WorldWideScience

Sample records for all-or-none network events

  1. Attention as Inference: Selection Is Probabilistic; Responses Are All-or-None Samples

    Science.gov (United States)

    Vul, Edward; Hanus, Deborah; Kanwisher, Nancy

    2009-01-01

    Theories of probabilistic cognition postulate that internal representations are made up of multiple simultaneously held hypotheses, each with its own probability of being correct (henceforth, "probability distributions"). However, subjects make discrete responses and report the phenomenal contents of their mind to be all-or-none states rather than…

  2. Consciousness isn't all-or-none: Evidence for partial awareness during the attentional blink.

    Science.gov (United States)

    Elliott, James C; Baird, Benjamin; Giesbrecht, Barry

    2016-02-01

    Alternative views of the nature of consciousness posit that awareness of an object is either an all-or-none phenomenon or that awareness can be partial, occurring independently for different levels of representation. The all-or-none hypothesis predicts that when one feature of an object is identified, all other features should be consciously accessible. The partial awareness hypothesis predicts that one feature may reach consciousness while others do not. These competing predictions were tested in two experiments that presented two targets within a central stream of letters. We used the attentional blink evoked by the first target to assess consciousness for two different features of the second target. The results provide evidence that there can be a severe impairment in conscious access to one feature even when another feature is accurately reported. This behavioral evidence supports the partial awareness hypothesis, showing that consciousness of different features of the same object can be dissociated. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Footwear modification following hallux valgus surgery: The all-or-none phenomenon.

    Science.gov (United States)

    Robinson, Cal; Bhosale, Abhijit; Pillai, Anand

    2016-06-26

    To define footwear outcomes following hallux valgus surgery, focusing on patient return to comfortable and heeled footwear and patterns of post-operative footwear selection. Surgical intervention is indicated for symptomatic cases of hallux valgus unresponsive to conservative methods, with favourable reported outcomes. The return to various types of footwear post-operatively is reflective of the degree of correction achieved, and corresponds to patient satisfaction. Patients are expected to return to comfortable footwear post-operatively without significant residual symptoms. Many female patients will additionally attempt to return to high-heeled, narrow toe box shoes. However, minimal evidence exists to guide their expectations. Sixty-five female hallux valgus patients that had undergone primary surgery between 2011 and 2013 were retrospectively identified using our hospital surgical database. Patients were reviewed using a footwear-specific outcome questionnaire at a mean 18.5 mo follow-up. Eighty-six percent of patients were able to return to comfortable footwear post-operatively with minimal discomfort. Of those intending to resume wearing heeled footwear, 62% were able to do so, with 77% of these patients wearing these as or more frequently than pre-operatively. No significant difference was observed between pre- and post-operative heel size. Mean time to return to heeled footwear was 21.4 wk post-operation. Cosmetic outcomes were very high and did not adversely impact footwear selection. We report high rates of return to both comfortable and heeled shoes in female patients following primary hallux valgus surgery. We observed an "all-or-none phenomenon" where patients rejected a return to heeled footwear unless able to tolerate them at the same frequency and heel size as pre-operatively. A minority of patients were unable to return to comfortable footwear post-operatively, which had adverse ramifications on their quality-of-life. We recommend that the

  4. Cardiac action potential repolarization revisited: early repolarization shows all-or-none behaviour.

    Science.gov (United States)

    Trenor, Beatriz; Cardona, Karen; Saiz, Javier; Noble, Denis; Giles, Wayne

    2017-11-01

    In healthy mammalian hearts the action potential (AP) waveform initiates and modulates each contraction, or heartbeat. As a result, AP height and duration are key physiological variables. In addition, rate-dependent changes in ventricular AP duration (APD), and variations in APD at a fixed heart rate are both reliable biomarkers of electrophysiological stability. Present guidelines for the likelihood that candidate drugs will increase arrhythmias rely on small changes in APD and Q-T intervals as criteria for safety pharmacology decisions. However, both of these measurements correspond to the final repolarization of the AP. Emerging clinical evidence draws attention to the early repolarization phase of the action potential (and the J-wave of the ECG) as an additional important biomarker for arrhythmogenesis. Here we provide a mechanistic background to this early repolarization syndrome by summarizing the evidence that both the initial depolarization and repolarization phases of the cardiac action potential can exhibit distinct time- and voltage-dependent thresholds, and also demonstrating that both can show regenerative all-or-none behaviour. An important consequence of this is that not all of the dynamics of action potential repolarization in human ventricle can be captured by data from single myocytes when these results are expressed as 'repolarization reserve'. For example, the complex pattern of cell-to-cell current flow that is responsible for AP conduction (propagation) within the mammalian myocardium can change APD and the Q-T interval of the electrocardiogram alter APD stability, and modulate responsiveness to pharmacological agents (such as Class III anti-arrhythmic drugs). © 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.

  5. Evidence for an All-Or-None Perceptual Response: Single-Trial Analyses of Magnetoencephalography Signals Indicate an Abrupt Transition Between Visual Perception and Its Absence

    Science.gov (United States)

    Sekar, Krithiga; Findley, William M.; Llinás, Rodolfo R.

