimensions, less weight, fewer conductors, no reactive power considerations, and less overall losses due to the absence of proximity and skin effects. This work describes a study about the simulation of a Medium Voltage DC (MVDC) grid in an offshore wind farm. Suitable converter concepts...

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

    Science.gov (United States)

    Spitzer, W.

    2015-12-01

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

  15. Collective firing regularity of a scale-free Hodgkin–Huxley neuronal network in response to a subthreshold signal

    Energy Technology Data Exchange (ETDEWEB)

    Yilmaz, Ergin, E-mail: erginyilmaz@yahoo.com [Department of Biomedical Engineering, Engineering Faculty, Bülent Ecevit University, 67100 Zonguldak (Turkey); Ozer, Mahmut [Department of Electrical and Electronics Engineering, Engineering Faculty, Bülent Ecevit University, 67100 Zonguldak (Turkey)

    2013-08-01

    We consider a scale-free network of stochastic HH neurons driven by a subthreshold periodic stimulus and investigate how the collective spiking regularity or the collective temporal coherence changes with the stimulus frequency, the intrinsic noise (or the cell size), the network average degree and the coupling strength. We show that the best temporal coherence is obtained for a certain level of the intrinsic noise when the frequencies of the external stimulus and the subthreshold oscillations of the network elements match. We also find that the collective regularity exhibits a resonance-like behavior depending on both the coupling strength and the network average degree at the optimal values of the stimulus frequency and the cell size, indicating that the best temporal coherence also requires an optimal coupling strength and an optimal average degree of the connectivity.

  16. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections

    Science.gov (United States)

    de Vos, Marjon G. J.; Bollenbach, Tobias

    2017-01-01

    Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. PMID:28923953

  17. Modelling energy production by small hydro power plants in collective irrigation networks of Calabria (Southern Italy)

    Science.gov (United States)

    Zema, Demetrio Antonio; Nicotra, Angelo; Tamburino, Vincenzo; Marcello Zimbone, Santo

    2017-04-01

    The availability of geodetic heads and considerable water flows in collective irrigation networks suggests the possibility of recovery potential energy using small hydro power plants (SHPP) at sustainable costs. This is the case of many Water Users Associations (WUA) in Calabria (Southern Italy), where it could theoretically be possible to recovery electrical energy out of the irrigation season. However, very few Calabrian WUAs have currently built SHPP in their irrigation networks and thus in this region the potential energy is practically fully lost. A previous study (Zema et al., 2016) proposed an original and simple model to site turbines and size their power output as well as to evaluate profits of SHPP in collective irrigation networks. Applying this model at regional scale, this paper estimates the theoretical energy production and the economic performances of SHPP installed in collective irrigation networks of Calabrian WUAs. In more detail, based on digital terrain models processed by GIS and few parameters of the water networks, for each SHPP the model provides: (i) the electrical power output; (iii) the optimal water discharge; (ii) costs, revenues and profits. Moreover, the map of the theoretical energy production by SHPP in collective irrigation networks of Calabria was drawn. The total network length of the 103 water networks surveyed is equal to 414 km and the total geodetic head is 3157 m, of which 63% is lost due to hydraulic losses. Thus, a total power output of 19.4 MW could theoretically be installed. This would provide an annual energy production of 103 GWh, considering SHPPs in operation only out of the irrigation season. The single irrigation networks have a power output in the range 0.7 kW - 6.4 MW. However, the lowest SHPPs (that is, turbines with power output under 5 kW) have been neglected, because the annual profit is very low (on average less than 6%, Zema et al., 2016). On average each irrigation network provides an annual revenue from

  18. Model-free inference of direct network interactions from nonlinear collective dynamics.

    Science.gov (United States)

    Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

    2017-12-19

    The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

  19. The simplest maximum entropy model for collective behavior in a neural network

    International Nuclear Information System (INIS)

    Tkačik, Gašper; Marre, Olivier; Mora, Thierry; Amodei, Dario; Bialek, William; Berry II, Michael J

    2013-01-01

    Recent work emphasizes that the maximum entropy principle provides a bridge between statistical mechanics models for collective behavior in neural networks and experiments on networks of real neurons. Most of this work has focused on capturing the measured correlations among pairs of neurons. Here we suggest an alternative, constructing models that are consistent with the distribution of global network activity, i.e. the probability that K out of N cells in the network generate action potentials in the same small time bin. The inverse problem that we need to solve in constructing the model is analytically tractable, and provides a natural ‘thermodynamics’ for the network in the limit of large N. We analyze the responses of neurons in a small patch of the retina to naturalistic stimuli, and find that the implied thermodynamics is very close to an unusual critical point, in which the entropy (in proper units) is exactly equal to the energy. (paper)

  20. Collective Efficacy of a Regional Network: Extending the Social Embeddedness Perspective of Entrepreneurship

    OpenAIRE

    Muhammad, Nabeel; Léo-Paul, Dana

    2015-01-01

    Through participatory observation and in-depth interviews with members of the Memon community, in Pakistan, this paper probes into how the collective efforts of a regional network can facilitate entrepreneurship, social enterprises and regional development. The setting is a developing country that is lacking a large-scale entrepreneurial culture. Despite caste differences, Memons throughout the Karachi region meet and share experiences with other Memon members of their network – including Mem...

  1. Collective iteration behavior for online social networks

    Science.gov (United States)

    Liu, Jian-Guo; Li, Ren-De; Guo, Qiang; Zhang, Yi-Cheng

    2018-06-01

    Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users' online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the ego network. The empirical results show that there are robust social signatures of interactions no matter how friends change over time, which indicates that a stable commutation pattern exists in online communication. By comparing a random null model, we find the that commutation pattern is heterogeneous between ego and alters. Furthermore, in order to regenerate the pattern of the social signature, we present a preferential interaction model, which assumes that new users intend to look for the old users with strong ties while old users have tendency to interact with new friends. The experimental results show that the presented model can reproduce the heterogeneity of social signature by adjusting 2 parameters, the number of communicating targets m and the max number of interactions n, for Facebook users, m = n = 5, for Wiki users, m = 2 and n = 8. This work helps in deeply understanding the regularity of social signature.

  2. A cost-effective traffic data collection system based on the iDEN mobile telecommunication network.

    Science.gov (United States)

    2008-10-01

    This report describes a cost-effective data collection system for Caltrans 170 traffic signal : controller. The data collection system is based on TCP/IP communication over existing : low-cost mobile communication networks and Motorola iDEN1 mobile...

  3. Collective almost synchronisation in complex networks.

    Science.gov (United States)

    Baptista, Murilo S; Ren, Hai-Peng; Swarts, Johen C M; Carareto, Rodrigo; Nijmeijer, Henk; Grebogi, Celso

    2012-01-01

    This work introduces the phenomenon of Collective Almost Synchronisation (CAS), which describes a universal way of how patterns can appear in complex networks for small coupling strengths. The CAS phenomenon appears due to the existence of an approximately constant local mean field and is characterised by having nodes with trajectories evolving around periodic stable orbits. Common notion based on statistical knowledge would lead one to interpret the appearance of a local constant mean field as a consequence of the fact that the behaviour of each node is not correlated to the behaviours of the others. Contrary to this common notion, we show that various well known weaker forms of synchronisation (almost, time-lag, phase synchronisation, and generalised synchronisation) appear as a result of the onset of an almost constant local mean field. If the memory is formed in a brain by minimising the coupling strength among neurons and maximising the number of possible patterns, then the CAS phenomenon is a plausible explanation for it.

  4. Solution of weakly compressible isothermal flow in landfill gas collection networks

    Science.gov (United States)

    Nec, Y.; Huculak, G.

    2017-12-01

    Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy-Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein.

  5. Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Zhujie Chu

    2016-02-01

    Full Text Available Municipal household solid waste (MHSW has become a serious problem in China over the course of the last two decades, resulting in significant side effects to the environment. Therefore, effective management of MHSW has attracted wide attention from both researchers and practitioners. Separate collection, the first and crucial step to solve the MHSW problem, however, has not been thoroughly studied to date. An empirical survey has been conducted among 387 households in Harbin, China in this study. We use Bayesian Belief Networks model to determine the influencing factors on separate collection. Four types of factors are identified, including political, economic, social cultural and technological based on the PEST (political, economic, social and technological analytical method. In addition, we further analyze the influential power of different factors, based on the network structure and probability changes obtained by Netica software. Results indicate that technological dimension has the greatest impact on MHSW separate collection, followed by the political dimension and economic dimension; social cultural dimension impacts MHSW the least.

  6. Collective signaling behavior in a networked-oscillator model

    Science.gov (United States)

    Liu, Z.-H.; Hui, P. M.

    2007-09-01

    We propose and study the collective behavior of a model of networked signaling objects that incorporates several ingredients of real-life systems. These ingredients include spatial inhomogeneity with grouping of signaling objects, signal attenuation with distance, and delayed and impulsive coupling between non-identical signaling objects. Depending on the coupling strength and/or time-delay effect, the model exhibits completely, partially, and locally collective signaling behavior. In particular, a correlated signaling (CS) behavior is observed in which there exist time durations when nearly a constant fraction of oscillators in the system are in the signaling state. These time durations are much longer than the duration of a spike when a single oscillator signals, and they are separated by regular intervals in which nearly all oscillators are silent. Such CS behavior is similar to that observed in biological systems such as fireflies, cicadas, crickets, and frogs. The robustness of the CS behavior against noise is also studied. It is found that properly adjusting the coupling strength and noise level could enhance the correlated behavior.

  7. Solution of weakly compressible isothermal flow in landfill gas collection networks

    Energy Technology Data Exchange (ETDEWEB)

    Nec, Y [Thompson Rivers University, Kamloops, British Columbia (Canada); Huculak, G, E-mail: cranberryana@gmail.com, E-mail: greg@gnhconsulting.ca [GNH Consulting, Delta, British Columbia (Canada)

    2017-12-15

    Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy–Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein. (paper)

  8. Solution of weakly compressible isothermal flow in landfill gas collection networks

    International Nuclear Information System (INIS)

    Nec, Y; Huculak, G

    2017-01-01

    Pipe networks collecting gas in sanitary landfills operate under the regime of a weakly compressible isothermal flow of ideal gas. The effect of compressibility has been traditionally neglected in this application in favour of simplicity, thereby creating a conceptual incongruity between the flow equations and thermodynamic equation of state. Here the flow is solved by generalisation of the classic Darcy–Weisbach equation for an incompressible steady flow in a pipe to an ordinary differential equation, permitting continuous variation of density, viscosity and related fluid parameters, as well as head loss or gain due to gravity, in isothermal flow. The differential equation is solved analytically in the case of ideal gas for a single edge in the network. Thereafter the solution is used in an algorithm developed to construct the flow equations automatically for a network characterised by an incidence matrix, and determine pressure distribution, flow rates and all associated parameters therein. (paper)

  9. Raging Against the Machine: Network Gatekeeping and Collective Action on Social Media Platforms

    Directory of Open Access Journals (Sweden)

    Sarah Myers West

    2017-09-01

    Full Text Available Social media platforms act as networked gatekeepers—by ranking, channeling, promoting, censoring, and deleting content they hold power to facilitate or hinder information flows. One of the mechanisms they use is content moderation, or the enforcement of which content is allowed or disallowed on the platform. Though content moderation relies on users’ labor to identify content to delete, users have little capacity to influence content policies or enforcement. Despite this, some social media users are turning to collective action campaigns, redirecting information flows by subverting the activities of moderators, raising the visibility of otherwise hidden moderation practices, and organizing constituencies in opposition to content policies. Drawing on the example of the campaign to change Facebook’s nudity policy, this paper examines the strategies and tactics of users turning to collective action, considering which factors are most influential in determining the success or failure of a campaign. It finds that network gatekeeping salience is a good model for assessing which collective action efforts are most likely to be effective in achieving individual user goals. This indicates that the users who are already most able to harness the attention economy of social media platforms are more likely to successfully navigate the content moderation process. The analysis concludes by attending to what users might learn from the dynamics of network gatekeeping as they seek to resist the asymmetrical power relations of platforms.

  10. Indian Jute in Australian Collections: Forgetting and Recollecting Transnational Networks

    Directory of Open Access Journals (Sweden)

    Andrew Hassam

    2011-12-01

    Full Text Available Indian jute sacking played an essential role in Australian life for over 150 years, yet its contribution to Australian development and its Indian origins have been barely recognised in Australian public collections. What has Australian history gained by this erasing of jute from public memory? Wool, sugar and hop sacks are displayed in public collections as evidence of an Australian national story, but their national dimension depends on the cultural invisibility of jute and jute’s connections to the stories of other communities in other places. Developing an awareness of the contribution of Indian jute to the development of Australia requires an awareness not simply that jute comes from India but that the construction of national identity by collecting institutions relies on forgetting those transnational connections evident in their own collections. Where jute sacks have been preserved, it is because they are invested with memories of a collective way of life, yet in attempting to speak on behalf of the nation, the public museum denies more multidimensional models of cultural identity that are less linear and less place-based. If Indian jute is to be acknowledged as part of ‘the Australian story’, the concept of an Australian story must change and exhibitions need to explore, rather than ignore, transnational networks.

  11. Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network.

    Science.gov (United States)

    Han, Changcai; Yang, Jinsheng

    2017-10-30

    The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes.

  12. OzFlux data: network integration from collection to curation

    Directory of Open Access Journals (Sweden)

    P. Isaac

    2017-06-01

    Full Text Available Measurement of the exchange of energy and mass between the surface and the atmospheric boundary-layer by the eddy covariance technique has undergone great change in the last 2 decades. Early studies of these exchanges were confined to brief field campaigns in carefully controlled conditions followed by months of data analysis. Current practice is to run tower-based eddy covariance systems continuously over several years due to the need for continuous monitoring as part of a global effort to develop local-, regional-, continental- and global-scale budgets of carbon, water and energy. Efficient methods of processing the increased quantities of data are needed to maximise the time available for analysis and interpretation. Standardised methods are needed to remove differences in data processing as possible contributors to observed spatial variability. Furthermore, public availability of these data sets assists with undertaking global research efforts. The OzFlux data path has been developed (i to provide a standard set of quality control and post-processing tools across the network, thereby facilitating inter-site integration and spatial comparisons; (ii to increase the time available to researchers for analysis and interpretation by reducing the time spent collecting and processing data; (iii to propagate both data and metadata to the final product; and (iv to facilitate the use of the OzFlux data by adopting a standard file format and making the data available from web-based portals. Discovery of the OzFlux data set is facilitated through incorporation in FLUXNET data syntheses and the publication of collection metadata via the RIF-CS format. This paper serves two purposes. The first is to describe the data sets, along with their quality control and post-processing, for the other papers of this Special Issue. The second is to provide an example of one solution to the data collection and curation challenges that are encountered by similar flux

  13. Wireless Power Transfer and Data Collection in Wireless Sensor Networks

    OpenAIRE

    Li, Kai; Ni, Wei; Duan, Lingjie; Abolhasan, Mehran; Niu, Jianwei

    2017-01-01

    In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using Wireless Power Transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, while the other nodes waste their harvested energy, which is more than they need...

  14. The simplest problem in the collective dynamics of neural networks: is synchrony stable?

    International Nuclear Information System (INIS)

    Timme, Marc; Wolf, Fred

    2008-01-01

    For spiking neural networks we consider the stability problem of global synchrony, arguably the simplest non-trivial collective dynamics in such networks. We find that even this simplest dynamical problem—local stability of synchrony—is non-trivial to solve and requires novel methods for its solution. In particular, the discrete mode of pulsed communication together with the complicated connectivity of neural interaction networks requires a non-standard approach. The dynamics in the vicinity of the synchronous state is determined by a multitude of linear operators, in contrast to a single stability matrix in conventional linear stability theory. This unusual property qualitatively depends on network topology and may be neglected for globally coupled homogeneous networks. For generic networks, however, the number of operators increases exponentially with the size of the network. We present methods to treat this multi-operator problem exactly. First, based on the Gershgorin and Perron–Frobenius theorems, we derive bounds on the eigenvalues that provide important information about the synchronization process but are not sufficient to establish the asymptotic stability or instability of the synchronous state. We then present a complete analysis of asymptotic stability for topologically strongly connected networks using simple graph-theoretical considerations. For inhibitory interactions between dissipative (leaky) oscillatory neurons the synchronous state is stable, independent of the parameters and the network connectivity. These results indicate that pulse-like interactions play a profound role in network dynamical systems, and in particular in the dynamics of biological synchronization, unless the coupling is homogeneous and all-to-all. The concepts introduced here are expected to also facilitate the exact analysis of more complicated dynamical network states, for instance the irregular balanced activity in cortical neural networks

  15. Cacades: A reliable dissemination protocol for data collection sensor network

    Science.gov (United States)

    Peng, Y.; Song, W.; Huang, R.; Xu, M.; Shirazi, B.; LaHusen, R.; Pei, G.

    2009-01-01

    In this paper, we propose a fast and reliable data dissemination protocol Cascades to disseminate data from the sink(base station) to all or a subset of nodes in a data collection sensor network. Cascades makes use of the parentmonitor-children analogy to ensure reliable dissemination. Each node monitors whether or not its children have received the broadcast messages through snooping children's rebroadcasts or waiting for explicit ACKs. If a node detects a gap in its message sequences, it can fetch the missing messages from its neighbours reactively. Cascades also considers many practical issues for field deployment, such as dynamic topology, link/node failure, etc.. It therefore guarantees that a disseminated message from the sink will reach all intended receivers and the dissemination is terminated in a short time period. Notice that, all existing dissemination protocols either do not guarantee reliability or do not terminate [1, 2], which does not meet the requirement of real-time command control. We conducted experiment evaluations in both TOSSIM simulator and a sensor network testbed to compare Cascades with those existing dissemination protocols in TinyOS sensor networks, which show that Cascades achieves a higher degree of reliability, lower communication cost, and less delivery delay. ??2009 IEEE.

  16. Design of artificial neural networks using a genetic algorithm to predict collection efficiency in venturi scrubbers.

    Science.gov (United States)

    Taheri, Mahboobeh; Mohebbi, Ali

    2008-08-30

    In this study, a new approach for the auto-design of neural networks, based on a genetic algorithm (GA), has been used to predict collection efficiency in venturi scrubbers. The experimental input data, including particle diameter, throat gas velocity, liquid to gas flow rate ratio, throat hydraulic diameter, pressure drop across the venturi scrubber and collection efficiency as an output, have been used to create a GA-artificial neural network (ANN) model. The testing results from the model are in good agreement with the experimental data. Comparison of the results of the GA optimized ANN model with the results from the trial-and-error calibrated ANN model indicates that the GA-ANN model is more efficient. Finally, the effects of operating parameters such as liquid to gas flow rate ratio, throat gas velocity, and particle diameter on collection efficiency were determined.

  17. Collection, transfer and processing of information in systems of monitoring of objects based on wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Sergievskiy Maxim

    2016-01-01

    Full Text Available Monitoring of the aircraft structures’ during the pre-fiight testing is a critical task of the aerospace industry. One of the most promising solutions, not yet widely applied, is continuous monitoring of aircraft structures using wireless sensor network technology. The brief summary of the proposed system is the following: special sensors send signals to the local motes (autonomous computing device equipped with a wireless transmitter. Information from motes is gathered by routers which then transfer the aggregated information to the datacenter. Applications of corporate network control and define flexible patterns for processing of the information received from sensors. This network structure allows to centralize data collection modes in the process of testing; implement continuous data collection at a defined frequency; process and display data in real-time.

  18. Research on the Application of Wireless Network in Collecting Road Traffic Information

    Institute of Scientific and Technical Information of China (English)

    DU Hui-jiang

    2015-01-01

    Due to the characteristics of variability and dispersion in traffic information, to get the reliable real-time traffic information has been a bottleneck in the development of intelligent transportation systems. However, with the development of wireless network technology and mobile Internet, the mobile phones are rapidly developed and more popular, so it is possible to get road traffic information by locating the mobile phones in vehicles. The system structure for the road traffic information collection is designed based on wireless network and mobile phones in vehicles, and the vehicle recognition and its information computation methods are given and discussed. Also the simulation is done for vehicle recognition and computation based on fuzzy cluster analysis method and the results are obtained and analyzed.

  19. THE ART OF COLLECTING EXPERIMENTAL DATA INTERNATIONALLY: EXFOR, CINDA AND THE NRDC NETWORK

    International Nuclear Information System (INIS)

    HENRIKSSON, H.; SCHWERER, O.; ROCHMAN, D.; MIKHAYLYUKOVA, M.V.; OTUKA, N.

    2007-01-01

    The world-wide network of nuclear reaction data centers (NRDC) has, for about 40 years, provided data services to the scientific community. This network covers all types of nuclear reaction data, including neutron-induced, charged-particle-induced, and photonuclear data, used in a wide range of applications, such as fission reactors, accelerator driven systems, fusion facilities, nuclear medicine, materials analysis, environmental monitoring, and basic research. The now 13 nuclear data centers included in the NRDC are dividing the efforts of compilation and distribution for particular types of reactions and/or geographic regions all over the world. A central activity of the network is the collection and compilation of experimental nuclear reaction data and the related bibliographic information in the EXFOR and CINDA databases. Many of the individual data centers also distribute other types of nuclear data information, including evaluated data libraries, nuclear structure and decay data, and nuclear data reports. The network today ensures the world-wide transfer of information and coordinated evolution of an important source of nuclear data for current and future nuclear applications

  20. The art of collecting experimental data internationally: EXFOR, CINDA and the NRDC network

    International Nuclear Information System (INIS)

    Henriksson, H.; Schwerer, O.; Rochman, D.; Mikhaylyukova, M.V.; Otuka, N.

    2008-01-01

    The world-wide network of nuclear reaction data centres (NRDC) has, for about 40 years, provided data services to the scientific community. This network covers all types of nuclear reaction data, including neutron-induced, charged-particle-induced, and photonuclear data, used in a wide range of applications, such as fission reactors, accelerator driven systems, fusion facilities, nuclear medicine, materials analysis, environmental monitoring, and basic research. The now 13 nuclear data centres included in the NRDC are dividing the efforts of compilation and distribution for particular types of reactions and/or geographic regions all over the world. A central activity of the network is the collection and compilation of experimental nuclear reaction data and the related bibliographic information in the EXFOR and CINDA databases. Many of the individual data centres also distribute other types of nuclear data information, including evaluated data libraries, nuclear structure and decay data, and nuclear data reports. The network today ensures the world-wide transfer of information and coordinated evolution of an important source of nuclear data for current and future nuclear applications. (authors)

  1. Collecting sustainability data in different organisational settings of the European Farm Accountancy Data Network

    NARCIS (Netherlands)

    Vrolijk, H.C.J.; Poppe, K.J.; Keszthelyi, Szilard

    2016-01-01

    The European Farm Accountancy Data Network (FADN) collects detailed financial economic information on a sample of farms in Europe. These data are used intensively for the evaluation of the European Union’s Common Agricultural Policy. Owing to changes in policies, there is a need for a broader set of

  2. Addressing the Issue of Routing Unfairness in Opportunistic Backhaul Networks for Collecting Sensed Data

    Directory of Open Access Journals (Sweden)

    Tekenate E. Amah

    2017-12-01

    Full Text Available Widely deploying sensors in the environment and embedding them in physical objects is a crucial step towards realizing smart and sustainable cities. To cope with rising resource demands and limited budgets, opportunistic networks (OppNets offer a scalable backhaul option for collecting delay-tolerant data from sensors to gateways in order to enable efficient urban operations and services. While pervasive devices such as smartphones and tablets contribute significantly to the scalability of OppNets, closely following human movement patterns and social structure introduces network characteristics that pose routing challenges. Our study on the impact of these characteristics reveals that existing routing protocols subject a key set of devices to higher resource consumption, to which their users may respond by withdrawing participation. Unfortunately, existing solutions addressing this unfairness do not guarantee achievable throughput since they are not specifically designed for sensed data collection scenarios. Based on concepts derived from the study, we suggest design guidelines for adapting applicable routing protocols to sensed data collection scenarios. We also follow our design guidelines to propose the Fair Locality Aware Routing (FLARoute technique. Evaluating FLARoute within an existing routing protocol confirms improved fairness and throughput under conditions that compromise the performance of existing solutions.

  3. Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks.

    Science.gov (United States)

    Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A

    2016-10-26

    Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called "Collective Influence (CI)" has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes' significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct "virtual" information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes' importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community.

  4. NETWORK FOLKLORE AND ITS ROLE IN THE FORMATION OF A COLLECTIVE COGNITIVE SPACE

    Directory of Open Access Journals (Sweden)

    Anastasija Belovodskaja

    2014-04-01

    Full Text Available The global implementation of information-communicative technologies into every sphere of human activity is being accompanied by the emergence of new forms of communication, le­ading to inevitable changes in the means of both the representation and reception of information. In this respect, the field of interest encompasses research into modern anonymous network creative writing, which, as a result of the technological qualities of the Internet space, produces such texts that require particular skills in both comprehension and reproduction. In turn, the products of network folklore, as they spontaneously spread on the Internet, acquire the status of particular signs of a precedent nature. At the same time, the very nature of anonymous network creative writing—amusing and colloquial—raises the attractiveness of such texts and facilitates their reception, allowing them to be used for manipulative aims. The fact that such network folklore can influence the process of idea-formation in society is predetermined by the fact that, by definition, it is the milieu where collective representations are condensed and transmitted. Thus, network folklore is in the focus of attention not only in folklore studies, but is extremely topical for research in such fields as cognitive science, linguistic-cultural studies, public relations, speech effect, and any others which take interest in the processes of keeping, receiving, and transmitting information.

  5. Informal networks and resilience to climate change impacts: A collective approach to index insurance

    DEFF Research Database (Denmark)

    Trærup, Sara Lærke Meltofte

    2012-01-01

    This article contributes to the understanding of how to proceed with the development of index-insurance in order to reach extended population coverage with the insurance. The approach is applied to an example from a region in Tanzania. One of the main coping strategies that resource-poor households...... networks become insufficient since the majority of risk-sharers will be affected by the shock at the same time. This paper proposes a collective approach to index-insurance in which the members of an informal network will be insured as one insurance taker. The paper raises a conceptual argument...... that targeting households through existing informal networks will remove a number of prevailing barriers to the takeup of insurance and consequently the approach has the potential to increase households’ resilience to climate change impacts. The policy implications of the conclusions are significant since...

  6. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-31

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

  7. Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

    Science.gov (United States)

    Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

    2017-03-01

    We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

  8. Physical parameters collection based on wireless senor network

    Science.gov (United States)

    Chen, Xin; Wu, Hong; Ji, Lei

    2013-12-01

    With the development of sensor technology, wireless senor network has been applied in the medical, military, entertainment field and our daily life. But the existing available wireless senor networks applied in human monitoring system still have some problems, such as big power consumption, low security and so on. To improve senor network applied in health monitoring system, the paper introduces a star wireless senor networks based on msp430 and DSP. We design a low-cost heart-rate monitor senor node. The communication between senor node and sink node is realized according to the newest protocol proposed by the IEEE 802.15.6 Task Group. This wireless senor network will be more energy-efficient and faster compared to traditional senor networks.

  9. Collective Influence of Multiple Spreaders Evaluated by Tracing Real Information Flow in Large-Scale Social Networks

    Science.gov (United States)

    Teng, Xian; Pei, Sen; Morone, Flaviano; Makse, Hernán A.

    2016-01-01

    Identifying the most influential spreaders that maximize information flow is a central question in network theory. Recently, a scalable method called “Collective Influence (CI)” has been put forward through collective influence maximization. In contrast to heuristic methods evaluating nodes’ significance separately, CI method inspects the collective influence of multiple spreaders. Despite that CI applies to the influence maximization problem in percolation model, it is still important to examine its efficacy in realistic information spreading. Here, we examine real-world information flow in various social and scientific platforms including American Physical Society, Facebook, Twitter and LiveJournal. Since empirical data cannot be directly mapped to ideal multi-source spreading, we leverage the behavioral patterns of users extracted from data to construct “virtual” information spreading processes. Our results demonstrate that the set of spreaders selected by CI can induce larger scale of information propagation. Moreover, local measures as the number of connections or citations are not necessarily the deterministic factors of nodes’ importance in realistic information spreading. This result has significance for rankings scientists in scientific networks like the APS, where the commonly used number of citations can be a poor indicator of the collective influence of authors in the community. PMID:27782207

  10. FCJ-157 Still ‘Searching for Safety Online’: collective strategies and discursive resistance to trolling and harassment in a feminist network

    Directory of Open Access Journals (Sweden)

    Frances Shaw

    2013-12-01

    Full Text Available This paper examines the discursive responses that participants in a network of feminist blogs developed to handle trolling in their community. Internet communities develop strategies to deal with trolls in their networks. In particular, participants provide instructions and guidance to support each other to deal with trolls and harassment, and engage in intra-community discussion about the significance or insignificance of trolls. My paper explores the practices that feminist bloggers engage in to resist silencing practices, and the ways in which the silencing of female voices does not work in these contexts. I argue that trolling and discursive responses to trolls are collectively developed and enforced. Using a case study from my research into Australian feminist blogging networks, I argue that these networks have developed particular collective responses to trolls.

  11. Collective Learning in Games through Social Networks

    NARCIS (Netherlands)

    Kosterman, S.; Gierasimczuk, N.; Armentano, M.G.; Monteserin, A.; Tang, J.; Yannibelli, V.

    2015-01-01

    This paper argues that combining social networks communication and games can positively influence the learning behavior of players. We propose a computational model that combines features of social network learning (communication) and game-based learning (strategy reinforcement). The focus is on

  12. Collection Directions: The Evolution of Library Collections and Collecting

    Science.gov (United States)

    Dempsey, Lorcan; Malpas, Constance; Lavoie, Brian

    2014-01-01

    This article takes a broad view of the evolution of collecting behaviors in a network environment and suggests some future directions based on various simple models. The authors look at the changing dynamics of print collections, at the greater engagement with research and learning behaviors, and at trends in scholarly communication. The goal is…

  13. Development of a System to Collect Social Network Data from College Students for Future Studies in Health Behavior and Academic Performance /

    OpenAIRE

    Lah, Mike Myoungwhan

    2013-01-01

    Researchers study social networks to understand how individuals with similar behavior form clusters, and what causes them to do so. Universities are interested in learning more about influential factors of student behavior, including the impact that their social networks have on these behaviors. We have done foundational work to collect a dataset about UCSD student social network data gathered from Facebook and academic data from the UCSD Registrar. Once complete, the social network portion o...

  14. Wireless Visual Sensor Network Robots- Based for the Emulation of Collective Behavior

    Directory of Open Access Journals (Sweden)

    Fredy Hernán Martinez Sarmiento

    2012-03-01

    Full Text Available We consider the problem of bacterial quorum sensing emulate on small mobile robots. Robots that reflect the behavior of bacteria are designed as mobile wireless camera nodes. They are able to structure a dynamic wireless sensor network. Emulated behavior corresponds to a simplification of bacterial quorum sensing, where the action of a network node is conditioned by the population density of robots(nodes in a given area. The population density reading is done visually using a camera. The robot makes an estimate of the population density of the images, and acts according to this information. The operation of the camera is done with a custom firmware, reducing the complexity of the node without loss of performance. It was noted the route planning and the collective behavior of robots without the use of any other external or local communication. Neither was it necessary to develop a model system, precise state estimation or state feedback.

  15. Pragmatism, persistence and patience: a user perspective on strategies for data collection using popular online social networks.

    Science.gov (United States)

    Mannix, Judy; Wilkes, Lesley; Daly, John

    2014-01-01

    The increasing pervasiveness of the internet and social networking globally presents new opportunities and challenges for empirical social science researchers including those in nursing. Developments in computer-mediated communication are not static and there is potential for further advances and innovation in research methods embracing this technology. The aim of this paper is to present a reflexive account and critique of the use of social media as a means of data collection in a study that sought to explore the aesthetics of clinical leadership in contemporary nursing. In doing so, comparisons are drawn from using Twitter, Facebook and e-learning announcements as methods of recruitment and subsequent data collection via an online survey. The pragmatics of the internet and online social networks as vehicles for data collection are discussed. While questions remain about best practice to safeguard the scientific integrity of these approaches and the researchers and research participants who choose to participate, the potential exists for researchers to enhance and expand research methods without compromising rigour and validity. In the interests of sharpening thinking about this means of data collection dialogue and debate are needed on a range of research aspects including but not limited to pragmatics, new requirements in research training and development, legal and ethical guidelines and strengths and limitations encountered.

  16. Social network sites as a mode to collect health data: a systematic review.

    Science.gov (United States)

    Alshaikh, Fahdah; Ramzan, Farzan; Rawaf, Salman; Majeed, Azeem

    2014-07-14

    To date, health research literature has focused on social network sites (SNS) either as tools to deliver health care, to study the effect of these networks on behavior, or to analyze Web health content. Less is known about the effectiveness of these sites as a method for collecting data for health research and the means to use such powerful tools in health research. The objective of this study was to systematically review the available literature and explore the use of SNS as a mode of collecting data for health research. The review aims to answer four questions: Does health research employ SNS as method for collecting data? Is data quality affected by the mode of data collection? What types of participants were reached by SNS? What are the strengths and limitations of SNS? The literature was reviewed systematically in March 2013 by searching the databases MEDLINE, Embase, and PsycINFO, using the Ovid and PubMed interface from 1996 to the third week of March 2013. The search results were examined by 2 reviewers, and exclusion, inclusion, and quality assessment were carried out based on a pre-set protocol. The inclusion criteria were met by 10 studies and results were analyzed descriptively to answer the review questions. There were four main results. (1) SNS have been used as a data collection tool by health researchers; all but 1 of the included studies were cross-sectional and quantitative. (2) Data quality indicators that were reported include response rate, cost, timeliness, missing data/completion rate, and validity. However, comparison was carried out only for response rate and cost as it was unclear how other reported indicators were measured. (3) The most targeted population were females and younger people. (4) All studies stated that SNS is an effective recruitment method but that it may introduce a sampling bias. SNS has a role in health research, but we need to ascertain how to use it effectively without affecting the quality of research. The field of

  17. The data collection/data distribution center: building a sustainable African-American church-based research network.

    Science.gov (United States)

    Goldmon, Moses; Roberson, James T; Carey, Tim; Godley, Paul; Howard, Daniel L; Boyd, Carlton; Ammerman, Alice

    2008-01-01

    This article describes the Carolina-Shaw Partnership for the Elimination of Health Disparities efforts to engage a diverse group of Black churches in a sustainable network. We sought to develop a diverse network of 25 churches to work with the Carolina-Shaw Partnership to develop sustainable health disparities research, education, and intervention initiatives. Churches were selected based on location, pastoral buy-in, and capacity to engage. A purposive sampling technique was applied. (1) Collecting information on the location and characteristics of churches helps to identify and recruit churches that possess the desired qualities and characteristics. (2) The process used to identify, recruit, and select churches is time intensive. (3) The time, energy, and effort required managing an inter-institutional partnership and engage churches in health disparities research and interventions lends itself to sustainability. The development of a sustainable network of churches could lead to successful health disparities initiatives.

  18. Team performance and collective efficacy in the dynamic psychology of competitive team: a Bayesian network analysis.

    Science.gov (United States)

    Fuster-Parra, P; García-Mas, A; Ponseti, F J; Leo, F M

    2015-04-01

    The purpose of this paper was to discover the relationships among 22 relevant psychological features in semi-professional football players in order to study team's performance and collective efficacy via a Bayesian network (BN). The paper includes optimization of team's performance and collective efficacy using intercausal reasoning pattern which constitutes a very common pattern in human reasoning. The BN is used to make inferences regarding our problem, and therefore we obtain some conclusions; among them: maximizing the team's performance causes a decrease in collective efficacy and when team's performance achieves the minimum value it causes an increase in moderate/high values of collective efficacy. Similarly, we may reason optimizing team collective efficacy instead. It also allows us to determine the features that have the strongest influence on performance and which on collective efficacy. From the BN two different coaching styles were differentiated taking into account the local Markov property: training leadership and autocratic leadership. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Energy-Efficient Data Collection Method for Sensor Networks by Integrating Asymmetric Communication and Wake-Up Radio

    Directory of Open Access Journals (Sweden)

    Masanari Iwata

    2018-04-01

    Full Text Available In large-scale wireless sensor networks (WSNs, nodes close to sink nodes consume energy more quickly than other nodes due to packet forwarding. A mobile sink is a good solution to this issue, although it causes two new problems to nodes: (i overhead of updating routing information; and (ii increased operating time due to aperiodic query. To solve these problems, this paper proposes an energy-efficient data collection method, Sink-based Centralized transmission Scheduling (SC-Sched, by integrating asymmetric communication and wake-up radio. Specifically, each node is equipped with a low-power wake-up receiver. The sink node determines transmission scheduling, and transmits a wake-up message using a large transmission power, directly activating a pair of nodes simultaneously which will communicate with a normal transmission power. This paper further investigates how to deal with frame loss caused by fading and how to mitigate the impact of the wake-up latency of communication modules. Simulation evaluations confirm that using multiple channels effectively reduces data collection time and SC-Sched works well with a mobile sink. Compared with the conventional duty-cycling method, SC-Sched greatly reduces total energy consumption and improves the network lifetime by 7.47 times in a WSN with 4 data collection points and 300 sensor nodes.

  20. An Interactive, Mobile-Based Tool for Personal Social Network Data Collection and Visualization Among a Geographically Isolated and Socioeconomically Disadvantaged Population: Early-Stage Feasibility Study With Qualitative User Feedback.

    Science.gov (United States)

    Eddens, Katherine S; Fagan, Jesse M; Collins, Tom

    2017-06-22

    Personal social networks have a profound impact on our health, yet collecting personal network data for use in health communication, behavior change, or translation and dissemination interventions has proved challenging. Recent advances in social network data collection software have reduced the burden of network studies on researchers and respondents alike, yet little testing has occurred to discover whether these methods are: (1) acceptable to a variety of target populations, including those who may have limited experience with technology or limited literacy; and (2) practical in the field, specifically in areas that are geographically and technologically disconnected, such as rural Appalachian Kentucky. We explored the early-stage feasibility (Acceptability, Demand, Implementation, and Practicality) of using innovative, interactive, tablet-based network data collection and visualization software (OpenEddi) in field collection of personal network data in Appalachian Kentucky. A total of 168 rural Appalachian women who had previously participated in a study on the use of a self-collected vaginal swab (SCVS) for human papillomavirus testing were recruited by community-based nurse interviewers between September 2013 and August 2014. Participants completed egocentric network surveys via OpenEddi, which captured social and communication network influences on participation in, and recruitment to, the SCVS study. After study completion, we conducted a qualitative group interview with four nurse interviewers and two participants in the network study. Using this qualitative data, and quantitative data from the network study, we applied guidelines from Bowen et al to assess feasibility in four areas of early-stage development of OpenEddi: Acceptability, Demand, Implementation, and Practicality. Basic descriptive network statistics (size, edges, density) were analyzed using RStudio. OpenEddi was perceived as fun, novel, and superior to other data collection methods or tools

  1. A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chunyang Lei

    2016-07-01

    Full Text Available Super dense wireless sensor networks (WSNs have become popular with the development of Internet of Things (IoT, Machine-to-Machine (M2M communications and Vehicular-to-Vehicular (V2V networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

  2. A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks.

    Science.gov (United States)

    Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk

    2016-07-18

    Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

  3. Competition between Local Collisions and Collective Hydrodynamic Feedback Controls Traffic Flows in Microfluidic Networks

    Science.gov (United States)

    Belloul, M.; Engl, W.; Colin, A.; Panizza, P.; Ajdari, A.

    2009-05-01

    By studying the repartition of monodisperse droplets at a simple T junction, we show that the traffic of discrete fluid systems in microfluidic networks results from two competing mechanisms, whose significance is driven by confinement. Traffic is dominated by collisions occurring at the junction for small droplets and by collective hydrodynamic feedback for large ones. For each mechanism, we present simple models in terms of the pertinent dimensionless parameters of the problem.

  4. The Impact of Message Replication on the Performance of Opportunistic Networks for Sensed Data Collection

    Directory of Open Access Journals (Sweden)

    Tekenate E. Amah

    2017-11-01

    Full Text Available Opportunistic networks (OppNets provide a scalable solution for collecting delay‑tolerant data from sensors for their respective gateways. Portable handheld user devices contribute significantly to the scalability of OppNets since their number increases according to user population and they closely follow human movement patterns. Hence, OppNets for sensed data collection are characterised by high node population and degrees of spatial locality inherent to user movement. We study the impact of these characteristics on the performance of existing OppNet message replication techniques. Our findings reveal that the existing replication techniques are not specifically designed to cope with these characteristics. This raises concerns regarding excessive message transmission overhead and throughput degradations due to resource constraints and technological limitations associated with portable handheld user devices. Based on concepts derived from the study, we suggest design guidelines to augment existing message replication techniques. We also follow our design guidelines to propose a message replication technique, namely Locality Aware Replication (LARep. Simulation results show that LARep achieves better network performance under high node population and degrees of spatial locality as compared with existing techniques.

  5. Announced document collection of the 3rd information exchange meeting on radioactive waste disposal research network

    International Nuclear Information System (INIS)

    2008-03-01

    The 3rd meeting on 'Radioactive Waste Disposal Research Network' was held at the Ricotti techno community square of JAEA on September 3 and 4, 2007. The 'Radioactive Waste Disposal Research Network' was established in Interorganization Atomic Energy Research Program under academic collaborative agreement between Japan Atomic Energy Agency and the University of Tokyo. The objective is to bring both research infrastructures and human expertise in Japan to an adequate performance level, thereby contributing to the development of the fundamental research area in the field of radioactive waste disposal. This lecture material is a collection of presentations and discussions during the information exchange meeting. (author)

  6. A Greedy Scanning Data Collection Strategy for Large-Scale Wireless Sensor Networks with a Mobile Sink.

    Science.gov (United States)

    Zhu, Chuan; Zhang, Sai; Han, Guangjie; Jiang, Jinfang; Rodrigues, Joel J P C

    2016-09-06

    Mobile sink is widely used for data collection in wireless sensor networks. It can avoid 'hot spot' problems but energy consumption caused by multihop transmission is still inefficient in real-time application scenarios. In this paper, a greedy scanning data collection strategy (GSDCS) is proposed, and we focus on how to reduce routing energy consumption by shortening total length of routing paths. We propose that the mobile sink adjusts its trajectory dynamically according to the changes of network, instead of predetermined trajectory or random walk. Next, the mobile sink determines which area has more source nodes, then it moves toward this area. The benefit of GSDCS is that most source nodes are no longer needed to upload sensory data for long distances. Especially in event-driven application scenarios, when event area changes, the mobile sink could arrive at the new event area where most source nodes are located currently. Hence energy can be saved. Analytical and simulation results show that compared with existing work, our GSDCS has a better performance in specific application scenarios.

  7. The U.S. Culture Collection Network Responding to the Requirements of the Nagoya Protocol on Access and Benefit Sharing

    Directory of Open Access Journals (Sweden)

    Kevin McCluskey

    2017-08-01

    Full Text Available The U.S. Culture Collection Network held a meeting to share information about how culture collections are responding to the requirements of the recently enacted Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity (CBD. The meeting included representatives of many culture collections and other biological collections, the U.S. Department of State, U.S. Department of Agriculture, Secretariat of the CBD, interested scientific societies, and collection groups, including Scientific Collections International and the Global Genome Biodiversity Network. The participants learned about the policies of the United States and other countries regarding access to genetic resources, the definition of genetic resources, and the status of historical materials and genetic sequence information. Key topics included what constitutes access and how the CBD Access and Benefit-Sharing Clearing-House can help guide researchers through the process of obtaining Prior Informed Consent on Mutually Agreed Terms. U.S. scientists and their international collaborators are required to follow the regulations of other countries when working with microbes originally isolated outside the United States, and the local regulations required by the Nagoya Protocol vary by the country of origin of the genetic resource. Managers of diverse living collections in the United States described their holdings and their efforts to provide access to genetic resources. This meeting laid the foundation for cooperation in establishing a set of standard operating procedures for U.S. and international culture collections in response to the Nagoya Protocol.

  8. Applied network security monitoring collection, detection, and analysis

    CERN Document Server

    Sanders, Chris

    2013-01-01

    Applied Network Security Monitoring is the essential guide to becoming an NSM analyst from the ground up. This book takes a fundamental approach to NSM, complete with dozens of real-world examples that teach you the key concepts of NSM. Network security monitoring is based on the principle that prevention eventually fails. In the current threat landscape, no matter how much you try, motivated attackers will eventually find their way into your network. At that point, it is your ability to detect and respond to that intrusion that can be the difference between a small incident and a major di

  9. SCADA System for the Modeling and Optimization of Oil Collecting Pipeline Network: A Case Study of Hassi Messaoud Oilfield

    OpenAIRE

    M. Aouadj; F. Naceri; M. Touileb; D. Sellami; M. Boukhatem

    2015-01-01

    This study aims are data acquisition, control and online modeling of an oil collection pipeline network using a SCADA «Supervisory Control and Data Acquisition» system, allowing the optimization of this network in real time by creating more exact models of onsite facilities. Indeed, fast development of computing systems makes obsolete usage of old systems for which maintenance became more and more expensive and their performances don’t comply any more with modern company operations. SCADA sys...

  10. Integrated forward/reverse logistics network design under uncertainty with pricing for collection of used products

    DEFF Research Database (Denmark)

    Fattahi, Mohammad; Govindan, Kannan

    2017-01-01

    This paper addresses design and planning of an integrated forward/reverse logistics network over a planning horizon with multiple tactical periods. In the network, demand for new products and potential return of used products are stochastic. Furthermore, collection amounts of used products...... with different quality levels are assumed dependent on offered acquisition prices to customer zones. A uniform distribution function defines the expected price of each customer zone for one unit of each used product. Using two-stage stochastic programming, a mixed-integer linear programming model is proposed....... To cope with demand and potential return uncertainty, Latin Hypercube Sampling method is applied to generate fan of scenarios and then, backward scenario reduction technique is used to reduce the number of scenarios. Due to the problem complexity, a novel simulation-based simulated annealing algorithm...

  11. Agroecology in Europe: Research, Education, Collective Action Networks, and Alternative Food Systems

    Directory of Open Access Journals (Sweden)

    Alexander Wezel

    2018-04-01

    Full Text Available Agroecology is considered with different focus and weight in different parts of the world as a social and political movement, as science, and as practice. Despite its multitude of definitions, agroecology has begun in Europe to develop in different regional, national and continental networks of researchers, practitioners, advocates and movements. However, there is a lack of a comprehensive overview about these different developments and networks. Therefore, this paper attempts to document and provide a mapping of the development of European agroecology in its diverse forms. Through a literature review, interviews, active conference participation, and an extensive internet search we have collected information about the current state and development of agroecology in Europe. Agroecological research and higher education exist more in western and northern Europe, but farm schools and farmer-to-farmer training are also present in other regions. Today a large variety of topics are studied at research institutions. There is an increasing number of bottom-up agroecological initiatives and national or continental networks and movements. Important movements are around food sovereignty, access to land and seeds. Except for France, there are very few concrete policies for agroecology in Europe. Agroecology is increasingly linked to different fields of agri-food systems. This includes Community Supported Agriculture systems, but also agroecological territories, and some examples of labelling products. To amplify agroecology in Europe in the coming years, policy development will be crucial and proponents of agroecology must join forces and work hand-in-hand with the many stakeholders engaged in initiatives to develop more sustainable agriculture and food systems.

  12. A Structure Fidelity Approach for Big Data Collection in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mou Wu

    2014-12-01

    Full Text Available One of the most widespread and important applications in wireless sensor networks (WSNs is the continuous data collection, such as monitoring the variety of ambient temperature and humidity. Due to the sensor nodes with a limited energy supply, the reduction of energy consumed in the continuous observation of physical phenomenon plays a significant role in extending the lifetime of WSNs. However, the high redundancy of sensing data leads to great waste of energy as a result of over-deployed sensor nodes. In this paper, we develop a structure fidelity data collection (SFDC framework leveraging the spatial correlations between nodes to reduce the number of the active sensor nodes while maintaining the low structural distortion of the collected data. A structural distortion based on the image quality assessment approach is used to perform the nodes work/sleep scheduling, such that the number of the working nodes is reduced while the remainder of nodes can be put into the low-power sleep mode during the sampling period. The main contribution of SFDC is to provide a unique perspective on how to maintain the data fidelity in term of structural similarity in the continuous sensing applications for WSNs. The simulation results based on synthetic and real world datasets verify the effectiveness of SFDC framework both on energy saving and data fidelity.

  13. Older adolescents' motivations for social network site use: the influence of gender, group identity, and collective self-esteem.

    Science.gov (United States)

    Barker, Valerie

    2009-04-01

    This study assessed motives for social network site (SNS) use, group belonging, collective self-esteem, and gender effects among older adolescents. Communication with peer group members was the most important motivation for SNS use. Participants high in positive collective self-esteem were strongly motivated to communicate with peer group via SNS. Females were more likely to report high positive collective self-esteem, greater overall use, and SNS use to communicate with peers. Females also posted higher means for group-in-self, passing time, and entertainment. Negative collective self-esteem correlated with social compensation, suggesting that those who felt negatively about their social group used SNS as an alternative to communicating with other group members. Males were more likely than females to report negative collective self-esteem and SNS use for social compensation and social identity gratifications.

  14. Fragmenting networks by targeting collective influencers at a mesoscopic level

    Science.gov (United States)

    Kobayashi, Teruyoshi; Masuda, Naoki

    2016-11-01

    A practical approach to protecting networks against epidemic processes such as spreading of infectious diseases, malware, and harmful viral information is to remove some influential nodes beforehand to fragment the network into small components. Because determining the optimal order to remove nodes is a computationally hard problem, various approximate algorithms have been proposed to efficiently fragment networks by sequential node removal. Morone and Makse proposed an algorithm employing the non-backtracking matrix of given networks, which outperforms various existing algorithms. In fact, many empirical networks have community structure, compromising the assumption of local tree-like structure on which the original algorithm is based. We develop an immunization algorithm by synergistically combining the Morone-Makse algorithm and coarse graining of the network in which we regard a community as a supernode. In this way, we aim to identify nodes that connect different communities at a reasonable computational cost. The proposed algorithm works more efficiently than the Morone-Makse and other algorithms on networks with community structure.

  15. The Network Completion Problem: Inferring Missing Nodes and Edges in Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, M; Leskovec, J

    2011-11-14

    Network structures, such as social networks, web graphs and networks from systems biology, play important roles in many areas of science and our everyday lives. In order to study the networks one needs to first collect reliable large scale network data. While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomplete with nodes and edges missing. Commonly, only a part of the network can be observed and we would like to infer the unobserved part of the network. We address this issue by studying the Network Completion Problem: Given a network with missing nodes and edges, can we complete the missing part? We cast the problem in the Expectation Maximization (EM) framework where we use the observed part of the network to fit a model of network structure, and then we estimate the missing part of the network using the model, re-estimate the parameters and so on. We combine the EM with the Kronecker graphs model and design a scalable Metropolized Gibbs sampling approach that allows for the estimation of the model parameters as well as the inference about missing nodes and edges of the network. Experiments on synthetic and several real-world networks show that our approach can effectively recover the network even when about half of the nodes in the network are missing. Our algorithm outperforms not only classical link-prediction approaches but also the state of the art Stochastic block modeling approach. Furthermore, our algorithm easily scales to networks with tens of thousands of nodes.

  16. Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

    Science.gov (United States)

    Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

    2015-01-01

    Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915 measured samples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rate and heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08.

  17. Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters

    Science.gov (United States)

    Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

    2015-01-01

    Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915measuredsamples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rateand heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08. PMID:26624613

  18. The ecology of collective behavior.

    Directory of Open Access Journals (Sweden)

    Deborah M Gordon

    2014-03-01

    Full Text Available Similar patterns of interaction, such as network motifs and feedback loops, are used in many natural collective processes, probably because they have evolved independently under similar pressures. Here I consider how three environmental constraints may shape the evolution of collective behavior: the patchiness of resources, the operating costs of maintaining the interaction network that produces collective behavior, and the threat of rupture of the network. The ants are a large and successful taxon that have evolved in very diverse environments. Examples from ants provide a starting point for examining more generally the fit between the particular pattern of interaction that regulates activity, and the environment in which it functions.

  19. Road networks as collections of minimum cost paths

    Science.gov (United States)

    Wegner, Jan Dirk; Montoya-Zegarra, Javier Alexander; Schindler, Konrad

    2015-10-01

    We present a probabilistic representation of network structures in images. Our target application is the extraction of urban roads from aerial images. Roads appear as thin, elongated, partially curved structures forming a loopy graph, and this complex layout requires a prior that goes beyond standard smoothness and co-occurrence assumptions. In the proposed model the network is represented as a union of 1D paths connecting distant (super-)pixels. A large set of putative candidate paths is constructed in such a way that they include the true network as much as possible, by searching for minimum cost paths in the foreground (road) likelihood. Selecting the optimal subset of candidate paths is posed as MAP inference in a higher-order conditional random field. Each path forms a higher-order clique with a type of clique potential, which attracts the member nodes of cliques with high cumulative road evidence to the foreground label. That formulation induces a robust PN -Potts model, for which a global MAP solution can be found efficiently with graph cuts. Experiments with two road data sets show that the proposed model significantly improves per-pixel accuracies as well as the overall topological network quality with respect to several baselines.

  20. Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

    Science.gov (United States)

    Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

    2017-11-08

    Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

  1. Social Networks and Collective Intelligence: A Return to the Agora

    DEFF Research Database (Denmark)

    Mazzara, Manuel; Biselli, Luca; Greco, Pier Paolo

    2013-01-01

    backgrounds and institutes with significantly different agendas. Polidoxa aims at offering: 1) a trust-based search engine algorithm, which exploits stigmergic behaviours of users? network, 2) a trust-based social network, where the notion of trust derives from network activity and 3) a holonic system...... for bottom-up self-protection and social privacy. By presenting the Polidoxa solution, this work also describes the current state of traditional media as well as newer ones, providing an accurate analysis of major search engines such as Google and social network (e.g., Facebook). The advantages that Polidoxa...

  2. Collective navigation of complex networks: Participatory greedy routing.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Helbing, Dirk

    2017-06-06

    Many networks are used to transfer information or goods, in other words, they are navigated. The larger the network, the more difficult it is to navigate efficiently. Indeed, information routing in the Internet faces serious scalability problems due to its rapid growth, recently accelerated by the rise of the Internet of Things. Large networks like the Internet can be navigated efficiently if nodes, or agents, actively forward information based on hidden maps underlying these systems. However, in reality most agents will deny to forward messages, which has a cost, and navigation is impossible. Can we design appropriate incentives that lead to participation and global navigability? Here, we present an evolutionary game where agents share the value generated by successful delivery of information or goods. We show that global navigability can emerge, but its complete breakdown is possible as well. Furthermore, we show that the system tends to self-organize into local clusters of agents who participate in the navigation. This organizational principle can be exploited to favor the emergence of global navigability in the system.

  3. Cluster emergence and network evolution A longitudinal analysis of the inventor network in Sophia-Antipolis

    OpenAIRE

    Anne L. J. ter Wal

    2008-01-01

    Abstract It is increasingly acknowledged that clusters do not necessarily exhibit networks of local collective learning. This paper addresses the question under which conditions this is the case. Through a longitudinal case study of the business park Sophia-Antipolis it investigates how networks of collective learning emerged throughout the growth of the cluster. Network reconstruction with patent data shows that an innovation network emerged only in Information Technology, in whic...

  4. 77 FR 13135 - Agency Information Collection Activities: Submission for Review; Information Collection Request...

    Science.gov (United States)

    2012-03-05

    ... and network operational data for use in cyber security research and development through the... collection: Department of Homeland Security, Science & Technology Directorate, Cyber Security Division (CSD... DEPARTMENT OF HOMELAND SECURITY [Docket No. DHS-2012-0006] Agency Information Collection...

  5. 78 FR 54660 - Agency Information Collection Activities; Proposed Collection; Public Comment Request

    Science.gov (United States)

    2013-09-05

    ... efficiency; and improve patient outcomes. In each of these categories, specific indicators were designed to be reported through a performance monitoring Web site. Likely Respondents: Telehealth Network... quality, utility, and clarity of the information to be collected, and (4) the use of automated collection...

  6. Sonata: Query-Driven Network Telemetry

    KAUST Repository

    Gupta, Arpit; Harrison, Rob; Pawar, Ankita; Birkner, Rü diger; Canini, Marco; Feamster, Nick; Rexford, Jennifer; Willinger, Walter

    2017-01-01

    Operating networks depends on collecting and analyzing measurement data. Current technologies do not make it easy to do so, typically because they separate data collection (e.g., packet capture or flow monitoring) from analysis, producing either too much data to answer a general question or too little data to answer a detailed question. In this paper, we present Sonata, a network telemetry system that uses a uniform query interface to drive the joint collection and analysis of network traffic. Sonata takes the advantage of two emerging technologies---streaming analytics platforms and programmable network devices---to facilitate joint collection and analysis. Sonata allows operators to more directly express network traffic analysis tasks in terms of a high-level language. The underlying runtime partitions each query into a portion that runs on the switch and another that runs on the streaming analytics platform iteratively refines the query to efficiently capture only the traffic that pertains to the operator's query, and exploits sketches to reduce state in switches in exchange for more approximate results. Through an evaluation of a prototype implementation, we demonstrate that Sonata can support a wide range of network telemetry tasks with less state in the network, and lower data rates to streaming analytics systems, than current approaches can achieve.

  7. Sonata: Query-Driven Network Telemetry

    KAUST Repository

    Gupta, Arpit

    2017-05-02

    Operating networks depends on collecting and analyzing measurement data. Current technologies do not make it easy to do so, typically because they separate data collection (e.g., packet capture or flow monitoring) from analysis, producing either too much data to answer a general question or too little data to answer a detailed question. In this paper, we present Sonata, a network telemetry system that uses a uniform query interface to drive the joint collection and analysis of network traffic. Sonata takes the advantage of two emerging technologies---streaming analytics platforms and programmable network devices---to facilitate joint collection and analysis. Sonata allows operators to more directly express network traffic analysis tasks in terms of a high-level language. The underlying runtime partitions each query into a portion that runs on the switch and another that runs on the streaming analytics platform iteratively refines the query to efficiently capture only the traffic that pertains to the operator\\'s query, and exploits sketches to reduce state in switches in exchange for more approximate results. Through an evaluation of a prototype implementation, we demonstrate that Sonata can support a wide range of network telemetry tasks with less state in the network, and lower data rates to streaming analytics systems, than current approaches can achieve.

  8. Information theoretic description of networks

    Science.gov (United States)

    Wilhelm, Thomas; Hollunder, Jens

    2007-11-01

    We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rdictatorship network. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.

  9. Report on Asian Environment Information Network; 'Asia kankyo joho network' ni kansuru hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    The goal is the construction of Asian Environment Information Network (AEInet) in accordance with a contract signed between Indonesia's LIPI (Indonesian Institute of Science) and NEDO under NEDO's Research Cooperation Project Concerning the Development of Environment Measuring Laser Radar (LR). The network is so designed and constituted as to operate on a private line between Indonesia and Japan via IP (Internet protocol) and to enable the exchange on the Internet network of the data collected/analyzed by the Indonesian LR system and of articles of e-mail between scientists of the two countries. The AEInet will be utilized for the collection/analysis of LR-collected data; exchange of observed data and the result of processing; provision of support to environment information scientists in exchanging e-mail and information; and the search of databases for the implementation of the project. In this paper, the outline and functions of the system, network system design, WWW server construction, network operating status, joint researches with Indonesia, etc., are described. (NEDO)

  10. Surface-water data and statistics from U.S. Geological Survey data-collection networks in New Jersey on the World Wide Web

    Science.gov (United States)

    Reiser, Robert G.; Watson, Kara M.; Chang, Ming; Nieswand, Steven P.

    2002-01-01

    The U.S. Geological Survey (USGS), in cooperation with other Federal, State, and local agencies, operates and maintains a variety of surface-water data-collection networks throughout the State of New Jersey. The networks include streamflow-gaging stations, low-flow sites, crest-stage gages, tide gages, tidal creststage gages, and water-quality sampling sites. Both real-time and historical surface-water data for many of the sites in these networks are available at the USGS, New Jersey District, web site (http://nj.usgs.gov/), and water-quality data are available at the USGS National Water Information System (NWIS) web site (http://waterdata.usgs.gov/nwis/). These data are an important source of information for water managers, engineers, environmentalists, and private citizens.

  11. Determination of collective behavior of the financial market.

    Science.gov (United States)

    Li, Shouwei; Xu, Tao; He, Jianmin

    2016-01-01

    In this paper, we adopt the network synchronization to measure the collective behavior in the financial market, and then analyze the factors that affect the collective behavior. Based on the data from the Chinese financial market, we find that the clustering coefficient, the average shortest path length and the volatility fluctuation have a positive effect on the collective behavior respectively, while the average return has a negative effect on it; the effect of the average shortest path length on the collective behavior is the greatest in the above four variables; the above results are robust against the window size and the time interval between adjacent windows of the stock network; the effect of network structures and stock market properties on the collective behavior during the financial crisis is the same as those during other periods.

  12. Eu-social science: the role of internet social networks in the collection of bee biodiversity data.

    Directory of Open Access Journals (Sweden)

    Richard Stafford

    2010-12-01

    Full Text Available Monitoring change in species diversity, community composition and phenology is vital to assess the impacts of anthropogenic activity and natural change. However, monitoring by trained scientists is time consuming and expensive.Using social networks, we assess whether it is possible to obtain accurate data on bee distribution across the UK from photographic records submitted by untrained members of the public, and if these data are in sufficient quantity for ecological studies. We used Flickr and Facebook as social networks and Flickr for the storage of photographs and associated data on date, time and location linked to them. Within six weeks, the number of pictures uploaded to the Flickr BeeID group exceeded 200. Geographic coverage was excellent; the distribution of photographs covered most of the British Isles, from the south coast of England to the Highlands of Scotland. However, only 59% of photographs were properly uploaded according to instructions, with vital information such as 'tags' or location information missing from the remainder. Nevertheless, this incorporation of information on location of photographs was much higher than general usage on Flickr (∼13%, indicating the need for dedicated projects to collect spatial ecological data. Furthermore, we found identification of bees is not possible from all photographs, especially those excluding lower abdomen detail. This suggests that giving details regarding specific anatomical features to include on photographs would be useful to maximise success.The study demonstrates the power of social network sites to generate public interest in a project and details the advantages of using a group within an existing popular social network site over a traditional (specifically-designed web-based or paper-based submission process. Some advantages include the ability to network with other individuals or groups with similar interests, and thus increasing the size of the dataset and participation

  13. Real-Time Network Management

    National Research Council Canada - National Science Library

    Riolo, Joseph

    1998-01-01

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

  14. 76 FR 62756 - Agency Information Collection Activities: Proposed Collection; Comment Request-People's Garden...

    Science.gov (United States)

    2011-10-11

    ...: Proposed Collection; Comment Request--People's Garden Initiative Evaluation of Healthy Gardens Healthy... on proposed information collections. This is a new information for the ``Healthy Gardens, Healthy Youth Study,'' part of the USDA's People's Garden program. This study will use the network of...

  15. On the Design of Energy Efficient Optical Networks with Software Defined Networking Control Across Core and Access Networks

    DEFF Research Database (Denmark)

    Wang, Jiayuan; Yan, Ying; Dittmann, Lars

    2013-01-01

    This paper presents a Software Defined Networking (SDN) control plane based on an overlay GMPLS control model. The SDN control platform manages optical core networks (WDM/DWDM networks) and the associated access networks (GPON networks), which makes it possible to gather global information...... and enable wider areas' energy efficiency networking. The energy related information of the networks and the types of the traffic flows are collected and utilized for the end-to-end QoS provision. Dynamic network simulation results show that by applying different routing algorithms according to the type...... of traffic in the core networks, the energy efficiency of the network is improved without compromising the quality of service....

  16. The Analysis of Duocentric Social Networks: A Primer.

    Science.gov (United States)

    Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

    2015-02-01

    Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

  17. From Offline Social Networks to Online Social Networks: Changes in Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Yang SONG

    2015-01-01

    Full Text Available The paper reviewed studies of entrepreneurship based on the emergency of online social networks. Similar to offline social networks, entrepreneurs’ online social networks have their own unique characteristics. We first reviewed the offline network based research on entrepreneurship. Then we reviewed the studies of entrepreneurship in the context of online social networks including those focusing on topics of network structures and network ties. We highlighted online network communities based on the data collected from LinkedIn, Facebook and Twitter. Our research implies that both researcher and entrepreneurs are facing new opportunities due to the emergence of online social networks.

  18. A Comprehensive Study of Data Collection Schemes Using Mobile Sinks in Wireless Sensor Networks

    Science.gov (United States)

    Khan, Abdul Waheed; Abdullah, Abdul Hanan; Anisi, Mohammad Hossein; Bangash, Javed Iqbal

    2014-01-01

    Recently sink mobility has been exploited in numerous schemes to prolong the lifetime of wireless sensor networks (WSNs). Contrary to traditional WSNs where sensory data from sensor field is ultimately sent to a static sink, mobile sink-based approaches alleviate energy-holes issues thereby facilitating balanced energy consumption among nodes. In mobility scenarios, nodes need to keep track of the latest location of mobile sinks for data delivery. However, frequent propagation of sink topological updates undermines the energy conservation goal and therefore should be controlled. Furthermore, controlled propagation of sinks' topological updates affects the performance of routing strategies thereby increasing data delivery latency and reducing packet delivery ratios. This paper presents a taxonomy of various data collection/dissemination schemes that exploit sink mobility. Based on how sink mobility is exploited in the sensor field, we classify existing schemes into three classes, namely path constrained, path unconstrained, and controlled sink mobility-based schemes. We also organize existing schemes based on their primary goals and provide a comparative study to aid readers in selecting the appropriate scheme in accordance with their particular intended applications and network dynamics. Finally, we conclude our discussion with the identification of some unresolved issues in pursuit of data delivery to a mobile sink. PMID:24504107

  19. Distributed Joint Cluster Formation and Resource Allocation Scheme for Cooperative Data Collection in Virtual MIMO-Based M2M Networks

    Directory of Open Access Journals (Sweden)

    Xi Luan

    2015-01-01

    Full Text Available An efficient data collection scheme plays an important role for the real-time intelligent monitoring in many machine-to-machine (M2M networks. In this paper, a distributed joint cluster formation and resource allocation scheme for data collection in cluster-based M2M networks is proposed. Specifically, in order to utilize the advantages of cooperation, we first propose a hierarchical transmission model which contains two communication phases. In the first phase, the intracluster information sharing is carried out by all the nodes within the same cluster. Then these nodes transmit the total information to the BS cooperatively with virtual-MIMO (VMIMO protocol in the second phase. To grasp the properties and advantages of this cooperative transmission strategy, the theoretical analysis results are provided. The key issue in this system is to form the clusters and allocate resources efficiently. Since the optimization problem on this issue is an NP-hard problem, a feasible joint scheme for the cluster formation and resource allocation is proposed in this paper, which is carried out via coalition formation game with a distributed algorithm. This scheme can reduce the complexity while keeping an attractive performance. Simulation results show the properties of the proposed scheme and its advantages when comparing with the noncooperative scheme for the data collection in a practical scenario.

  20. The salience of social referents: a field experiment on collective norms and harassment behavior in a school social network.

    Science.gov (United States)

    Paluck, Elizabeth Levy; Shepherd, Hana

    2012-12-01

    Persistent, widespread harassment in schools can be understood as a product of collective school norms that deem harassment, and behavior allowing harassment to escalate, as typical and even desirable. Thus, one approach to reducing harassment is to change students' perceptions of these collective norms. Theory suggests that the public behavior of highly connected and chronically salient actors in a group, called social referents, may provide influential cues for individuals' perception of collective norms. Using repeated, complete social network surveys of a public high school, we demonstrate that changing the public behavior of a randomly assigned subset of student social referents changes their peers' perceptions of school collective norms and their harassment behavior. Social referents exert their influence over peers' perceptions of collective norms through the mechanism of everyday social interaction, particularly interaction that is frequent and personally motivated, in contrast to interaction shaped by institutional channels like shared classes. These findings clarify the development of collective social norms: They depend on certain patterns of and motivations for social interactions within groups across time, and are not static but constantly reshaped and reproduced through these interactions. Understanding this process creates opportunities for changing collective norms and behavior. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

  1. Linux Networking Cookbook

    CERN Document Server

    Schroder, Carla

    2008-01-01

    If you want a book that lays out the steps for specific Linux networking tasks, one that clearly explains the commands and configurations, this is the book for you. Linux Networking Cookbook is a soup-to-nuts collection of recipes that covers everything you need to know to perform your job as a Linux network administrator. You'll dive straight into the gnarly hands-on work of building and maintaining a computer network

  2. Searching for collective behavior in a large network of sensory neurons.

    Directory of Open Access Journals (Sweden)

    Gašper Tkačik

    2014-01-01

    Full Text Available Maximum entropy models are the least structured probability distributions that exactly reproduce a chosen set of statistics measured in an interacting network. Here we use this principle to construct probabilistic models which describe the correlated spiking activity of populations of up to 120 neurons in the salamander retina as it responds to natural movies. Already in groups as small as 10 neurons, interactions between spikes can no longer be regarded as small perturbations in an otherwise independent system; for 40 or more neurons pairwise interactions need to be supplemented by a global interaction that controls the distribution of synchrony in the population. Here we show that such "K-pairwise" models--being systematic extensions of the previously used pairwise Ising models--provide an excellent account of the data. We explore the properties of the neural vocabulary by: 1 estimating its entropy, which constrains the population's capacity to represent visual information; 2 classifying activity patterns into a small set of metastable collective modes; 3 showing that the neural codeword ensembles are extremely inhomogenous; 4 demonstrating that the state of individual neurons is highly predictable from the rest of the population, allowing the capacity for error correction.

  3. A Web GIS-Based Platform to Harvest Georeferenced Data from Social Networks: Examples of Data Collection Regarding Disaster Events

    Directory of Open Access Journals (Sweden)

    Cidália Costa Fonte

    2018-02-01

    Full Text Available Whenever disaster situations occur the civil protection authorities need to have fast access to data that may help to plan emergency response. To contribute to the collection and integration of all available data a platform that aims to harvest Volunteered Geographical Information (VGI from social networks and collaborative projects was created. This enables the integration of VGI with data coming from other sources, such as data collected by physical sensors in real time and made available through Applications Programming Interface (APIs, as well as, for example, official maps. The architecture of the created platform is described and its first prototype presented. Some example queries are performed and the results are analyzed.

  4. Collective Travel Planning in Spatial Networks

    KAUST Repository

    Shang, Shuo; Chen, Lisi; Wei, Zhewei; Jensen, Christian S.; Wen, Ji-Rong; Kalnis, Panos

    2017-01-01

    We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large

  5. Interconnected networks

    CERN Document Server

    2016-01-01

    This volume provides an introduction to and overview of the emerging field of interconnected networks which include multi layer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave – understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant – for example regarding diffusion, robustness and competition – the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

  6. automatic data collection design for neural networks detection

    African Journals Online (AJOL)

    Dr Obe

    Automated data collection is necessary to alleviate problems inherent in data collection for investigation ... (iv) Costs the employing organisation assets, ..... velocity (rate of cash flow over a period of time). ... Mining and Knowledge Discovery,.

  7. Networks of networks – An introduction

    International Nuclear Information System (INIS)

    Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

    2015-01-01

    Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

  8. Computer-communication networks

    CERN Document Server

    Meditch, James S

    1983-01-01

    Computer- Communication Networks presents a collection of articles the focus of which is on the field of modeling, analysis, design, and performance optimization. It discusses the problem of modeling the performance of local area networks under file transfer. It addresses the design of multi-hop, mobile-user radio networks. Some of the topics covered in the book are the distributed packet switching queuing network design, some investigations on communication switching techniques in computer networks and the minimum hop flow assignment and routing subject to an average message delay constraint

  9. Opportunistic Data Collection in Sparse Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Franceschinis Mirko

    2011-01-01

    Full Text Available Opportunistic wireless sensor networks (WSNs have recently been proposed as solutions for many remote monitoring problems. Many such problems, including environmental monitoring, involve large deployment scenarios with lower-than-average node density, as well as a long time scale and limited budgets. Traditional approaches designed for conventional situations, and thus not optimized for these scenarios, entail unnecessary complexity and larger costs. This paper discusses the issues related with the design and test of opportunistic architectures, and presents one possible solution—CHARON (Convergent Hybrid-replication Approach to Routing in Opportunistic Networks. Both algorithm-specific and comparative simulation results are presented, as well as real-world tests using a reference implementation. A comprehensive experimental setup was also used to seek a full characterization of the devised opportunistic approach including the derivation of a simple analytical model that is able to accurately predict the opportunistic message delivery performance in the used test bed.

  10. Home area networks

    NARCIS (Netherlands)

    Koonen, A.M.J.

    2013-01-01

    This article consists of a collection of slides from the author's conference presentation. Some of the specific areas/topics discussed include: Convergence in home networks, home service scenarios; Home wired network architectures, CapEx and OpEx; Residential Gateway; Optical fiber types;

  11. Network performance of a wireless sensor network for temperature monitoring in vineyards

    DEFF Research Database (Denmark)

    Liscano, Ramiro; Jacoub, John Khalil; Dersingh, Anand

    2011-01-01

    Wireless sensor networks (WSNs) are an emerging technology which can be used for outdoor environmental monitoring. This paper presents challenges that arose from the development and deployment of a WSN for environmental monitoring as well as network performance analysis of this network. Different...... components in our sensor network architecture are presented like the physical nodes, the sensor node code, and two messaging protocols; one for collecting sensor and network values and the other for sensor node commands. An information model for sensor nodes to support plug-and-play capabilities in sensor...... networks is also presented....

  12. 4th International Conference in Network Analysis

    CERN Document Server

    Koldanov, Petr; Pardalos, Panos

    2016-01-01

    The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The "Fourth International Conference in Network Analysis," held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis.

  13. Report on Asian Environment Information Network; 'Asia kankyo joho network' ni kansuru hokokusho

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    The goal is the construction of Asian Environment Information Network (AEInet) in accordance with a contract signed between Indonesia's LIPI (Indonesian Institute of Science) and NEDO under NEDO's Research Cooperation Project Concerning the Development of Environment Measuring Laser Radar (LR). The network is so designed and constituted as to operate on a private line between Indonesia and Japan via IP (Internet protocol) and to enable the exchange on the Internet network of the data collected/analyzed by the Indonesian LR system and of articles of e-mail between scientists of the two countries. The AEInet will be utilized for the collection/analysis of LR-collected data; exchange of observed data and the result of processing; provision of support to environment information scientists in exchanging e-mail and information; and the search of databases for the implementation of the project. In this paper, the outline and functions of the system, network system design, WWW server construction, network operating status, joint researches with Indonesia, etc., are described. (NEDO)

  14. Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

    Science.gov (United States)

    Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

    2015-12-01

    The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

  15. The Surge, Wave, and Tide Hydrodynamics (SWaTH) network of the U.S. Geological Survey—Past and future implementation of storm-response monitoring, data collection, and data delivery

    Science.gov (United States)

    Verdi, Richard J.; Lotspeich, R. Russell; Robbins, Jeanne C.; Busciolano, Ronald J.; Mullaney, John R.; Massey, Andrew J.; Banks, William S.; Roland, Mark A.; Jenter, Harry L.; Peppler, Marie C.; Suro, Thomas P.; Schubert, Christopher E.; Nardi, Mark R.

    2017-06-20

    After Hurricane Sandy made landfall along the northeastern Atlantic coast of the United States on October 29, 2012, the U.S. Geological Survey (USGS) carried out scientific investigations to assist with protecting coastal communities and resources from future flooding. The work included development and implementation of the Surge, Wave, and Tide Hydrodynamics (SWaTH) network consisting of more than 900 monitoring stations. The SWaTH network was designed to greatly improve the collection and timely dissemination of information related to storm surge and coastal flooding. The network provides a significant enhancement to USGS data-collection capabilities in the region impacted by Hurricane Sandy and represents a new strategy for observing and monitoring coastal storms, which should result in improved understanding, prediction, and warning of storm-surge impacts and lead to more resilient coastal communities.As innovative as it is, SWaTH evolved from previous USGS efforts to collect storm-surge data needed by others to improve storm-surge modeling, warning, and mitigation. This report discusses the development and implementation of the SWaTH network, and some of the regional stories associated with the landfall of Hurricane Sandy, as well as some previous events that informed the SWaTH development effort. Additional discussions on the mechanics of inundation and how the USGS is working with partners to help protect coastal communities from future storm impacts are also included.

  16. Organising collective reputation: An Ostromian perspective

    Directory of Open Access Journals (Sweden)

    Boldizsár Megyesi

    2016-09-01

    Full Text Available What do collective reputation and communal pastures have in common? Collective reputation is an important type of collective good produced by many business networks. We argue that it has the structure of a common-pool resource, which points to the relevance of Elinor Ostrom’s theory about the community governance of natural common-pool resources. After adapting the Ostromian framework to the phenomenon of collective reputation, we explore the experience of two groups of winemaking enterprises in Hungary who set up systems of quality assurance in order to protect and improve their joint reputation. We examine if the conditions identified by Ostrom as favourable for the self-governance of commons are also conducive to the governance of collective reputation. Our findings validate our conjecture that research on goal-oriented business networks may use insights from the mature theory of ‘governing the commons’. Potential pathways for further research are outlined.