    2014-01-01

    Whether consciousness is an all-or-none or graded phenomenon is an area of inquiry that has received considerable interest in neuroscience and is as of yet, still debated. In this magnetoencephalography (MEG) study we used a single stimulus paradigm with sub-threshold, threshold and supra-threshold duration inputs to assess whether stimulus perception is continuous with or abruptly differentiated from unconscious stimulus processing in the brain. By grouping epochs according to stimulus identification accuracy and exposure duration, we were able to investigate whether a high-amplitude perception-related cortical event was (1) only evoked for conditions where perception was most probable (2) had invariant amplitude once evoked and (3) was largely absent for conditions where perception was least probable (criteria satisfying an all-on-none hypothesis). We found that averaged evoked responses showed a gradual increase in amplitude with increasing perceptual strength. However, single trial analyses demonstrated that stimulus perception was correlated with an all-or-none response, the temporal precision of which increased systematically as perception transitioned from ambiguous to robust states. Due to poor signal-to-noise resolution of single trial data, whether perception-related responses, whenever present, were invariant in amplitude could not be unambiguously demonstrated. However, our findings strongly suggest that visual perception of simple stimuli is associated with an all-or-none cortical evoked response the temporal precision of which varies as a function of perceptual strength. PMID:22020091

  6. Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

    Science.gov (United States)

    Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

    2018-04-01

    Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

  7. Cortical response tracking the conscious experience of threshold duration visual stimuli indicates visual perception is all or none

    Science.gov (United States)

    Sekar, Krithiga; Findley, William M.; Poeppel, David; Llinás, Rodolfo R.

    2013-01-01

    At perceptual threshold, some stimuli are available for conscious access whereas others are not. Such threshold inputs are useful tools for investigating the events that separate conscious awareness from unconscious stimulus processing. Here, viewing unmasked, threshold-duration images was combined with recording magnetoencephalography to quantify differences among perceptual states, ranging from no awareness to ambiguity to robust perception. A four-choice scale was used to assess awareness: “didn’t see” (no awareness), “couldn’t identify” (awareness without identification), “unsure” (awareness with low certainty identification), and “sure” (awareness with high certainty identification). Stimulus-evoked neuromagnetic signals were grouped according to behavioral response choices. Three main cortical responses were elicited. The earliest response, peaking at ∼100 ms after stimulus presentation, showed no significant correlation with stimulus perception. A late response (∼290 ms) showed moderate correlation with stimulus awareness but could not adequately differentiate conscious access from its absence. By contrast, an intermediate response peaking at ∼240 ms was observed only for trials in which stimuli were consciously detected. That this signal was similar for all conditions in which awareness was reported is consistent with the hypothesis that conscious visual access is relatively sharply demarcated. PMID:23509248

  8. All or none cell responses of Ca2+-dependent K channels elicited by calcium or lead in human red cells can be explained by heterogeneity of agonist distribution

    International Nuclear Information System (INIS)

    Alvarez, J.; Garcia-Sancho, J.; Herreros, B.

    1988-01-01

    We have studied the all or none cell response of Ca2+-dependent K+ channels to added Ca in human red cells depleted of ATP by incubation with iodoacetate and inosine. A procedure was used which allows separation and differential analysis of responding and nonresponding cells. Responding (H for heavy) cells incubated in medium containing 5 mM K lose KCl and water and increase their density to the point of sinking on diethylphthalate (specific gravity = 1.12) on centrifugation. Nonresponding (L for light) cells do not lose KCl at all. There is no intermediate behavior. Increasing the Ca concentration in the medium increases the fraction of cells which become H. No differences in the sensitivity to Ca2+ of the individual K+ channels were detected in inside-out vesicles prepared either from H or from L cells. The Ca content of H cells was higher than that of L cells. Cells depleted of ATP by incubation with iodoacetate and inosine sustain pump-leak Ca fluxes of about 15 mumol/liter cells per hour. ATP seems to be resynthesized in these cells at the expense of cell 2,3-diphosphoglycerate stores at a rate of about 150 mumol/liter cells per hour. Inhibition of 2,3-diphosphoglycerate phosphatase by tetrathionate increased 6-8 times the measured rate of uptake of external 45Ca. This was accompanied by an increase in the fraction of H cells. All or none cell responses of Ca2+-dependent K channels have also been evidenced in intact human red cells on addition of Pb. They have the same characteristics as those in responding and nonresponding cells. The detailed study of the kinetics of Pb-induced shrinkage of red cells suspended in medium containing 5 mM K showed that changes of Pb concentration changed not only the fraction of H cells but also the rate of shrinkage of responding cells. H cells generated by Pb treatment contained significantly more lead than L cells

  9. Nuclear Factor of Activated T Cells Regulates the Expression of Interleukin-4 in Th2 Cells in an All-or-none Fashion*

    Science.gov (United States)

    Köck, Juliana; Kreher, Stephan; Lehmann, Katrin; Riedel, René; Bardua, Markus; Lischke, Timo; Jargosch, Manja; Haftmann, Claudia; Bendfeldt, Hanna; Hatam, Farahnaz; Mashreghi, Mir-Farzin; Baumgrass, Ria; Radbruch, Andreas; Chang, Hyun-Dong

    2014-01-01

    Th2 memory lymphocytes have imprinted their Il4 genes epigenetically for expression in dependence of T cell receptor restimulation. However, in a given restimulation, not all Th cells with a memory for IL-4 expression express IL-4. Here, we show that in reactivated Th2 cells, the transcription factors NFATc2, NF-kB p65, c-Maf, p300, Brg1, STAT6, and GATA-3 assemble at the Il4 promoter in Th2 cells expressing IL-4 but not in Th2 cells not expressing it. NFATc2 is critical for assembly of this transcription factor complex. Because NFATc2 translocation into the nucleus occurs in an all-or-none fashion, dependent on complete dephosphorylation by calcineurin, NFATc2 controls the frequencies of cells reexpressing Il4, translates analog differences in T cell receptor stimulation into a digital decision for Il4 reexpression, and instructs all reexpressing cells to express the same amount of IL-4. This analog-to-digital conversion may be critical for the immune system to respond to low concentrations of antigens. PMID:25037220

  10. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

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

  11. 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.

  12. Autocorrel I: A Neural Network Based Network Event Correlation Approach

    National Research Council Canada - National Science Library

    Japkowicz, Nathalie; Smith, Reuben

    2005-01-01

    .... We use the autoassociator to build prototype software to cluster network alerts generated by a Snort intrusion detection system, and discuss how the results are significant, and how they can be applied to other types of network events.

  13. Importance of individual events in temporal networks

    International Nuclear Information System (INIS)

    Takaguchi, Taro; Masuda, Naoki; Sato, Nobuo; Yano, Kazuo

    2012-01-01

    Records of time-stamped social interactions between pairs of individuals (e.g. face-to-face conversations, e-mail exchanges and phone calls) constitute a so-called temporal network. A remarkable difference between temporal networks and conventional static networks is that time-stamped events rather than links are the unit elements generating the collective behavior of nodes. We propose an importance measure for single interaction events. By generalizing the concept of the advance of events proposed by Kossinets et al (2008 Proc. 14th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining p 435), we propose that an event is central when it carries new information about others to the two nodes involved in the event. We find that the proposed measure properly quantifies the importance of events in connecting nodes along time-ordered paths. Because of strong heterogeneity in the importance of events present in real data, a small fraction of highly important events is necessary and sufficient to sustain the connectivity of temporal networks. Nevertheless, in contrast to the behavior of scale-free networks against link removal, this property mainly results from bursty activity patterns and not heterogeneous degree distributions. (paper)

  14. EVENT, Explosive Transients in Flow Networks

    International Nuclear Information System (INIS)

    Andrae, R.W.; Tang, P.K.; Bolstad, J.W.; Gregory, W.S.

    1985-01-01

    1 - Description of problem or function: A major concern of the chemical, nuclear, and mining industries is the occurrence of an explosion in one part of a facility and subsequent transmission of explosive effects through the ventilation system. An explosive event can cause performance degradation of the ventilation system or even structural failures. A more serious consequence is the release of hazardous materials to the environment if vital protective devices such as air filters, are damaged. EVENT was developed to investigate the effects of explosive transients through fluid-flow networks. Using the principles of fluid mechanics and thermodynamics, governing equations for the conservation of mass, energy, and momentum are formulated. These equations are applied to the complete network subdivided into two general components: nodes and branches. The nodes represent boundaries and internal junctions where the conservation of mass and energy applies. The branches can be ducts, valves, blowers, or filters. Since in EVENT the effect of the explosion, not the characteristics of the explosion itself, is of interest, the transient is simulated in the simplest possible way. A rapid addition of mass and energy to the system at certain locations is used. This representation is adequate for all of the network except the region where the explosion actually occurs. EVENT84 is a modification of EVENT which includes a new explosion chamber model subroutine based on the NOL BLAST program developed at the Naval Ordnance Laboratory, Silver Spring, Maryland. This subroutine calculates the confined explosion near-field parameters and supplies the time functions of energy and mass injection. Solid-phase or TNT-equivalent explosions (which simulate 'point source' explosions in nuclear facilities) as well as explosions in gas-air mixtures can be simulated. The four types of explosions EVENT84 simulates are TNT, hydrogen in air, acetylene in air, and tributyl phosphate (TBP or 'red oil

  15. Evaluation of Graduated vs All-or-None Contingencies on Rate Tasks for Individuals Diagnosed with Autism

    Science.gov (United States)

    Kassardjian, Alyne; Leaf, Jeremy A.; Leaf, Justin B.; Townley-Cochran, Donna; Alcalay, Aditt; Milne, Christine; Dale, Stephanie; Tsuji, Kathleen; Leaf, Ronald; Taubman, Mitchell; McEachin, John

    2016-01-01

    The graduated reinforcement procedure (also known as differential reinforcement) is an often-used procedure in the field of Applied Behavior Analysis to teach new skills and increase pro-social behaviors. In this study, the researchers used a multi-element design to evaluated the graduated reinforcement procedure for six children with a diagnosis…

  16. Dynamical Networks Characterization of Space Weather Events

    Science.gov (United States)

    Orr, L.; Chapman, S. C.; Dods, J.; Gjerloev, J. W.

    2017-12-01

    Space weather can cause disturbances to satellite systems, impacting navigation technology and telecommunications; it can cause power loss and aviation disruption. A central aspect of the earth's magnetospheric response to space weather events are large scale and rapid changes in ionospheric current patterns. Space weather is highly dynamic and there are still many controversies about how the current system evolves in time. The recent SuperMAG initiative, collates ground-based vector magnetic field time series from over 200 magnetometers with 1-minute temporal resolution. In principle this combined dataset is an ideal candidate for quantification using dynamical networks. Network properties and parameters allow us to characterize the time dynamics of the full spatiotemporal pattern of the ionospheric current system. However, applying network methodologies to physical data presents new challenges. We establish whether a given pair of magnetometers are connected in the network by calculating their canonical cross correlation. The magnetometers are connected if their cross correlation exceeds a threshold. In our physical time series this threshold needs to be both station specific, as it varies with (non-linear) individual station sensitivity and location, and able to vary with season, which affects ground conductivity. Additionally, the earth rotates and therefore the ground stations move significantly on the timescales of geomagnetic disturbances. The magnetometers are non-uniformly spatially distributed. We will present new methodology which addresses these problems and in particular achieves dynamic normalization of the physical time series in order to form the network. Correlated disturbances across the magnetometers capture transient currents. Once the dynamical network has been obtained [1][2] from the full magnetometer data set it can be used to directly identify detailed inferred transient ionospheric current patterns and track their dynamics. We will show

  17. Predicting the evolution of social networks with life cycle events

    NARCIS (Netherlands)

    Sharmeen, F.; Arentze, T.A.; Timmermans, H.J.P.