  17. 75 FR 69671 - Agency Information Collection Activities: Proposed Collection; Comment Request

    Science.gov (United States)

    2010-11-15

    ... behavior. All 147 networked crisis centers will complete the Web-based Crisis Center Survey annually. The Survey requests information about organizational structure, staffing, scope of services, call center operations, quality assurance, community outreach/marketing, telephone equipment, data collection, and...

  18. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

  19. Automatic Data Collection Design for Neural Networks Detection of ...

    African Journals Online (AJOL)

    Automated data collection is necessary to alleviate problems inherent in data collection for investigation of management frauds. Once we have gathered a realistic data, several methods then exist for proper analysis and detection of anomalous transactions. However, in Nigeria, collecting fraudulent data is relatively difficult ...

  20. Dynamics of High-Resolution Networks

    DEFF Research Database (Denmark)

    Sekara, Vedran

    the unprecedented amounts of information collected by mobile phones to gain detailed insight into the dynamics of social systems. This dissertation presents an unparalleled data collection campaign, collecting highly detailed traces for approximately 1000 people over the course of multiple years. The availability...... are we all affected by an ever changing network structure? Answering these questions will enrich our understanding of ourselves, our organizations, and our societies. Yet, mapping the dynamics of social networks has traditionally been an arduous undertaking. Today, however, it is possible to use...... of such dynamic maps allows us to probe the underlying social network and understand how individuals interact and form lasting friendships. More importantly, these highly detailed dynamic maps provide us new perspectives at traditional problems and allow us to quantify and predict human life....

  1. Network of Green Areas within Collective Housing Communities - Case Study from Timişoara, Romania

    Science.gov (United States)

    Branea, Ana-Maria; Stelian Găman, Marius; Bădescu, Ştefana

    2017-10-01

    Green areas have always been an essential feature of urban developments, improving the quality of life within a community, both from a social perspective - offering residents a place for relaxation and interaction, as well as from the point of view of disease prevention - improving the overall air quality, but also encouraging inhabitants to spend more time outside. The importance of these areas within a settlement further increases in the present-day context, in which the constant expansion of cities in their surrounding territory, phenomenon known as “urban sprawl”, gradually eliminates the natural green spaces and agricultural terrains from our landscape. This trend has devastating effects on the environment, as well as on the micro-climate of our settlements, characterized, in recent years, by the formation of heat islands within the built tissue. Moreover, the disappearance of natural green areas leads to the constant estrangement of the inhabitants, and especially of young generations, from the natural values and realities. It is thus more important than ever to ensure an adequate percentage of green areas for our cities, uniformly distributed within the urban tissue. Green belts, urban forests, parks, green squares or even urban gardens - all these entities play their parts within the urban green network, having certain radiuses of influence and attraction and thus occupying a specific position within the urban hierarchy. In Romania, the terrains left un-built between the collective housing buildings - or apartment blocks, erected during the communist administration and currently constituting public property, have a huge potential regarding the matter of urban greenery, being easily transformed into active and qualitative green areas. However, the local authorities lack the resources (both financial and in terms of human resources) to efficiently develop and then administrate these areas, which are consequently either abandoned, or used as illegal

  2. On the Security of Data Collection and Transmission from Wireless Sensor Networks in the Context of Internet of Things

    OpenAIRE

    Yu, Hong; He, Jingsha; Liu, Ruohong; Ji, Dajie

    2013-01-01

    In the context of Internet of Things (IoT), multiple cooperative nodes in wireless sensor networks (WSNs) can be used to monitor an event, jointly generate a report and then send it to one or more Internet nodes for further processing. A primary security requirement in such applications is that every event data report be authenticated to intended Internet users and effectively filtered on its way to the Internet users to realize the security of data collection and transmission from the WSN. H...

  3. Metro Optical Networks for Homeland Security

    Science.gov (United States)

    Bechtel, James H.

    Metro optical networks provide an enticing opportunity for strengthening homeland security. Many existing and emerging fiber-optic networks can be adapted for enhanced security applications. Applications include airports, theme parks, sports venues, and border surveillance systems. Here real-time high-quality video and captured images can be collected, transported, processed, and stored for security applications. Video and data collection are important also at correctional facilities, courts, infrastructure (e.g., dams, bridges, railroads, reservoirs, power stations), and at military and other government locations. The scaling of DWDM-based networks allows vast amounts of data to be collected and transported including biometric features of individuals at security check points. Here applications will be discussed along with potential solutions and challenges. Examples of solutions to these problems are given. This includes a discussion of metropolitan aggregation platforms for voice, video, and data that are SONET compliant for use in SONET networks and the use of DWDM technology for scaling and transporting a variety of protocols. Element management software allows not only network status monitoring, but also provides optimized allocation of network resources through the use of optical switches or electrical cross connects.

  4. Operating systems and network protocols for wireless sensor networks.

    Science.gov (United States)

    Dutta, Prabal; Dunkels, Adam

    2012-01-13

    Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

  5. Inference on network statistics by restricting to the network space: applications to sexual history data.

    Science.gov (United States)

    Goyal, Ravi; De Gruttola, Victor

    2018-01-30

    Analysis of sexual history data intended to describe sexual networks presents many challenges arising from the fact that most surveys collect information on only a very small fraction of the population of interest. In addition, partners are rarely identified and responses are subject to reporting biases. Typically, each network statistic of interest, such as mean number of sexual partners for men or women, is estimated independently of other network statistics. There is, however, a complex relationship among networks statistics; and knowledge of these relationships can aid in addressing concerns mentioned earlier. We develop a novel method that constrains a posterior predictive distribution of a collection of network statistics in order to leverage the relationships among network statistics in making inference about network properties of interest. The method ensures that inference on network properties is compatible with an actual network. Through extensive simulation studies, we also demonstrate that use of this method can improve estimates in settings where there is uncertainty that arises both from sampling and from systematic reporting bias compared with currently available approaches to estimation. To illustrate the method, we apply it to estimate network statistics using data from the Chicago Health and Social Life Survey. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  6. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    connected to the switch. iv. Accessibility of historical data and event data In general, network discovery tools keep a history of the collected...has the following software dependencies: - Java Virtual machine 76 - Perl modules - RRD Tool - TomCat - PostgreSQL STRENGTHS AND...systems - provide a simple view of the current network status - generate alarms on status change - generate history of status change VISUAL MAP

  7. Broadcasting collective operation contributions throughout a parallel computer

    Science.gov (United States)

    Faraj, Ahmad [Rochester, MN

    2012-02-21

    Methods, systems, and products are disclosed for broadcasting collective operation contributions throughout a parallel computer. The parallel computer includes a plurality of compute nodes connected together through a data communications network. Each compute node has a plurality of processors for use in collective parallel operations on the parallel computer. Broadcasting collective operation contributions throughout a parallel computer according to embodiments of the present invention includes: transmitting, by each processor on each compute node, that processor's collective operation contribution to the other processors on that compute node using intra-node communications; and transmitting on a designated network link, by each processor on each compute node according to a serial processor transmission sequence, that processor's collective operation contribution to the other processors on the other compute nodes using inter-node communications.

  8. New challenges in computational collective intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Ngoc Thanh; Katarzyniak, Radoslaw Piotr [Wroclaw Univ. of Technology (Poland). Inst. of Informatics; Janiak, Adam (eds.) [Wroclaw Univ. of Technology (Poland). Inst. of Computer Engineering, Control and Robotics

    2009-07-01

    The book consists of 29 chapters which have been selected and invited from the submissions to the 1{sup st} International Conference on Collective Intelligence - Semantic Web, Social Networks and Multiagent Systems (ICCCI 2009). All chapters in the book discuss various examples of applications of computational collective intelligence and related technologies to such fields as semantic web, information systems ontologies, social networks, agent and multiagent systems. The editors hope that the book can be useful for graduate and Ph.D. students in Computer Science, in particular participants to courses on Soft Computing, Multi-Agent Systems and Robotics. This book can also be useful for researchers working on the concept of computational collective intelligence in artificial populations. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to create new cases intelligent collectives. Many such challenges are suggested by particular approaches and models presented in particular chapters of this book. (orig.)

  9. Integrating Information Networks for Collective Planetary Stewardship

    Science.gov (United States)

    Tiwari, A.

    2016-12-01

    Responsible behaviour resulting from climate literacy in global environmental movement is limited to policy and planning institutions in the Global South, while remaining absent for ends-user. Thus, planetary stewardship exists only at earth system boundaries where pressures sink to the local scale while ethics remains afloat. Existing citizen participation is restricted within policy spheres, appearing synonymous to enforcements in social psychology. Much, accounted reason is that existing information mechanisms operate mostly through linear exchanges between institutions and users, therefore reinforcing only hierarchical relationships. This study discloses such relationships that contribute to broad networking gaps through information demand assessment of stakeholders in a dozen development projects based in South Asia. Two parameters widely used for this purpose are: a. Feedback: Ends-user feedback to improve consumption literacy of climate sensitive resources (through consumption displays, billing, advisory services ecolabelling, sensors) and, b. Institutional Policy: Rewarding punishing to enforce desired behaviour (subsidies, taxation). Research answered: 1. Who gets the information (Equity in Information Distribution)? As existing information publishing mechanisms are designed by and for analysts, 2. How information translates to climate action Transparency of Execution)? Findings suggested that climate goals manifested in economic policy, than environmental policy, have potential clear short-term benefits and costs, and coincide with people's economic goals Also grassroots roles for responsible behaviour are empowered with presence of end user information. Barier free climate communication process and decision making is ensured among multiplicity of stakeholders with often conflicting perspectives. Research finds significance where collaboration among information networks can better translate regional policies into local action for climate adaptation and

  10. Cooperative and supportive neural networks

    International Nuclear Information System (INIS)

    Sree Hari Rao, V.; Raja Sekhara Rao, P.

    2007-01-01

    This Letter deals with the concepts of co-operation and support among neurons existing in a network which contribute to their collective capabilities and distributed operations. Activational dynamical properties of these networks are discussed

  11. Essays on Networks: Theory and Applications

    NARCIS (Netherlands)

    A.M. Babus (Ana Maria)

    2008-01-01

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

  12. Comparison of sputum collection methods for tuberculosis diagnosis: a systematic review and pairwise and network meta-analysis.

    Science.gov (United States)

    Datta, Sumona; Shah, Lena; Gilman, Robert H; Evans, Carlton A

    2017-08-01

    The performance of laboratory tests to diagnose pulmonary tuberculosis is dependent on the quality of the sputum sample tested. The relative merits of sputum collection methods to improve tuberculosis diagnosis are poorly characterised. We therefore aimed to investigate the effects of sputum collection methods on tuberculosis diagnosis. We did a systematic review and meta-analysis to investigate whether non-invasive sputum collection methods in people aged at least 12 years improve the diagnostic performance of laboratory testing for pulmonary tuberculosis. We searched PubMed, Google Scholar, ProQuest, Web of Science, CINAHL, and Embase up to April 14, 2017, to identify relevant experimental, case-control, or cohort studies. We analysed data by pairwise meta-analyses with a random-effects model and by network meta-analysis. All diagnostic performance data were calculated at the sputum-sample level, except where authors only reported data at the individual patient-level. Heterogeneity was assessed, with potential causes identified by logistic meta-regression. We identified 23 eligible studies published between 1959 and 2017, involving 8967 participants who provided 19 252 sputum samples. Brief, on-demand spot sputum collection was the main reference standard. Pooled sputum collection increased tuberculosis diagnosis by microscopy (odds ratio [OR] 1·6, 95% CI 1·3-1·9, pmeta-analysis confirmed these findings, and revealed that both pooled and instructed spot sputum collections were similarly effective techniques for increasing the diagnostic performance of microscopy. Tuberculosis diagnoses were substantially increased by either pooled collection or by providing instruction on how to produce a sputum sample taken at any time of the day. Both interventions had a similar effect to that reported for the introduction of new, expensive laboratory tests, and therefore warrant further exploration in the drive to end the global tuberculosis epidemic. Wellcome Trust

  13. Design and implementation of dynamic hybrid Honeypot network

    Science.gov (United States)

    Qiao, Peili; Hu, Shan-Shan; Zhai, Ji-Qiang

    2013-05-01

    The method of constructing a dynamic and self-adaptive virtual network is suggested to puzzle adversaries, delay and divert attacks, exhaust attacker resources and collect attacking information. The concepts of Honeypot and Honeyd, which is the frame of virtual Honeypot are introduced. The techniques of network scanning including active fingerprint recognition are analyzed. Dynamic virtual network system is designed and implemented. A virtual network similar to real network topology is built according to the collected messages from real environments in this system. By doing this, the system can perplex the attackers when Hackers attack and can further analyze and research the attacks. The tests to this system prove that this design can successfully simulate real network environment and can be used in network security analysis.

  14. Lossy Data Aggregation with Network Coding in Stand-Alone Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Madsen, Tatiana Kozlova

    2011-01-01

    in chemical plants, etc. Given resource constrained operation of a sensor network where the nodes are battery powered and buffer sizes are limited, efficient methods for in-network data storage abd it subsequent fast and reliable transmission to a gateway is desirable. To save scarse resources and to prolong......This work focuses on a special type of wireless sensor networks (WSNs) that we refer to as a stand alone network. These netwoks operate in harsh and extreme environments where data collection is done only occasionally. Typical examples include habitat monitoring systems, monitoring systems...

  15. Network bursts in cortical neuronal cultures: 'noise - versus pacemaker'- driven neural network simulations

    NARCIS (Netherlands)

    Gritsun, T.; Stegenga, J.; le Feber, Jakob; Rutten, Wim

    2009-01-01

    In this paper we address the issue of spontaneous bursting activity in cortical neuronal cultures and explain what might cause this collective behavior using computer simulations of two different neural network models. While the common approach to acivate a passive network is done by introducing

  16. Integrating networks with Mathematica

    NARCIS (Netherlands)

    Strijkers, R.J.; Meijer, R.J.

    2008-01-01

    We have developed a concept that considers network behavior as a collection of software objects, which can be used or modified in computer programs. The interfaces of these software objects are exposed as web services and enable applications to analyze and manipulate networks, e.g. to find

  17. Innovation in the collective brain

    Science.gov (United States)

    Muthukrishna, Michael; Henrich, Joseph

    2016-01-01

    Innovation is often assumed to be the work of a talented few, whose products are passed on to the masses. Here, we argue that innovations are instead an emergent property of our species' cultural learning abilities, applied within our societies and social networks. Our societies and social networks act as collective brains. We outline how many human brains, which evolved primarily for the acquisition of culture, together beget a collective brain. Within these collective brains, the three main sources of innovation are serendipity, recombination and incremental improvement. We argue that rates of innovation are heavily influenced by (i) sociality, (ii) transmission fidelity, and (iii) cultural variance. We discuss some of the forces that affect these factors. These factors can also shape each other. For example, we provide preliminary evidence that transmission efficiency is affected by sociality—languages with more speakers are more efficient. We argue that collective brains can make each of their constituent cultural brains more innovative. This perspective sheds light on traits, such as IQ, that have been implicated in innovation. A collective brain perspective can help us understand otherwise puzzling findings in the IQ literature, including group differences, heritability differences and the dramatic increase in IQ test scores over time. PMID:26926282

  18. OTDM Networking for Short Range High-Capacity Highly Dynamic Networks

    DEFF Research Database (Denmark)

    Medhin, Ashenafi Kiros

    This PhD thesis aims at investigating the possibility of designing energy-efficient high-capacity (up to Tbit/s) optical network scenarios, leveraging on the effect of collective switching of many bits simultaneously, as is inherent in high bit rate serial optical data signals. The focus...... is on short range highly dynamic networks, catering to data center needs. The investigation concerns optical network scenarios, and experimental implementations of high bit rate serial data packet generation and reception, scalable optical packet labeling, simple optical label extraction and stable ultra...

  19. Incremental Centrality Algorithms for Dynamic Network Analysis

    Science.gov (United States)

    2013-08-01

    literature.   7.1.3 Small World Networks In 1998, Watts and Strogatz introduced a model that starts with a regular lattice (ring) of n nodes and...and S. Strogatz , "Collective Dynamics of ‘Small-World’ Networks," Nature, vol. 393, pp. 440-442, 1998. [13] T. Opsahl, "Structure and Evolution of...34On Random Graphs," Publicationes Mathematicae, vol. 6, 1959. [167] D.J. Watts and S.H. Strogatz , "Collective Dynamics of ‘Small-World’ Networks

  20. Annotating gene sets by mining large literature collections with protein networks.

    Science.gov (United States)

    Wang, Sheng; Ma, Jianzhu; Yu, Michael Ku; Zheng, Fan; Huang, Edward W; Han, Jiawei; Peng, Jian; Ideker, Trey

    2018-01-01

    Analysis of patient genomes and transcriptomes routinely recognizes new gene sets associated with human disease. Here we present an integrative natural language processing system which infers common functions for a gene set through automatic mining of the scientific literature with biological networks. This system links genes with associated literature phrases and combines these links with protein interactions in a single heterogeneous network. Multiscale functional annotations are inferred based on network distances between phrases and genes and then visualized as an ontology of biological concepts. To evaluate this system, we predict functions for gene sets representing known pathways and find that our approach achieves substantial improvement over the conventional text-mining baseline method. Moreover, our system discovers novel annotations for gene sets or pathways without previously known functions. Two case studies demonstrate how the system is used in discovery of new cancer-related pathways with ontological annotations.

  1. Data Exchange Network

    DEFF Research Database (Denmark)

    Grau Larsen, Anton; Ellersgaard, Christoph

    2015-01-01

    This article presents the extensive Danish elite network. Collected during 2012 and 2013, the data comprises 56,536 positions within 5,079 affiliations, and connects 37,750 individuals. The network consists of the largest Danish corporations, state institutions, NGO’s, and other integrative...... networks such as social clubs or royal events. Data were gathered through an inclusion principle, adding all potentially interesting affiliations. Procedures of name-matching and quality control are presented. Finally, the data are introduced: made available through a package for R, which enables...

  2. Collective Travel Planning in Spatial Networks

    KAUST Repository

    Shang, Shuo

    2017-05-18

    We propose and investigate a novel query, the Collective Travel Planning (CTP) query, that finds the lowest-cost route connecting multiple query sources and a destination via at most k meeting points. This type of query is useful in organizing large events, and it can bring significant benefits to society and the environment: it can help optimize the allocation of transportation resources, reduce resource consumption, and enable smarter and greener transportation; and it can help reduce greenhouse-gas emissions and traffic congestion.

  3. Dynamic social networks based on movement

    Science.gov (United States)

    Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

    2016-01-01

    Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

  4. Crawling Facebook for Social Network Analysis Purposes

    OpenAIRE

    Catanese, Salvatore A.; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo; Provetti, Alessandro

    2011-01-01

    We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that w...

  5. Inter-cooperative collective intelligence techniques and applications

    CERN Document Server

    Bessis, Nik

    2014-01-01

    This book covers the latest advances in the rapid growing field of inter-cooperative collective intelligence aiming the integration and cooperation of various computational resources, networks and intelligent processing paradigms to collectively build intelligence and advanced decision support and interfaces for end-users. The book brings a comprehensive view of the state-of-the-art in the field of integration of sensor networks, IoT and Cloud computing, massive and intelligent querying and processing of data. As a result, the book presents lessons learned so far and identifies new research issues, challenges and opportunities for further research and development agendas. Emerging areas of applications are also identified and usefulness of inter-cooperative collective intelligence is envisaged.   Researchers, software developers, practitioners and students interested in the field of inter-cooperative collective intelligence will find the comprehensive coverage of this book useful for their research, academic...

  6. Networks and centroid metrics for understanding football | Gama ...

    African Journals Online (AJOL)

    This study aimedto verifythe network of contacts resulting from the collective behaviour of professional football teams through the centroid method and networks as well, therebyproviding detailed information about the match to coaches and sport analysts. For this purpose, 999 collective attacking actions from twoteams were ...

  7. Neural network classifier of attacks in IP telephony

    Science.gov (United States)

    Safarik, Jakub; Voznak, Miroslav; Mehic, Miralem; Partila, Pavol; Mikulec, Martin

    2014-05-01

    Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a different part of networks, which are logically or geographically divided and use the information from one network to harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.

  8. Collective influence in evolutionary social dilemmas

    Science.gov (United States)

    Szolnoki, Attila; Perc, Matjaž

    2016-03-01

    When evolutionary games are contested in structured populations, the degree of each player in the network plays an important role. If they exist, hubs often determine the fate of the population in remarkable ways. Recent research based on optimal percolation in random networks has shown, however, that the degree is neither the sole nor the best predictor of influence in complex networks. Low-degree nodes may also be optimal influencers if they are hierarchically linked to hubs. Taking this into account leads to the formalism of collective influence in complex networks, which as we show here, has far-reaching implications for the favorable resolution of social dilemmas. In particular, there exists an optimal hierarchical depth for the determination of collective influence that we use to describe the potency of players for passing their strategies, which depends on the strength of the social dilemma. Interestingly, the degree, which corresponds to the baseline depth zero, is optimal only when the temptation to defect is small. Our research reveals that evolutionary success stories are related to spreading processes which are rooted in favorable hierarchical structures that extend beyond local neighborhoods.

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

    Science.gov (United States)

    2015-03-26

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

  10. Sustainable Operation of Arterial Networks

    Science.gov (United States)

    2017-07-14

    This report describes operational data analysis and modeling of arterial networks with signalized intersections as follows: The setup for data collection, analysis and simulation is presented in Section 2.1. Detailed analysis of collected signal phas...

  11. Emerging wireless networks concepts, techniques and applications

    CERN Document Server

    Makaya, Christian

    2011-01-01

    An authoritative collection of research papers and surveys, Emerging Wireless Networks: Concepts, Techniques, and Applications explores recent developments in next-generation wireless networks (NGWNs) and mobile broadband networks technologies, including 4G (LTE, WiMAX), 3G (UMTS, HSPA), WiFi, mobile ad hoc networks, mesh networks, and wireless sensor networks. Focusing on improving the performance of wireless networks and provisioning better quality of service and quality of experience for users, it reports on the standards of different emerging wireless networks, applications, and service fr

  12. Novel Method for Measuring the Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters Based on Artificial Neural Networks and Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Zhijian Liu

    2015-08-01

    Full Text Available The determinations of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, the direct determination requires complex detection devices and a series of standard experiments, which also wastes too much time and manpower. To address this problem, we propose machine learning models including artificial neural networks (ANNs and support vector machines (SVM to predict the heat collection rate and heat loss coefficient without a direct determination. Parameters that can be easily obtained by “portable test instruments” were set as independent variables, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, final temperature and angle between tubes and ground, while the heat collection rate and heat loss coefficient determined by the detection device were set as dependent variables respectively. Nine hundred fifteen samples from in-service water-in-glass evacuated tube solar water heaters were used for training and testing the models. Results show that the multilayer feed-forward neural network (MLFN with 3 nodes is the best model for the prediction of heat collection rate and the general regression neural network (GRNN is the best model for the prediction of heat loss coefficient due to their low root mean square (RMS errors, short training times, and high prediction accuracies (under the tolerances of 30%, 20%, and 10%, respectively.

  13. Analog-to-digital clinical data collection on networked workstations with graphic user interface.

    Science.gov (United States)

    Lunt, D

    1991-02-01

    An innovative respiratory examination system has been developed that combines physiological response measurement, real-time graphic displays, user-driven operating sequences, and networked file archiving and review into a scientific research and clinical diagnosis tool. This newly constructed computer network is being used to enhance the research center's ability to perform patient pulmonary function examinations. Respiratory data are simultaneously acquired and graphically presented during patient breathing maneuvers and rapidly transformed into graphic and numeric reports, suitable for statistical analysis or database access. The environment consists of the hardware (Macintosh computer, MacADIOS converters, analog amplifiers), the software (HyperCard v2.0, HyperTalk, XCMDs), and the network (AppleTalk, fileservers, printers) as building blocks for data acquisition, analysis, editing, and storage. System operation modules include: Calibration, Examination, Reports, On-line Help Library, Graphic/Data Editing, and Network Storage.

  14. Simulating synchronization in neuronal networks

    Science.gov (United States)

    Fink, Christian G.

    2016-06-01

    We discuss several techniques used in simulating neuronal networks by exploring how a network's connectivity structure affects its propensity for synchronous spiking. Network connectivity is generated using the Watts-Strogatz small-world algorithm, and two key measures of network structure are described. These measures quantify structural characteristics that influence collective neuronal spiking, which is simulated using the leaky integrate-and-fire model. Simulations show that adding a small number of random connections to an otherwise lattice-like connectivity structure leads to a dramatic increase in neuronal synchronization.

  15. Synchronization coupled systems to complex networks

    CERN Document Server

    Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas

    2018-01-01

    A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...

  16. Networking activities in technology-based entrepreneurial teams

    DEFF Research Database (Denmark)

    Neergaard, Helle

    2005-01-01

    Based on social network theoy, this article investigates the distribution of networking roles and responsibilities in entrepreneurial founding teams. Its focus is on the team as a collection of individuals, thus allowing the research to address differences in networking patterns. It identifies six...... central networking activities and shows that not all founding team members are equally active 'networkers'. The analyses show that team members prioritize different networking activities and that one member in particular has extensive networking activities whereas other memebrs of the team are more...

  17. Collective action, clientelism and connectivity

    DEFF Research Database (Denmark)

    Shami, Mahvish

    that the unequal relationship between landlords and peasants does not, in and by itself, block peasant collective action. Rather, it is the interaction between clientelism and isolation that allow patrons to block community based projects. Despite still relying on powerful landlords, peasants in connected villages...... face no such constraints. On the contrary, their patrons assisted them in their collective endeavours, making the hierarchical network an added resource for peasants to rely upon....

  18. Efficient collective influence maximization in cascading processes with first-order transitions

    Science.gov (United States)

    Pei, Sen; Teng, Xian; Shaman, Jeffrey; Morone, Flaviano; Makse, Hernán A.

    2017-01-01

    In many social and biological networks, the collective dynamics of the entire system can be shaped by a small set of influential units through a global cascading process, manifested by an abrupt first-order transition in dynamical behaviors. Despite its importance in applications, efficient identification of multiple influential spreaders in cascading processes still remains a challenging task for large-scale networks. Here we address this issue by exploring the collective influence in general threshold models of cascading process. Our analysis reveals that the importance of spreaders is fixed by the subcritical paths along which cascades propagate: the number of subcritical paths attached to each spreader determines its contribution to global cascades. The concept of subcritical path allows us to introduce a scalable algorithm for massively large-scale networks. Results in both synthetic random graphs and real networks show that the proposed method can achieve larger collective influence given the same number of seeds compared with other scalable heuristic approaches. PMID:28349988

  19. Unified Alignment of Protein-Protein Interaction Networks.

    Science.gov (United States)

    Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

    2017-04-19

    Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

  20. Networking of safeguards systems

    International Nuclear Information System (INIS)

    Chare, P.; Dutrannois, A.; Kloeckner, W.; Swinhoe, M.

    1995-01-01

    This paper discusses the design of a safeguards system that can be incorporated into a plant during the final phase of its construction to permit the acquisition and transmission of data during plant operation in the absence of an inspector. The system is an example of a networked data system of weighing, identity, and NDA information. It collects all of its non-surveillance data produced by safeguards equipment in a fuel fabrication plant. The data collection and transfer tasks are carried out by two software packages: NEGUS, a redundant data acquisition system designed to record neutron coincidence data, high-resolution gamma spectra, and sensor data for the NDA information and associated barcode identity information, and BRANCH, which deals with weighing and associated identity information. These processes collect data from local electronics using an ethernet network and provide information to the main review program

  1. Network Sampling with Memory: A proposal for more efficient sampling from social networks

    Science.gov (United States)

    Mouw, Ted; Verdery, Ashton M.

    2013-01-01

    Techniques for sampling from networks have grown into an important area of research across several fields. For sociologists, the possibility of sampling from a network is appealing for two reasons: (1) A network sample can yield substantively interesting data about network structures and social interactions, and (2) it is useful in situations where study populations are difficult or impossible to survey with traditional sampling approaches because of the lack of a sampling frame. Despite its appeal, methodological concerns about the precision and accuracy of network-based sampling methods remain. In particular, recent research has shown that sampling from a network using a random walk based approach such as Respondent Driven Sampling (RDS) can result in high design effects (DE)—the ratio of the sampling variance to the sampling variance of simple random sampling (SRS). A high design effect means that more cases must be collected to achieve the same level of precision as SRS. In this paper we propose an alternative strategy, Network Sampling with Memory (NSM), which collects network data from respondents in order to reduce design effects and, correspondingly, the number of interviews needed to achieve a given level of statistical power. NSM combines a “List” mode, where all individuals on the revealed network list are sampled with the same cumulative probability, with a “Search” mode, which gives priority to bridge nodes connecting the current sample to unexplored parts of the network. We test the relative efficiency of NSM compared to RDS and SRS on 162 school and university networks from Add Health and Facebook that range in size from 110 to 16,278 nodes. The results show that the average design effect for NSM on these 162 networks is 1.16, which is very close to the efficiency of a simple random sample (DE=1), and 98.5% lower than the average DE we observed for RDS. PMID:24159246

  2. Longitudinal research and data collection in primary care.

    Science.gov (United States)

    van Weel, Chris

    2005-01-01

    This article reviews examples of and experience with longitudinal research in family medicine. The objective is to use this empirical information to formulate recommendations for improving longitudinal research. The article discusses 3 longitudinal studies from the Nijmegen academic family practice research network: 1 on the prognosis of depression and 1 each on the prognosis of and outcomes of care for type 2 diabetes mellitus. The Nijmegen network has recorded all episodes of morbidity encountered in Dutch family medicine since 1971 in a stable practice population. This network's experience is evaluated to identify lessons that may help other practice-based research networks (PBRNs) in pursuing longitudinal research. In terms of external conditions (conditions related to the general setting), the stability of a population and a high level of continuity of care substantially enhance the ability to perform longitudinal research. In terms of internal conditions (conditions related to the PBRN), motivation of family physicians and their staff to conduct ongoing data collection, and their ownership of the data are key for success. Other critical internal conditions include standardization of data; collection of data by clinician-friendly means; training of family physicians and their staff in data collection, as well as meetings for discussion of this task; provision of feedback to practices on the research findings; use of standard procedures to promote adherence to data collection; availability of facilities for regular measurement of patients' health status or chart review; and use of mechanisms for tracking patients who leave the practice area. Insight from existing experience suggests that longitudinal research can be enhanced in PBRNs. The best way forward is to build longitudinal data collection by drawing on lessons from successful studies. Primary care research policy should advocate for a role of longitudinal research and stimulate its development in PBRNs

  3. Statistical indicators of collective behavior and functional clusters in gene networks of yeast

    Science.gov (United States)

    Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

    2006-03-01

    We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

  4. Wireless rechargeable sensor networks

    CERN Document Server

    Yang, Yuanyuan

    2015-01-01

    This SpringerBrief provides a concise guide to applying wireless energy transfer techniques in traditional battery-powered sensor networks. It examines the benefits and challenges of wireless power including efficiency and reliability. The authors build a wireless rechargeable sensor networks from scratch and aim to provide perpetual network operation. Chapters cover a wide range of topics from the collection of energy information and recharge scheduling to joint design with typical sensing applications such as data gathering. Problems are approached using a natural combination of probability

  5. Competing dynamic phases of active polymer networks

    Science.gov (United States)

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

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

  6. Comparing personal image collections with PICTuReVis

    NARCIS (Netherlands)

    van der Corput, P.N.A.; van Wijk, J.J.

    2017-01-01

    Digital image collections contain a wealth of information, which for instance can be used to trace illegal activities and investigate criminal networks. We present a method that enables analysts to reveal relations among people, based on the patterns in their collections. Similar temporal and

  7. On Model Design for Simulation of Collective Intelligence

    NARCIS (Netherlands)

    Schut, M.C.

    2010-01-01

    The study of collective intelligence (CI) systems is increasingly gaining interest in a variety of research and application domains. Those domains range from existing research areas such as computer networks and collective robotics to upcoming areas of agent-based and insect-based computing; also

  8. Controlling noise-induced behavior of excitable networks

    International Nuclear Information System (INIS)

    Patidar, S; Pototsky, A; Janson, N B

    2009-01-01

    The paper demonstrates the possibility to control the collective behavior of a large network of excitable stochastic units, in which oscillations are induced merely by external random input. Each network element is represented by the FitzHugh-Nagumo system under the influence of noise, and the elements are coupled through the mean field. As known previously, the collective behavior of units in such a network can range from synchronous to non-synchronous spiking with a variety of states in between. We apply the Pyragas delayed feedback to the mean field of the network and demonstrate that this technique is capable of suppressing or weakening the collective synchrony, or of inducing the synchrony where it was absent. On the plane of control parameters we indicate the areas where suppression of synchrony is achieved. To explain the numerical observations on a qualitative level, we use the semi-analytic approach based on the cumulant expansion of the distribution density within Gaussian approximation. We perform bifurcation analysis of the obtained cumulant equations with delay and demonstrate that the regions of stability of its steady state have qualitatively the same structure as the regions of synchrony suppression of the original stochastic equations. We also demonstrate the delay-induced multistability in the stochastic network. These results are relevant to the control of unwanted behavior in neural networks.

  9. A Smart Home Gateway Platform for Data Collection and Awareness

    OpenAIRE

    Wang, Pan; Ye, Feng; Chen, Xuejiao

    2018-01-01

    Smart homes have attracted much attention due to the expanding of Internet-of-Things (IoT) and smart devices. In this paper, we propose a smart gateway platform for data collection and awareness in smart home networks. A smart gateway will replace the traditional network gateway to connect the home network and the Internet. A smart home network supports different types of smart devices, such as in home IoT devices, smart phones, smart electric appliances, etc. A traditional network gateway is...

  10. Associative memory in phasing neuron networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-01-01

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

  11. Weighted Networks at the Polish Market

    Science.gov (United States)

    Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

    During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.

  12. Web-based networking within the framework of ANENT

    International Nuclear Information System (INIS)

    Han, K.W.; Lee, E.J.; Kim, Y.T.; Nam, Y.M.; Kim, H.K.

    2004-01-01

    The Korea Atomic Energy Research Institute (KAERI) is actively participating in the Asian Network for Education in Nuclear Technology (ANENT), which is an IAEA activity to promote nuclear knowledge management. This has led KAERI to conduct a web-based networking for nuclear education and training in Asia. The networking encompasses the establishment of a relevant website and a system for a sustainable operation of the website. The established ANENT website features function as a database providing collected information, a link facilitating a systematic worldwide access to relevant websites, and an activity implementation for supporting the individual tasks of ANENT. The required information is being collected and loaded onto the database, and the website will be improved step by step. Consequently, networking is expected to play an important role, through cooperating with other networks, and thus contributing to a future global network for a sustainable development of nuclear technology. (author)

  13. A radio network collects the data sent by the sensors

    International Nuclear Information System (INIS)

    Zani-Demange, M.L.

    2008-01-01

    The Malvesi site in southern France is the most important uranium conversion plant in the world. It belongs to Comurhex and its purpose is to turn uranium ore into uranium tetrafluoride (UF 4 ). This transformation requires successive purification stages for the ore. This purification process generates large amount of liquid effluents containing nitrates. Large reservoirs in open air covering an area of about 80 hectares are used to evaporate water and concentrate the effluents. A new system based on a network of ultrasound level sensors that send information to the control room through radio waves, is operating to control the levels of the reservoirs. For some reservoirs solar panels supply energy for the sensors and the radio modem. The main assets of this wireless installation is its reduced cost compared to the cost of setting a cable network and its flexibility when an ancient reservoir is put aside or when a new one is added, the installation can be easily moved. (A.C.)

  14. Mob control models of threshold collective behavior

    CERN Document Server

    Breer, Vladimir V; Rogatkin, Andrey D

    2017-01-01

    This book presents mathematical models of mob control with threshold (conformity) collective decision-making of the agents. Based on the results of analysis of the interconnection between the micro- and macromodels of active network structures, it considers the static (deterministic, stochastic and game-theoretic) and dynamic (discrete- and continuous-time) models of mob control, and highlights models of informational confrontation. Many of the results are applicable not only to mob control problems, but also to control problems arising in social groups, online social networks, etc. Aimed at researchers and practitioners, it is also a valuable resource for undergraduate and postgraduate students as well as doctoral candidates specializing in the field of collective behavior modeling.

  15. Information Collection using Handheld Devices in Unreliable Networking Environments

    Science.gov (United States)

    2014-06-01

    joint logistics operations center JMS Java Message System JUNG Java Universal Network/Graph Framework KTG Kestral Technology Group MILOB... Java Message System, a Publisher/Subscriber system that is explained in greater detail at either Oracle’s JMS site (Oracle 2014) or the JMS Wikipedia...Google’s infrastructure and local servers with MySQL and PostgreSQL on the backend (ODK 2014b). (2) Google Fusion Tables are used to do basic link

  16. Complex Networks IX

    CERN Document Server

    Coronges, Kate; Gonçalves, Bruno; Sinatra, Roberta; Vespignani, Alessandro; Proceedings of the 9th Conference on Complex Networks; CompleNet 2018

    2018-01-01

    This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) 2018 in Boston, MA in March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

  17. Adverse Outcome Pathway Networks II: Network Analytics.

    Science.gov (United States)

    Villeneuve, Daniel L; Angrish, Michelle M; Fortin, Marie C; Katsiadaki, Ioanna; Leonard, Marc; Margiotta-Casaluci, Luigi; Munn, Sharon; O'Brien, Jason M; Pollesch, Nathan L; Smith, L Cody; Zhang, Xiaowei; Knapen, Dries

    2018-02-28

    Toxicological responses to stressors are more complex than the simple one biological perturbation to one adverse outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present paper introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using two example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses, or previously undefined emergent patterns of response, are introduced. Along with a companion article (Knapen et al. part I), these concepts set the stage for development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. Collectively, this work addresses one of the major themes identified through a SETAC Horizon Scanning effort focused on advancing the AOP framework. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  18. Volunteer-based distributed traffic data collection system

    DEFF Research Database (Denmark)

    Balachandran, Katheepan; Broberg, Jacob Honoré; Revsbech, Kasper

    2010-01-01

    An architecture for a traffic data collection system is proposed, which can collect data without having access to a backbone network. Contrary to other monitoring systems it relies on volunteers to install a program on their own computers, which will capture incoming and outgoing packets, group t...... case performance estimates indicate that this is obtained. Tests conducted by volunteers using an implemented prototype confirm the feasibility of the system......An architecture for a traffic data collection system is proposed, which can collect data without having access to a backbone network. Contrary to other monitoring systems it relies on volunteers to install a program on their own computers, which will capture incoming and outgoing packets, group...... them into flows and send the flow data to a central server. Data can be used for studying and characterising internet traffic and for testing traffic models by regenerating real traffic. The architecture is designed to have efficient and light usage of resources on both client and server sides. Worst...

  19. Analysis and monitoring design for networks

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.; Flanagan, D.; Rowan, T.; Batsell, S.