    2015-01-01

    This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social

  18. Event localization in underwater wireless sensor networks using Monitoring Courses

    KAUST Repository

    Debont, Matthew John Robert; Jamshaid, Kamran; Shihada, Basem; Ho, Pin-Han

    2012-01-01

    We propose m-courses (Monitoring Courses), a novel solution to localize events in an underwater wireless sensor network. These networks consists of surface gateways and relay nodes. GPS can localize the position of surface gateways which can

  19. Sleep Scheduling in Critical Event Monitoring with Wireless Sensor Networks

    NARCIS (Netherlands)

    Guo, Peng; Jiang, Tao; Zhang, Qian; Zhang, Kui

    In this paper, we focus on the applications of wireless sensor networks (WSNs) for critical event monitoring, where normally there are only small number of packets need to be transmitted, while when urgent event occurs, the alarm should be broadcast to the entire network as soon as possible. During

  20. Neural networks for event filtering at D/O/

    International Nuclear Information System (INIS)

    Cutts, D.; Hoftun, J.S.; Sornborger, A.; Johnson, C.R.; Zeller, R.T.

    1989-01-01

    Neural networks may provide important tools for pattern recognition in high energy physics. We discuss an initial exploration of these techniques, presenting the result of network simulations of several filter algorithms. The D0 data acquisition system, a MicroVAX farm, will perform critical event selection; we describe a possible implementation of neural network algorithms in this system. 7 refs., 4 figs

  1. Neutral networks for event filtering at D0

    International Nuclear Information System (INIS)

    Cutts, D.; Hoftun, J.S.; Sornborger, A.; Johnson, R.C.; Zeller, R.T.

    1989-01-01

    Neutral networks may provide important tools for pattern recognition in high energy physics. We discuss an initial exploration of these techniques, presenting the result of network simulations of several filter algorithms. The D0 data acquisition system, a MicroVAX farm, will perform critical event selection; we describe a possible implementation of neural network algorithms in this system. (orig.)

  2. Neural network real time event selection for the DIRAC experiment

    CERN Document Server

    Kokkas, P; Tauscher, Ludwig; Vlachos, S

    2001-01-01

    The neural network first level trigger for the DIRAC experiment at CERN is presented. Both the neural network algorithm used and its actual hardware implementation are described. The system uses the fast plastic scintillator information of the DIRAC spectrometer. In 210 ns it selects events with two particles having low relative momentum. Such events are selected with an efficiency of more than 0.94. The corresponding rate reduction for background events is a factor of 2.5. (10 refs).

  3. Understanding Event-based Business Networks

    OpenAIRE

    2008-01-01

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

  4. Event Localization in Underwater Wireless Sensor Networks using Monitoring Courses

    KAUST Repository

    Debont, Matthew

    2011-11-01

    In this thesis we consider different methods to localize events in a multi-hop wireless sensor network operating underwater using acoustic modems. The network consists of surface gateway nodes and relay nodes. Localization of surface gateways can be achieved through GPS, but we cannot rely on this technology for localizing underwater nodes. Surface Gateway nodes can distribute their locations through the network using the incoming signals by the acoustic modems from the relay nodes. Relay nodes are deployed to remain static but due to water currents, floating, and the untethered nature of the nodes, they often suffer from frequent drifting which can result in a deployed network suffering link failures. In this work, we developed a novel concept of an underwater alarming system, which adapts a cyclic graph model. In the event of link failure, a series of alarm packets are broadcasted in the network. These alarms are then captured through a novel concept of underwater Monitoring Courses (M-Courses), which can also be used to assure network connectivity and identify node faults. M-Courses also allow the network to localize events and identify network issues at a local level before forwarding any results upwards to a Surface Gateway nodes. This reduces the amount of communication overhead needed and allowing for distributed management of nodes in a network which may be constantly moving. We show that the proposed algorithms can reduce the number of send operations needed for an event to be localized in a network. We have found that M-Course routing reduces the number of sends required to report an event to a Surface Gateway by up to 80% in some cases when compared to a naive routing implementation. But this is achieved by increasing the time for an event to reach a Surface Gateway. These effects are both due to the buffering effect of M-Course routing, which allows us to efficiently deal with multiple events in an local area and we find that the performance of M

  5. Event localization in underwater wireless sensor networks using Monitoring Courses

    KAUST Repository

    Debont, Matthew John Robert

    2012-08-01

    We propose m-courses (Monitoring Courses), a novel solution to localize events in an underwater wireless sensor network. These networks consists of surface gateways and relay nodes. GPS can localize the position of surface gateways which can then distribute their locations through the network using acoustic modems. Relay nodes are deployed to remain static, but these untethered nodes may drift due to water currents, resulting in disruption of communication links. We develop a novel underwater alarm system using a cyclic graph model. In the event of link failure, a series of alarm packets are broadcast in the network. These alarms are then captured by the underwater m-courses, which can also be used to assure network connectivity and identify node failures. M-courses also allow the network to localize events and identify network issues locally before forwarding results upwards to a Surface Gateway node. This reduces communication overhead and allows for efficient management of nodes in a mobile network. Our results show that m-course routing reduces the number of sends required to report an event to a Surface Gateway by up to 80% when compared to a naïve routing implementation.

  6. A convolutional neural network neutrino event classifier

    International Nuclear Information System (INIS)

    Aurisano, A.; Sousa, A.; Radovic, A.; Vahle, P.; Rocco, D.; Pawloski, G.; Himmel, A.; Niner, E.; Messier, M.D.; Psihas, F.

    2016-01-01

    Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  7. Network Science Research Laboratory (NSRL) Discrete Event Toolkit

    Science.gov (United States)

    2016-01-01

    ARL-TR-7579 ● JAN 2016 US Army Research Laboratory Network Science Research Laboratory (NSRL) Discrete Event Toolkit by...Laboratory (NSRL) Discrete Event Toolkit by Theron Trout and Andrew J Toth Computational and Information Sciences Directorate, ARL...Research Laboratory (NSRL) Discrete Event Toolkit 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Theron Trout

  8. ATLAS, CMS, LHCb and ALICE Career Networking Event 2015

    CERN Multimedia

    Marinov, Andrey; Strom, Derek Axel

    2015-01-01

    A networking event for alumni of the ATLAS, CMS, LHCb and ALICE experiments as well as current ATLAS/CMS/LHCb/ALICE postdocs and graduate students. This event offers an insight into career opportunities outside of academia. Various former members of the ATLAS, CMS, LHCb and ALICE collaborations will give presentations and be part of a panel discussion and elaborate on their experience in companies in a diverse range of fields (industry, finance, IT,...). Details at https://indico.cern.ch/event/440616

  9. A classification of event sequences in the influence network

    Science.gov (United States)

    Walsh, James Lyons; Knuth, Kevin H.

    2017-06-01

    We build on the classification in [1] of event sequences in the influence network as respecting collinearity or not, so as to determine in future work what phenomena arise in each case. Collinearity enables each observer to uniquely associate each particle event of influencing with one of the observer's own events, even in the case of events of influencing the other observer. We further classify events as to whether they are spacetime events that obey in the fine-grained case the coarse-grained conditions of [2], finding that Newton's First and Second Laws of motion are obeyed at spacetime events. A proof of Newton's Third Law under particular circumstances is also presented.

  10. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Directory of Open Access Journals (Sweden)

    Muhannad T. Suleiman

    2012-11-01

    Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  11. Subsurface event detection and classification using Wireless Signal Networks.

    Science.gov (United States)

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-11-05

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  12. On Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Suresh, Mahima Agumbe

    2013-05-01

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures have been proven costly and imprecise, particularly when dealing with large-scale distribution systems. In this article, to the best of our knowledge, for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. We propose the idea of using sensors that move along the edges of the network and detect events (i.e., attacks). To localize the events, sensors detect proximity to beacons, which are devices with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensors and beacons deployed) in a predetermined zone of interest, while ensuring a degree of coverage by sensors and a required accuracy in locating events using beacons. We propose algorithms for solving the aforementioned problem and demonstrate their effectiveness with results obtained from a realistic flow network simulator.

  13. Rare events in networks with internal and external noise

    Science.gov (United States)

    Hindes, J.; Schwartz, I. B.

    2017-12-01

    We study rare events in networks with both internal and external noise, and develop a general formalism for analyzing rare events that combines pair-quenched techniques and large-deviation theory. The probability distribution, shape, and time scale of rare events are considered in detail for extinction in the Susceptible-Infected-Susceptible model as an illustration. We find that when both types of noise are present, there is a crossover region as the network size is increased, where the probability exponent for large deviations no longer increases linearly with the network size. We demonstrate that the form of the crossover depends on whether the endemic state is localized near the epidemic threshold or not.

  14. Exponential Synchronization of Networked Chaotic Delayed Neural Network by a Hybrid Event Trigger Scheme.

    Science.gov (United States)

    Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun; Zhongyang Fei; Chaoxu Guan; Huijun Gao; Fei, Zhongyang; Guan, Chaoxu; Gao, Huijun

    2018-06-01

    This paper is concerned with the exponential synchronization for master-slave chaotic delayed neural network with event trigger control scheme. The model is established on a network control framework, where both external disturbance and network-induced delay are taken into consideration. The desired aim is to synchronize the master and slave systems with limited communication capacity and network bandwidth. In order to save the network resource, we adopt a hybrid event trigger approach, which not only reduces the data package sending out, but also gets rid of the Zeno phenomenon. By using an appropriate Lyapunov functional, a sufficient criterion for the stability is proposed for the error system with extended ( , , )-dissipativity performance index. Moreover, hybrid event trigger scheme and controller are codesigned for network-based delayed neural network to guarantee the exponential synchronization between the master and slave systems. The effectiveness and potential of the proposed results are demonstrated through a numerical example.