    1998-06-01

    The idea of applying experimental design methodologies to develop monitoring systems for computer networks is relatively novel even though it was applied in other areas such as meteorology, seismology, and transportation. One objective of a monitoring system should always be to collect as little data as necessary to be able to monitor specific parameters of the system with respect to assigned targets and objectives. This implies a purposeful monitoring where each piece of data has a reason to be collected and stored for future use. When a computer network system as large and complex as the Internet is the monitoring subject, providing an optimal and parsimonious observing system becomes even more important. Many data collection decisions must be made by the developers of a monitoring system. These decisions include but are not limited to the following: (1) The type data collection hardware and software instruments to be used; (2) How to minimize interruption of regular network activities during data collection; (3) Quantification of the objectives and the formulation of optimality criteria; (4) The placement of data collection hardware and software devices; (5) The amount of data to be collected in a given time period, how large a subset of the available data to collect during the period, the length of the period, and the frequency of data collection; (6) The determination of the data to be collected (for instance, selection of response and explanatory variables); (7) Which data will be retained and how long (i.e., data storage and retention issues); and (8) The cost analysis of experiments. Mathematical statistics, and, in particular, optimal experimental design methods, may be used to address the majority of problems generated by 3--7. In this study, the authors focus their efforts on topics 3--5.

  20. GROWTH OF COLLECTIVE INTELLIGENCE BY LINKING KNOWLEDGE WORKERS THROUGH SOCIAL MEDIA

    Directory of Open Access Journals (Sweden)

    JAROSLAVA KUBÁTOVÁ

    2012-05-01

    Full Text Available Collective intelligence can be defined, very broadly, as groups of individuals that do things collectively, and that seem to be intelligent. Collective intelligence has existed for ages. Families, tribes, companies, countries, etc., are all groups of individuals doing things collectively, and that seem to be intelligent. However, over the past two decades, the rise of the Internet has given upturn to new types of collective intelligence. Companies can take advantage from the so-called Web-enabled collective intelligence. Web-enabled collective intelligence is based on linking knowledge workers through social media. That means that companies can hire geographically dispersed knowledge workers and create so-called virtual teams of these knowledge workers (members of the virtual teams are connected only via the Internet and do not meet face to face. By providing an online social network, the companies can achieve significant growth of collective intelligence. But to create and use an online social network within a company in a really efficient way, the managers need to have a deep understanding of how such a system works. Thus the purpose of this paper is to share the knowledge about effective use of social networks in companies. The main objectives of this paper are as follows: to introduce some good practices of the use of social media in companies, to analyze these practices and to generalize recommendations for a successful introduction and use of social media to increase collective intelligence of a company.

  1. Temporal fidelity in dynamic social networks

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’

    2015-01-01

    of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution...

  2. Smart Collection and Storage Method for Network Traffic Data

    Science.gov (United States)

    2014-09-01

    to the root of an incident or under- stand what goes on in a network may mean looking at data from weeks, months, or even years ago, as has been the...KB 1.01% 69.42 TB 694.20 TB 6,941.99 TB SuSE 6.3 .pcap 51,706 KB 1.01% 104.03 TB 1,040.27 TB 10,402.68 TB HP-UX nettl .trc0 53,391 KB 1.04% 451.13

  3. From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

    OpenAIRE

    Sueur, Cédric; Deneubourg, Jean-Louis; Petit, Odile

    2012-01-01

    Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the...

  4. Composite Social Network for Predicting Mobile Apps Installation

    Science.gov (United States)

    2011-06-02

    Social network tools (such as the Facebook app and the Twitter app) can observe users’ online friendship network . In this work, our key idea is...the friendship network from phones by collecting data from social networking apps such as the Facebook and Twitter apps. We summarize all the networks ...ar X iv :1 10 6. 03 59 v1 [ cs .S I] 2 J un 2 01 1 Composite Social Network for Predicting Mobile Apps Installation Wei Pan

  5. Maintenance of family networks

    DEFF Research Database (Denmark)

    marsico, giuseppina; Chaudhary, N; Valsiner, Jaan

    2015-01-01

    Families are social units that expand in time (across generations) and space (as a geographically distributed sub-structures of wider kinship networks). Understanding of intergenerational family relations thus requires conceptualization of communication processes that take place within a small...... collective of persons linked with one another by a flexible social network. Within such networks, Peripheral Communication Patterns set the stage for direct everyday life activities within the family context. Peripheral Communication Patterns are conditions where one family network member (A) communicates...... manifestly with another member (B) with the aim of bringing the communicative message to the third member (C) who is present but is not explicitly designated as the manifest addressee of the intended message. Inclusion of physically non-present members of the family network (elders living elsewhere, deceased...

  6. Preparing for a Career as a Network Engineer

    Science.gov (United States)

    Morris, Gerard; Fustos, Janos; Haga, Wayne

    2012-01-01

    A network engineer is an Information Technology (IT) professional who designs, implements, maintains, and troubleshoots computer networks. While the United States is still experiencing relatively high unemployment, demand for network engineers remains strong. To determine what skills employers are looking for, data was collected and analyzed from…

  7. Evaluating the feasibility of using online software to collect patient information in a chiropractic practice-based research network.

    Science.gov (United States)

    Kania-Richmond, Ania; Weeks, Laura; Scholten, Jeffrey; Reney, Mikaël

    2016-03-01

    Practice based research networks (PBRNs) are increasingly used as a tool for evidence based practice. We developed and tested the feasibility of using software to enable online collection of patient data within a chiropractic PBRN to support clinical decision making and research in participating clinics. To assess the feasibility of using online software to collect quality patient information. The study consisted of two phases: 1) Assessment of the quality of information provided, using a standardized form; and 2) Exploration of patients' perspectives and experiences regarding online information provision through semi-structured interviews. Data analysis was descriptive. Forty-five new patients were recruited. Thirty-six completed online forms, which were submitted by an appropriate person 100% of the time, with an error rate of less than 1%, and submitted in a timely manner 83% of the time. Twenty-one participants were interviewed. Overall, online forms were preferred given perceived security, ease of use, and enabling provision of more accurate information. Use of online software is feasible, provides high quality information, and is preferred by most participants. A pen-and-paper format should be available for patients with this preference and in case of technical difficulties.

  8. Mobility-aware Hybrid Synchronization for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2015-01-01

    Random mobility of node causes the frequent changes in the network dynamics causing the increased cost in terms of energy and bandwidth. It needs the additional efforts to synchronize the activities of nodes during data collection and transmission in Wireless Sensor Networks (WSNs). A key challenge...... in maintaining the effective data collection and transmission is to schedule and synchronize the activities of the nodes with the global clock. This paper proposes the Mobility-aware Hybrid Synchronization Algorithm (MHS) which works on the formation of cluster based on spanning tree mechanism (SPT). Nodes used...... for formation of the network have random mobility and heterogeneous in terms of energy with static sink. The nodes in the cluster and cluster heads in the network are synchronized with the notion of global time scale. In the initial stage, the algorithm establishes the hierarchical structure of the network...

  9. Towards a Community Environmental Observation Network

    Science.gov (United States)

    Mertl, Stefan; Lettenbichler, Anton

    2014-05-01

    The Community Environmental Observation Network (CEON) is dedicated to the development of a free sensor network to collect and distribute environmental data (e.g. ground shaking, climate parameters). The data collection will be done with contributions from citizens, research institutions and public authorities like communities or schools. This will lead to a large freely available data base which can be used for public information, research, the arts,..... To start a free sensor network, the most important step is to provide easy access to free data collection and -distribution tools. The initial aims of the project CEON are dedicated to the development of these tools. A high quality data logger based on open hardware and free software is developed and a software suite of already existing free software for near-real time data communication and data distribution over the Internet will be assembled. Foremost, the development focuses on the collection of data related to the deformation of the earth (such as ground shaking, surface displacement of mass movements and glaciers) and the collection of climate data. The extent to other measurements will be considered in the design. The data logger is built using open hardware prototyping platforms like BeagleBone Black and Arduino. Main features of the data logger are: a 24Bit analog-to-digital converter; a GPS module for time reference and positioning; wireless mesh networking using Optimized Link State Routing; near real-time data transmission and communication; and near real-time differential GNSS positioning using the RTKLIB software. The project CEON is supported by the Internet Foundation Austria (IPA) within the NetIdee 2013 call.

  10. The Network Data Handling War: MySQL vs. NfDump

    NARCIS (Netherlands)

    Hofstede, Rick; Hofstede, R.J.; Sperotto, Anna; Fioreze, Tiago; Pras, Aiko

    Network monitoring plays a crucial role in any network management environment. Especially nowadays, with network speed and load constantly increasing, more and more data needs to be collected and efficiently processed. In highly interactive network monitoring systems, a quick response time from

  11. Communication and Networking in Smart Grids

    CERN Document Server

    Xiao, Yang

    2012-01-01

    Appropriate for researchers, practitioners, and students alike, Communication and Networking in Smart Grids presents state-of-the-art approaches and novel technologies for communication networks in smart grids. It explains how contemporary grid networks are developed and deployed and presents a collection of cutting-edge advances to help improve current practice. Prominent researchers working on smart grids and in related fields around the world explain the fundamental aspects and applications of smart grids. Describing the role that communication and networking will play in future smart grids

  12. Markets on Networks

    Science.gov (United States)

    Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

    2003-03-01

    The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

  13. Efficient Networks Communication Routing Using Swarm Intelligence

    OpenAIRE

    Koushal Kumar

    2012-01-01

    As demonstrated by natural biological swarm’s collective intelligence has an abundance of desirable properties for problem-solving like in network routing. The focus of this paper is in the applications of swarm based intelligence in information routing for communication networks. As we know networks are growing and adopting new platforms as new technologies comes. Also according to new demands and requirements networks topologies and its complexity is increasing with time. Thus it is becomin...

  14. Intelligence Collection Targeting and Interdiction of Dark Networks

    Science.gov (United States)

    2014-06-01

    examples of terrorist technological communications countered by a baseline of NTM collection with OSINT and HUMINT only serving as enablers or...he visits while traveling as an ostensible tourist ( OSINT ) would be useful.54 In summary, Sims’s observation not only enforce the strategic

  15. Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

    Science.gov (United States)

    Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

    2016-05-01

    This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

  16. Individual heterogeneity generating explosive system network dynamics.

    Science.gov (United States)

    Manrique, Pedro D; Johnson, Neil F

    2018-03-01

    Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

  17. Individual heterogeneity generating explosive system network dynamics

    Science.gov (United States)

    Manrique, Pedro D.; Johnson, Neil F.

    2018-03-01

    Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

  18. VRML metabolic network visualizer.

    Science.gov (United States)

    Rojdestvenski, Igor

    2003-03-01

    A successful date collection visualization should satisfy a set of many requirements: unification of diverse data formats, support for serendipity research, support of hierarchical structures, algorithmizability, vast information density, Internet-readiness, and other. Recently, virtual reality has made significant progress in engineering, architectural design, entertainment and communication. We experiment with the possibility of using the immersive abstract three-dimensional visualizations of the metabolic networks. We present the trial Metabolic Network Visualizer software, which produces graphical representation of a metabolic network as a VRML world from a formal description written in a simple SGML-type scripting language.

  19. Auditing information structures in organizations: A review of data collection techniques for network analysis

    NARCIS (Netherlands)

    Koning, K.H.; de Jong, Menno D.T.

    2005-01-01

    Network analysis is one of the current techniques for investigating organizational communication. Despite the amount of how-to literature about using network analysis to assess information flows and relationships in organizations, little is known about the methodological strengths and weaknesses of

  20. Revealing networks from dynamics: an introduction

    International Nuclear Information System (INIS)

    Timme, Marc; Casadiego, Jose

    2014-01-01

    What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity. (topical review)

  1. Quantifying collective attention from tweet stream.

    Directory of Open Access Journals (Sweden)

    Kazutoshi Sasahara

    Full Text Available Online social media are increasingly facilitating our social interactions, thereby making available a massive "digital fossil" of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of "collective attention" on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or "tweets." Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. "Retweet" networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.

  2. A Collaborative Learning Network Approach to Improvement: The CUSP Learning Network.

    Science.gov (United States)

    Weaver, Sallie J; Lofthus, Jennifer; Sawyer, Melinda; Greer, Lee; Opett, Kristin; Reynolds, Catherine; Wyskiel, Rhonda; Peditto, Stephanie; Pronovost, Peter J

    2015-04-01

    Collaborative improvement networks draw on the science of collaborative organizational learning and communities of practice to facilitate peer-to-peer learning, coaching, and local adaption. Although significant improvements in patient safety and quality have been achieved through collaborative methods, insight regarding how collaborative networks are used by members is needed. Improvement Strategy: The Comprehensive Unit-based Safety Program (CUSP) Learning Network is a multi-institutional collaborative network that is designed to facilitate peer-to-peer learning and coaching specifically related to CUSP. Member organizations implement all or part of the CUSP methodology to improve organizational safety culture, patient safety, and care quality. Qualitative case studies developed by participating members examine the impact of network participation across three levels of analysis (unit, hospital, health system). In addition, results of a satisfaction survey designed to evaluate member experiences were collected to inform network development. Common themes across case studies suggest that members found value in collaborative learning and sharing strategies across organizational boundaries related to a specific improvement strategy. The CUSP Learning Network is an example of network-based collaborative learning in action. Although this learning network focuses on a particular improvement methodology-CUSP-there is clear potential for member-driven learning networks to grow around other methods or topic areas. Such collaborative learning networks may offer a way to develop an infrastructure for longer-term support of improvement efforts and to more quickly diffuse creative sustainment strategies.

  3. Environmental monitoring network for India

    Science.gov (United States)

    P.V. Sundareshwar; R. Murtugudde; G. Srinivasan; S. Singh; K.J. Ramesh; R. Ramesh; S.B. Verma; D. Agarwal; D. Baldocchi; C.K. Baru; K.K. Baruah; G.R. Chowdhury; V.K. Dadhwal; C.B.S. Dutt; J. Fuentes; Prabhat Gupta; W.W. Hardgrove; M. Howard; C.S. Jha; S. Lal; W.K. Michener; A.P. Mitra; J.T. Morris; R.R. Myneni; M. Naja; R. Nemani; R. Purvaja; S. Raha; S.K. Santhana Vanan; M. Sharma; A. Subramaniam; R. Sukumar; R.R. Twilley; P.R. Zimmerman

    2007-01-01

    Understanding the consequences of global environmental change and its mitigation will require an integrated global effort of comprehensive long-term data collection, synthesis, and action (1). The last decade has seen a dramatic global increase in the number of networked monitoring sites. For example, FLUXNET is a global collection of >300 micrometeorological...

  4. Relationship between Social Networks Adoption and Social Intelligence

    Science.gov (United States)

    Gunduz, Semseddin

    2017-01-01

    The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

  5. Deflating link buffers in a wireless mesh network

    KAUST Repository

    Jamshaid, Kamran; Shihada, Basem; Showail, Ahmad; Levis, Philip

    2014-01-01

    We analyze the problem of buffer sizing for backlogged TCP flows in 802.11-based wireless mesh networks. Our objective is to maintain high network utilization while providing low queueing delays. Unlike wired networks where a single link buffer feeds a bottleneck link, the radio spectral resource in a mesh network is shared among a set of contending mesh routers. We account for this by formulating the buffer size problem as sizing a collective buffer distributed over a set of interfering nodes. In this paper we propose mechanisms for sizing and distributing this collective buffer among the mesh nodes constituting the network bottleneck. Our mechanism factors in the network topology and wireless link rates, improving on pre-set buffer allocations that cannot optimally work across the range of configurations achievable with 802.11 radios. We evaluate our mechanisms using simulations as well as experiments on a testbed. Our results show that we can reduce the RTT of a flow by 6× or more, at the cost of less than 10% drop in end-to-end flow throughput.

  6. Deflating link buffers in a wireless mesh network

    KAUST Repository

    Jamshaid, Kamran

    2014-05-01

    We analyze the problem of buffer sizing for backlogged TCP flows in 802.11-based wireless mesh networks. Our objective is to maintain high network utilization while providing low queueing delays. Unlike wired networks where a single link buffer feeds a bottleneck link, the radio spectral resource in a mesh network is shared among a set of contending mesh routers. We account for this by formulating the buffer size problem as sizing a collective buffer distributed over a set of interfering nodes. In this paper we propose mechanisms for sizing and distributing this collective buffer among the mesh nodes constituting the network bottleneck. Our mechanism factors in the network topology and wireless link rates, improving on pre-set buffer allocations that cannot optimally work across the range of configurations achievable with 802.11 radios. We evaluate our mechanisms using simulations as well as experiments on a testbed. Our results show that we can reduce the RTT of a flow by 6× or more, at the cost of less than 10% drop in end-to-end flow throughput.

  7. Network Science Center Research Team’s Visit to Kampala, Uganda

    Science.gov (United States)

    2013-04-15

    TERMS Network Analysis, Economic Networks, Entrepreneurial Ecosystems , Economic Development, Data Collection 16. SECURITY CLASSIFICATION OF: 17...the Project Synopsis, Developing Network Models of Entrepreneurial Ecosystems in Developing Economies, on the Network Science Center web site.) A...Thomas visited Kampala, Uganda in support of an ongoing Network Science Center project to develop models of entrepreneurial networks. Our Center has

  8. Modular networks with delayed coupling: Synchronization and frequency control

    Science.gov (United States)

    Maslennikov, Oleg V.; Nekorkin, Vladimir I.

    2014-07-01

    We study the collective dynamics of modular networks consisting of map-based neurons which generate irregular spike sequences. Three types of intramodule topology are considered: a random Erdös-Rényi network, a small-world Watts-Strogatz network, and a scale-free Barabási-Albert network. The interaction between the neurons of different modules is organized by relatively sparse connections with time delay. For all the types of the network topology considered, we found that with increasing delay two regimes of module synchronization alternate with each other: inphase and antiphase. At the same time, the average rate of collective oscillations decreases within each of the time-delay intervals corresponding to a particular synchronization regime. A dual role of the time delay is thus established: controlling a synchronization mode and degree and controlling an average network frequency. Furthermore, we investigate the influence on the modular synchronization by other parameters: the strength of intermodule coupling and the individual firing rate.

  9. Physical profile data collected in the Equatorial Pacific during cruises to service the TAO/TRITON array, a network of deep ocean moored buoys, February 23 - December 16, 2005 (NODC Accession 0002644)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — During 2005, CTD data were collected in the equatorial Pacific Ocean during cruises to service the TAO/TRITON array, a network of deep ocean moored buoys to support...

  10. Evaluation of Persian Professional Web Social Networks\\\\\\' Features, to Provide a Suitable Solution for Optimization of These Networks in Iran

    Directory of Open Access Journals (Sweden)

    Nadjla Hariri

    2013-03-01

    Full Text Available This study aimed to determine the status of Persian professional web social networks' features and provide a suitable solution for optimization of these networks in Iran. The research methods were library research and evaluative method, and study population consisted of 10 Persian professional web social networks. In this study, for data collection, a check list of social networks important tools and features was used. According to the results, “Cloob”, “IR Experts” and “Doreh” were the most compatible networks with the criteria of social networks. Finally, some solutions were presented for optimization of capabilities of Persian professional web social networks.

  11. Research@ARL: Network Sciences

    Science.gov (United States)

    2013-03-01

    function in concert. Consider the behavior of social insects, such as bees and ants. Fish and birds are other examples of animals whose collective...Tropical Watershed, Springer/Kluwer, 83–95, 2005. Lehner, B. and Döll, P.: Development and validation of a global database of lakes, reservoirs and wetlands ...what it would be in an unperturbed network. A biological network with this sensitivity to error would not survive for very long in the wild . For

  12. Collection Metadata Solutions for Digital Library Applications

    Science.gov (United States)

    Hill, Linda L.; Janee, Greg; Dolin, Ron; Frew, James; Larsgaard, Mary

    1999-01-01

    Within a digital library, collections may range from an ad hoc set of objects that serve a temporary purpose to established library collections intended to persist through time. The objects in these collections vary widely, from library and data center holdings to pointers to real-world objects, such as geographic places, and the various metadata schemas that describe them. The key to integrated use of such a variety of collections in a digital library is collection metadata that represents the inherent and contextual characteristics of a collection. The Alexandria Digital Library (ADL) Project has designed and implemented collection metadata for several purposes: in XML form, the collection metadata "registers" the collection with the user interface client; in HTML form, it is used for user documentation; eventually, it will be used to describe the collection to network search agents; and it is used for internal collection management, including mapping the object metadata attributes to the common search parameters of the system.

  13. Managing Evolving Global Operations Networks

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Johansen, John

    2015-01-01

    For many globally dispersed organisations, the home base (HB) is a historic locus of integrative and coordinating efforts that safeguard overall performance. However, the dynamism of global operations networks is increasingly pulling the centre of gravity away from the HB and dispersing it across...... the network, challenging the HB’s ability to sustain its centrality over time. To counteract this tendency, this paper addresses the gap in the literature regarding the development of the network management capability of the HB within the context of its network. Data was collected through a retrospective...... longitudinal case study of an intra-organisational operations network of one OEM and its three foreign subsidiaries. The findings suggest a row of strategic roles and corresponding managerial capabilities, which the HB needs to develop depending on the changing subsidiaries’ competencies and HB...

  14. Mobile phone collection, reuse and recycling in the UK

    International Nuclear Information System (INIS)

    Ongondo, F.O.; Williams, I.D.

    2011-01-01

    Highlights: → We characterized the key features of the voluntary UK mobile phone takeback network via a survey. → We identified 3 flows: information; product (handsets and accessories); and incentives. → There has been a significant rise in the number of UK takeback schemes since 1997. → Most returned handsets are low quality; little data exists on quantities of mobile phones collected. → Takeback schemes increasingly divert EoL mobile phones from landfill and enable reuse/recycling. - Abstract: Mobile phones are the most ubiquitous electronic product on the globe. They have relatively short lifecycles and because of their (perceived) in-built obsolescence, discarded mobile phones represent a significant and growing problem with respect to waste electrical and electronic equipment (WEEE). An emerging and increasingly important issue for industry is the shortage of key metals, especially the types of metals found in mobile phones, and hence the primary aim of this timely study was to assess and evaluate the voluntary mobile phone takeback network in the UK. The study has characterised the information, product and incentives flows in the voluntary UK mobile phone takeback network and reviewed the merits and demerits of the incentives offered. A survey of the activities of the voluntary mobile phone takeback schemes was undertaken in 2008 to: identify and evaluate the takeback schemes operating in the UK; determine the target groups from whom handsets are collected; and assess the collection, promotion and advertising methods used by the schemes. In addition, the survey sought to identify and critically evaluate the incentives offered by the takeback schemes, evaluate their ease and convenience of use; and determine the types, qualities and quantities of mobile phones they collect. The study has established that the UK voluntary mobile phone takeback network can be characterised as three distinctive flows: information flow; product flow (handsets and related

  15. A generational comparison of social networking site use: the influence of age and social identity.

    Science.gov (United States)

    Barker, Valerie

    2012-01-01

    An online survey (N=256) compared social networking site (SNS) use among younger (millennial: 18-29) and older (baby-boomer: 41-64) subscribers focusing on the influence of collective self-esteem and group identity on motives for SNS use. Younger participants reported higher positive collective self-esteem, social networking site use for peer communication, and social compensation. Regardless of age, participants reporting high collective self-esteem and group identity were more likely to use social networking sites for peer communication and social identity gratifications, while those reporting negative collective self-esteem were more likely to use social networking sites for social compensation. The theoretical implications of the strong relationship between social identity gratifications and social compensation are discussed.

  16. Phytoplankton Monitoring Network - Phytoplankton Analysis with Associated Collection Information

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A qualitative collection of data that includes salinity, temperature, phytoplankton counts and abundance ratios obtained from surface tows in the estuarine and...

  17. A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

    Science.gov (United States)

    Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

    2014-01-01

    Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

  18. National campaign - 100 collectivities connected to the green electric power

    International Nuclear Information System (INIS)

    2004-01-01

    Since july 2004, the local collectivities, the little and medium enterprises and the craft workers can choose their electric power supplier. This offer can be a chance for the renewable energy. The association ''eco maires'' with the help of the WWF began a campaign to obtain the involvement of 100 collectivities interested by the green electric power. The project is presented. The authors presents also the new European Network on the green electric power, Eugene (European Green Electricity Network), which aims to harmonize criteria on the green electric power and to deliver certificates of quality. (A.L.B.)

  19. Network Coding Protocols for Data Gathering Applications

    DEFF Research Database (Denmark)

    Nistor, Maricica; Roetter, Daniel Enrique Lucani; Barros, João

    2015-01-01

    Tunable sparse network coding (TSNC) with various sparsity levels of the coded packets and different feedback mechanisms is analysed in the context of data gathering applications in multi-hop networks. The goal is to minimize the completion time, i.e., the total time required to collect all data ...

  20. Web server's reliability improvements using recurrent neural networks

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Rǎzvan-Daniel; Felea, Ioan

    2012-01-01

    In this paper we describe an interesting approach to error prediction illustrated by experimental results. The application consists of monitoring the activity for the web servers in order to collect the specific data. Predicting an error with severe consequences for the performance of a server (t...... usage, network usage and memory usage. We collect different data sets from monitoring the web server's activity and for each one we predict the server's reliability with the proposed recurrent neural network. © 2012 Taylor & Francis Group...

  1. Review of Biological Network Data and Its Applications

    Directory of Open Access Journals (Sweden)

    Donghyeon Yu

    2013-12-01

    Full Text Available Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

  2. Energy-efficient data collection in wireless sensor networks with time constraints

    NARCIS (Netherlands)

    Mitici, M.A.; Goseling, Jasper; de Graaf, Maurits; Boucherie, Richardus J.

    We consider the problem of retrieving a reliable estimate of an attribute from a wireless sensor network within a fixed time window and with minimum energy consumption for the sensors. The sensors are located in the plane according to some random spatial process. They perform energy harvesting and

  3. Psychology of collective protests: preliminary remarks

    Directory of Open Access Journals (Sweden)

    Cojocaru Natalia

    2016-12-01

    Full Text Available In this article, we present some theoretical syntheses pertaining to the psychology of collective protests, concerning particular factors that determine adherence to and resignation from protest actions, the role of emotions and rituals in the collective protests and new forms of mobilization through online networks. Studies show that mobilization is significantly correlated with the degree of identification with the in-group, identity threat and perception of success, while resignation may be caused by uncertainty about the use of protest or by repressive measures imposed by security forces. One aspect scarcely clarified is what was called the paradox of participation – the persistence of protest despite failures, causing individuals to join again protest actions. Regarding the role of emotions, researchers found that negative emotions against the out-group have an essential role in maintaining the protest action on a longer period. Currently, researchers are particularly interested in the implications of online communication networks (forums, Twitter, Facebook in the organization and unfolding of protest events.

  4. AfSIS MODIS Collection: Vegetation Indices, April 2014

    Data.gov (United States)

    Center for International Earth Science Information Network, Columbia University — The Africa Soil Information Service (AfSIS) Moderate Resolution Imaging Spectroradiometer (MODIS) Collection's Vegetation Indices data set contains rasters with the...

  5. Mechanisms for Prolonging Network Lifetime in Wireless Sensor Networks

    Science.gov (United States)

    Yang, Yinying

    2010-01-01

    Sensors are used to monitor and control the physical environment. A Wireless Sensor Network (WSN) is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it [18][5]. Sensor nodes measure various parameters of the environment and transmit data collected to one or more sinks, using…

  6. A Data Scheduling and Management Infrastructure for the TEAM Network

    Science.gov (United States)

    Andelman, S.; Baru, C.; Chandra, S.; Fegraus, E.; Lin, K.; Unwin, R.

    2009-04-01

    The objective of the Tropical Ecology Assessment and Monitoring Network (www.teamnetwork.org) is "To generate real time data for monitoring long-term trends in tropical biodiversity through a global network of TEAM sites (i.e. field stations in tropical forests), providing an early warning system on the status of biodiversity to effectively guide conservation action". To achieve this, the TEAM Network operates by collecting data via standardized protocols at TEAM Sites. The standardized TEAM protocols include the Climate, Vegetation and Terrestrial Vertebrate Protocols. Some sites also implement additional protocols. There are currently 7 TEAM Sites with plans to grow the network to 15 by June 30, 2009 and 50 TEAM Sites by the end of 2010. Climate Protocol The Climate Protocol entails the collection of climate data via meteorological stations located at the TEAM Sites. This includes information such as precipitation, temperature, wind direction and strength and various solar radiation measurements. Vegetation Protocol The Vegetation Protocol collects standardized information on tropical forest trees and lianas. A TEAM Site will have between 6-9 1ha plots where trees and lianas larger than a pre-specified size are mapped, identified and measured. This results in each TEAM Site repeatedly measuring between 3000-5000 trees annually. Terrestrial Vertebrate Protocol The Terrestrial Vertebrate Protocol collects standardized information on mid-sized tropical forest fauna (i.e. birds and mammals). This information is collected via camera traps (i.e. digital cameras with motion sensors housed in weather proof casings). The images taken by the camera trap are reviewed to identify what species are captured in the image by the camera trap. The image and the interpretation of what is in the image are the data for the Terrestrial Vertebrate Protocol. The amount of data collected through the TEAM protocols provides a significant yet exciting IT challenge. The TEAM Network is

  7. On a new concept of community: social networks, personal communities and collective intelligence

    Directory of Open Access Journals (Sweden)

    Rogério da Costa

    2006-01-01

    Full Text Available This text essentially deals with the transmutation of the concept of "community" into "social networks". This change is due largely to the boom of virtual communities in cyberspace, a fact that has generated a number of studies not only on this new way of weaving a society, but also on the dynamic structure of communication networks. At the core of this transformation, concepts such as social capital, trust and partial sympathy are called upon, to enable us to think about the new forms of association that regulate human activity in our time.

  8. Connecting the Dots and Nodes: A Survey of Skills Requested by Employers for Network Administrators

    Science.gov (United States)

    Morris, Gerard; Fustos, Janos; Haga, Wayne

    2018-01-01

    One definition of a network administrator describes a person who works with computer infrastructures with an emphasis on networking. To determine the specific skills required of a network administrator by employers, data was collected from 698 nationwide job advertisements on Dice.com. The data collection focused on technical skills rather than…

  9. Monitoring interaction and collective text production through text mining

    Directory of Open Access Journals (Sweden)

    Macedo, Alexandra Lorandi

    2014-04-01

    Full Text Available This article presents the Concepts Network tool, developed using text mining technology. The main objective of this tool is to extract and relate terms of greatest incidence from a text and exhibit the results in the form of a graph. The Network was implemented in the Collective Text Editor (CTE which is an online tool that allows the production of texts in synchronized or non-synchronized forms. This article describes the application of the Network both in texts produced collectively and texts produced in a forum. The purpose of the tool is to offer support to the teacher in managing the high volume of data generated in the process of interaction amongst students and in the construction of the text. Specifically, the aim is to facilitate the teacher’s job by allowing him/her to process data in a shorter time than is currently demanded. The results suggest that the Concepts Network can aid the teacher, as it provides indicators of the quality of the text produced. Moreover, messages posted in forums can be analyzed without their content necessarily having to be pre-read.

  10. Privacy-Preserving Trajectory Collection

    DEFF Research Database (Denmark)

    Gidofalvi, Gyozo; Xuegang, Huang; Pedersen, Torben Bach

    2008-01-01

    In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy....... To remedy this situation, this paper first formally defines novel location privacy requirements. Then, it briefly presents a system for privacy--preserving trajectory collection that meets these requirements. The system is composed of an untrusted server and clients communicating in a P2P network. Location...... data is anonymized in the system using data cloaking and data swapping techniques. Finally, the paper empirically demonstrates that the proposed system is effective and feasible....

  11. Emergence of communities and diversity in social networks.

    Science.gov (United States)

    Han, Xiao; Cao, Shinan; Shen, Zhesi; Zhang, Boyu; Wang, Wen-Xu; Cressman, Ross; Stanley, H Eugene

    2017-03-14

    Communities are common in complex networks and play a significant role in the functioning of social, biological, economic, and technological systems. Despite widespread interest in detecting community structures in complex networks and exploring the effect of communities on collective dynamics, a deep understanding of the emergence and prevalence of communities in social networks is still lacking. Addressing this fundamental problem is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in society. An elusive question is how communities with common internal properties arise in social networks with great individual diversity. Here, we answer this question using the ultimatum game, which has been a paradigm for characterizing altruism and fairness. We experimentally show that stable local communities with different internal agreements emerge spontaneously and induce social diversity into networks, which is in sharp contrast to populations with random interactions. Diverse communities and social norms come from the interaction between responders with inherent heterogeneous demands and rational proposers via local connections, where the former eventually become the community leaders. This result indicates that networks are significant in the emergence and stabilization of communities and social diversity. Our experimental results also provide valuable information about strategies for developing network models and theories of evolutionary games and social dynamics.

  12. Cluster-based single-sink wireless sensor networks and passive optical network converged network incorporating sideband modulation schemes

    Science.gov (United States)

    Kumar, Love; Sharma, Vishal; Singh, Amarpal

    2018-02-01

    Wireless sensor networks have tremendous applications, such as civil, military, and environmental monitoring. In most of the applications, sensor data are required to be propagated over the internet/core networks, which result in backhaul setback. Subsequently, there is a necessity to backhaul the sensed information of such networks together with prolonging of the transmission link. Passive optical network (PON) is next-generation access technology emerging as a potential candidate for convergence of the sensed data to the core system. Earlier, the work with single-optical line terminal-PON was demonstrated and investigated merely analytically. This work is an attempt to demonstrate a practical model of a bidirectional single-sink wireless sensor network-PON converged network in which the collected data from cluster heads are transmitted over PON networks. Further, modeled converged structure has been investigated under the influence of double, single, and tandem sideband modulation schemes incorporating a corresponding phase-delay to the sensor data entities that have been overlooked in the past. The outcome illustrates the successful fusion of the sensor data entities over PON with acceptable bit error rate and signal to noise ratio serving as a potential development in the sphere of such converged networks. It has also been revealed that the data entities treated with tandem side band modulation scheme help in improving the performance of the converged structure. Additionally, analysis for uplink transmission reported with queue theory in terms of time cycle, average time delay, data packet generation, and bandwidth utilization. An analytical analysis of proposed converged network shows that average time delay for data packet transmission is less as compared with time cycle delay.

  13. Computer Networks and Globalization

    Directory of Open Access Journals (Sweden)

    J. Magliaro

    2007-07-01

    Full Text Available Communication and information computer networks connect the world in ways that make globalization more natural and inequity more subtle. As educators, we look at these phenomena holistically analyzing them from the realist’s view, thus exploring tensions, (in equity and (injustice, and from the idealist’s view, thus embracing connectivity, convergence and development of a collective consciousness. In an increasingly market- driven world we find examples of openness and human generosity that are based on networks, specifically the Internet. After addressing open movements in publishing, software industry and education, we describe the possibility of a dialectic equilibrium between globalization and indigenousness in view of ecologically designed future smart networks

  14. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  15. Controllability of Surface Water Networks

    Science.gov (United States)

    Riasi, M. Sadegh; Yeghiazarian, Lilit

    2017-12-01

    To sustainably manage water resources, we must understand how to control complex networked systems. In this paper, we study surface water networks from the perspective of structural controllability, a concept that integrates classical control theory with graph-theoretic formalism. We present structural controllability theory and compute four metrics: full and target controllability, control centrality and control profile (FTCP) that collectively determine the structural boundaries of the system's control space. We use these metrics to answer the following questions: How does the structure of a surface water network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Finally, we demonstrate the structural controllability theory in the analysis of a wide range of surface water networks, such as tributary, deltaic, and braided river systems.

  16. Social networks and small businesses performance in West African border regions

    DEFF Research Database (Denmark)

    Kuépié, Mathias; Tenikue, Michel; Walther, Olivier

    2016-01-01

    burden that leads to a negative economic impact. Testing the effect of social networks between small traders and three categories of actors, we find that the most well-connected actors are also the most successful in terms of monthly profit. The effects of social networks are, however, dependent...... with traditional religious leaders has a negative effect on economic performance. Our work has two implications: first, collecting data on social networks remains challenging due to endogeneity. Second, network-enhancing policies should aim at improving both the internal connectivity of economic actors......This paper studies the link between economic performance and social networks in West Africa. Using data collected about 358 small-scale traders in five border markets, we show that social network can simultaneously be a resource which positively contributes to labor market outcomes and a social...

  17. Electricity networks: how 'natural' is the monopoly?

    International Nuclear Information System (INIS)

    Kuenneke, Rolf W.

    1999-01-01

    This article deals with the changing economic characteristics of the electricity network. Traditionally, electricity networks are considered natural monopolies for various kinds of market failures coincide in this essential part of the electricity infrastructure. Technological induced complementarities between nodes and links are causing network externalities, economies of scale, a high degree of mono-functionality, collective good characteristics and an inherent tendency towards concentrated market structures. It is argued that recent technological trends imply a dramatic change of the network economics, leading to possibilities of inter- and intra-network competition, as well as inter fuel competition. The possible implications for the regulatory framework of this sector are addressed. (Author)

  18. Reference hydrologic networks I. The status and potential future directions of national reference hydrologic networks for detecting trends

    Science.gov (United States)

    Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Higgins, Hélène; Hodgkins, Glenn A.; Marsh, Terry; Looser, Ulrich

    2012-01-01

    Identifying climate-driven trends in river flows on a global basis is hampered by a lack of long, quality time series data for rivers with relatively undisturbed regimes. This is a global problem compounded by the lack of support for essential long-term monitoring. Experience demonstrates that, with clear strategic objectives, and the support of sponsoring organizations, reference hydrologic networks can constitute an exceptionally valuable data source to effectively identify, quantify and interpret hydrological change—the speed and magnitude of which is expected to a be a primary driver of water management and flood alleviation strategies through the future—and for additional applications. Reference hydrologic networks have been developed in many countries in the past few decades. These collections of streamflow gauging stations, that are maintained and operated with the intention of observing how the hydrology of watersheds responds to variations in climate, are described. The status of networks under development is summarized. We suggest a plan of actions to make more effective use of this collection of networks.

  19. Delay-tolerant mobile network protocol for rice field monitoring using wireless sensor networks

    Science.gov (United States)

    Guitton, Alexandre; Andres, Frédéric; Cardoso, Jarbas Lopes; Kawtrakul, Asanee; Barbin, Silvio E.

    2015-10-01

    The monitoring of rice fields can improve productivity by helping farmers throughout the rice cultivation cycle, on various issues: when to harvest, when to treat the crops against disease, when to increase the water level, how to share observations and decisions made in a collaborative way, etc. In this paper, we propose an architecture to monitor a rice field by a wireless sensor network. Our architecture is based on static sensor nodes forming a disconnected network, and mobile nodes communicating with the sensor nodes in a delay-tolerant manner. The data collected by the static sensor nodes are transmitted to mobile nodes, which in turn transmit them to a gateway, connected to a database, for further analysis. We focus on the related architecture, as well as on the energy-efficient protocols intended to perform the data collection.