  15. Event Coverage Detection and Event Source Determination in Underwater Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Zhangbing Zhou

    2015-12-01

    Full Text Available With the advent of the Internet of Underwater Things, smart things are deployed in the ocean space and establish underwater wireless sensor networks for the monitoring of vast and dynamic underwater environments. When events are found to have possibly occurred, accurate event coverage should be detected, and potential event sources should be determined for the enactment of prompt and proper responses. To address this challenge, a technique that detects event coverage and determines event sources is developed in this article. Specifically, the occurrence of possible events corresponds to a set of neighboring sensor nodes whose sensory data may deviate from a normal sensing range in a collective fashion. An appropriate sensor node is selected as the relay node for gathering and routing sensory data to sink node(s. When sensory data are collected at sink node(s, the event coverage is detected and represented as a weighted graph, where the vertices in this graph correspond to sensor nodes and the weight specified upon the edges reflects the extent of sensory data deviating from a normal sensing range. Event sources are determined, which correspond to the barycenters in this graph. The results of the experiments show that our technique is more energy efficient, especially when the network topology is relatively steady.

  16. Distributed Event Detection in Wireless Sensor Networks for Disaster Management

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Poel, Mannes; Taghikhaki, Zahra; Havinga, Paul J.M.

    2010-01-01

    Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and become one of the enabling technologies for disaster early-warning systems. Event detection functionality of WSNs can be of great help and importance for

  17. Forecasting solar proton event with artificial neural network

    Science.gov (United States)

    Gong, J.; Wang, J.; Xue, B.; Liu, S.; Zou, Z.

    Solar proton event (SPE), relatively rare but popular in solar maximum, can bring hazard situation to spacecraft. As a special event, SPE always accompanies flare, which is also called proton flare. To produce such an eruptive event, large amount energy must be accumulated within the active region. So we can investigate the character of the active region and its evolving trend, together with other such as cm radio emission and soft X-ray background to evaluate the potential of SEP in chosen area. In order to summarize the omen of SPEs in the active regions behind the observed parameters, we employed AI technology. Full connecting neural network was chosen to fulfil this job. After constructing the network, we train it with 13 parameters that was able to exhibit the character of active regions and their evolution trend. More than 80 sets of event parameter were defined to teach the neural network to identify whether an active region was potential of SPE. Then we test this model with a data base consisting SPE and non-SPE cases that was not used to train the neural network. The result showed that 75% of the choice by the model was right.

  18. Characterizing interactions in online social networks during exceptional events

    Science.gov (United States)

    Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

    2015-08-01

    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

  19. Towards Optimal Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Agumbe Suresh, Mahima

    2012-01-03

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil & gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against these infrastructures, have been proven costly and imprecise, especially when dealing with large scale distribution systems. In this paper, to the best of our knowledge for the first time, we investigate how mobile sensor networks can be used for optimal event detection and localization in acyclic flow networks. Sensor nodes move along the edges of the network and detect events (i.e., attacks) and proximity to beacon nodes with known placement in the network. We formulate the problem of minimizing the cost of monitoring infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate their effectiveness with results obtained from a high fidelity simulator.

  20. Mining the key predictors for event outbreaks in social networks

    Science.gov (United States)

    Yi, Chengqi; Bao, Yuanyuan; Xue, Yibo

    2016-04-01

    It will be beneficial to devise a method to predict a so-called event outbreak. Existing works mainly focus on exploring effective methods for improving the accuracy of predictions, while ignoring the underlying causes: What makes event go viral? What factors that significantly influence the prediction of an event outbreak in social networks? In this paper, we proposed a novel definition for an event outbreak, taking into account the structural changes to a network during the propagation of content. In addition, we investigated features that were sensitive to predicting an event outbreak. In order to investigate the universality of these features at different stages of an event, we split the entire lifecycle of an event into 20 equal segments according to the proportion of the propagation time. We extracted 44 features, including features related to content, users, structure, and time, from each segment of the event. Based on these features, we proposed a prediction method using supervised classification algorithms to predict event outbreaks. Experimental results indicate that, as time goes by, our method is highly accurate, with a precision rate ranging from 79% to 97% and a recall rate ranging from 74% to 97%. In addition, after applying a feature-selection algorithm, the top five selected features can considerably improve the accuracy of the prediction. Data-driven experimental results show that the entropy of the eigenvector centrality, the entropy of the PageRank, the standard deviation of the betweenness centrality, the proportion of re-shares without content, and the average path length are the key predictors for an event outbreak. Our findings are especially useful for further exploring the intrinsic characteristics of outbreak prediction.

  1. Networked event-triggered control: an introduction and research trends

    Science.gov (United States)

    Mahmoud, Magdi S.; Sabih, Muhammad

    2014-11-01

    A physical system can be studied as either continuous time or discrete-time system depending upon the control objectives. Discrete-time control systems can be further classified into two categories based on the sampling: (1) time-triggered control systems and (2) event-triggered control systems. Time-triggered systems sample states and calculate controls at every sampling instant in a periodic fashion, even in cases when states and calculated control do not change much. This indicates unnecessary and useless data transmission and computation efforts of a time-triggered system, thus inefficiency. For networked systems, the transmission of measurement and control signals, thus, cause unnecessary network traffic. Event-triggered systems, on the other hand, have potential to reduce the communication burden in addition to reducing the computation of control signals. This paper provides an up-to-date survey on the event-triggered methods for control systems and highlights the potential research directions.

  2. Automatic Seismic-Event Classification with Convolutional Neural Networks.

    Science.gov (United States)

    Bueno Rodriguez, A.; Titos Luzón, M.; Garcia Martinez, L.; Benitez, C.; Ibáñez, J. M.

    2017-12-01

    Active volcanoes exhibit a wide range of seismic signals, providing vast amounts of unlabelled volcano-seismic data that can be analyzed through the lens of artificial intelligence. However, obtaining high-quality labelled data is time-consuming and expensive. Deep neural networks can process data in their raw form, compute high-level features and provide a better representation of the input data distribution. These systems can be deployed to classify seismic data at scale, enhance current early-warning systems and build extensive seismic catalogs. In this research, we aim to classify spectrograms from seven different seismic events registered at "Volcán de Fuego" (Colima, Mexico), during four eruptive periods. Our approach is based on convolutional neural networks (CNNs), a sub-type of deep neural networks that can exploit grid structure from the data. Volcano-seismic signals can be mapped into a grid-like structure using the spectrogram: a representation of the temporal evolution in terms of time and frequency. Spectrograms were computed from the data using Hamming windows with 4 seconds length, 2.5 seconds overlapping and 128 points FFT resolution. Results are compared to deep neural networks, random forest and SVMs. Experiments show that CNNs can exploit temporal and frequency information, attaining a classification accuracy of 93%, similar to deep networks 91% but outperforming SVM and random forest. These results empirically show that CNNs are powerful models to classify a wide range of volcano-seismic signals, and achieve good generalization. Furthermore, volcano-seismic spectrograms contains useful discriminative information for the CNN, as higher layers of the network combine high-level features computed for each frequency band, helping to detect simultaneous events in time. Being at the intersection of deep learning and geophysics, this research enables future studies of how CNNs can be used in volcano monitoring to accurately determine the detection and

  3. Event management for large scale event-driven digital hardware spiking neural networks.

    Science.gov (United States)

    Caron, Louis-Charles; D'Haene, Michiel; Mailhot, Frédéric; Schrauwen, Benjamin; Rouat, Jean

    2013-09-01

    The interest in brain-like computation has led to the design of a plethora of innovative neuromorphic systems. Individually, spiking neural networks (SNNs), event-driven simulation and digital hardware neuromorphic systems get a lot of attention. Despite the popularity of event-driven SNNs in software, very few digital hardware architectures are found. This is because existing hardware solutions for event management scale badly with the number of events. This paper introduces the structured heap queue, a pipelined digital hardware data structure, and demonstrates its suitability for event management. The structured heap queue scales gracefully with the number of events, allowing the efficient implementation of large scale digital hardware event-driven SNNs. The scaling is linear for memory, logarithmic for logic resources and constant for processing time. The use of the structured heap queue is demonstrated on a field-programmable gate array (FPGA) with an image segmentation experiment and a SNN of 65,536 neurons and 513,184 synapses. Events can be processed at the rate of 1 every 7 clock cycles and a 406×158 pixel image is segmented in 200 ms. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Event-Based Stabilization over Networks with Transmission Delays

    Directory of Open Access Journals (Sweden)

    Xiangyu Meng

    2012-01-01

    Full Text Available This paper investigates asymptotic stabilization for linear systems over networks based on event-driven communication. A new communication logic is proposed to reduce the feedback effort, which has some advantages over traditional ones with continuous feedback. Considering the effect of time-varying transmission delays, the criteria for the design of both the feedback gain and the event-triggering mechanism are derived to guarantee the stability and performance requirements. Finally, the proposed techniques are illustrated by an inverted pendulum system and a numerical example.

  5. Event-triggered output feedback control for distributed networked systems.

    Science.gov (United States)

    Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

    2016-01-01

    This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Korea Microlensing Telescope Network Microlensing Events from 2015: Event-finding Algorithm, Vetting, and Photometry

    Science.gov (United States)

    Kim, D.-J.; Kim, H.-W.; Hwang, K.-H.; Albrow, M. D.; Chung, S.-J.; Gould, A.; Han, C.; Jung, Y. K.; Ryu, Y.-H.; Shin, I.-G.; Yee, J. C.; Zhu, W.; Cha, S.-M.; Kim, S.-L.; Lee, C.-U.; Lee, D.-J.; Lee, Y.; Park, B.-G.; Pogge, R. W.; The KMTNet Collaboration

    2018-02-01

    We present microlensing events in the 2015 Korea Microlensing Telescope Network (KMTNet) data and our procedure for identifying these events. In particular, candidates were detected with a novel “completed-event” microlensing event-finder algorithm. The algorithm works by making linear fits to a ({t}0,{t}{eff},{u}0) grid of point-lens microlensing models. This approach is rendered computationally efficient by restricting u 0 to just two values (0 and 1), which we show is quite adequate. The implementation presented here is specifically tailored to the commission-year character of the 2015 data, but the algorithm is quite general and has already been applied to a completely different (non-KMTNet) data set. We outline expected improvements for 2016 and future KMTNet data. The light curves of the 660 “clear microlensing” and 182 “possible microlensing” events that were found in 2015 are presented along with our policy for their public release.

  7. Information spread of emergency events: path searching on social networks.

    Science.gov (United States)

    Dai, Weihui; Hu, Hongzhi; Wu, Tunan; Dai, Yonghui

    2014-01-01

    Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

  8. Information Spread of Emergency Events: Path Searching on Social Networks

    Directory of Open Access Journals (Sweden)

    Weihui Dai

    2014-01-01

    Full Text Available Emergency has attracted global attentions of government and the public, and it will easily trigger a series of serious social problems if it is not supervised effectively in the dissemination process. In the Internet world, people communicate with each other and form various virtual communities based on social networks, which lead to a complex and fast information spread pattern of emergency events. This paper collects Internet data based on data acquisition and topic detection technology, analyzes the process of information spread on social networks, describes the diffusions and impacts of that information from the perspective of random graph, and finally seeks the key paths through an improved IBF algorithm. Application cases have shown that this algorithm can search the shortest spread paths efficiently, which may help us to guide and control the information dissemination of emergency events on early warning.