  20. Digital Networked Information Society and Public Health: Problems and Promises of Networked Health Communication of Lay Publics.

    Science.gov (United States)

    Kim, Jeong-Nam

    2018-01-01

    This special issue of Health Communication compiles 10 articles to laud the promise and yet confront the problems in the digital networked information society related to public health. We present this anthology of symphony and cacophony of lay individuals' communicative actions in a digital networked information society. The collection of problems and promise of the new digital world may be a cornerstone joining two worlds-pre- and postdigital network society-and we hope this special issue will help better shape our future states of public health.

  1. Emergence of collective action and environmental networking in relation to radioactive waste management

    International Nuclear Information System (INIS)

    Williams, R.G.; Payne, B.A.

    1985-01-01

    This paper explores the relationship between the national environmental movement and nuclear technology in relation to a local emergent group. The historical development of nuclear technology in this conutry has followed a path leading to continued fear and mistrust of waste management by a portion of the population. At the forefront of opposition to nuclear technology are people and groups endorsing environmental values. Because of the antinuclear attitudes of environmentalists and the value orientation of appropriate technologists in the national environmental movement, it seems appropriate for local groups to call on these national groups for assistance regarding nuclear-related issues. A case study is used to illustrate how a local action group, once integrated into a national environmental network, can become an effective, legitimate participant in social change. The formation, emergence, mobilization, and networking of a local group opposed to a specific federal radioactive waste management plan is described based on organizational literature. However, inherent contradictions in defining the local versus national benefits plus inherent problems within the environmental movement could be acting to limit the effectiveness of such networks. 49 refs

  2. Updating Road Networks by Local Renewal from GPS Trajectories

    Directory of Open Access Journals (Sweden)

    Tao Wu

    2016-09-01

    Full Text Available The long production cycle and huge cost of collecting road network data often leave the data lagging behind the latest real conditions. However, this situation is rapidly changing as the positioning techniques ubiquitously used in mobile devices are gradually being implemented in road network research and applications. Currently, the predominant approaches infer road networks from mobile location information (e.g., GPS trajectory data directly using various extracting algorithms, which leads to expensive consumption of computational resources in the case of large-scale areas. For this reason, we propose an alternative that renews road networks with a novel spiral strategy, including a hidden Markov model (HMM for detecting potential problems in existing road network data and a method to update the data, on the local scale, by generating new road segments from trajectory data. The proposed approach reduces computation costs on roads with completed or updated information by updating problem road segments in the minimum range of the road network. We evaluated the performance of our proposals using GPS traces collected from taxies and OpenStreetMap (OSM road networks covering urban areas of Wuhan City.

  3. Network stigma towards people living with HIV/AIDS and their caregivers: An egocentric network study.

    Science.gov (United States)

    Wu, Fei; He, Xin; Guida, Jennifer; Xu, Yongfang; Liu, Hongjie

    2015-10-01

    HIV stigma occurs among peers in social networks. However, the features of social networks that drive HIV stigma are not well understood. The objective of this study is to investigate anticipated HIV stigma within the social networks of people living with HIV/AIDS (PLWHA) (N = 147) and the social networks of PLWHA's caregivers (N = 148). The egocentric social network data were collected in Guangxi, China. More than half of PLWHA (58%) and their caregivers (53%) anticipated HIV stigma from their network peers. Both PLWHA and their caregivers anticipated that spouses or other family members were less likely to stigmatise them, compared to friend peers or other relationships. Married network peers were believed to stigmatise caregivers more than unmarried peers. The association between frequent contacts and anticipated stigma was negative among caregivers. Being in a close relationship with PLWHA or caregivers (e.g., a spouse or other family member) was associated with less anticipated stigma. Lower network density was associated with higher anticipated stigma among PLWHA's alters, but not among caregivers' alters. Findings may shed light on innovative stigma reduction interventions at the social network level and therefore improve HIV/AIDS treatment utilisation.

  4. Synchronized Data Aggregation for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2014-01-01

    Wireless Sensor Networks (WSNs) are used for monitoring and data collection purposes. A key challenge in effective data collection is to schedule and synchronize the activities of the nodes with global clock. This paper proposes the Synchronized Data Aggregation Algorithm (SDA) using spanning tree...

  5. Mobile phone collection, reuse and recycling in the UK.

    Science.gov (United States)

    Ongondo, F O; Williams, I D

    2011-06-01

    Mobile phones are the most ubiquitous electronic product on the globe. They have relatively short lifecycles and because of their (perceived) in-built obsolescence, discarded mobile phones represent a significant and growing problem with respect to waste electrical and electronic equipment (WEEE). An emerging and increasingly important issue for industry is the shortage of key metals, especially the types of metals found in mobile phones, and hence the primary aim of this timely study was to assess and evaluate the voluntary mobile phone takeback network in the UK. The study has characterised the information, product and incentives flows in the voluntary UK mobile phone takeback network and reviewed the merits and demerits of the incentives offered. A survey of the activities of the voluntary mobile phone takeback schemes was undertaken in 2008 to: identify and evaluate the takeback schemes operating in the UK; determine the target groups from whom handsets are collected; and assess the collection, promotion and advertising methods used by the schemes. In addition, the survey sought to identify and critically evaluate the incentives offered by the takeback schemes, evaluate their ease and convenience of use; and determine the types, qualities and quantities of mobile phones they collect. The study has established that the UK voluntary mobile phone takeback network can be characterised as three distinctive flows: information flow; product flow (handsets and related accessories); and incentives flow. Over 100 voluntary schemes offering online takeback of mobile phone handsets were identified. The schemes are operated by manufacturers, retailers, mobile phone network service operators, charities and by mobile phone reuse, recycling and refurbishing companies. The latter two scheme categories offer the highest level of convenience and ease of use to their customers. Approximately 83% of the schemes are either for-profit/commercial-oriented and/or operate to raise funds

  6. Bandwidth Efficient Hybrid Synchronization for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2015-01-01

    Data collection and transmission are the fundamental operations of Wireless Sensor Networks (WSNs). A key challenge in effective data collection and transmission is to schedule and synchronize the activities of the nodes with the global clock. This paper proposes the Bandwidth Efficient Hybrid...... in the network and then perform the pair-wise synchronization. With the mobility of node, the structure frequently changes causing an increase in energy consumption. To mitigate the problem BESDA aggregate data with the notion of a global timescale throughout the network and schedule based time-division multiple...... accesses (TDMA) techniques as MAC layer protocol. It reduces the collision of packets. Simulation results show that BESDA is energy efficient, with increased throughput, and has less delay as compared with state-of-the-art....

  7. 2016 Network Games, Control, and Optimization Conference

    CERN Document Server

    Jimenez, Tania; Solan, Eilon

    2017-01-01

    This contributed volume offers a collection of papers presented at the 2016 Network Games, Control, and Optimization conference (NETGCOOP), held at the University of Avignon in France, November 23-25, 2016. These papers highlight the increasing importance of network control and optimization in many networking application domains, such as mobile and fixed access networks, computer networks, social networks, transportation networks, and, more recently, electricity grids and biological networks. Covering a wide variety of both theoretical and applied topics in the areas listed above, the authors explore several conceptual and algorithmic tools that are needed for efficient and robust control operation, performance optimization, and better understanding the relationships between entities that may be acting cooperatively or selfishly in uncertain and possibly adversarial environments. As such, this volume will be of interest to applied mathematicians, computer scientists, engineers, and researchers in other relate...

  8. Pinning control of complex networked systems synchronization, consensus and flocking of networked systems via pinning

    CERN Document Server

    Su, Housheng

    2013-01-01

    Synchronization, consensus and flocking are ubiquitous requirements in networked systems. Pinning Control of Complex Networked Systems investigates these requirements by using the pinning control strategy, which aims to control the whole dynamical network with huge numbers of nodes by imposing controllers for only a fraction of the nodes. As the direct control of every node in a dynamical network with huge numbers of nodes might be impossible or unnecessary, it’s then very important to use the pinning control strategy for the synchronization of complex dynamical networks. The research on pinning control strategy in consensus and flocking of multi-agent systems can not only help us to better understand the mechanisms of natural collective phenomena, but also benefit applications in mobile sensor/robot networks. This book offers a valuable resource for researchers and engineers working in the fields of control theory and control engineering.   Housheng Su is an Associate Professor at the Department of Contro...

  9. Communication Network Architectures Based on Ethernet Passive Optical Network for Offshore Wind Power Farms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Ahmed

    2016-03-01

    Full Text Available Nowadays, with large-scale offshore wind power farms (WPFs becoming a reality, more efforts are needed to maintain a reliable communication network for WPF monitoring. Deployment topologies, redundancy, and network availability are the main items to enhance the communication reliability between wind turbines (WTs and control centers. Traditional communication networks for monitoring and control (i.e., supervisory control and data acquisition (SCADA systems using switched gigabit Ethernet will not be sufficient for the huge amount of data passing through the network. In this paper, the optical power budget, optical path loss, reliability, and network cost of the proposed Ethernet Passive Optical Network (EPON-based communication network for small-size offshore WPFs have been evaluated for five different network architectures. The proposed network model consists of an optical network unit device (ONU deployed on the WT side for collecting data from different internal networks. All ONUs from different WTs are connected to a central optical line terminal (OLT, placed in the control center. There are no active electronic elements used between the ONUs and the OLT, which reduces the costs and complexity of maintenance and deployment. As fiber access networks without any protection are characterized by poor reliability, three different protection schemes have been configured, explained, and discussed. Considering the cost of network components, the total implementation expense of different architectures with, or without, protection have been calculated and compared. The proposed network model can significantly contribute to the communication network architecture for next generation WPFs.

  10. Collective Travel Planning in Spatial Networks

    KAUST Repository

    Shang, Shuo

    2015-12-17

    Travel planning and recommendation are important aspects of transportation.We propose and investigate a novel Collective Travel Planning (CTP) query that finds the lowest-cost route connecting multiple sources and a destination, via at most k meeting points. When multiple travelers target the same destination (e.g., a stadium or a theater), they may want to assemble at meeting points and then go together to the destination by public transport to reduce their global travel cost (e.g., energy, money, or greenhouse-gas emissions). This type of functionality holds the potential to bring significant benefits to society and the environment, such as reducing energy consumption and greenhouse-gas emissions, enabling smarter and greener transportation, and reducing traffic congestions. The CTP query is Max SNP-hard. To compute the query efficiently, we develop two algorithms, including an exact algorithm and an approximation algorithm. The exact algorithm is capable finding the optimal result for small values of k (e.g., k = 2) in interactive time, while the approximation algorithm, which has a 5-approximation ratio, is suitable for other situations. The performance of the CTP query is studied experimentally with real and synthetic spatial data.

  11. Collaborative Trust Networks in Engineering Design Adaptation

    DEFF Research Database (Denmark)

    Atkinson, Simon Reay; Maier, Anja; Caldwell, Nicholas

    2011-01-01

    ); applying the Change Prediction Method (CPM) tool. It posits the idea of the ‘Networks-in-Being’ with varying individual and collective characteristics. [Social] networks are considered to facilitate information exchange between actors. At the same time, networks failing to provide trusted-information can...... hinder effective communication and collaboration. Different combinations of trust may therefore improve or impair the likelihood of information flow, transfer and subsequent action (cause and effect). This paper investigates how analysing different types of network-structures-in-being can support......Within organisations, decision makers have to rely on collaboration with other actors from different disciplines working within highly dynamic and distributed associated networks of varying size and scales. This paper develops control and influence networks within Design Structure Matrices (DSM...

  12. Pattern formation and firing synchronization in networks of map neurons

    International Nuclear Information System (INIS)

    Wang Qingyun; Duan Zhisheng; Huang Lin; Chen Guanrong; Lu Qishao

    2007-01-01

    Patterns and collective phenomena such as firing synchronization are studied in networks of nonhomogeneous oscillatory neurons and mixtures of oscillatory and excitable neurons, with dynamics of each neuron described by a two-dimensional (2D) Rulkov map neuron. It is shown that as the coupling strength is increased, typical patterns emerge spatially, which propagate through the networks in the form of beautiful target waves or parallel ones depending on the size of networks. Furthermore, we investigate the transitions of firing synchronization characterized by the rate of firing when the coupling strength is increased. It is found that there exists an intermediate coupling strength; firing synchronization is minimal simultaneously irrespective of the size of networks. For further increasing the coupling strength, synchronization is enhanced. Since noise is inevitable in real neurons, we also investigate the effects of white noise on firing synchronization for different networks. For the networks of oscillatory neurons, it is shown that firing synchronization decreases when the noise level increases. For the missed networks, firing synchronization is robust under the noise conditions considered in this paper. Results presented in this paper should prove to be valuable for understanding the properties of collective dynamics in real neuronal networks

  13. The Graph Laplacian and the Dynamics of Complex Networks

    Energy Technology Data Exchange (ETDEWEB)

    Thulasidasan, Sunil [Los Alamos National Laboratory

    2012-06-11

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

  14. Tropical Plant Collections

    DEFF Research Database (Denmark)

    Friis, Ib; Balslev, Henrik

    that involved Germany, Britain and France, until independence, which was brightened by exemplary collaboration. Muasya focussed on South Africa, which is the most developed country in sub-Saharan Africa with a well-functioning network of herbaria that covers widely different biota. Sanjappa outlined the history...... crisis. Friis gave a broad overview of the history of herbaria and botanical gardens and the changing conceptual frameworks behind their existence. Baldini talked about early Italian botanical collectors and the fate of their collections. Baas accounted for the Golden Age of Dutch botany during pre......-colonial and early colonial periods. With the presentation by Cribb on the botany of the British Empire we were fully into the colonial period, focussing on the Royal Botanic Gardens at Kew. The situation in North America was treated by Funk, who illustrated the development of collections of tropical plants...

  15. Sea Turtle Stranding Network Reports

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Sea Turtle Stranding and Salvage Network (STSSN) was formally established in 1980 to collect information on and document the stranding of marine turtles along...

  16. NESSIE: Network Example Source Supporting Innovative Experimentation

    Science.gov (United States)

    Taylor, Alan; Higham, Desmond J.

    We describe a new web-based facility that makes available some realistic examples of complex networks. NESSIE (Network Example Source Supporting Innovative Experimentation) currently contains 12 specific networks from a diverse range of application areas, with a Scottish emphasis. This collection of data sets is designed to be useful for researchers in network science who wish to evaluate new algorithms, concepts and models. The data sets are available to download in two formats (MATLAB's .mat format and .txt files readable by packages such as Pajek), and some basic MATLAB tools for computing summary statistics are also provided.

  17. The First Year of Croatian Meteor Network

    Science.gov (United States)

    Andreic, Zeljko; Segon, Damir

    2010-08-01

    The idea and a short history of Croatian Meteor Network (CMN) is described. Based on use of cheap surveillance cameras, standard PC-TV cards and old PCs, the Network allows schools, amateur societies and individuals to participate in photographic meteor patrol program. The network has a strong educational component and many cameras are located at or around teaching facilities. Data obtained by these cameras are collected and processed by the scientific team of the network. Currently 14 cameras are operable, covering a large part of the croatian sky, data gathering is fully functional, and data reduction software is in testing phase.

  18. Construct mine environment monitoring system based on wireless mesh network

    Science.gov (United States)

    Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

    2018-04-01

    The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

  19. Sync in Complex Dynamical Networks: Stability, Evolution, Control, and Application

    OpenAIRE

    Li, Xiang

    2005-01-01

    In the past few years, the discoveries of small-world and scale-free properties of many natural and artificial complex networks have stimulated significant advances in better understanding the relationship between the topology and the collective dynamics of complex networks. This paper reports recent progresses in the literature of synchronization of complex dynamical networks including stability criteria, network synchronizability and uniform synchronous criticality in different topologies, ...

  20. Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model.

    Directory of Open Access Journals (Sweden)

    Guido Gigante

    2015-11-01

    Full Text Available Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed 'quasi-orbits', which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network's firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms.

  1. Information Propagation in Complex Networks : Structures and Dynamics

    NARCIS (Netherlands)

    Märtens, M.

    2018-01-01

    This thesis is a contribution to a deeper understanding of how information propagates and what this process entails. At its very core is the concept of the network: a collection of nodes and links, which describes the structure of the systems under investigation. The network is a mathematical model

  2. Availability Issues in Wireless Visual Sensor Networks

    Science.gov (United States)

    Costa, Daniel G.; Silva, Ivanovitch; Guedes, Luiz Affonso; Vasques, Francisco; Portugal, Paulo

    2014-01-01

    Wireless visual sensor networks have been considered for a large set of monitoring applications related with surveillance, tracking and multipurpose visual monitoring. When sensors are deployed over a monitored field, permanent faults may happen during the network lifetime, reducing the monitoring quality or rendering parts or the entire network unavailable. In a different way from scalar sensor networks, camera-enabled sensors collect information following a directional sensing model, which changes the notions of vicinity and redundancy. Moreover, visual source nodes may have different relevancies for the applications, according to the monitoring requirements and cameras' poses. In this paper we discuss the most relevant availability issues related to wireless visual sensor networks, addressing availability evaluation and enhancement. Such discussions are valuable when designing, deploying and managing wireless visual sensor networks, bringing significant contributions to these networks. PMID:24526301

  3. Crowdsourcing methodology: establishing the Cervid Disease Network and the North American Mosquito Project.

    Science.gov (United States)

    Cohnstaedt, Lee W; Snyder, Darren; Maki, Elin; Schafer, Shawn

    2016-06-30

    Crowdsourcing is obtaining needed services, ideas, or content by soliciting contributions from a large group of people. This new method of acquiring data works well for single reports, but fails when long-term data collection is needed, mainly due to reporting fatigue or failure of repeated sampling by individuals. To establish a crowdsourced collections network researchers must recruit, reward, and retain contributors to the project. These 3 components of crowdsourcing are discussed using the United States Department of Agriculture social networks, the Cervid Disease Network, and the North American Mosquito Project. The North American Mosquito Project is a large network of professional mosquito control districts and public health agencies, which collects mosquito specimens for genetic studies. The Cervid Disease Network is a crowd-sourced disease monitoring system, which uses voluntary sentinel farms or wildlife programs throughout the United States of America to report the onset and severity of diseases in local areas for pathogen surveillance studies.

  4. Complex network synchronization of chaotic systems with delay coupling

    International Nuclear Information System (INIS)

    Theesar, S. Jeeva Sathya; Ratnavelu, K.

    2014-01-01

    The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology

  5. Emergence of robustness in networks of networks

    Science.gov (United States)

    Roth, Kevin; Morone, Flaviano; Min, Byungjoon; Makse, Hernán A.

    2017-06-01

    A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017), 10.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.

  6. Forecasting short-term data center network traffic load with convolutional neural networks

    Science.gov (United States)

    Ordozgoiti, Bruno; Gómez-Canaval, Sandra

    2018-01-01

    Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution. PMID:29408936

  7. Forecasting short-term data center network traffic load with convolutional neural networks.

    Science.gov (United States)

    Mozo, Alberto; Ordozgoiti, Bruno; Gómez-Canaval, Sandra

    2018-01-01

    Efficient resource management in data centers is of central importance to content service providers as 90 percent of the network traffic is expected to go through them in the coming years. In this context we propose the use of convolutional neural networks (CNNs) to forecast short-term changes in the amount of traffic crossing a data center network. This value is an indicator of virtual machine activity and can be utilized to shape the data center infrastructure accordingly. The behaviour of network traffic at the seconds scale is highly chaotic and therefore traditional time-series-analysis approaches such as ARIMA fail to obtain accurate forecasts. We show that our convolutional neural network approach can exploit the non-linear regularities of network traffic, providing significant improvements with respect to the mean absolute and standard deviation of the data, and outperforming ARIMA by an increasingly significant margin as the forecasting granularity is above the 16-second resolution. In order to increase the accuracy of the forecasting model, we exploit the architecture of the CNNs using multiresolution input distributed among separate channels of the first convolutional layer. We validate our approach with an extensive set of experiments using a data set collected at the core network of an Internet Service Provider over a period of 5 months, totalling 70 days of traffic at the one-second resolution.

  8. Consensus group sessions are useful to reconcile stakeholders’ perspectives about network performance evaluation

    Directory of Open Access Journals (Sweden)

    Marie-Eve Lamontagne

    2010-12-01

    Full Text Available Background: Having a common vision among network stakeholders is an important ingredient to developing a performance evaluation process. Consensus methods may be a viable means to reconcile the perceptions of different stakeholders about the dimensions to include in a performance evaluation framework.Objectives: To determine whether individual organizations within traumatic brain injury (TBI networks differ in perceptions about the importance of performance dimensions for the evaluation of TBI networks and to explore the extent to which group consensus sessions could reconcile these perceptions.Methods: We used TRIAGE, a consensus technique that combines an individual and a group data collection phase to explore the perceptions of network stakeholders and to reach a consensus within structured group discussions.Results: One hundred and thirty-nine professionals from 43 organizations within eight TBI networks participated in the individual data collection; 62 professionals from these same organisations contributed to the group data collection. The extent of consensus based on questionnaire results (e.g. individual data collection was low, however, 100% agreement was obtained for each network during the consensus group sessions. The median importance scores and mean ranks attributed to the dimensions by individuals compared to groups did not differ greatly. Group discussions were found useful in understanding the reasons motivating the scoring, for resolving differences among participants, and for harmonizing their values.Conclusion: Group discussions, as part of a consensus technique, appear to be a useful process to reconcile diverging perceptions of network performance among stakeholders.

  9. VoIP attacks detection engine based on neural network

    Science.gov (United States)

    Safarik, Jakub; Slachta, Jiri

    2015-05-01

    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  10. Analysis Of Data Collected By Epidemio-Surveillance Network For ...

    African Journals Online (AJOL)

    Summary During the period 1996 - 2002, 82 suspected cases of pasteurellosis were recorded and 88 samples taken from suspected animals were collected and analysed by the national laboratory Laboratoire de Recherches Vétérinaires et Zootechniques de Farcha. Out of 82 suspected cases, only 7 % were confirmed by ...

  11. Optimal pinnate leaf-like network/matrix structure for enhanced conductive cooling

    International Nuclear Information System (INIS)

    Hu, Liguo; Zhou, Han; Zhu, Hanxing; Fan, Tongxiang; Zhang, Di

    2015-01-01

    Highlights: • We present a pinnate leaf-like network/matrix structure for conductive cooling. • We study the effect of matrix thickness on network conductive cooling performance. • Matrix thickness determines optimal distance between collection channels in network. • We determine the optimal network architecture from a global perspective. • Optimal network greatly reduces the maximum temperature difference in the network. - Abstract: Heat generated in electronic devices has to be effectively removed because excessive temperature strongly impairs their performance and reliability. Embedding a high thermal conductivity network into an electronic device is an effective method to conduct the generated heat to the outside. In this study, inspired by the pinnate leaf, we present a pinnate leaf-like network embedded in the matrix (i.e., electronic device) to cool the matrix by conduction and develop a method to construct the optimal network. In this method, we first investigate the effect of the matrix thickness on the conductive cooling performance of the network, and then optimize the network architecture from a global perspective so that to minimize the maximum temperature difference between the heat sink and the matrix. The results indicate that the matrix thickness determines the optimal distance of the neighboring collection channels in the network, which minimizes the maximum temperature difference between the matrix and the network, and that the optimal network greatly reduces the maximum temperature difference in the network. The results can serve as a design guide for efficient conductive cooling of electronic devices

  12. The Dynamics of Protest Recruitment through an Online Network

    Science.gov (United States)

    González-Bailón, Sandra; Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir

    2011-12-01

    The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to be more central in the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.

  13. SOLAR PHOTOVOLTAIC OUTPUT POWER FORECASTING USING BACK PROPAGATION NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    B. Jency Paulin

    2016-01-01

    Full Text Available Solar Energy is an important renewable and unlimited source of energy. Solar photovoltaic power forecasting, is an estimation of the expected power production, that help the grid operators to better manage the electric balance between power demand and supply. Neural network is a computational model that can predict new outcomes from past trends. The artificial neural network is used for photovoltaic plant energy forecasting. The output power for solar photovoltaic cell is predicted on hourly basis. In historical dataset collection process, two dataset was collected and used for analysis. The dataset was provided with three independent attributes and one dependent attributes. The implementation of Artificial Neural Network structure is done by Multilayer Perceptron (MLP and training procedure for neural network is done by error Back Propagation (BP. In order to train and test the neural network, the datasets are divided in the ratio 70:30. The accuracy of prediction can be done by using various error measurement criteria and the performance of neural network is to be noted.

  14. The Strip Clustering Scheme for data collection in large-scale Wireless Sensing Network of the road

    Directory of Open Access Journals (Sweden)

    Zhoujing Ye

    2018-03-01

    Full Text Available For intelligent traffic and road structural health monitoring, Wireless Sensing Network has been applied widely in transportation, and large quantity of sensor nodes have been embedded in roadways. Now the service lives of sensors are limited mainly because of their battery power storage. So the life cycle of the whole network can be extended if the service life of each sensor in the network is prolonged. In this paper, the Strip Clustering Scheme (SCS is proposed to replace the Conventional Scheme (CS. This method includes region division, cluster head node selection, link construction, data fusion and transmission. Adopting SCS can reduce a lot of redundant data and the total energy consumption of the network by data fusion. In addition, adopting SCS can also extend the monitoring area without increasing the communication range of the Access Point (AP, and facilitate further expansion of the network as a result. Based on the numerically simulated results, CS method can be used for the WSN within 75 m, and SCS method is more suitable when the monitoring range is larger than 75 m. To achieve the optimal network costs and the network life cycle by using SCS, the range of d (the longitudinal spacing of adjacent nodes, is suggested as 10–12.5 m and the energy of cluster head nodes is 60% higher than the energy of non-head nodes with fixed w (the transverse distance of adjacent nodes. And the extra energy of head nodes can be obtained by adding the number of battery within the head nodes or using renewable energy technologies. Keywords: WSN, Road, Energy consumption, Conventional Scheme, Strip Clustering Scheme

  15. Theses on Distributed Aesthetics. Or, What a Network is Not

    Directory of Open Access Journals (Sweden)

    Geert Lovink

    2005-01-01

    Full Text Available In this essay Lovink and Munster set forward a number of proposals for a distributed aesthetics. If new media artistic practice and aesthetic experience were most often characterised by recourse to computational culture, then distributed aesthetics is dominated by networks. Networked media and technologies help to disperse experience so that we never seem to be having our experiences in the one place anymore. However, the authors suggest, most of the images and rhetoric attempting to characterise this distributed experience are drawn from the cartographic traditions of geographic information systems and/or conceptions of biological networking and growth. These do not assist in coming to terms with the specifically social aspects of online networking. The authors speculate that a distributed aesthetics must take into account the collective and personal 'aesthesia' of online networks - the experience of labouring towards new forms of social collectivity that produces not only euphoria but also boredom and frustration.

  16. Cooperation and Development: a study of case in network cooperation

    Directory of Open Access Journals (Sweden)

    June Alisson Westarb Cruz

    2009-03-01

    Full Text Available The need to develop new surviving strategies and competitive advantage by individuals and organizations make cooperation to obtain complementary competences and potentialities very important, through the insertion of social actors in multiple networks of relationships and interactions.  This research was made in an Association Network of Carrinheiros[1] located in Curitiba and in the coast of Paraná.  The objective of the study was to analyze the structural characteristics of the network and its implications to develop collective actions. The data was collected through questionnaires, interviews, document analysis, and the daily direct observation of the network.  An interaction system between individuals and organizations from various sectors in society could be verified. This interaction stimulates the structured work connected to associations and cooperatives.  Between the actors of the network, concepts and realities are different, as well as individual objectives are distinct.  However, they converge to a common general objective that establish a common base for collaborative work.

  17. Towards an Information Theory of Complex Networks

    CERN Document Server

    Dehmer, Matthias; Mehler, Alexander

    2011-01-01

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

  18. Small diameter symmetric networks from linear groups

    Science.gov (United States)

    Campbell, Lowell; Carlsson, Gunnar E.; Dinneen, Michael J.; Faber, Vance; Fellows, Michael R.; Langston, Michael A.; Moore, James W.; Multihaupt, Andrew P.; Sexton, Harlan B.

    1992-01-01

    In this note is reported a collection of constructions of symmetric networks that provide the largest known values for the number of nodes that can be placed in a network of a given degree and diameter. Some of the constructions are in the range of current potential engineering significance. The constructions are Cayley graphs of linear groups obtained by experimental computation.

  19. Feedback surveys for transnational social change networks : a step ...

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

    Feedback surveys are an assessment exercise that differs from conventional evaluation by creating a comparative data set. Transnational social change networks are international networks with members spread across multiple countries working to collectively organize towards a common long-term goal that would not be ...

  20. Wood heat networks - Scope of relevancy

    International Nuclear Information System (INIS)

    Baiz, Adam; Monnoyer-Smith, Laurence

    2017-01-01

    As the French law of energy transition for a green growth foresees a strong development of heat networks based on renewable energies, this study aims at proposing elements of answer about wood-based heat networks: can they be competitive with respect to cheap gas? Would high power networks result in important economies of scale? Which will be the impact of a reduction of energy consumption in a renewed area on the profitability of a heat network? A model of actor-based and social-economic costs has been developed to compare the profitability of wood-supplied heat networks with that of conventional heating means (individual electric heating, individual or collective gas heating, heat pump, individual fuel heating, and individual wood heating). The model makes the distinction between investment fixed costs, varying energy consumption and exploitation costs, and also externalised environmental costs. Then, different scale effects are assessed. They may concern investment costs for boiler, for sub-stations and for the distribution network. The cost interval of heat networks is then studied among the very heterogeneous existing heat networks. Investment and production costs of different configurations of the different above-mentioned heat networks are discussed

  1. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  2. Predicting and controlling infectious disease epidemics using temporal networks.

    Science.gov (United States)

    Masuda, Naoki; Holme, Petter

    2013-01-01

    Infectious diseases can be considered to spread over social networks of people or animals. Mainly owing to the development of data recording and analysis techniques, an increasing amount of social contact data with time stamps has been collected in the last decade. Such temporal data capture the dynamics of social networks on a timescale relevant to epidemic spreading and can potentially lead to better ways to analyze, forecast, and prevent epidemics. However, they also call for extended analysis tools for network epidemiology, which has, to date, mostly viewed networks as static entities. We review recent results of network epidemiology for such temporal network data and discuss future developments.

  3. Structural analysis of behavioral networks from the Internet

    International Nuclear Information System (INIS)

    Meiss, M R; Menczer, F; Vespignani, A

    2008-01-01

    In spite of the Internet's phenomenal growth and social impact, many aspects of the collective communication behavior of its users are largely unknown. Understanding the structure and dynamics of the behavioral networks that connect users with each other and with services across the Internet is key to modeling the network and designing future applications. We present a characterization of the properties of the behavioral networks generated by several million users of the Abilene (Internet2) network. Structural features of these networks offer new insights into scaling properties of network activity and ways of distinguishing particular patterns of traffic. For example, we find that the structure of the behavioral network associated with Web activity is characterized by such extreme heterogeneity as to challenge any simple attempt to model Web server traffic

  4. Structural analysis of behavioral networks from the Internet

    Energy Technology Data Exchange (ETDEWEB)

    Meiss, M R; Menczer, F [Department of Computer Science, Indiana University, Bloomington, IN 47405 (United States); Vespignani, A [Department of Informatics, Indiana University, Bloomington, IN 47408 (United States)], E-mail: mmeiss@indiana.edu

    2008-06-06

    In spite of the Internet's phenomenal growth and social impact, many aspects of the collective communication behavior of its users are largely unknown. Understanding the structure and dynamics of the behavioral networks that connect users with each other and with services across the Internet is key to modeling the network and designing future applications. We present a characterization of the properties of the behavioral networks generated by several million users of the Abilene (Internet2) network. Structural features of these networks offer new insights into scaling properties of network activity and ways of distinguishing particular patterns of traffic. For example, we find that the structure of the behavioral network associated with Web activity is characterized by such extreme heterogeneity as to challenge any simple attempt to model Web server traffic.

  5. 8th Conference on Complex Networks

    CERN Document Server

    Menezes, Ronaldo; Sinatra, Roberta; Zlatic, Vinko

    2017-01-01

    This book collects the works presented at the 8th International Conference on Complex Networks (CompleNet) 2017 in Dubrovnik, Croatia, on March 21-24, 2017. CompleNet aims at bringing together researchers and practitioners working in areas related to complex networks. The past two decades has witnessed an exponential increase in the number of publications within this field. From biological systems to computer science, from economic to social systems, complex networks are becoming pervasive in many fields of science. It is this interdisciplinary nature of complex networks that CompleNet aims at addressing. The last decades have seen the emergence of complex networks as the language with which a wide range of complex phenomena in fields as diverse as physics, computer science, and medicine (to name a few) can be properly described and understood. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as network controllability, social structure, online behavior, recommend...

  6. A small-world network model of facial emotion recognition.

    Science.gov (United States)

    Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto

    2016-01-01

    Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.

  7. Applications of social media and social network analysis

    CERN Document Server

    Kazienko, Przemyslaw

    2015-01-01

    This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

  8. New trends in computational collective intelligence

    CERN Document Server

    Kim, Sang-Wook; Trawiński, Bogdan

    2015-01-01

    This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods an...

  9. 7th China Conference on Wireless Sensor Networks

    CERN Document Server

    Cui, Li; Guo, Zhongwen

    2014-01-01

    Advanced Technologies in Ad Hoc and Sensor Networks collects selected papers from the 7th China Conference on Wireless Sensor Networks (CWSN2013) held in Qingdao, October 17-19, 2013. The book features state-of-the-art studies on Sensor Networks in China with the theme of “Advances in wireless sensor networks of China”. The selected works can help promote development of sensor network technology towards interconnectivity, resource sharing, flexibility and high efficiency. Researchers and engineers in the field of sensor networks can benefit from the book. Xue Wang is a professor at Tsinghua University; Li Cui is a professor at Institute of Computing Technology, Chinese Academy of Sciences; Zhongwen Guo is a professor at Ocean University of China.

  10. Twisted network programming essentials

    CERN Document Server

    Fettig, Abe

    2005-01-01

    Twisted Network Programming Essentials from O'Reilly is a task-oriented look at this new open source, Python-based technology. The book begins with recommendations for various plug-ins and add-ons to enhance the basic package as installed. It then details Twisted's collection simple network protocols, and helper utilities. The book also includes projects that let you try out the Twisted framework for yourself. For example, you'll find examples of using Twisted to build web services applications using the REST architecture, using XML-RPC, and using SOAP. Written for developers who want to s

  11. Evaluation of a Cyber Security System for Hospital Network.

    Science.gov (United States)

    Faysel, Mohammad A

    2015-01-01

    Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time. On an evaluation using real-world hospital network data consisting of incoming network connections collected for a 24-hour period, the proposed system detected 15 unusual connections which were undetected by a commercial intrusion prevention system for the same network connections. Evaluation of the proposed system shows a potential to secure protected patient health information on a hospital network.

  12. Planning and Scheduling for Environmental Sensor Networks

    Science.gov (United States)

    Frank, J. D.

    2005-12-01

    Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory

  13. Capacity of Intelligent Underlay and Overlay Network

    DEFF Research Database (Denmark)

    Ling, Yim; Elling, Jan; Nielsen, Thomas Toftegaard

    1996-01-01

    traffic. The formulas of the model have been implemented with the use of MatLab. To verify the model, measurement methods have been developed to collect the teletraffic information in a real-live GSM network. The measured data indicates that the teletraffic model describes the capacity with high accuracy...... and therefore can be used to dimension the network. The model shows that the increase of capacity for a GSM network with 34 frequencies is about 30%. Further capacity enhancement can be achieved by intelligent frequency planning method which is currently being developed...

  14. Evaluation of Topology-Aware Broadcast Algorithms for Dragonfly Networks

    Energy Technology Data Exchange (ETDEWEB)

    Dorier, Matthieu; Mubarak, Misbah; Ross, Rob; Li, Jianping Kelvin; Carothers, Christopher D.; Ma, Kwan-Liu

    2016-09-12

    Two-tiered direct network topologies such as Dragonflies have been proposed for future post-petascale and exascale machines, since they provide a high-radix, low-diameter, fast interconnection network. Such topologies call for redesigning MPI collective communication algorithms in order to attain the best performance. Yet as increasingly more applications share a machine, it is not clear how these topology-aware algorithms will react to interference with concurrent jobs accessing the same network. In this paper, we study three topology-aware broadcast algorithms, including one designed by ourselves. We evaluate their performance through event-driven simulation for small- and large-sized broadcasts (in terms of both data size and number of processes). We study the effect of different routing mechanisms on the topology-aware collective algorithms, as well as their sensitivity to network contention with other jobs. Our results show that while topology-aware algorithms dramatically reduce link utilization, their advantage in terms of latency is more limited.

  15. Privacy in Sensor-Driven Human Data Collection: A Guide for Practitioners

    OpenAIRE

    Stopczynski, Arkadiusz; Pietri, Riccardo; Pentland, Alex; Lazer, David; Lehmann, Sune

    2014-01-01

    In recent years, the amount of information collected about human beings has increased dramatically. This development has been partially driven by individuals posting and storing data about themselves and friends using online social networks or collecting their data for self-tracking purposes (quantified-self movement). Across the sciences, researchers conduct studies collecting data with an unprecedented resolution and scale. Using computational power combined with mathematical models, such r...

  16. From Isolated to Networked: A Paradigmatic Shift in Mitochondrial Physiology

    OpenAIRE

    Aon, Miguel A.

    2010-01-01

    A new paradigm of mitochondrial function in networks is emerging which includes, without undermining, the glorious and still useful paradigm of the isolated mitochondrion. The mitochondrial network paradigm introduces new concepts, tools, and analytical techniques. Among them is that mitochondrial function in networks exhibits interdependence and multiplicative effects based on synchronization mechanisms, which involve communication between mitochondrial neighbors. The collective dynamics of ...

  17. Reliability of transmission networks : Impact of EHV underground cables & interaction of offshore-onshore networks

    NARCIS (Netherlands)

    Tuinema, B.W.

    2017-01-01

    For the future, several developments of the power system are expected. The transition towards a more sustainable energy supply puts new requirements on the design and operation of power systems, and the transmission network in particular. Offshore, a transmission grid will be implemented to collect

  18. Smart Waste Collection System Based on Location Intelligence

    DEFF Research Database (Denmark)

    Lopez, Jose Manuel Guterrez Lopez; Jensen, Michael; Andreasen, Morten Henius

    2015-01-01

    (IoT) integration with data access networks, Geographic Information Systems (GIS), combinatorial optimization, and electronic engineering can contribute to improve cities’ management systems. We present a waste collection solution based on providing intelligence to trashcans, by using an IoT prototype...... to contribute and develop Smart city solutions.......Cities around the world are on the run to become smarter. Some of these have seen an opportunity on deploying dedicated municipal access networks to support all types of city management and maintenance services requiring a data connection. This paper practically demonstrates how Internet of Things...

  19. AfSIS MODIS Collection: Leaf Area Index - FPAR, 2012 Release

    Data.gov (United States)

    Center for International Earth Science Information Network, Columbia University — The Africa Soil Information Service (AfSIS) Moderate Resolution Imaging Spectroradiometer (MODIS) Collection Leaf Area Index (LAI) and Photosynthetically Active...

  20. Identity Practices of Multilingual Writers in Social Networking Spaces

    Science.gov (United States)

    Chen, Hsin-I

    2013-01-01

    This study examines the literacy practices of two multilingual writers in social networking communities. The findings show that the multilingual writers explored and reappropriated symbolic resources afforded by the social networking site as they aligned themselves with particular collective and personal identities at local and global levels.…

  1. An Analysis of and Recommendations for the Peruvian Blood Collection and Transfusion System.

    Science.gov (United States)

    George, Paul E; Vidal, Julio; Garcia, Patricia J

    2016-05-01

    Peru experienced a crisis in its blood collection and supply system in the mid-2000s, as contaminated blood led to several transfusion-transmitted infections (TTI), occurring in the backdrop of extremely low voluntary donation rates and a national blood supply shortage. Thus, the Peruvian Ministry of Health (MINSA) implemented a national investigation on the safety and quality of the Peruvian blood collection/transfusion network. Every Peruvian blood bank was evaluated by MINSA from 2007-2008. These evaluations consisted of an update of the national registry of blood banks and visits to each blood bank from MINSA oversight teams. Information was collected on the condition of the blood bank personnel, equipment, supplies, and practices. Further, previously-collected blood at each blood bank was randomly selected and screened for TTI-causing pathogens. Uncovered in this investigation was a fragmented, under-equipped, and poorly-staffed blood collection and transfusion network, consisting of 241 independent blood banks and resulting in suboptimal allocation of resources. Further, blood with evidence of TTI-causing pathogens (including Hepatitis B, Hepatitis C, and syphilis) and set for transfusion was discovered at three separate blood banks as part of the random screening process. Using the successful reorganizations of national blood supply systems in other Latin American countries as examples, Peru would be well-served to form large, high-volume, regional blood collection and transfusion centers, responsible for blood collection and screening for the entire country. The small, separate blood banks would then be transformed into a network of blood transfusion centers, not responsible for blood collection. This reorganization would allow Peru to better utilize its resources, standardize the blood collection and transfusion process, and increase voluntary donation, resulting in a safer, more abundant national blood product.

  2. A Survey of Collectives

    Science.gov (United States)

    Tumer, Kagan; Wolpert, David

    2004-01-01

    Due to the increasing sophistication and miniaturization of computational components, complex, distributed systems of interacting agents are becoming ubiquitous. Such systems, where each agent aims to optimize its own performance, but where there is a well-defined set of system-level performance criteria, are called collectives. The fundamental problem in analyzing/designing such systems is in determining how the combined actions of self-interested agents leads to 'coordinated' behavior on a iarge scale. Examples of artificial systems which exhibit such behavior include packet routing across a data network, control of an array of communication satellites, coordination of multiple deployables, and dynamic job scheduling across a distributed computer grid. Examples of natural systems include ecosystems, economies, and the organelles within a living cell. No current scientific discipline provides a thorough understanding of the relation between the structure of collectives and how well they meet their overall performance criteria. Although still very young, research on collectives has resulted in successes both in understanding and designing such systems. It is eqected that as it matures and draws upon other disciplines related to collectives, this field will greatly expand the range of computationally addressable tasks. Moreover, in addition to drawing on them, such a fully developed field of collective intelligence may provide insight into already established scientific fields, such as mechanism design, economics, game theory, and population biology. This chapter provides a survey to the emerging science of collectives.

  3. The art collectives: microcosm and commons engine of the arts

    Directory of Open Access Journals (Sweden)

    Teresa Marín García

    2013-03-01

    Full Text Available The collective artistic activity can be seen as a metaphor for the small-scale cultural commons. In its processes and strategies can be traced many of the key issues and conflicts that make the keys of the commons in regard to the arts, as cultural and intangible. The artistic groups are also essential elements for building assets/goods and resources that make up the cultural structure, very particular local contexts, while having great potential as builders of larger scale networks. After a brief discussion of these issues is presented an initiative of a collaborative platform project, CCCV, starting from the reality of a local context arises the objective of generating a network-file-laboratory to create and share knowledge about the collective culture.

  4. Mobile telecommunication networks choice among Ghanaians

    Directory of Open Access Journals (Sweden)

    Boateng Henry

    2013-07-01

    Full Text Available The paper investigates the factors influencing customers choice of telecommunication network in Ghana. The survey design was employed to enable the researchers perform statistical analysis. Questionnaire consisting of Likert scale question was used to collect the primary data. Multiple regression analysis was performed to ascertain the factors influencing customers’ choice of telecommunication networks. The study found six factors that influence customers to choose a particular network. These factors include; brand awareness, brand image, perceived quality, price, convenience and brand loyalty. The study concludes that all the six factors contribute to the factors that drive consumer choice of telecommunications service in Ghana.

  5. Controlling extreme events on complex networks

    Science.gov (United States)

    Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng

    2014-08-01

    Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

  6. Experiment of Wireless Sensor Network to Monitor Field Data

    Directory of Open Access Journals (Sweden)

    Kwang Sik Kim

    2009-08-01

    Full Text Available Recently the mobile wireless network has been drastically enhanced and one of the most efficient ways to realize the ubiquitous network will be to develop the converged network by integrating the mobile wireless network with other IP fixed network like NGN (Next Generation Network. So in this paper the term of the wireless ubiquitous network is used to describe this approach. In this paper, first, the wireless ubiquitous network architecture is described based on IMS which has been standardized by 3GPP (3rd Generation Partnership Program. Next, the field data collection system to match the satellite data using location information is proposed based on the concept of the wireless ubiquitous network architecture. The purpose of the proposed system is to provide more accurate analyzing method with the researchers in the remote sensing area.

  7. Network analysis applications in hydrology

    Science.gov (United States)

    Price, Katie

    2017-04-01

    Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

  8. Learning and coding in biological neural networks

    Science.gov (United States)

    Fiete, Ila Rani

    How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and

  9. Optical Access Networks

    Science.gov (United States)

    Zheng, Jun; Ansari, Nirwan

    2005-06-01

    are now underway this hot area. The purpose of this feature issue is to expose the networking community to the latest research breakthroughs and progresses in the area of optical access networks. This feature issue aims to present a collection of papers that focus on the state-of-the-art research in various networking aspects of optical access networks. Original papers are solicited from all researchers involved in area of optical access networks. Topics of interest include but not limited to: Optical access network architectures and protocols Passive optical networks (BPON, EPON, GPON, etc.) Active optical networks Multiple access control Multiservices and QoS provisioning Network survivability Field trials and standards Performance modeling and analysis

  10. Social networking mining, visualization, and security

    CERN Document Server

    Dehuri, Satchidananda; Wang, Gi-Nam

    2014-01-01

    With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques, and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining.  

  11. Entrepreneur online social networks: structure, diversity and impact on start-up survival

    NARCIS (Netherlands)

    Song, Y.; Vinig, T.

    2012-01-01

    In this paper, we discuss the results of a pilot study in which we use a novel approach to collect entrepreneur online social network data from LinkedIn, Facebook and Twitter. We studied the size and structure of entrepreneur social networks by analysing the online network industry and location

  12. Identification of illicit drugs by using SOM neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Liang Meiyan; Shen Jingling; Wang Guangqin [Beijing Key Lab for Terahertz Spectroscopy and Imaging, Key Laboratory of Terahertz Optoelectronics, Ministry of Education, Department of Physics, Capital Normal University, Beijing 100037 (China)], E-mail: liangyan661982@163.com, E-mail: jinglingshen@gmail.com, E-mail: pywgq2004@163.com

    2008-07-07

    Absorption spectra of six illicit drugs were measured by using the terahertz time-domain spectroscopy technique in the range 0.2-2.6 THz and then clustered with self-organization feature map (SOM) artificial neural network. After the network training process, the spectra collected at another time were identified successfully by the well-trained SOM network. An effective distance was introduced as a quantitative criterion to decide which cluster the new spectra were affiliated with.

  13. Identification of illicit drugs by using SOM neural networks

    International Nuclear Information System (INIS)

    Liang Meiyan; Shen Jingling; Wang Guangqin

    2008-01-01

    Absorption spectra of six illicit drugs were measured by using the terahertz time-domain spectroscopy technique in the range 0.2-2.6 THz and then clustered with self-organization feature map (SOM) artificial neural network. After the network training process, the spectra collected at another time were identified successfully by the well-trained SOM network. An effective distance was introduced as a quantitative criterion to decide which cluster the new spectra were affiliated with

  14. Action Research as a Network

    DEFF Research Database (Denmark)

    Boulus-Rødje, Nina

    2012-01-01

    This paper explores roles and interventions in IS action research. I draw upon a four-year research project about electronic medical records, conducted in close collaboration with a community partner. Following a self-reflexive stance, I trace the trajectory of the research engagement...... and the different roles I occupied. To better understand the complex nature of collaboration found within action research projects, I propose conceptualizing action research as a network. The network framework directs our attention to the collective production and the conditions through which roles...... this influences the researcher’s agency....

  15. Collective assemblage in the experimentation of the ‘PACTO Trabalho’ group

    Directory of Open Access Journals (Sweden)

    Eliane Dias de Castro

    2013-04-01

    Full Text Available This article presents the experience of an Occupational Therapy group, the ‘Pacto Trabalho’. For six years, the objective of this group has been to propose possible ways of generating income, by collectively discussing issues related to work together with the participants in a socially vulnerable situation associated to mental health problems. The work-in-progress method, borrowed from the field of the arts, was used to collectively develop, operate and construct these interventions based on individual demands, but oriented towards the construction of a collective device. Considering that work is a core issue in the subjective constitution and social life, actions were taken and partnerships were made, mainly through the articulation with several networks directly linked to projects of income generation, and social, health, transportation and legal action support networks. The complexity of the participants’ lives, marked by fragilities, required multiple supports.

  16. Antagonistic Phenomena in Network Dynamics

    Science.gov (United States)

    Motter, Adilson E.; Timme, Marc

    2018-03-01

    Recent research on the network modeling of complex systems has led to a convenient representation of numerous natural, social, and engineered systems that are now recognized as networks of interacting parts. Such systems can exhibit a wealth of phenomena that not only cannot be anticipated from merely examining their parts, as per the textbook definition of complexity, but also challenge intuition even when considered in the context of what is now known in network science. Here, we review the recent literature on two major classes of such phenomena that have far-reaching implications: (a) antagonistic responses to changes of states or parameters and (b) coexistence of seemingly incongruous behaviors or properties - both deriving from the collective and inherently decentralized nature of the dynamics. They include effects as diverse as negative compressibility in engineered materials, rescue interactions in biological networks, negative resistance in fluid networks, and the Braess paradox occurring across transport and supply networks. They also include remote synchronization, chimera states, and the converse of symmetry breaking in brain, power-grid, and oscillator networks as well as remote control in biological and bioinspired systems. By offering a unified view of these various scenarios, we suggest that they are representative of a yet broader class of unprecedented network phenomena that ought to be revealed and explained by future research.

  17. Homeless but Connected: The Role of Heterogeneous Social Network Ties and Social Networking Technology in the Mental Health Outcomes of Street-Living Youth

    OpenAIRE

    Rice, Eric; Ray, Diana; Kurzban, Seth

    2011-01-01

    Although social integration tends to have positive effects on the mental health of housed adolescents, the role of homeless adolescents’ social networks is more ambiguous. Social network data were collected from 136 homeless adolescents in Hollywood, California to examine how network ties are associated with symptoms of anxiety and depression. Face-to-face relationships with street-based peers were a risk factor for both anxiety and depression, while contacting home-based friends through soci...

  18. A Gossip-based Energy Efficient Protocol for Robust In-network Aggregation in Wireless Sensor Networks

    Science.gov (United States)

    Fauji, Shantanu

    We consider the problem of energy efficient and fault tolerant in--network aggregation for wireless sensor networks (WSNs). In-network aggregation is the process of aggregation while collecting data from sensors to the base station. This process should be energy efficient due to the limited energy at the sensors and tolerant to the high failure rates common in sensor networks. Tree based in--network aggregation protocols, although energy efficient, are not robust to network failures. Multipath routing protocols are robust to failures to a certain degree but are not energy efficient due to the overhead in the maintenance of multiple paths. We propose a new protocol for in-network aggregation in WSNs, which is energy efficient, achieves high lifetime, and is robust to the changes in the network topology. Our protocol, gossip--based protocol for in-network aggregation (GPIA) is based on the spreading of information via gossip. GPIA is not only adaptive to failures and changes in the network topology, but is also energy efficient. Energy efficiency of GPIA comes from all the nodes being capable of selective message reception and detecting convergence of the aggregation early. We experimentally show that GPIA provides significant improvement over some other competitors like the Ridesharing, Synopsis Diffusion and the pure version of gossip. GPIA shows ten fold, five fold and two fold improvement over the pure gossip, the synopsis diffusion and Ridesharing protocols in terms of network lifetime, respectively. Further, GPIA retains gossip's robustness to failures and improves upon the accuracy of synopsis diffusion and Ridesharing.

  19. Quantitative analysis of bloggers' collective behavior powered by emotions

    Science.gov (United States)

    Mitrović, Marija; Paltoglou, Georgios; Tadić, Bosiljka

    2011-02-01

    Large-scale data resulting from users' online interactions provide the ultimate source of information to study emergent social phenomena on the Web. From individual actions of users to observable collective behaviors, different mechanisms involving emotions expressed in the posted text play a role. Here we combine approaches of statistical physics with machine-learning methods of text analysis to study the emergence of emotional behavior among Web users. Mapping the high-resolution data from digg.com onto bipartite networks of users and their comments onto posted stories, we identify user communities centered around certain popular posts and determine emotional contents of the related comments by the emotion classifier developed for this type of text. Applied over different time periods, this framework reveals strong correlations between the excess of negative emotions and the evolution of communities. We observe avalanches of emotional comments exhibiting significant self-organized critical behavior and temporal correlations. To explore the robustness of these critical states, we design a network-automaton model on realistic network connections and several control parameters, which can be inferred from the dataset. Dissemination of emotions by a small fraction of very active users appears to critically tune the collective states.

  20. Searching Information Sources in Networks

    Science.gov (United States)

    2017-06-14

    with partial observations,” in AAAI Conference on Artificial Intelligence , 2017. [6] D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small...critical infrastructure of our society. The failure of the power grid network will have catastrophic impacts on water supplies, transportation

  1. Reliability Improved Cooperative Communication over Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhuangbin Chen

    2017-10-01

    Full Text Available With the development of smart devices and connection technologies, Wireless Sensor Networks (WSNs are becoming increasingly intelligent. New or special functions can be obtained by receiving new versions of program codes to upgrade their software systems, forming the so-called smart Internet of Things (IoT. Due to the lossy property of wireless channels, data collection in WSNs still suffers from a long delay, high energy consumption, and many retransmissions. Thanks to wireless software-defined networks (WSDNs, software in sensors can now be updated to help them transmit data cooperatively, thereby achieving more reliable communication. In this paper, a Reliability Improved Cooperative Communication (RICC data collection scheme is proposed to improve the reliability of random-network-coding-based cooperative communications in multi-hop relay WSNs without reducing the network lifetime. In WSNs, sensors in different positions can have different numbers of packets to handle, resulting in the unbalanced energy consumption of the network. In particular, nodes in non-hotspot areas have up to 90% of their original energy remaining when the network dies. To efficiently use the residual energy, in RICC, high data transmission power is adopted in non-hotspot areas to achieve a higher reliability at the cost of large energy consumption, and relatively low transmission power is adopted in hotspot areas to maintain the long network lifetime. Therefore, high reliability and a long network lifetime can be obtained simultaneously. The simulation results show that compared with other scheme, RICC can reduce the end-to-end Message Fail delivering Ratio (MFR by 59.4%–62.8% under the same lifetime with a more balanced energy utilization.

  2. Neuromorphic atomic switch networks.

    Directory of Open Access Journals (Sweden)

    Audrius V Avizienis

    Full Text Available Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.

  3. Buffer Sizing in 802.11 Wireless Mesh Networks

    KAUST Repository

    Jamshaid, Kamran; Shihada, Basem; Xia, Li; Levis, Philip

    2011-01-01

    We analyze the problem of buffer sizing for TCP flows in 802.11-based Wireless Mesh Networks. Our objective is to maintain high network utilization while providing low queueing delays. The problem is complicated by the time-varying capacity of the wireless channel as well as the random access mechanism of 802.11 MAC protocol. While arbitrarily large buffers can maintain high network utilization, this results in large queueing delays. Such delays may affect TCP stability characteristics, and also increase queueing delays for other flows (including real-time flows) sharing the buffer. In this paper we propose sizing link buffers collectively for a set of nodes within mutual interference range called the 'collision domain'. We aim to provide a buffer just large enough to saturate the available capacity of the bottleneck collision domain that limits the carrying capacity of the network. This neighborhood buffer is distributed over multiple nodes that constitute the network bottleneck; a transmission by any of these nodes fully utilizes the available spectral resource for the duration of the transmission. We show that sizing routing buffers collectively for this bottleneck allows us to have small buffers (as low as 2 - 3 packets) at individual nodes without any significant loss in network utilization. We propose heuristics to determine these buffer sizes in WMNs. Our results show that we can reduce the end-to-end delays by 6× to 10× at the cost of losing roughly 5% of the network capacity achievable with large buffers.

  4. Buffer Sizing in 802.11 Wireless Mesh Networks

    KAUST Repository

    Jamshaid, Kamran

    2011-10-01

    We analyze the problem of buffer sizing for TCP flows in 802.11-based Wireless Mesh Networks. Our objective is to maintain high network utilization while providing low queueing delays. The problem is complicated by the time-varying capacity of the wireless channel as well as the random access mechanism of 802.11 MAC protocol. While arbitrarily large buffers can maintain high network utilization, this results in large queueing delays. Such delays may affect TCP stability characteristics, and also increase queueing delays for other flows (including real-time flows) sharing the buffer. In this paper we propose sizing link buffers collectively for a set of nodes within mutual interference range called the \\'collision domain\\'. We aim to provide a buffer just large enough to saturate the available capacity of the bottleneck collision domain that limits the carrying capacity of the network. This neighborhood buffer is distributed over multiple nodes that constitute the network bottleneck; a transmission by any of these nodes fully utilizes the available spectral resource for the duration of the transmission. We show that sizing routing buffers collectively for this bottleneck allows us to have small buffers (as low as 2 - 3 packets) at individual nodes without any significant loss in network utilization. We propose heuristics to determine these buffer sizes in WMNs. Our results show that we can reduce the end-to-end delays by 6× to 10× at the cost of losing roughly 5% of the network capacity achievable with large buffers.

  5. Emergence, evolution and scaling of online social networks.

    Science.gov (United States)

    Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

    2014-01-01

    Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  6. Emergence, evolution and scaling of online social networks.

    Directory of Open Access Journals (Sweden)

    Le-Zhi Wang

    Full Text Available Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  7. Energy-Efficient Querying of Wireless Sensor Networks

    National Research Council Canada - National Science Library

    Mann, Christopher R

    2007-01-01

    Due to the distributed nature of information collection in wireless sensor networks and the inherent limitations of the component devices, the ability to store, locate, and retrieve data and services...

  8. Social network analyzer on the example of Twitter

    Science.gov (United States)

    Gorodetskaia, Mariia; Khruslova, Diana

    2017-09-01

    Social networks are powerful sources of data due to their popularity. Twitter is one of the networks providing a lot of data. There is need to collect this data for future usage from linguistics to SMM and marketing. The report examines the existing software solutions and provides new ones. The study includes information about the software developed. Some future features are listed.

  9. Output power distributions of terminals in a 3G mobile communication network.

    Science.gov (United States)

    Persson, Tomas; Törnevik, Christer; Larsson, Lars-Eric; Lovén, Jan

    2012-05-01

    The objective of this study was to examine the distribution of the output power of mobile phones and other terminals connected to a 3G network in Sweden. It is well known that 3G terminals can operate with very low output power, particularly for voice calls. Measurements of terminal output power were conducted in the Swedish TeliaSonera 3G network in November 2008 by recording network statistics. In the analysis, discrimination was made between rural, suburban, urban, and dedicated indoor networks. In addition, information about terminal output power was possible to collect separately for voice and data traffic. Information from six different Radio Network Controllers (RNCs) was collected during at least 1 week. In total, more than 800000 h of voice calls were collected and in addition to that a substantial amount of data traffic. The average terminal output power for 3G voice calls was below 1 mW for any environment including rural, urban, and dedicated indoor networks. This is <1% of the maximum available output power. For data applications the average output power was about 6-8 dB higher than for voice calls. For rural areas the output power was about 2 dB higher, on average, than in urban areas. Copyright © 2011 Wiley Periodicals, Inc.

  10. Competing opinion diffusion on social networks.

    Science.gov (United States)

    Hu, Haibo

    2017-11-01

    Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people's opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world.

  11. DogMATIC--A Remote Biospecimen Collection Kit for Biobanking.

    Science.gov (United States)

    Milley, Kristi M; Nimmo, Judith S; Bacci, Barbara; Ryan, Stewart D; Richardson, Samantha J; Danks, Janine A

    2015-08-01

    Canine tumors are valuable comparative oncology models. This research was designed to create a sustainable biobank of canine mammary tumors for breast cancer research. The aim was to provide a well-characterized sample cohort for specimen sharing, data mining, and long-term research aims. Canine mammary tumors are most frequently managed at a local veterinary clinic or hospital. We adopted a biobank framework based on a large number of participating veterinary hospitals and clinics acting as collection centers that were serviced by a centralized storage facility. Recruitment was targeted at rural veterinary clinics. A tailored, stable collection kit (DogMATIC) was designed that was used by veterinarians in remote or rural locations to collect both fresh and fixed tissue for submission to the biobank. To validate this methodology the kit design, collection rate, and sample quality were analyzed. The Australian Veterinary Cancer Biobank was established as a network of 47 veterinary clinics and three veterinary pathology laboratories spanning over 200,000 km(2). In the first 12 months, 30 canine mammary tumor cases were submitted via the DogMATIC kit. Pure intact RNA was isolated in over 80% of samples with an average yield of 14.49 μg. A large network biobank, utilizing off-site collection with the DogMATIC kit, was successfully coordinated. The creation of the Australian Veterinary Cancer Biobank has established a long-term, sustainable, comparative oncology research resource in Australia. There are broader implications for biobanking with this very different form of collection and banking.

  12. Instantiating a Global Network Measurement Framework

    Energy Technology Data Exchange (ETDEWEB)

    Tierney, Brian L.; Boote, Jeff; Boyd, Eric; Brown, Aaron; Grigoriev, Maxim; Metzger, Joe; Swany, Martin; Zekauskas, Matt; Zurawski, Jason

    2008-12-15

    perfSONAR is a web services-based infrastructure for collecting and publishing network performance monitoring. A primary goal of perfSONAR is making it easier to solve end-to-end performance problems on paths crossing several networks. It contains a set of services delivering performance measurements in a federated environment. These services act as an intermediate layer, between the performance measurement tools and the diagnostic or visualization applications. This layer is aimed at making and exchanging performance measurements across multiple networks and multiple user communities, using well-defined protocols. This paper summarizes the key perfSONAR components, and describes how they are deployed by the US-LHC community to monitor the networks distributing LHC data from CERN. All monitoring data described herein is publicly available, and we hope the availability of this data via a standard schema will inspire others to contribute to the effort by building network data analysis applications that use perfSONAR.

  13. Social network analysis applied to team sports analysis

    CERN Document Server

    Clemente, Filipe Manuel; Mendes, Rui Sousa

    2016-01-01

    Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

  14. Cooperative and networking strategies in small business

    CERN Document Server

    Ferreira, João

    2017-01-01

    The book aims to collect the most recent research and best practices in the cooperative and networking small business field identifying new theoretical models and describing the relationship between cooperation and networks in the small business strategy context. It examines different concepts and analytical techniques better understand the links between cooperative strategies and networks in small business. It also studies the existing economic conditions of network and strategic implications to small business from the point of view of their internal and external consistency. Cooperation and networks is a fashionable topic. It is receiving increasing attention in popular management publications, as well as specialized academic journals. Cooperation between firms and industries is a means of leveraging and aggregating knowledge also generating direct benefits in terms of innovation, productivity and competitiveness. Various options and decisions made within the framework of strategic alliances may be identifi...

  15. Connective Versus Collective Action in Social Movements

    DEFF Research Database (Denmark)

    Lundgaard, Daniel; Razmerita, Liana

    of connective action is are sult of mediating technologies especially web 2.0 that inspire and affords emergent digitally networked action, based on large‐scale self‐organized, fluid and weak‐tied networks (Ibid.). These logics are investigated in three different social media movements; #YesAllWomen, #Black......LivesMatter and the #IceBucketChallenge by analyzing Twitter and Facebook data from key periods of these movements,through a net nographic study. In particular, this study has investigated the following research questions: How are the logics of collective and connective action reflected in online social media interactions...... in large‐scale, weak‐tied networks with morphing boundaries. The nature of social media ensures that personalized action frames (e.g. personal stories or memes) and the self‐motivating act of voluntary sharing, as well how this act is reciprocated, is integral for the potential reach and impact...

  16. Finding the Sweet Spot: Network Structures and Processes for Increased Knowledge Mobilization

    Science.gov (United States)

    Briscoe, Patricia; Pollock, Katina; Campbell, Carol; Carr-Harris, Shasta

    2015-01-01

    The use of networks in public education is one of many knowledge mobilization (KMb) strategies utilized to promote evidence-based research into practice. However, challenges exist in the ability to mobilize knowledge through networks. The purpose of this paper is to explore how networks work. Data were collected from virtual discussions for an…

  17. Tourist activated networks: Implications for dynamic packaging systems in tourism

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike; Fesenmaier, Daniel R.

    2008-01-01

    This paper discusses tourist activated networks as a concept to inform technological applications supporting dynamic bundling and en-route recommendations. Empirical data was collected from travellers who visited a regional destination in the US and then analyzed with respect to its network...... structure. The results indicate that the tourist activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist activated network and provide implications for technology design and tourism...

  18. Studies for Characterisation of Electrical Properties of DC Collection System in Offshore Wind Farms

    DEFF Research Database (Denmark)

    Chen, Yu-Hsing; Dincan, Catalin Gabriel; Olsen, Rolant Joannesarson

    2016-01-01

    Offshore HVDC-connected wind farms where the wind plant power collection network becomes DC, rather than AC, offer reduced electrical losses, lower equipment ratings potentially leading to lower bill-of-material cost, and undiminished functionality. However, no standards exist for an offshore...... medium-voltage DC power collection cable-based system, routing power from MVDC wind turbines all the way to the HVDC export cable. To progress, it is therefore important to establish some common reference for the design and performance of the components needed in an MVDC collection network. Any suggested...... of the MVDC power collection, regardless of choice of turbine converter circuit, MVDC cable configuration, use of DC circuit breakers, substation converter circuit, control and protection. The paper presents the necessary list of studies, and includes examples of simulation results for an exemplary MVDC wind...

  19. Criminal Network Investigation: Processes, Tools, and Techniques

    DEFF Research Database (Denmark)

    Petersen, Rasmus Rosenqvist

    important challenge for criminal network investigation, despite the massive attention it receives from research and media. Challenges such as the investigation process, the context of the investigation, human factors such as thinking and creativity, and political decisions and legal laws are all challenges...... that could mean the success or failure of criminal network investigations. % include commission reports as indications of process related problems .. to "play a little politics" !! Information, process, and human factors, are challenges we find to be addressable by software system support. Based on those......Criminal network investigations such as police investigations, intelligence analysis, and investigative journalism involve a range of complex knowledge management processes and tasks. Criminal network investigators collect, process, and analyze information related to a specific target to create...

  20. Mobile Phone Assessment in Egocentric Networks: A Pilot Study on Gay Men and Their Peers.

    OpenAIRE

    Comulada, WS

    2014-01-01

    Mobile phone-based data collection encompasses the richness of social network research. Both individual-level and network-level measures can be recorded. For example, health-related behaviors can be reported via mobile assessment. Social interactions can be assessed by phone-log data. Yet the potential of mobile phone data collection has largely been untapped. This is especially true of egocentric studies in public health settings where mobile phones can enhance both data collection and inter...

  1. Provable network activity for protecting users against false accusation

    NARCIS (Netherlands)

    Papadopoulos, Panagiotis; Athanasopoulos, Ilias; Kosta, Eleni; Siganos, George; Keromytis, Angelos D.; Markatos, Evangelos P.

    2016-01-01

    With the proliferation of the World Wide Web, data traces that correspond to users’ network activity can be collected by several Internet actors, including (i) web sites, (ii) smartphone apps, and even (iii) Internet Service Providers. Given that the collection and storage of these data are beyond

  2. The time-dependent prize-collecting arc routing problem

    DEFF Research Database (Denmark)

    Black, Dan; Eglese, Richard; Wøhlk, Sanne

    2013-01-01

    with the time of day. Two metaheuristic algorithms, one based on Variable Neighborhood Search and one based on Tabu Search, are proposed and tested for a set of benchmark problems, generated from real road networks and travel time information. Both algorithms are capable of finding good solutions, though......A new problem is introduced named the Time-Dependent Prize-Collecting Arc Routing Problem (TD-PARP). It is particularly relevant to situations where a transport manager has to choose between a number of full truck load pick-ups and deliveries on a road network where travel times change...

  3. Empirical Studies on the Network of Social Groups: The Case of Tencent QQ.

    Science.gov (United States)

    You, Zhi-Qiang; Han, Xiao-Pu; Lü, Linyuan; Yeung, Chi Ho

    2015-01-01

    Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. In this paper, we analyze a comprehensive dataset released from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members-the hypergraph of groups, the network of groups and the user network-to reveal social interactions at microscopic and mesoscopic level. Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in social networks based on personal contacts.

  4. A Generational Comparison of Social Networking Site Use: The Influence of Age and Social Identity

    Science.gov (United States)

    Barker, Valerie

    2012-01-01

    An online survey (N = 256) compared social networking site (SNS) use among younger (millennial: 18-29) and older (baby-boomer: 41-64) subscribers focusing on the influence of collective self-esteem and group identity on motives for SNS use. Younger participants reported higher positive collective self-esteem, social networking site use for peer…

  5. Building ties: social capital network analysis of a forest community in a biosphere reserve in Chiapas, Mexico

    Directory of Open Access Journals (Sweden)

    Luis Rico García-Amado

    2012-09-01

    Full Text Available Governance of the commons depends on the capacity to generate collective action. Networks and rules that foster that collective action have been defined as social capital. However, their causal link is still not fully understood. We use social network analysis to assess social capital, decision-making, and collective action in a forest-based common pool resource management in La Sepultura Biosphere Reserve (Chiapas, Mexico. Our research analyzes the productive networks and the evolution of coffee groups in one community. The network shows some centrality, with richer landholders tending to occupy core positions and poorer landless peasants occupying peripheral ones. This has fostered the community's environmentally oriented development but has also caused internal conflicts. Market requirements have shaped different but complementary productive networks, where organic coffee commercialization is the main source of bridging ties, which has resulted in more connectivity and resilience. Conservation attitudes, along with the institutional setting of the community, have promoted collective action. The unresolved conflicts, however, still leave some concerns about governance in the future.

  6. Network Enabled - Unresolved Residual Analysis and Learning (NEURAL)

    Science.gov (United States)

    Temple, D.; Poole, M.; Camp, M.

    Since the advent of modern computational capacity, machine learning algorithms and techniques have served as a method through which to solve numerous challenging problems. However, for machine learning methods to be effective and robust, sufficient data sets must be available; specifically, in the space domain, these are generally difficult to acquire. Rapidly evolving commercial space-situational awareness companies boast the capability to collect hundreds of thousands nightly observations of resident space objects (RSOs) using a ground-based optical sensor network. This provides the ability to maintain custody of and characterize thousands of objects persistently. With this information available, novel deep learning techniques can be implemented. The technique discussed in this paper utilizes deep learning to make distinctions between nightly data collects with and without maneuvers. Implementation of these techniques will allow the data collected from optical ground-based networks to enable well informed and timely the space domain decision making.

  7. Initial Results of a New Mobile Spectrum Occupancy Monitoring Network

    NARCIS (Netherlands)

    van Bloem, J.W.H.; Schiphorst, Roelof; Slump, Cornelis H.

    2010-01-01

    In this paper we present results of the new monitoring network for spectrum governance. The network is based on the RFeye system of CRFS where the data is collected employing mobile monitoring vehicles. The measurement data, obtained from a frequency sweep between 10 MHz and 6 GHz, is further

  8. An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network.

    Science.gov (United States)

    Petropoulos, George P; McCalmont, Jon P

    2017-06-23

    This paper describes a soil moisture dataset that has been collecting ground measurements of soil moisture, soil temperature and related parameters for west Wales, United Kingdom. Already acquired in situ data have been archived to the autonomous Wales Soil Moisture Network (WSMN) since its foundation in July 2011. The sites from which measurements are being collected represent a range of conditions typical of the Welsh environment, with climate ranging from oceanic to temperate and a range of the most typical land use/cover types found in Wales. At present, WSMN consists of a total of nine monitoring sites across the area with a concentration of sites in three sub-areas around the region of Aberystwyth located in Mid-Wales. The dataset of composed of 0-5 (or 0-10) cm soil moisture, soil temperature, precipitation, and other ancillary data. WSMN data are provided openly to the public via the International Soil Moisture Network (ISMN) platform. At present, WSMN is also rapidly expanding thanks to funding obtained recently which allows more monitoring sites to be added to the network to the wider community interested in using its data.

  9. Hybrid architecture for building secure sensor networks

    Science.gov (United States)

    Owens, Ken R., Jr.; Watkins, Steve E.

    2012-04-01

    Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

  10. Evolutionary games on multilayer networks: a colloquium

    Science.gov (United States)

    Wang, Zhen; Wang, Lin; Szolnoki, Attila; Perc, Matjaž

    2015-05-01

    Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

  11. Sampling of temporal networks: Methods and biases

    Science.gov (United States)

    Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter

    2017-11-01

    Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.

  12. Measuring and monitoring collective attention during shocking events

    Directory of Open Access Journals (Sweden)

    Xingsheng He

    2017-11-01

    Full Text Available Abstract There has been growing interest in leveraging Web-based social and communication technologies for better crisis response. How might the Web platforms be used as an observatory to systematically understand the dynamics of the public’s attention during disaster events? And how could we monitor such attention in a cost-effective way? In this work, we propose an ‘attention shift network’ framework to systematically observe, measure, and analyze the dynamics of collective attention in response to real-world exogenous shocks such as disasters. Through tracing hashtags that appeared in Twitter users’ complete timeline around several violent terrorist attacks, we study the properties of network structures and reveal the temporal dynamics of the collective attention across multiple disasters. Further, to enable an efficient monitoring of the collective attention dynamics, we propose an effective stochastic sampling approach that accounts for the users’ hashtag adoption frequency, connectedness and diversity, as well as data variability. We conduct extensive experiments to show that the proposed sampling approach significantly outperforms several alternative methods in both retaining the network structures and preserving the information with a small set of sampling targets, suggesting the utility of the proposed method in various realistic settings.

  13. Research information network survey of innovative technology for the earth. 2; Chikyu kankyo taisaku gijutsu no kenkyu joho network chosa. 2

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    In order to construct the information network system for a research of innovative technology for the earth, a prototype has been made. To draw necessary functions for the information network system, an information flow in a general research work is analyzed to classify it based on the functions. The information collecting function, information accumulating and sharing function, special information system for research, information providing function, and communication function of the net work correspond to the collecting information, accumulating information, being engaged in research, providing information, and communication of researcher`s actions, respectively. The services on network system supposed from these functions are the homepage search mailing list, intranet service, special information system for research, WWW Internet broadcasting, and BBS/news/conference tool, respectively. It was found that latest Internet technology enabled to construct easily controlled system environment for users and WWW would develop as a standard communication tool. 2 refs., 26 figs., 27 tabs.

  14. Networks in Social Policy Problems

    Science.gov (United States)

    Vedres, Balázs; Scotti, Marco

    2012-08-01

    1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.

  15. Extraction of temporal networks from term co-occurrences in online textual sources.

    Directory of Open Access Journals (Sweden)

    Marko Popović

    Full Text Available A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to estimate the significance of co-occurrences, and a benchmark model against which their robustness is evaluated. The approach is applied to a large set of financial news, collected over a period of two years. The entities we consider are 50 countries which issue sovereign bonds, and which are insured by Credit Default Swaps (CDS in turn. We compare the country co-occurrence networks to the CDS networks constructed from the correlations between the CDS. The results show relatively small, but significant overlap between the networks extracted from the news and those from the CDS correlations.

  16. Altered Synchronizations among Neural Networks in Geriatric Depression.

    Science.gov (United States)

    Wang, Lihong; Chou, Ying-Hui; Potter, Guy G; Steffens, David C

    2015-01-01

    Although major depression has been considered as a manifestation of discoordinated activity between affective and cognitive neural networks, only a few studies have examined the relationships among neural networks directly. Because of the known disconnection theory, geriatric depression could be a useful model in studying the interactions among different networks. In the present study, using independent component analysis to identify intrinsically connected neural networks, we investigated the alterations in synchronizations among neural networks in geriatric depression to better understand the underlying neural mechanisms. Resting-state fMRI data was collected from thirty-two patients with geriatric depression and thirty-two age-matched never-depressed controls. We compared the resting-state activities between the two groups in the default-mode, central executive, attention, salience, and affective networks as well as correlations among these networks. The depression group showed stronger activity than the controls in an affective network, specifically within the orbitofrontal region. However, unlike the never-depressed controls, geriatric depression group lacked synchronized/antisynchronized activity between the affective network and the other networks. Those depressed patients with lower executive function has greater synchronization between the salience network with the executive and affective networks. Our results demonstrate the effectiveness of the between-network analyses in examining neural models for geriatric depression.

  17. Networked innovations in guided tours

    DEFF Research Database (Denmark)

    Meged, Jane Widtfeldt; Zillinger, Malin

    This presentation is about a case study being done on networked innovation that is taking place within the scene of free guided tours in Copenhagen. Data has been collected on interactions between actors within the network of peers. In this way, both the own organisation and the actual market...... is being continually developed. ICT plays a key role, just as well as the relationships between the individual actors. It has been shown that close relationships building on friendship and trust are beneficial for the process of innovation. The fast growth of the sector of free guided tours however poses...

  18. The control network of air quality in the Lorraine steel industry country: an example of a specific steel industry network

    International Nuclear Information System (INIS)

    Poncin, G.

    1991-01-01

    This specific (for steel industry region) network for the air quality control mainly measures the concentrations in sulfur dioxide, airborne dust and fall out particles. The recent automation of this network implied a preliminary optimization study which consisted of a statistical analysis of the numerous data collected by many hand operated sensors. The implementation and working conditions of the new equipment have required the use of air-conditioned monoblock metallic cabins

  19. Discovering the Network Topology: An Efficient Approach for SDN

    Directory of Open Access Journals (Sweden)

    Leonardo OCHOA-ADAY

    2016-11-01

    Full Text Available Network topology is a physical description of the overall resources in the network. Collecting this information using efficient mechanisms becomes a critical task for important network functions such as routing, network management, quality of service (QoS, among many others. Recent technologies like Software-Defined Networks (SDN have emerged as promising approaches for managing the next generation networks. In order to ensure a proficient topology discovery service in SDN, we propose a simple agents-based mechanism. This mechanism improves the overall efficiency of the topology discovery process. In this paper, an algorithm for a novel Topology Discovery Protocol (SD-TDP is described. This protocol will be implemented in each switch through a software agent. Thus, this approach will provide a distributed solution to solve the problem of network topology discovery in a more simple and efficient way.

  20. Social Networks and Sales Performance

    Directory of Open Access Journals (Sweden)

    Danny Pimentel Claro

    2011-05-01

    Full Text Available This paper argues that an informal network can itself be a basis for the increase in a sales manager’s performance. Informal networks create a structure that surpasses the formal hierarchical structure defined by the firm. We concentrated on the advice network and considered two different views of network structure that claim to have impact on performance. To explore this claim, we examined whether sales managers develop either a highly cohesive network structure (i.e. Coleman’s view or one containing structural holes (i.e. Burt’s view in order to achieve higher sales. We also investigated the matter of tie strength put forward by Granovetter in his seminal 1973 work. Census data was collected from about 500 personnel from an agricultural input retailer having 23 divisions. Estimates from a sample of 101 sales managers showed the importance of a highly cohesive structure (degree centrality for the three measures of sales manager’s performance. The strong ties have a positive impact on performance, suggesting the importance of building up strong bonds with network contacts. Sales managers’ age, time within the retailer and education also influence performance. These results imply that firms should stimulate contacts among personnel to spread technical and commercial information.

  1. The signal extraction of fetal heart rate based on wavelet transform and BP neural network

    Science.gov (United States)

    Yang, Xiao Hong; Zhang, Bang-Cheng; Fu, Hu Dai

    2005-04-01

    This paper briefly introduces the collection and recognition of bio-medical signals, designs the method to collect FM signals. A detailed discussion on the system hardware, structure and functions is also given. Under LabWindows/CVI,the hardware and the driver do compatible, the hardware equipment work properly actively. The paper adopts multi threading technology for real-time analysis and makes use of latency time of CPU effectively, expedites program reflect speed, improves the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the signal in real-time. Wavelet transform to remove the main interference in the FM and by adding time-window to recognize with BP network; Finally the results of collecting signals and BP networks are discussed. 8 pregnant women's signals of FM were collected successfully by using the sensor. The correctness rate of BP network recognition is about 83.3% by using the above measure.

  2. Mobile infostation network technology

    Science.gov (United States)

    Rajappan, Gowri; Acharya, Joydeep; Liu, Hongbo; Mandayam, Narayan; Seskar, Ivan; Yates, Roy

    2006-05-01

    Inefficient use of network resources on the battlefield is a serious liability: if an asset communicates with the network command for data-a terrain map, for instance-it ties up the end-to-end network resources. When many such assets contend for data simultaneously, traffic is limited by the slowest link along the path from the network command to the asset. A better approach is for a local server, known as an infostation, to download data on an anticipated-need basis when the network load is low. The infostation can then dump data when needed to the assets over a high-speed wireless connection. The infostation serves the local assets over an OFDM-based wireless data link that has MIMO enhancements for high data rate and robustness. We aim for data rate in excess of 100 Mbps, spectral efficiency in excess of 5 bits/sec/Hz, and robustness to poor channel conditions and jammers. We propose an adaptive physical layer that determines power levels, modulation schemes, and the MIMO enhancements to use based on the channel state and the level of interference in the system. We also incorporate the idea of superuser: a user who is allowed preferential use of the high data rate link. We propose a MAC that allows for this priority-based bandwidth allocation scheme. The proposed infostation MAC is integrated tightly with the physical layer through a cross-layer design. We call the proposed infostation PHY, MAC, and network technology, collectively, as the Mobile Infostation Network Technology (MINT).

  3. A Network Inference Workflow Applied to Virulence-Related Processes in Salmonella typhimurium

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Singhal, Mudita; Weller, Jennifer B.; Khoshnevis, Saeed; Shi, Liang; McDermott, Jason E.

    2009-04-20

    Inference of the structure of mRNA transcriptional regulatory networks, protein regulatory or interaction networks, and protein activation/inactivation-based signal transduction networks are critical tasks in systems biology. In this article we discuss a workflow for the reconstruction of parts of the transcriptional regulatory network of the pathogenic bacterium Salmonella typhimurium based on the information contained in sets of microarray gene expression data now available for that organism, and describe our results obtained by following this workflow. The primary tool is one of the network inference algorithms deployed in the Software Environment for BIological Network Inference (SEBINI). Specifically, we selected the algorithm called Context Likelihood of Relatedness (CLR), which uses the mutual information contained in the gene expression data to infer regulatory connections. The associated analysis pipeline automatically stores the inferred edges from the CLR runs within SEBINI and, upon request, transfers the inferred edges into either Cytoscape or the plug-in Collective Analysis of Biological of Biological Interaction Networks (CABIN) tool for further post-analysis of the inferred regulatory edges. The following article presents the outcome of this workflow, as well as the protocols followed for microarray data collection, data cleansing, and network inference. Our analysis revealed several interesting interactions, functional groups, metabolic pathways, and regulons in S. typhimurium.

  4. A network flow algorithm to position tiles for LAMOST

    International Nuclear Information System (INIS)

    Li Guangwei; Zhao Gang

    2009-01-01

    We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly. To solve this problem, firstly we divide the sky into many small blocks, and we also assume that all the targets that are in the same block have the same position, which is the center of the block. Secondly, we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block. Thirdly, because the network flow algorithm used in this paper is a bipartite network, we do not use the general solution algorithm that was used by SDSS. Instead, we give our new faster solution method for this special network. Compared with the Convergent Mean Shift Algorithm, the network flow algorithm can decrease observation times with improved mean imaging quality. This algorithm also has a very fast running speed. It can distribute millions of targets in a few minutes using a common personal computer.

  5. Interorganizational networks: fundamental to the Accreditation Canada program.

    Science.gov (United States)

    Mitchell, Jonathan I; Nicklin, Wendy; MacDonald, Bernadette

    2014-01-01

    Within the Canadian healthcare system, the term population-accountable health network defines the use of collective resources to optimize the health of a population through integrated interventions. The leadership of these networks has also been identified as a critical factor, highlighting the need for creative management of resources in determining effective, balanced sets of interventions. In this article, using specific principles embedded in the Accreditation Canada program, the benefits of a network approach are highlighted, including knowledge sharing, improving the consistency of practice through standards, and a broader systems-and-population view of healthcare delivery across the continuum of care. The implications for Canadian health leaders to leverage the benefits of interorganizational networks are discussed.

  6. Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

    Directory of Open Access Journals (Sweden)

    Po-Chiang Lin

    2016-01-01

    Full Text Available Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.

  7. Webdatanet: Innovation and quality in web-based data collection

    NARCIS (Netherlands)

    Steinmetz, S.; Slavec, A.; Tijdens, K.; Reips, U.-D.; de Pedraza, P.; Popescu, A.; Belchior, A.; Birgegard, A.; Bianchi, A.; Ayalon, A.; Selkala, A.; Villacampa, A.; Winer, B.; Mlacic, B.; Vogel, C.; Gravem, D.; Gayo Avello, D.; Constantin, D.; Toninelli, D.; Troitino, D.; Horvath, D.; de Leeuw, E.; Oren, E.; Fernandez-Macias, E.; Thorsdottir, F.; Ortega, F.; Funke, F.; Campagnolo, G.M.; Milas, G.; Grünwald, C.; Jonsdottir, G.; Haraldsen, G.; Doron, G.; Margetts, H.; Miklousic, I.; Andreadis, I.; Berzelak, J.; Angelovska, J.; Schrittwieser, K.; Kissau, K.; Lozar Manfreda, K.; Kolsrud, K.; Kalgraff Skjak, K.; Tsagarakis, K.; Kaczmirek, L.; Lesnard, L.; Moga, L.M.; Lopes Teixeira, L.; Plate, M.; Kozak, M.; Fuchs, M.; Callegaro, M.; Cantijoch, M.; Kahanec, M.; Stopa, M.; Ernst Staehli, M.; Neculita, M.; Ivanovic, M.; Foulonneau, M.; Cheikhrouhou, N.; Fornara, N.; Finnemann, N.O.; Zajc, N.; Nyirå, N.; Louca, P.; Osse, P.; Mavrikiou, P.; Gibson, R.; Vatrapu, R.; Dar, R.; Pinter, R.; Martinez Torres, R.; Douhou, S.; Biffignandi, S.; Grceva, S.; David, S.; Ronkainen, T.; Csordas, T.; Lenzner, T.; Vesteinsdottir, V.; Vehovar, V.; Markov, Y.

    2014-01-01

    In light of the growing importance of web-based data in the social and behavioral sciences, WEBDATANET was established in 2011 as a COST Action (IS 1004) to create a multidisciplinary network of web-based data collection experts: (web) survey methodologists, psychologists, sociologists, linguists,

  8. Shapley ratings in brain networks

    Directory of Open Access Journals (Sweden)

    Rolf Kötter

    2007-11-01

    Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

  9. The Role of Middlemen inEfficient and Strongly Pairwise Stable Networks

    NARCIS (Netherlands)

    Gilles, R.P.; Chakrabarti, S.; Sarangi, S.; Badasyan, N.

    2004-01-01

    We examine the strong pairwise stability concept in network formation theory under collective network benefits.Strong pairwise stability considers a pair of players to add a link through mutual consent while permitting them to unilaterally delete any subset of links under their control.We examine

  10. Quality Utilization Aware Based Data Gathering for Vehicular Communication Networks

    Directory of Open Access Journals (Sweden)

    Yingying Ren

    2018-01-01

    Full Text Available The vehicular communication networks, which can employ mobile, intelligent sensing devices with participatory sensing to gather data, could be an efficient and economical way to build various applications based on big data. However, high quality data gathering for vehicular communication networks which is urgently needed faces a lot of challenges. So, in this paper, a fine-grained data collection framework is proposed to cope with these new challenges. Different from classical data gathering which concentrates on how to collect enough data to satisfy the requirements of applications, a Quality Utilization Aware Data Gathering (QUADG scheme is proposed for vehicular communication networks to collect the most appropriate data and to best satisfy the multidimensional requirements (mainly including data gathering quantity, quality, and cost of application. In QUADG scheme, the data sensing is fine-grained in which the data gathering time and data gathering area are divided into very fine granularity. A metric named “Quality Utilization” (QU is to quantify the ratio of quality of the collected sensing data to the cost of the system. Three data collection algorithms are proposed. The first algorithm is to ensure that the application which has obtained the specified quantity of sensing data can minimize the cost and maximize data quality by maximizing QU. The second algorithm is to ensure that the application which has obtained two requests of application (the quantity and quality of data collection, or the quantity and cost of data collection could maximize the QU. The third algorithm is to ensure that the application which aims to satisfy the requirements of quantity, quality, and cost of collected data simultaneously could maximize the QU. Finally, we compare our proposed scheme with the existing schemes via extensive simulations which well justify the effectiveness of our scheme.

  11. Collective leadership and safety cultures (Co-Lead): protocol for a mixed-methods pilot evaluation of the impact of a co-designed collective leadership intervention on team performance and safety culture in a hospital group in Ireland.

    Science.gov (United States)

    McAuliffe, Eilish; De Brún, Aoife; Ward, Marie; O'Shea, Marie; Cunningham, Una; O'Donovan, Róisín; McGinley, Sinead; Fitzsimons, John; Corrigan, Siobhán; McDonald, Nick

    2017-11-03

    There is accumulating evidence implicating the role of leadership in system failures that have resulted in a range of errors in healthcare, from misdiagnoses to failures to recognise and respond to patient deterioration. This has led to concerns about traditional hierarchical leadership structures and created an interest in the development of collective ways of working that distribute leadership roles and responsibilities across team members. Such collective leadership approaches have been associated with improved team performance and staff engagement. This research seeks to improve our understanding of collective leadership by addressing two specific issues: (1) Does collective leadership emerge organically (and in what forms) in a newly networked structure? and (2) Is it possible to design and implement collective leadership interventions that enable teams to collectively improve team performance and patient safety? The first phase will include a social network analysis, using an online survey and semistructured interviews at three time points over 12 months, to document the frequency of contact and collaboration between senior hospital management staff in a recently configured hospital group. This study will explore how the network of 11 hospitals is operating and will assess whether collective leadership emerges organically. Second, collective leadership interventions will be co-designed during a series of workshops with healthcare staff, researchers and patient representatives, and then implemented and evaluated with four healthcare teams within the hospital network. A mixed-methods evaluation will explore the impact of the intervention on team effectiveness and team performance indicators to assess whether the intervention is suitable for wider roll-out and evaluation across the hospital group. Favourable ethical opinion has been received from the University College Dublin Research Ethics Committee (HREC-LS-16-116397/LS-16-20). Results will be disseminated

  12. Approximate Sensory Data Collection: A Survey.

    Science.gov (United States)

    Cheng, Siyao; Cai, Zhipeng; Li, Jianzhong

    2017-03-10

    With the rapid development of the Internet of Things (IoTs), wireless sensor networks (WSNs) and related techniques, the amount of sensory data manifests an explosive growth. In some applications of IoTs and WSNs, the size of sensory data has already exceeded several petabytes annually, which brings too many troubles and challenges for the data collection, which is a primary operation in IoTs and WSNs. Since the exact data collection is not affordable for many WSN and IoT systems due to the limitations on bandwidth and energy, many approximate data collection algorithms have been proposed in the last decade. This survey reviews the state of the art of approximatedatacollectionalgorithms. Weclassifythemintothreecategories: themodel-basedones, the compressive sensing based ones, and the query-driven ones. For each category of algorithms, the advantages and disadvantages are elaborated, some challenges and unsolved problems are pointed out, and the research prospects are forecasted.

  13. Convolutional neural network-based classification system design with compressed wireless sensor network images.

    Science.gov (United States)

    Ahn, Jungmo; Park, JaeYeon; Park, Donghwan; Paek, Jeongyeup; Ko, JeongGil

    2018-01-01

    With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.

  14. Optimized and Executive Survey of Physical Node Capture Attack in Wireless Sensor Network

    OpenAIRE

    Bhavana Butani; Piyush Kumar Shukla; Sanjay Silakari

    2014-01-01

    Wireless sensor networks (WSNs) are novel large-scale wireless networks that consist of distributed, self organizing, low-power, low-cost, tiny sensor devices to cooperatively collect information through infrastructure less wireless networks. These networks are envisioned to play a crucial role in variety of applications like critical military surveillance applications, forest fire monitoring, commercial applications such as building security monitoring, traffic surveillance, habitat monitori...

  15. E-expertise modern collective intelligence

    CERN Document Server

    Gubanov, Dmitry; Novikov, Dmitry; Raikov, Alexander

    2014-01-01

      This book focuses on organization and mechanisms of expert decision-making support using modern information and communication technologies, as well as information analysis and collective intelligence technologies (electronic expertise or simply e-expertise). Chapter 1 (E-Expertise) discusses the role of e-expertise in decision-making processes. The procedures of e-expertise are classified, their benefits and shortcomings are identified, and the efficiency conditions are considered. Chapter 2 (Expert Technologies and Principles) provides a comprehensive overview of modern expert technologies. A special emphasis is placed on the specifics of e-expertise. Moreover, the authors study the feasibility and reasonability of employing well-known methods and approaches in e-expertise. Chapter 3 (E-Expertise: Organization and Technologies) describes some examples of up-to-date technologies to perform e-expertise. Chapter 4 (Trust Networks and Competence Networks) deals with the problems of expert finding and grouping...

  16. A Mixed Transmission Strategy to Achieve Energy Balancing in Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Liu, Tong; Gu, Tao; Jin, Ning

    2017-01-01

    In this paper, we investigate the problem of energy balanced data collection in wireless sensor networks, aiming to balance energy consumption among all sensor nodes during the data propagation process. Energy balanced data collection can potentially save energy consumption and prolong network...... lifetime, and hence, it has many practical implications for sensor network design and deployment. The traditional hop-by-hop transmission model allows a sensor node to propagate its packets in a hop-by-hop manner toward the sink, resulting in poor energy balancing for the entire network. To address...... the problem, we apply a slice-based energy model, and divide the problem into inter-slice and intra-slice energy balancing problems. We then propose a probability-based strategy named inter-slice mixed transmission protocol and an intra-slice forwarding technique to address each of the problems. We propose...

  17. Processing data collected from radiometric experiments by multivariate technique

    International Nuclear Information System (INIS)

    Urbanski, P.; Kowalska, E.; Machaj, B.; Jakowiuk, A.

    2005-01-01

    Multivariate techniques applied for processing data collected from radiometric experiments can provide more efficient extraction of the information contained in the spectra. Several techniques are considered: (i) multivariate calibration using Partial Least Square Regression and Artificial Neural Network, (ii) standardization of the spectra, (iii) smoothing of collected spectra were autocorrelation function and bootstrap were used for the assessment of the processed data, (iv) image processing using Principal Component Analysis. Application of these techniques is illustrated on examples of some industrial applications. (author)

  18. Impact of degree truncation on the spread of a contagious process on networks.

    Science.gov (United States)

    Harling, Guy; Onnela, Jukka-Pekka

    2018-03-01

    Understanding how person-to-person contagious processes spread through a population requires accurate information on connections between population members. However, such connectivity data, when collected via interview, is often incomplete due to partial recall, respondent fatigue or study design, e.g., fixed choice designs (FCD) truncate out-degree by limiting the number of contacts each respondent can report. Past research has shown how FCD truncation affects network properties, but its implications for predicted speed and size of spreading processes remain largely unexplored. To study the impact of degree truncation on predictions of spreading process outcomes, we generated collections of synthetic networks containing specific properties (degree distribution, degree-assortativity, clustering), and also used empirical social network data from 75 villages in Karnataka, India. We simulated FCD using various truncation thresholds and ran a susceptible-infectious-recovered (SIR) process on each network. We found that spreading processes propagated on truncated networks resulted in slower and smaller epidemics, with a sudden decrease in prediction accuracy at a level of truncation that varied by network type. Our results have implications beyond FCD to truncation due to any limited sampling from a larger network. We conclude that knowledge of network structure is important for understanding the accuracy of predictions of process spread on degree truncated networks.

  19. On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition

    Directory of Open Access Journals (Sweden)

    Marco Zennaro

    2010-12-01

    Full Text Available Achieving situation recognition in ubiquitous sensor networks (USNs is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

  20. Network Physiology: How Organ Systems Dynamically Interact

    Science.gov (United States)

    Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

  1. Network Physiology: How Organ Systems Dynamically Interact.

    Science.gov (United States)

    Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  2. Opinion formation driven by PageRank node influence on directed networks

    Science.gov (United States)

    Eom, Young-Ho; Shepelyansky, Dima L.

    2015-10-01

    We study a two states opinion formation model driven by PageRank node influence and report an extensive numerical study on how PageRank affects collective opinion formations in large-scale empirical directed networks. In our model the opinion of a node can be updated by the sum of its neighbor nodes' opinions weighted by the node influence of the neighbor nodes at each step. We consider PageRank probability and its sublinear power as node influence measures and investigate evolution of opinion under various conditions. First, we observe that all networks reach steady state opinion after a certain relaxation time. This time scale is decreasing with the heterogeneity of node influence in the networks. Second, we find that our model shows consensus and non-consensus behavior in steady state depending on types of networks: Web graph, citation network of physics articles, and LiveJournal social network show non-consensus behavior while Wikipedia article network shows consensus behavior. Third, we find that a more heterogeneous influence distribution leads to a more uniform opinion state in the cases of Web graph, Wikipedia, and Livejournal. However, the opposite behavior is observed in the citation network. Finally we identify that a small number of influential nodes can impose their own opinion on significant fraction of other nodes in all considered networks. Our study shows that the effects of heterogeneity of node influence on opinion formation can be significant and suggests further investigations on the interplay between node influence and collective opinion in networks.

  3. Random catalytic reaction networks

    Science.gov (United States)

    Stadler, Peter F.; Fontana, Walter; Miller, John H.

    1993-03-01

    We study networks that are a generalization of replicator (or Lotka-Volterra) equations. They model the dynamics of a population of object types whose binary interactions determine the specific type of interaction product. Such a system always reduces its dimension to a subset that contains production pathways for all of its members. The network equation can be rewritten at a level of collectives in terms of two basic interaction patterns: replicator sets and cyclic transformation pathways among sets. Although the system contains well-known cases that exhibit very complicated dynamics, the generic behavior of randomly generated systems is found (numerically) to be extremely robust: convergence to a globally stable rest point. It is easy to tailor networks that display replicator interactions where the replicators are entire self-sustaining subsystems, rather than structureless units. A numerical scan of random systems highlights the special properties of elementary replicators: they reduce the effective interconnectedness of the system, resulting in enhanced competition, and strong correlations between the concentrations.

  4. Multi-Channel Scheduling for Fast Convergecast in Wireless Sensor Networks

    NARCIS (Netherlands)

    Durmaz, O.; Ghosh, A.; Krishnamachari, B.; Chintalapudi, K.

    We explore the following fundamental question - how fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data collection

  5. Automated collection and dissemination of ionospheric data from the digisonde network

    Directory of Open Access Journals (Sweden)

    B.W. Reinisch

    2004-01-01

    Full Text Available The growing demand for fast access to accurate ionospheric electron density profiles and ionospheric characteristics calls for efficient dissemination of data from the many ionosondes operating around the globe. The global digisonde network with over 70 stations takes advantage of the Internet to make many of these sounders remotely accessible for data transfer and control. Key elements of the digisonde system data management are the visualization and editing tool SAO Explorer, the digital ionogram database DIDBase, holding raw and derived digisonde data under an industrial-strength database management system, and the automated data request execution system ADRES.

  6. Local and global responses in complex gene regulation networks

    Science.gov (United States)

    Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

    2009-04-01

    An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

  7. Wind Resource Assessment and Forecast Planning with Neural Networks

    Directory of Open Access Journals (Sweden)

    Nicolus K. Rotich

    2014-06-01

    Full Text Available In this paper we built three types of artificial neural networks, namely: Feed forward networks, Elman networks and Cascade forward networks, for forecasting wind speeds and directions. A similar network topology was used for all the forecast horizons, regardless of the model type. All the models were then trained with real data of collected wind speeds and directions over a period of two years in the municipal of Puumala, Finland. Up to 70th percentile of the data was used for training, validation and testing, while 71–85th percentile was presented to the trained models for validation. The model outputs were then compared to the last 15% of the original data, by measuring the statistical errors between them. The feed forward networks returned the lowest errors for wind speeds. Cascade forward networks gave the lowest errors for wind directions; Elman networks returned the lowest errors when used for short term forecasting.

  8. Anomaly-based Network Intrusion Detection Methods

    Directory of Open Access Journals (Sweden)

    Pavel Nevlud

    2013-01-01

    Full Text Available The article deals with detection of network anomalies. Network anomalies include everything that is quite different from the normal operation. For detection of anomalies were used machine learning systems. Machine learning can be considered as a support or a limited type of artificial intelligence. A machine learning system usually starts with some knowledge and a corresponding knowledge organization so that it can interpret, analyse, and test the knowledge acquired. There are several machine learning techniques available. We tested Decision tree learning and Bayesian networks. The open source data-mining framework WEKA was the tool we used for testing the classify, cluster, association algorithms and for visualization of our results. The WEKA is a collection of machine learning algorithms for data mining tasks.

  9. Wireless Sensing Node Network Management for Monitoring Landslide Disaster

    International Nuclear Information System (INIS)

    Takayama, S; Akiyama, J; Fujiki, T; Mokhtar, N A B

    2013-01-01

    This paper shows the network management and operation to monitor landslide disaster at slop of mountain and hill. Natural disasters damage a measuring system easily. It is necessary for the measuring system to be flexible and robust. The measuring network proposed in this paper is the telemetry system consisted of host system (HS) and local sensing nodes network system (LSNNS). LSNNS operates autonomously and sometimes is controlled by commands from HS. HS collects data/information of landslide disaster from LSNNS, and controls LSNNS remotely. HS and LSNNS are communicated by using 'cloud' system. The dual communication is very effective and convenient to manage a network system operation

  10. Leaders in social networks, the Delicious case.

    Science.gov (United States)

    Lü, Linyuan; Zhang, Yi-Cheng; Yeung, Chi Ho; Zhou, Tao

    2011-01-01

    Finding pertinent information is not limited to search engines. Online communities can amplify the influence of a small number of power users for the benefit of all other users. Users' information foraging in depth and breadth can be greatly enhanced by choosing suitable leaders. For instance in delicious.com, users subscribe to leaders' collection which lead to a deeper and wider reach not achievable with search engines. To consolidate such collective search, it is essential to utilize the leadership topology and identify influential users. Google's PageRank, as a successful search algorithm in the World Wide Web, turns out to be less effective in networks of people. We thus devise an adaptive and parameter-free algorithm, the LeaderRank, to quantify user influence. We show that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data. These results suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.

  11. Leaders in social networks, the Delicious case.

    Directory of Open Access Journals (Sweden)

    Linyuan Lü

    Full Text Available Finding pertinent information is not limited to search engines. Online communities can amplify the influence of a small number of power users for the benefit of all other users. Users' information foraging in depth and breadth can be greatly enhanced by choosing suitable leaders. For instance in delicious.com, users subscribe to leaders' collection which lead to a deeper and wider reach not achievable with search engines. To consolidate such collective search, it is essential to utilize the leadership topology and identify influential users. Google's PageRank, as a successful search algorithm in the World Wide Web, turns out to be less effective in networks of people. We thus devise an adaptive and parameter-free algorithm, the LeaderRank, to quantify user influence. We show that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data. These results suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.

  12. Inferring network topology from complex dynamics

    International Nuclear Information System (INIS)

    Shandilya, Srinivas Gorur; Timme, Marc

    2011-01-01

    Inferring the network topology from dynamical observations is a fundamental problem pervading research on complex systems. Here, we present a simple, direct method for inferring the structural connection topology of a network, given an observation of one collective dynamical trajectory. The general theoretical framework is applicable to arbitrary network dynamical systems described by ordinary differential equations. No interference (external driving) is required and the type of dynamics is hardly restricted in any way. In particular, the observed dynamics may be arbitrarily complex; stationary, invariant or transient; synchronous or asynchronous and chaotic or periodic. Presupposing a knowledge of the functional form of the dynamical units and of the coupling functions between them, we present an analytical solution to the inverse problem of finding the network topology from observing a time series of state variables only. Robust reconstruction is achieved in any sufficiently long generic observation of the system. We extend our method to simultaneously reconstructing both the entire network topology and all parameters appearing linear in the system's equations of motion. Reconstruction of network topology and system parameters is viable even in the presence of external noise that distorts the original dynamics substantially. The method provides a conceptually new step towards reconstructing a variety of real-world networks, including gene and protein interaction networks and neuronal circuits.

  13. Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks

    DEFF Research Database (Denmark)

    Yan, Ying; Dittmann, Lars

    2011-01-01

    In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...... by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....

  14. QoS support over ultrafast TDM optical networks

    Science.gov (United States)

    Narvaez, Paolo; Siu, Kai-Yeung; Finn, Steven G.

    1999-08-01

    HLAN is a promising architecture to realize Tb/s access networks based on ultra-fast optical TDM technologies. This paper presents new research results on efficient algorithms for the support of quality of service over the HLAN network architecture. In particular, we propose a new scheduling algorithm that emulates fair queuing in a distributed manner for bandwidth allocation purpose. The proposed scheduler collects information on the queue of each host on the network and then instructs each host how much data to send. Our new scheduling algorithm ensures full bandwidth utilization, while guaranteeing fairness among all hosts.

  15. Network dynamics of social influence in the wisdom of crowds.

    Science.gov (United States)

    Becker, Joshua; Brackbill, Devon; Centola, Damon

    2017-06-27

    A longstanding problem in the social, biological, and computational sciences is to determine how groups of distributed individuals can form intelligent collective judgments. Since Galton's discovery of the "wisdom of crowds" [Galton F (1907) Nature 75:450-451], theories of collective intelligence have suggested that the accuracy of group judgments requires individuals to be either independent, with uncorrelated beliefs, or diverse, with negatively correlated beliefs [Page S (2008) The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies ]. Previous experimental studies have supported this view by arguing that social influence undermines the wisdom of crowds. These results showed that individuals' estimates became more similar when subjects observed each other's beliefs, thereby reducing diversity without a corresponding increase in group accuracy [Lorenz J, Rauhut H, Schweitzer F, Helbing D (2011) Proc Natl Acad Sci USA 108:9020-9025]. By contrast, we show general network conditions under which social influence improves the accuracy of group estimates, even as individual beliefs become more similar. We present theoretical predictions and experimental results showing that, in decentralized communication networks, group estimates become reliably more accurate as a result of information exchange. We further show that the dynamics of group accuracy change with network structure. In centralized networks, where the influence of central individuals dominates the collective estimation process, group estimates become more likely to increase in error.

  16. PSO-Optimized Hopfield Neural Network-Based Multipath Routing for Mobile Ad-hoc Networks

    Directory of Open Access Journals (Sweden)

    Mansour Sheikhan

    2012-06-01

    Full Text Available Mobile ad-hoc network (MANET is a dynamic collection of mobile computers without the need for any existing infrastructure. Nodes in a MANET act as hosts and routers. Designing of robust routing algorithms for MANETs is a challenging task. Disjoint multipath routing protocols address this problem and increase the reliability, security and lifetime of network. However, selecting an optimal multipath is an NP-complete problem. In this paper, Hopfield neural network (HNN which its parameters are optimized by particle swarm optimization (PSO algorithm is proposed as multipath routing algorithm. Link expiration time (LET between each two nodes is used as the link reliability estimation metric. This approach can find either node-disjoint or link-disjoint paths in singlephase route discovery. Simulation results confirm that PSO-HNN routing algorithm has better performance as compared to backup path set selection algorithm (BPSA in terms of the path set reliability and number of paths in the set.

  17. Inferential ecosystem models, from network data to prediction

    Science.gov (United States)

    James S. Clark; Pankaj Agarwal; David M. Bell; Paul G. Flikkema; Alan Gelfand; Xuanlong Nguyen; Eric Ward; Jun Yang

    2011-01-01

    Recent developments suggest that predictive modeling could begin to play a larger role not only for data analysis, but also for data collection. We address the example of efficient wireless sensor networks, where inferential ecosystem models can be used to weigh the value of an observation against the cost of data collection. Transmission costs make observations ‘‘...

  18. Tourist activated networks: Implications for dynamic bundling and en-route recommendations

    DEFF Research Database (Denmark)

    Zach, Florian; Gretzel, Ulrike

    2011-01-01

    This article discusses tourist-activated networks as a concept to inform technological applications supporting dynamic bundling and en route recommendations. Empirical data were collected from travelers who visited a regional destination in the US and then analyzed with respect to its network...... structure. The results indicate that the tourist-activated network for the destination is rather sparse and that there are clearly differences in core and peripheral nodes. The findings illustrate the structure of a tourist-activated network and provide implications for technology design and tourism...

  19. Data Gathering in Delay Tolerant Wireless Sensor Networks Using a Ferry

    Directory of Open Access Journals (Sweden)

    Mariam Alnuaimi

    2015-10-01

    Full Text Available In delay tolerant WSNs mobile ferries can be used for collecting data from sensor nodes, especially in large-scale networks. Unlike data collection via multi-hop forwarding among the nodes, ferries travel across the sensing field and collect data from sensors. The advantage of using a ferry-based approach is that, it eliminates the need for multi-hop forwarding of data, and as a result energy consumption at the nodes is significantly reduced. However, this increases data delivery latency and as such might not be suitable for all applications. In this paper an efficient data collection algorithm using a ferry node is proposed while considering the overall ferry roundtrip travel time and the overall consumed energy in the network. To minimize the overall roundtrip travel time, we divided the sensing field area into virtual grids based on the assumed sensing range and assigned a checkpoint in each one. A Genetic Algorithm with weight metrics to solve the Travel Sales Man Problem (TSP and decide on an optimum path for the ferry to collect data is then used. We utilized our previously published node ranking clustering algorithm (NRCA in each virtual grid and in choosing the location for placing the ferry’s checkpoints. In NRCA the decision of selecting cluster heads is based on their residual energy and their distance from their associated checkpoint which acts as a temporary sink. We simulated the proposed algorithm in MATLAB and showed its performance in terms of the network lifetime, total energy consumption and the total travel time. Moreover, we showed through simulation that nonlinear trajectory achieves a better optimization in term of network lifetime, overall energy consumed and the roundtrip travel time of the ferry compared to linear predetermined trajectory. In additional to that, we compared the performance of your algorithm to other recent algorithms in terms of the network lifetime using same and different initial energy values.

  20. Optical Access Networks

    Science.gov (United States)

    Zheng, Jun; Ansari, Nirwan

    2005-01-01

    have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or are now underway this hot area. The purpose of this feature issue is to expose the networking community to the latest research breakthroughs and progresses in the area of optical access networks. Scope of Contributions This feature issue aims to present a collection of papers that focus on the state-of-the-art research in various networking aspects of optical access networks. Original papers are solicited from all researchers involved in area of optical access networks. Topics of interest include but not limited to: Optical access network architectures and protocols Passive optical networks (BPON, EPON, GPON, etc.) Active optical networks Multiple access control Multiservices and QoS provisioning Network survivability Field trials and standards Performance modeling and analysis Manuscript Submission To submit to this special issue, follow the normal procedure for submission to JON, indicating ``Optical Access Networks feature' in the ``Comments' field of the online submission form. For all other questions relating to this feature issue, please send an e-mail to jon@osa.org, subject line ``Optical Access Networks' Additional information can be found on the JON website: http://www.osa-jon.org/submission/. Submission Deadline: 1 June 2005

  1. Data Collection Manual for Academic and Research Library Network Statistics and Performance Measures.

    Science.gov (United States)

    Shim, Wonsik "Jeff"; McClure, Charles R.; Fraser, Bruce T.; Bertot, John Carlo

    This manual provides a beginning approach for research libraries to better describe the use and users of their networked services. The manual also aims to increase the visibility and importance of developing such statistics and measures. Specific objectives are: to identify selected key statistics and measures that can describe use and users of…

  2. The ties that bind? Social networks of nursing staff and staff’s behaviour towards residents with dementia.

    NARCIS (Netherlands)

    Beek, A.P.A. van; Wagner, C.; Frijters, D.H.M.; Ribbe, M.W.; Groenewegen, P.P.

    2013-01-01

    This study investigated social networks of nursing staff and staff's behaviour towards residents with dementia. We focused on two types of networks: communication networks among staff, and networks between nursing staff and relatives/acquaintances of residents. Data was collected in 37 long-term

  3. Consciousness, cognition and brain networks: New perspectives.

    Science.gov (United States)

    Aldana, E M; Valverde, J L; Fábregas, N

    2016-10-01

    A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

  4. Horizontal and Vertical Networks for Innovation in the Traditional Food Sector

    Directory of Open Access Journals (Sweden)

    Xavier Gellynck

    2010-05-01

    Full Text Available The locus of innovation is not the individual firm anymore but increasingly the network in which the firm is embedded. Hence, in this paper innovation is investigated in the broader context of networks and applied to the traditional food sector. Networking refers to a process of identifying and acting on complementary interests with or without formal means of cooperation and plays an important role for the diffusion and adoption of innovations, because they increase the flow of information. Two main types of networks exist. Vertical networks relate to cooperation of partners belonging to the same chain. Meanwhile, horizontal networks refer to coopereation among firms which are primarily competitors. Data were collected during focus groups and in-depths interviews in three European contries: Belgium, Hungary, and Italy.In each country, data are collected from retailers/wholesalers, food manufacturers and suppliers in the beer, hard and half hard cheese, ham, sausage, or white paprika chain. In the investigated countries both vertical and horizontal networks exist. However, the intensity of using the network differs. On the one hand vertical networks are well developed based on quality assurance schemes and traceability, though these networks often face difficulties due to high lack of trust. On the other hand, horizontal networks are well developed when a producer consortium is involved. However, these networks can be inhibited through strong competition. The partners in traditional food networks focus mainly on innovation related to product characteristics such as new size, form and packaging without changing the traditional character of the product. The main barriers for innovation in the traditional food networks are the lack of understanding the benefits of networking activities for innovation, the lack of trust, the lack of knowledge of appropriate methods and skills, and the lack of financial and physical resources. Our study points out

  5. Software-defined Quantum Networking Ecosystem

    Energy Technology Data Exchange (ETDEWEB)

    2017-01-01

    The software enables a user to perform modeling and simulation of software-defined quantum networks. The software addresses the problem of how to synchronize transmission of quantum and classical signals through multi-node networks and to demonstrate quantum information protocols such as quantum teleportation. The software approaches this problem by generating a graphical model of the underlying network and attributing properties to each node and link in the graph. The graphical model is then simulated using a combination of discrete-event simulators to calculate the expected state of each node and link in the graph at a future time. A user interacts with the software by providing an initial network model and instantiating methods for the nodes to transmit information with each other. This includes writing application scripts in python that make use of the software library interfaces. A user then initiates the application scripts, which invokes the software simulation. The user then uses the built-in diagnostic tools to query the state of the simulation and to collect statistics on synchronization.

  6. Clustering network layers with the strata multilayer stochastic block model.

    Science.gov (United States)

    Stanley, Natalie; Shai, Saray; Taylor, Dane; Mucha, Peter J

    2016-01-01

    Multilayer networks are a useful data structure for simultaneously capturing multiple types of relationships between a set of nodes. In such networks, each relational definition gives rise to a layer. While each layer provides its own set of information, community structure across layers can be collectively utilized to discover and quantify underlying relational patterns between nodes. To concisely extract information from a multilayer network, we propose to identify and combine sets of layers with meaningful similarities in community structure. In this paper, we describe the "strata multilayer stochastic block model" (sMLSBM), a probabilistic model for multilayer community structure. The central extension of the model is that there exist groups of layers, called "strata", which are defined such that all layers in a given stratum have community structure described by a common stochastic block model (SBM). That is, layers in a stratum exhibit similar node-to-community assignments and SBM probability parameters. Fitting the sMLSBM to a multilayer network provides a joint clustering that yields node-to-community and layer-to-stratum assignments, which cooperatively aid one another during inference. We describe an algorithm for separating layers into their appropriate strata and an inference technique for estimating the SBM parameters for each stratum. We demonstrate our method using synthetic networks and a multilayer network inferred from data collected in the Human Microbiome Project.

  7. Mapping dynamic social networks in real life using participants' own smartphones

    Directory of Open Access Journals (Sweden)

    Tjeerd W. Boonstra

    2015-11-01

    Full Text Available Interpersonal relationships are vital for our daily functioning and wellbeing. Social networks may form the primary means by which environmental influences determine individual traits. Several studies have shown the influence of social networks on decision-making, behaviors and wellbeing. Smartphones have great potential for measuring social networks in a real world setting. Here we tested the feasibility of using people's own smartphones as a data collection platform for face-to-face interactions. We developed an application for iOS and Android to collect Bluetooth data and acquired one week of data from 14 participants in our organization. The Bluetooth scanning statistics were used to quantify the time-resolved connection strength between participants and define the weights of a dynamic social network. We used network metrics to quantify changes in network topology over time and non-negative matrix factorization to identify cliques or subgroups that reoccurred during the week. The scanning rate varied considerably between smartphones running Android and iOS and egocentric networks metrics were correlated with the scanning rate. The time courses of two identified subgroups matched with two meetings that took place that week. These findings demonstrate the feasibility of using participants' own smartphones to map social network, whilst identifying current limitations of using generic smartphones. The bias introduced by variations in scanning rate and missing data is an important limitation that needs to be addressed in future studies.

  8. From genomes to in silico cells via metabolic networks

    DEFF Research Database (Denmark)

    Borodina, Irina; Nielsen, Jens

    2005-01-01

    Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

  9. Dynamic baseline detection method for power data network service

    Science.gov (United States)

    Chen, Wei

    2017-08-01

    This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

  10. Global activism: new paths for Black people movement collective action in Colombia

    Directory of Open Access Journals (Sweden)

    Adriana Espinosa Bonilla

    2011-07-01

    Full Text Available This paper examines the transformations in actor-network collective action in the Process of Black Communities —pcn—, which were developed as a consequence of the armed conflict worsening in the Pacific region —specifically on the collective lands in the municipalities of Buenaventura and Suárez (Southwestern Colombia— in the last ten years. Information was gathered through semi-structured interviews, observation records, analysis of audio/text documents on the organizations’ claims and communiqués, and the drafting of aggregated data on displacement and conflictual facts in the region. Findings show a significant up surging of conflict within the period, in the face of which PCN’s coalitions with local and global actors have come both to neutralize and make visible armed actors’ actions against populations, and to reorient collective action, introducing innovations in the repertoires of action and setting new goals for this actor-network in the region.

  11. Computer networks and their implications for nuclear data

    International Nuclear Information System (INIS)

    Carlson, J.

    1992-01-01

    Computer networks represent a valuable resource for accessing information. Just as the computer has revolutionized the ability to process and analyze information, networks have and will continue to revolutionize data collection and access. A number of services are in routine use that would not be possible without the presence of an (inter)national computer network (which will be referred to as the internet). Services such as electronic mail, remote terminal access, and network file transfers are almost a required part of any large scientific/research organization. These services only represent a small fraction of the potential uses of the internet; however, the remainder of this paper discusses some of these uses and some technological developments that may influence these uses

  12. Memory-induced mechanism for self-sustaining activity in networks

    Science.gov (United States)

    Allahverdyan, A. E.; Steeg, G. Ver; Galstyan, A.

    2015-12-01

    We study a mechanism of activity sustaining on networks inspired by a well-known model of neuronal dynamics. Our primary focus is the emergence of self-sustaining collective activity patterns, where no single node can stay active by itself, but the activity provided initially is sustained within the collective of interacting agents. In contrast to existing models of self-sustaining activity that are caused by (long) loops present in the network, here we focus on treelike structures and examine activation mechanisms that are due to temporal memory of the nodes. This approach is motivated by applications in social media, where long network loops are rare or absent. Our results suggest that under a weak behavioral noise, the nodes robustly split into several clusters, with partial synchronization of nodes within each cluster. We also study the randomly weighted version of the models where the nodes are allowed to change their connection strength (this can model attention redistribution) and show that it does facilitate the self-sustained activity.

  13. Monitoring individual traffic flows within the ATLAS TDAQ network

    CERN Document Server

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

    2010-01-01

    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 a...

  14. Evolution of students’ friendship networks: Examining the influence of group size

    Directory of Open Access Journals (Sweden)

    Valentina Sokolovska

    2017-01-01

    Full Text Available  The main aim of this study was to examine the effect of the network size on formation and evolution of students’ friendship relations. Data was collected from two groups of sociology freshmen: a group from the University of Belgrade, which represents a larger group, and a group from the University of Novi Sad, which represents a smaller group. The data was collected in three periods of one academic year. We analyzed the structural features of students’ networks and constructed a stochastic model of network evolution in order to explore how friendships form and change during one year. The results showed that structural features of the larger and the smaller group differ in each stage of friendship formation. At the beginning of group forming, small world structure was noticeable in the larger group, although full small world structure was not confirmed in both groups. Furthermore, transitivity of triads had effect on the evolution of the larger network, while balance or structural equivalence had effect on the evolution of the smaller network. Results of the structural analysis are in line with findings of the network evolution model and together they provide an insight into how friendship evolves in groups of different sizes.

  15. Social Transmission of False Memory in Small Groups and Large Networks.

    Science.gov (United States)

    Maswood, Raeya; Rajaram, Suparna

    2018-05-21

    Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.

  16. Networking activism: implications for Greece

    Directory of Open Access Journals (Sweden)

    Pantelis Vatikiotis

    2011-12-01

    Full Text Available The outbreak of December 2008 against police brutality through a wave of demonstrations and street protests in Athens, which was strongly advocated by protest activities and practices across the world, addresses several issues in relation to the transformative potentials of mediated collective action. The paper critically evaluates different accounts of December events, probing then into thevery networking of that movement. From this perspective, it points out another aspect of the local-global interplay in protest culture along new mediating practices (beyond the creation of transnational publics, that of the implications of transnational networking for local social activism and identification, addressing relevant questions in the Greek context.

  17. Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.

    Science.gov (United States)

    Haibe-Kains, Benjamin; Olsen, Catharina; Djebbari, Amira; Bontempi, Gianluca; Correll, Mick; Bouton, Christopher; Quackenbush, John

    2012-01-01

    Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these 'known' interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.

  18. Approximate Sensory Data Collection: A Survey

    Directory of Open Access Journals (Sweden)

    Siyao Cheng

    2017-03-01

    Full Text Available With the rapid development of the Internet of Things (IoTs, wireless sensor networks (WSNs and related techniques, the amount of sensory data manifests an explosive growth. In some applications of IoTs and WSNs, the size of sensory data has already exceeded several petabytes annually, which brings too many troubles and challenges for the data collection, which is a primary operation in IoTs and WSNs. Since the exact data collection is not affordable for many WSN and IoT systems due to the limitations on bandwidth and energy, many approximate data collection algorithms have been proposed in the last decade. This survey reviews the state of the art of approximatedatacollectionalgorithms. Weclassifythemintothreecategories: themodel-basedones, the compressive sensing based ones, and the query-driven ones. For each category of algorithms, the advantages and disadvantages are elaborated, some challenges and unsolved problems are pointed out, and the research prospects are forecasted.

  19. Energy- Efficient Routing Protocols For Wireless Sensor Network A Review

    Directory of Open Access Journals (Sweden)

    Pardeep Kaur

    2017-12-01

    Full Text Available There has been plenty of interest in building and deploying sensor networks. Wireless sensor network is a collection of a large number of small nodes which acts as routers also. These nodes carry very limited power source which is non-rechargeable and non-replaceable which makes energy consumption an significant issue. Energy conservation is a very important issue for prolonging the lifetime of the network. As the sensor nodes act like routers as well the determination of routing technique plays a key role in controlling the consumption of energy. This paper describes the framework of wireless sensor network and the analysis and study of various research work related to Energy Efficient Routing in Wireless Sensor Networks.

  20. MET network in PubMed: a text-mined network visualization and curation system.

    Science.gov (United States)

    Dai, Hong-Jie; Su, Chu-Hsien; Lai, Po-Ting; Huang, Ming-Siang; Jonnagaddala, Jitendra; Rose Jue, Toni; Rao, Shruti; Chou, Hui-Jou; Milacic, Marija; Singh, Onkar; Syed-Abdul, Shabbir; Hsu, Wen-Lian

    2016-01-01

    Metastasis is the dissemination of a cancer/tumor from one organ to another, and it is the most dangerous stage during cancer progression, causing more than 90% of cancer deaths. Improving the understanding of the complicated cellular mechanisms underlying metastasis requires investigations of the signaling pathways. To this end, we developed a METastasis (MET) network visualization and curation tool to assist metastasis researchers retrieve network information of interest while browsing through the large volume of studies in PubMed. MET can recognize relations among genes, cancers, tissues and organs of metastasis mentioned in the literature through text-mining techniques, and then produce a visualization of all mined relations in a metastasis network. To facilitate the curation process, MET is developed as a browser extension that allows curators to review and edit concepts and relations related to metastasis directly in PubMed. PubMed users can also view the metastatic networks integrated from the large collection of research papers directly through MET. For the BioCreative 2015 interactive track (IAT), a curation task was proposed to curate metastatic networks among PubMed abstracts. Six curators participated in the proposed task and a post-IAT task, curating 963 unique metastatic relations from 174 PubMed abstracts using MET.Database URL: http://btm.tmu.edu.tw/metastasisway. © The Author(s) 2016. Published by Oxford University Press.

  1. Speech Quality Monitoring in Czech National Research Network

    Directory of Open Access Journals (Sweden)

    Miroslav Voznak

    2010-01-01

    Full Text Available This paper deals with techniques of measuring and assessment of the voice transmitted in IP networks and describes design of quality measurement, which can be used for Cisco Gateways. Cisco gateways send Calculated Planning Impairment Factor in every CDR (Call Detail Record. Our design is based on collection of CDR's, their storing into SQL database and their visualization through web page. This design was implemented and successfully tested in CESNET network.

  2. A Survey of Routing Issues and Associated Protocols in Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Khalid

    2017-01-01

    Full Text Available Underwater wireless sensor networks are a newly emerging wireless technology in which small size sensors with limited energy and limited memory and bandwidth are deployed in deep sea water and various monitoring operations like tactical surveillance, environmental monitoring, and data collection are performed through these tiny sensors. Underwater wireless sensor networks are used for the exploration of underwater resources, oceanographic data collection, flood or disaster prevention, tactical surveillance systems, and unmanned underwater vehicles. Sensor nodes consist of a small memory, a central processing unit, and an antenna. Underwater networks are much different from terrestrial sensor networks as radio waves cannot be used in underwater wireless sensor networks. Acoustic channels are used for communication in deep sea water. Acoustic signals have many limitations, such as limited bandwidth, higher end-to-end delay, network path loss, higher propagation delay, and dynamic topology. Usually, these limitations result in higher energy consumption with a smaller number of packets delivered. The main aim nowadays is to operate sensor nodes having a smaller battery for a longer time in the network. This survey has discussed the state-of-the-art localization based and localization-free routing protocols. Routing associated issues in the area of underwater wireless sensor networks have also been discussed.

  3. An investigation of scalable anomaly detection techniques for a large network of Wi-Fi hotspots

    CSIR Research Space (South Africa)

    Machaka, P

    2015-01-01

    Full Text Available . The Neural Networks, Bayesian Networks and Artificial Immune Systems were used for this experiment. Using a set of data extracted from a live network of Wi-Fi hotspots managed by an ISP; we integrated algorithms into a data collection system to detect...

  4. Scientists do not Need More Communities, They Need Collectives; and Collectives need Community to Build Teamwork

    Science.gov (United States)

    Caron, B. R.

    2017-12-01

    Nearly a decade ago I was on a team that was exploring a new online network platform for ocean scientists—one of those "Facebook for X" forays that never took off. During the research phase I learned that online groups exhibited a wide range of "stickiness," a description for member engagement. In general, engagement could be plotted on the usual power law curve; a handful of really engaged members on one side, and hundreds or thousands of mostly un-engaged members in the "long-tail" end of the curve.One genre of online groups completely broke this curve. These were the most engaged groups online, and by a long ways. Their entire membership regularly contributed content. The problem was that these groups were made of individuals who had been diagnosed with terminal or incurable chronic physical diseases. Their members sought answers beyond the ken of their individual medical advisors, and they collectively shouldered the news when one of their members inevitably passed on.This leads me back to science (including data science) and to the online engagement of scientists in social networks. From a series of cases and anecdotes collected from other community managers who have attempted to "engage" scientists online, it is clear that science effects its "victims" (scientists) much like an incurable (intellectual) disease. Scientists commonly spend sixty or more hours a week chasing unknowns in their labs, gathering field data, or tracking down software bugs. They share a fever for knowledge and their own common foe: the specific unknown that stands between the state-of-the-science in their specialty and a better understanding of the object of their study; the peculiar intellectual challenge (disease) they have chosen as their quest and their foe.Scientists don't need to join online communities to do science. What scientists need are online collectives that can accelerate their own research, and reward their contributions to new knowledge in their chosen specialty

  5. Fishing out collective memory of migratory schools

    DEFF Research Database (Denmark)

    De Luca, G.; Mariani, Patrizio; MacKenzie, Brian

    2014-01-01

    Animals form groups for many reasons but there are costs and benefit associated with group formation. One of the benefits is collective memory. In groups on the move, social interactions play a crucial role in the cohesion and the ability to make consensus decisions. When migrating from spawning...... to feeding areas fish schools need to retain a collective memory of the destination site over thousand of kilometers and changes in group formation or individual preference can produce sudden changes in migration pathways. We propose a modelling framework, based on stochastic adaptive networks, that can...... reproduce this collective behaviour. We assume that three factors control group formation and school migration behaviour: the intensity of social interaction, the relative number of informed individuals and the preference that each individual has for the particular migration area. We treat these factors...

  6. Network performance and fault analytics for LTE wireless service providers

    CERN Document Server

    Kakadia, Deepak; Gilgur, Alexander

    2017-01-01

     This book is intended to describe how to leverage emerging technologies big data analytics and SDN, to address challenges specific to LTE and IP network performance and fault management data in order to more efficiently manage and operate an LTE wireless networks. The proposed integrated solutions permit the LTE network service provider to operate entire integrated network, from RAN to Core , from UE to application service, as one unified system and correspondingly collect and align disparate key metrics and data, using an integrated and holistic approach to network analysis. The LTE wireless network performance and fault involves the network performance and management of network elements in EUTRAN, EPC and IP transport components, not only as individual components, but also as nuances of inter-working of these components. The key metrics for EUTRAN include radio access network accessibility, retainability, integrity, availability and mobility. The key metrics for EPC include MME accessibility, mobility and...

  7. Mechanical response of biopolymer double networks

    Science.gov (United States)

    Carroll, Joshua; Das, Moumita

    We investigate a double network model of articular cartilage (AC) and characterize its equilibrium mechanical response. AC has very few cells and the extracellular matrix mainly determines its mechanical response. This matrix can be thought of as a double polymer network made of collagen and aggrecan. The collagen fibers are stiff and resist tension and compression forces, while aggrecans are flexible and control swelling and hydration. We construct a microscopic model made of two interconnected disordered polymer networks, with fiber elasticity chosen to qualitatively mimic the experimental system. We study the collective mechanical response of this double network as a function of the concentration and stiffness of the individual components as well as the strength of the connection between them using rigidity percolation theory. Our results may provide a better understanding of mechanisms underlying the mechanical resilience of AC, and more broadly may also lead to new perspectives on the mechanical response of multicomponent soft materials. This work was partially supported by a Cottrell College Science Award.

  8. Wireless Sensor Networks for Ambient Assisted Living

    Directory of Open Access Journals (Sweden)

    Raúl Aquino-Santos

    2013-11-01

    Full Text Available This paper introduces wireless sensor networks for Ambient Assisted Living as a proof of concept. Our workgroup has developed an arrhythmia detection algorithm that we evaluate in a closed space using a wireless sensor network to relay the information collected to where the information can be registered, monitored and analyzed to support medical decisions by healthcare providers. The prototype we developed is then evaluated using the TelosB platform. The proposed architecture considers very specific restrictions regarding the use of wireless sensor networks in clinical situations. The seamless integration of the system architecture enables both mobile node and network configuration, thus providing the versatile and robust characteristics necessary for real-time applications in medical situations. Likewise, this system architecture efficiently permits the different components of our proposed platform to interact efficiently within the parameters of this study.

  9. Social Networks, Engagement and Resilience in University Students

    Directory of Open Access Journals (Sweden)

    Elena Fernández-Martínez

    2017-12-01

    Full Text Available Analysis of social networks may be a useful tool for understanding the relationship between resilience and engagement, and this could be applied to educational methodologies, not only to improve academic performance, but also to create emotionally sustainable networks. This descriptive study was carried out on 134 university students. We collected the network structural variables, degree of resilience (CD-RISC 10, and engagement (UWES-S. The computer programs used were excel, UCINET for network analysis, and SPSS for statistical analysis. The analysis revealed results of means of 28.61 for resilience, 2.98 for absorption, 4.82 for dedication, and 3.13 for vigour. The students had two preferred places for sharing information: the classroom and WhatsApp. The greater the value for engagement, the greater the degree of centrality in the friendship network among students who are beginning their university studies. This relationship becomes reversed as the students move to later academic years. In terms of resilience, the highest values correspond to greater centrality in the friendship networks. The variables of engagement and resilience influenced the university students’ support networks.

  10. Social Networks, Engagement and Resilience in University Students.

    Science.gov (United States)

    Fernández-Martínez, Elena; Andina-Díaz, Elena; Fernández-Peña, Rosario; García-López, Rosa; Fulgueiras-Carril, Iván; Liébana-Presa, Cristina

    2017-12-01

    Analysis of social networks may be a useful tool for understanding the relationship between resilience and engagement, and this could be applied to educational methodologies, not only to improve academic performance, but also to create emotionally sustainable networks. This descriptive study was carried out on 134 university students. We collected the network structural variables, degree of resilience (CD-RISC 10), and engagement (UWES-S). The computer programs used were excel, UCINET for network analysis, and SPSS for statistical analysis. The analysis revealed results of means of 28.61 for resilience, 2.98 for absorption, 4.82 for dedication, and 3.13 for vigour. The students had two preferred places for sharing information: the classroom and WhatsApp. The greater the value for engagement, the greater the degree of centrality in the friendship network among students who are beginning their university studies. This relationship becomes reversed as the students move to later academic years. In terms of resilience, the highest values correspond to greater centrality in the friendship networks. The variables of engagement and resilience influenced the university students' support networks.

  11. Information collection and processing of dam distortion in digital reservoir system

    Science.gov (United States)

    Liang, Yong; Zhang, Chengming; Li, Yanling; Wu, Qiulan; Ge, Pingju

    2007-06-01

    The "digital reservoir" is usually understood as describing the whole reservoir with digital information technology to make it serve the human existence and development furthest. Strictly speaking, the "digital reservoir" is referred to describing vast information of the reservoir in different dimension and space-time by RS, GPS, GIS, telemetry, remote-control and virtual reality technology based on computer, multi-media, large-scale memory and wide-band networks technology for the human existence, development and daily work, life and entertainment. The core of "digital reservoir" is to realize the intelligence and visibility of vast information of the reservoir through computers and networks. The dam is main building of reservoir, whose safety concerns reservoir and people's safety. Safety monitoring is important way guaranteeing the dam's safety, which controls the dam's running through collecting the dam's information concerned and developing trend. Safety monitoring of the dam is the process from collection and processing of initial safety information to forming safety concept in the brain. The paper mainly researches information collection and processing of the dam by digital means.

  12. A Semantics-Based Approach for Business Categorization on Social Networking Sites

    OpenAIRE

    Memon , Atia ,; Zinke , Christian; Meyer , Kyrill

    2017-01-01

    Part 18: Design Science Research in CNs; International audience; As the number and adoption of social networking sites (SNSs) supporting business representation in the form of business pages continues to escalate, more scalable and robust mechanisms for integrating data from different networks in order to serve the special purposes need to be envisaged. An important concern of such SNS data integration is the platform dependencies that different networks impose in collecting, organizing, and ...

  13. The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

    Directory of Open Access Journals (Sweden)

    Valente Thomas W

    2010-06-01

    Full Text Available Abstract Background Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions. Objectives Our specific aims include: To collect social network data among staff in two long-term care (LTC facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports. Methods and design In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports. Discussion This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building

  14. Modular sensor network node

    Science.gov (United States)

    Davis, Jesse Harper Zehring [Berkeley, CA; Stark, Jr., Douglas Paul; Kershaw, Christopher Patrick [Hayward, CA; Kyker, Ronald Dean [Livermore, CA

    2008-06-10

    A distributed wireless sensor network node is disclosed. The wireless sensor network node includes a plurality of sensor modules coupled to a system bus and configured to sense a parameter. The parameter may be an object, an event or any other parameter. The node collects data representative of the parameter. The node also includes a communication module coupled to the system bus and configured to allow the node to communicate with other nodes. The node also includes a processing module coupled to the system bus and adapted to receive the data from the sensor module and operable to analyze the data. The node also includes a power module connected to the system bus and operable to generate a regulated voltage.

  15. Synchronization in oscillatory networks

    CERN Document Server

    Osipov, Grigory V; Zhou, Changsong

    2007-01-01

    The formation of collective behavior in large ensembles or networks of coupled oscillatory elements is one of the oldest and most fundamental aspects of dynamical systems theory. Potential and present applications span a vast spectrum of fields ranging from physics, chemistry, geoscience, through life- and neurosciences to engineering, the economic and the social sciences. This work systematically investigates a large number of oscillatory network configurations that are able to describe many real systems such as electric power grids, lasers or the heart muscle - to name but a few. This book is conceived as an introduction to the field for graduate students in physics and applied mathematics as well as being a compendium for researchers from any field of application interested in quantitative models.

  16. ‘The prehistory of Asian collections in Paris’: Ting Chang, Travel, Collecting, and Museums of Asian Art in Nineteenth-Century Paris, Aldershot: Ashgate 2013

    Directory of Open Access Journals (Sweden)

    Partha Mitter

    2014-12-01

    Full Text Available The work deals with three major collectors of Asian art in Paris in the 19th century. Enrico Cernuschi and Émile Guimet (founder of Musée Guimet acquired their substantial collection through travelling abroad while Edmond Goncourt amassed his collection at home through dealers. As the author argues, the influential postcolonial critiques of museum collections as instruments of power and authority do not take into account labour and social relations, and somatic experiences of travels to Asia. Cross-cultural encounters between Europe and Asia led to subtle inversions of power, undermining European sense of superiority. Additionally, she throws light on extensive networks and complex political, commercial, monetary relations, especially bimetallism, as well as the material conditions that affect art collection.

  17. Why General Outlier Detection Techniques Do Not Suffice For Wireless Sensor Networks?

    NARCIS (Netherlands)

    Zhang, Y.; Meratnia, Nirvana; Havinga, Paul J.M.

    2009-01-01

    Raw data collected in wireless sensor networks are often unreliable and inaccurate due to noise, faulty sensors and harsh environmental effects. Sensor data that significantly deviate from normal pattern of sensed data are often called outliers. Outlier detection in wireless sensor networks aims at

  18. Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

    Directory of Open Access Journals (Sweden)

    Raja Jurdak

    2008-11-01

    Full Text Available Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

  19. Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

    Science.gov (United States)

    Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

    2008-11-24

    Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

  20. How Collecting and Freely Sharing Geophysical Data Broadly Benefits Society

    Science.gov (United States)

    Frassetto, A.; Woodward, R.; Detrick, R. S.

    2017-12-01

    Valuable but often unintended observations of environmental and human-related processes have resulted from open sharing of multidisciplinary geophysical observations collected over the past 33 years. These data, intended to fuel fundamental academic research, are part of the Incorporated Research Institutions for Seismology (IRIS), which is sponsored by the National Science Foundation and has provided a community science facility supporting earthquake science and related disciplines since 1984. These community facilities have included arrays of geophysical instruments operated for EarthScope, an NSF-sponsored science initiative designed to understand the architecture and evolution of the North American continent, as well as the Global Seismographic Network, Greenland Ice Sheet Monitoring Network, a repository of data collected around the world, and other community assets. All data resulting from this facility have been made openly available to support researchers across any field of study and this has expanded the impact of these data beyond disciplinary boundaries. This presentation highlights vivid examples of how basic research activities using open data, collected as part of a community facility, can inform our understanding of manmade earthquakes, geomagnetic hazards, climate change, and illicit testing of nuclear weapons.

  1. Low-Power Wireless Sensor Network Infrastructures

    DEFF Research Database (Denmark)

    Hansen, Morten Tranberg

    Advancements in wireless communication and electronics improving form factor and hardware capabilities has expanded the applicability of wireless sensor networks. Despite these advancements, devices are still limited in terms of energy which creates the need for duty-cycling and low-power protocols...... peripherals need to by duty-cycled and the low-power wireless radios are severely influenced by the environmental effects causing bursty and unreliable wireless channels. This dissertation presents a communication stack providing services for low-power communication, secure communication, data collection......, and network management which enables construction of low-power wireless sensor network applications. More specifically, these services are designed with the extreme low-power scenarios of the SensoByg project in mind and are implemented as follows. First, low-power communication is implemented with Auto...

  2. Activists’ appropriations in social networking websites: the collective action dynamics in #forasarney

    Directory of Open Access Journals (Sweden)

    BATISTA, Jandré Corrêa

    2013-01-01

    Full Text Available This paper aims to study the appropriation of Twitter (twitter.com for activists ends. To this end, we intend to present the analysis of intentionality (Thompson, 2000 of symbolic forms perceived in the appropriations social networking site (Boyd and Elisson, 2006 in case # forasarney. From the Depth Hermeneutics of Thompson (2000, the study interprets five intentions: convocacional, informational, divulgacional, feedback and conversational. The messages were classified by analyzing categorical content analysis of Bardin (2009,interpreted in accordance with its purposes.

  3. PCs and networking for oceanographic research vessels

    Digital Repository Service at National Institute of Oceanography (India)

    Desai, R.G.P.; Desa, E.; Vithayathil, G.

    on IBM PC compatibles. The computers are located in different laboratories and are dedicated to data collection from one or more instruments. They are integratEd. by a local area network for real time sharing and integration of data. The special...

  4. AIDS communications through social networks: catalyst for ...

    African Journals Online (AJOL)

    Objective: To investigate distinctive communications through social networks which may be associated with population behaviour changes and HIV prevalence declines in Uganda compared to other countries. Methods: We undertook a comparative analysis of demographic and HIV behavioural data collected in ...

  5. The Colombia Seismological Network

    Science.gov (United States)

    Blanco Chia, J. F.; Poveda, E.; Pedraza, P.

    2013-05-01

    The latest seismological equipment and data processing instrumentation installed at the Colombia Seismological Network (RSNC) are described. System configuration, network operation, and data management are discussed. The data quality and the new seismological products are analyzed. The main purpose of the network is to monitor local seismicity with a special emphasis on seismic activity surrounding the Colombian Pacific and Caribbean oceans, for early warning in case a Tsunami is produced by an earthquake. The Colombian territory is located at the South America northwestern corner, here three tectonic plates converge: Nazca, Caribbean and the South American. The dynamics of these plates, when resulting in earthquakes, is continuously monitored by the network. In 2012, the RSNC registered in 2012 an average of 67 events per day; from this number, a mean of 36 earthquakes were possible to be located well. In 2010 the network was also able to register an average of 67 events, but it was only possible to locate a mean of 28 earthquakes daily. This difference is due to the expansion of the network. The network is made up of 84 stations equipped with different kind of broadband 40s, 120s seismometers, accelerometers and short period 1s sensors. The signal is transmitted continuously in real-time to the Central Recording Center located at Bogotá, using satellite, telemetry, and Internet. Moreover, there are some other stations which are required to collect the information in situ. Data is recorded and processed digitally using two different systems, EARTHWORM and SEISAN, which are able to process and share the information between them. The RSNC has designed and implemented a web system to share the seismological data. This innovative system uses tools like Java Script, Oracle and programming languages like PHP to allow the users to access the seismicity registered by the network almost in real time as well as to download the waveform and technical details. The coverage

  6. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

    Science.gov (United States)

    Valdivieso Caraguay, Ángel Leonardo; García Villalba, Luis Javier

    2017-01-01

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors. PMID:28362346

  7. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks.

    Science.gov (United States)

    Caraguay, Ángel Leonardo Valdivieso; Villalba, Luis Javier García

    2017-03-31

    This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors.

  8. Quantum metropolitan optical network based on wavelength division multiplexing.

    Science.gov (United States)

    Ciurana, A; Martínez-Mateo, J; Peev, M; Poppe, A; Walenta, N; Zbinden, H; Martín, V

    2014-01-27

    Quantum Key Distribution (QKD) is maturing quickly. However, the current approaches to its application in optical networks make it an expensive technology. QKD networks deployed to date are designed as a collection of point-to-point, dedicated QKD links where non-neighboring nodes communicate using the trusted repeater paradigm. We propose a novel optical network model in which QKD systems share the communication infrastructure by wavelength multiplexing their quantum and classical signals. The routing is done using optical components within a metropolitan area which allows for a dynamically any-to-any communication scheme. Moreover, it resembles a commercial telecom network, takes advantage of existing infrastructure and utilizes commercial components, allowing for an easy, cost-effective and reliable deployment.

  9. Tree resin composition, collection behavior and selective filters shape chemical profiles of tropical bees (Apidae: Meliponini.

    Directory of Open Access Journals (Sweden)

    Sara D Leonhardt

    Full Text Available The diversity of species is striking, but can be far exceeded by the chemical diversity of compounds collected, produced or used by them. Here, we relate the specificity of plant-consumer interactions to chemical diversity applying a comparative network analysis to both levels. Chemical diversity was explored for interactions between tropical stingless bees and plant resins, which bees collect for nest construction and to deter predators and microbes. Resins also function as an environmental source for terpenes that serve as appeasement allomones and protection against predators when accumulated on the bees' body surfaces. To unravel the origin of the bees' complex chemical profiles, we investigated resin collection and the processing of resin-derived terpenes. We therefore analyzed chemical networks of tree resins, foraging networks of resin collecting bees, and their acquired chemical networks. We revealed that 113 terpenes in nests of six bee species and 83 on their body surfaces comprised a subset of the 1,117 compounds found in resins from seven tree species. Sesquiterpenes were the most variable class of terpenes. Albeit widely present in tree resins, they were only found on the body surface of some species, but entirely lacking in others. Moreover, whereas the nest profile of Tetragonula melanocephala contained sesquiterpenes, its surface profile did not. Stingless bees showed a generalized collecting behavior among resin sources, and only a hitherto undescribed species-specific "filtering" of resin-derived terpenes can explain the variation in chemical profiles of nests and body surfaces from different species. The tight relationship between bees and tree resins of a large variety of species elucidates why the bees' surfaces contain a much higher chemodiversity than other hymenopterans.

  10. Measure of Node Similarity in Multilayer Networks

    DEFF Research Database (Denmark)

    Møllgaard, Anders; Zettler, Ingo; Dammeyer, Jesper

    2016-01-01

    university.Our analysis is based on data obtained using smartphones equipped with customdata collection software, complemented by questionnaire-based data. The networkof social contacts is represented as a weighted multilayer network constructedfrom different channels of telecommunication as well as data...... might bepresent in one layer of the multilayer network and simultaneously be absent inthe other layers. For a variable such as gender, our measure reveals atransition from similarity between nodes connected with links of relatively lowweight to dis-similarity for the nodes connected by the strongest...

  11. Network biology concepts in complex disease comorbidities

    DEFF Research Database (Denmark)

    Hu, Jessica Xin; Thomas, Cecilia Engel; Brunak, Søren

    2016-01-01

    collected electronically, disease co-occurrences are starting to be quantitatively characterized. Linking network dynamics to the real-life, non-ideal patient in whom diseases co-occur and interact provides a valuable basis for generating hypotheses on molecular disease mechanisms, and provides knowledge......The co-occurrence of diseases can inform the underlying network biology of shared and multifunctional genes and pathways. In addition, comorbidities help to elucidate the effects of external exposures, such as diet, lifestyle and patient care. With worldwide health transaction data now often being...

  12. Social Network Types and Acute Stroke Preparedness Behavior

    Directory of Open Access Journals (Sweden)

    Bernadette Boden-Albala

    2011-08-01

    Full Text Available Objectives: Presence of informal social networks has been associated with favorable health and behaviors, but whether different types of social networks impact on different health outcomes remains largely unknown. We examined the associations of different social network types (marital dyad, household, friendship, and informal community networks with acute stroke preparedness behavior. We hypothesized that marital dyad best matched the required tasks and is the most effective network type for this behavior. Methods: We collected in-person interview and medical record data for 1,077 adults diagnosed with stroke and transient ischemic attack. We used logistic regression analyses to examine the association of each social network with arrival at the emergency department (ED within 3 h of stroke symptoms. Results: Adjusting for age, race-ethnicity, education, gender, transportation type to ED and vascular diagnosis, being married or living with a partner was significantly associated with early arrival at the ED (odds ratio = 2.0, 95% confidence interval: 1.2–3.1, but no significant univariate or multivariate associations were observed for household, friendship, and community networks. Conclusions: The marital/partnership dyad is the most influential type of social network for stroke preparedness behavior.

  13. Optimal control of epidemic information dissemination over networks.

    Science.gov (United States)

    Chen, Pin-Yu; Cheng, Shin-Ming; Chen, Kwang-Cheng

    2014-12-01

    Information dissemination control is of crucial importance to facilitate reliable and efficient data delivery, especially in networks consisting of time-varying links or heterogeneous links. Since the abstraction of information dissemination much resembles the spread of epidemics, epidemic models are utilized to characterize the collective dynamics of information dissemination over networks. From a systematic point of view, we aim to explore the optimal control policy for information dissemination given that the control capability is a function of its distribution time, which is a more realistic model in many applications. The main contributions of this paper are to provide an analytically tractable model for information dissemination over networks, to solve the optimal control signal distribution time for minimizing the accumulated network cost via dynamic programming, and to establish a parametric plug-in model for information dissemination control. In particular, we evaluate its performance in mobile and generalized social networks as typical examples.

  14. Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

    Science.gov (United States)

    Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

    2015-01-01

    With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

  15. Climate Change Literacy across the Critical Zone Observatory Network

    Science.gov (United States)

    Moore, A.; Derry, L. A.; Zabel, I.; Duggan-Haas, D.; Ross, R. M.

    2017-12-01

    Earth's Critical Zone extends from the top of the tree canopy to the base of the groundwater lens. Thus the Critical Zone is examined as a suite of interconnected systems and study of the CZ is inherently interdisciplinary. Climate change is an important driver of CZ processes. The US Critical Zone Observatory Network comprises nine observatories and a coordinating National Office. Educational programs and materials developed at each CZO and the National Office have been collected, reviewed, and presented on-line at the CZONO (criticalzone.org/national/education-outreach/resources). Because the CZOs are designed to observe and measure a suite of common parameters on varying geological substrates and within different ecological contexts, educational resources reflect the diversity of processes represented across the network. As climate change has a network-wide impact, the fundamental building blocks of climate change literacy are key elements in many activities within the CZONO resource collection. Carbon-cycle and hydrologic cycle processes are well-represented, with emphasis on human interactions with these resources, as well as the impact of extreme events and the changing climate. Current work on the resource collection focuses on connecting individual resources to "Teach Climate Science" project and the Teacher-Friendly Guide to Climate Change (teachclimatescience.wordpress.com). The Teacher-Friendly Guide is a manual for K-12 teachers that presents both the fundamentals of climate science alongside resources for effective teaching of this controversial topic. Using the reach of the CZO network we hope to disseminate effective climate literacy resources and support to the K-12 community.

  16. 75 FR 80825 - Agency Information Collection Activities; Submission for Office of Management and Budget Review...

    Science.gov (United States)

    2010-12-23

    ...] Agency Information Collection Activities; Submission for Office of Management and Budget Review; Comment Request; Pet Event Tracking Network--State, Federal Cooperation To Prevent Spread of Pet Food Related... Administration (FDA) is announcing that a proposed collection of information has been submitted to the Office of...

  17. Cellular telephone-based wide-area radiation detection network

    Science.gov (United States)

    Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  18. Chimeralike states in networks of bistable time-delayed feedback oscillators coupled via the mean field.

    Science.gov (United States)

    Ponomarenko, V I; Kulminskiy, D D; Prokhorov, M D

    2017-08-01

    We study the collective dynamics of oscillators in a network of identical bistable time-delayed feedback systems globally coupled via the mean field. The influence of delay and inertial properties of the mean field on the collective behavior of globally coupled oscillators is investigated. A variety of oscillation regimes in the network results from the presence of bistable states with substantially different frequencies in coupled oscillators. In the physical experiment and numerical simulation we demonstrate the existence of chimeralike states, in which some of the oscillators in the network exhibit synchronous oscillations, while all other oscillators remain asynchronous.

  19. How Much Control is Enough for Network Connectivity Preservation and Collision Avoidance?

    Science.gov (United States)

    Chen, Zhiyong; Fan, Ming-Can; Zhang, Hai-Tao

    2015-08-01

    For a multiagent system in free space, the agents are required to generate sufficiently large cohesive force for network connectivity preservation and sufficiently large repulsive force for collision avoidance. This paper gives an energy function based approach for estimating the control force in a general setting. In particular, the force estimated for network connectivity preservation and collision avoidance is separated from the force for other collective behavior of the agents. Moreover, the estimation approach is applied in three typical collective control scenarios including swarming, flocking, and flocking without velocity measurement.

  20. The STARLINK software collection

    Science.gov (United States)

    Penny, A. J.; Wallace, P. T.; Sherman, J. C.; Terret, D. L.

    1993-12-01

    A demonstration will be given of some recent Starlink software. STARLINK is: a network of computers used by UK astronomers; a collection of programs for the calibration and analysis of astronomical data; a team of people giving hardware, software and administrative support. The Starlink Project has been in operation since 1980 to provide UK astronomers with interactive image processing and data reduction facilities. There are now Starlink computer systems at 25 UK locations, serving about 1500 registered users. The Starlink software collection now has about 25 major packages covering a wide range of astronomical data reduction and analysis techniques, as well as many smaller programs and utilities. At the core of most of the packages is a common `software environment', which provides many of the functions which applications need and offers standardized methods of structuring and accessing data. The software environment simplifies programming and support, and makes it easy to use different packages for different stages of the data reduction. Users see a consistent style, and can mix applications without hitting problems of differing data formats. The Project group coordinates the writing and distribution of this software collection, which is Unix based. Outside the UK, Starlink is used at a large number of places, which range from installations at major UK telescopes, which are Starlink-compatible and managed like Starlink sites, to individuals who run only small parts of the Starlink software collection.