  9. Parallel discrete-event simulation of FCFS stochastic queueing networks

    Science.gov (United States)

    Nicol, David M.

    1988-01-01

    Physical systems are inherently parallel. Intuition suggests that simulations of these systems may be amenable to parallel execution. The parallel execution of a discrete-event simulation requires careful synchronization of processes in order to ensure the execution's correctness; this synchronization can degrade performance. Largely negative results were recently reported in a study which used a well-known synchronization method on queueing network simulations. Discussed here is a synchronization method (appointments), which has proven itself to be effective on simulations of FCFS queueing networks. The key concept behind appointments is the provision of lookahead. Lookahead is a prediction on a processor's future behavior, based on an analysis of the processor's simulation state. It is shown how lookahead can be computed for FCFS queueing network simulations, give performance data that demonstrates the method's effectiveness under moderate to heavy loads, and discuss performance tradeoffs between the quality of lookahead, and the cost of computing lookahead.

  10. Event-based cluster synchronization of coupled genetic regulatory networks

    Science.gov (United States)

    Yue, Dandan; Guan, Zhi-Hong; Li, Tao; Liao, Rui-Quan; Liu, Feng; Lai, Qiang

    2017-09-01

    In this paper, the cluster synchronization of coupled genetic regulatory networks with a directed topology is studied by using the event-based strategy and pinning control. An event-triggered condition with a threshold consisting of the neighbors' discrete states at their own event time instants and a state-independent exponential decay function is proposed. The intra-cluster states information and extra-cluster states information are involved in the threshold in different ways. By using the Lyapunov function approach and the theories of matrices and inequalities, we establish the cluster synchronization criterion. It is shown that both the avoidance of continuous transmission of information and the exclusion of the Zeno behavior are ensured under the presented triggering condition. Explicit conditions on the parameters in the threshold are obtained for synchronization. The stability criterion of a single GRN is also given under the reduced triggering condition. Numerical examples are provided to validate the theoretical results.

  11. A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

    Science.gov (United States)

    Li, Haohan; Mao, Yunxiang; Yin, Zhaozheng; Xu, Yingke

    2017-09-01

    Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neural Network (HCNN) method to automatically identify vesicle fusion events in time-lapse Total Internal Reflection Fluorescence Microscopy (TIRFM) image sequences. Firstly, a detection and tracking method is developed to extract image patch sequences containing potential fusion events. Then, a Gaussian Mixture Model (GMM) is applied on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. By utilizing the high-level time-series intensity change features introduced by GMM and the visual appearance features embedded in some key moments of the fusion process, the proposed HCNN architecture is able to classify each candidate patch sequence into three classes: full fusion event, partial fusion event and non-fusion event. Finally, we validate the performance of our method on 9 challenging datasets that have been annotated by cell biologists, and our method achieves better performances when comparing with three previous methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Adult mouse motor units develop almost all of their force in the subprimary range: a new all-or-none strategy for force recruitment?

    Science.gov (United States)

    Manuel, Marin; Heckman, C J

    2011-10-19

    Classical studies of the mammalian neuromuscular system have shown an impressive adaptation match between the intrinsic properties of motoneurons and the contractile properties of their motor units. In these studies, the rate at which motoneurons start to fire repetitively corresponds to the rate at which individual twitches start to sum, and the firing rate increases linearly with the amount of excitation ("primary range") up to the point where the motor unit develops its maximal force. This allows for the gradation of the force produced by a motor unit by rate modulation. In adult mouse motoneurons, however, we recently described a regime of firing ("subprimary range") that appears at lower excitation than what is required for the primary range, a finding that might challenge the classical conception. To investigate the force production of mouse motor units, we simultaneously recorded, for the first time, the motoneuron discharge elicited by intracellular ramps of current and the force developed by its motor unit. We showed that the motor unit developed nearly its maximal force during the subprimary range. This was found to be the case regardless of the input resistance of the motoneuron, the contraction speed, or the tetanic force of the motor unit. Our work suggests that force modulation in small mammals mainly relies on the number of motor units that are recruited rather than on rate modulation of individual motor units.

  13. Event-triggered cooperative target tracking in wireless sensor networks

    Directory of Open Access Journals (Sweden)

    Lu Kelin

    2016-10-01

    Full Text Available Since the issues of low communication bandwidth supply and limited battery capacity are very crucial for wireless sensor networks, this paper focuses on the problem of event-triggered cooperative target tracking based on set-membership information filtering. We study some fundamental properties of the set-membership information filter with multiple sensor measurements. First, a sufficient condition is derived for the set-membership information filter, under which the boundedness of the outer ellipsoidal approximation set of the estimation means is guaranteed. Second, the equivalence property between the parallel and sequential versions of the set-membership information filter is presented. Finally, the results are applied to a 1D event-triggered target tracking scenario in which the negative information is exploited in the sense that the measurements that do not satisfy the triggering conditions are modelled as set-membership measurements. The tracking performance of the proposed method is validated with extensive Monte Carlo simulations.

  14. Event-Triggered Fault Detection of Nonlinear Networked Systems.

    Science.gov (United States)

    Li, Hongyi; Chen, Ziran; Wu, Ligang; Lam, Hak-Keung; Du, Haiping

    2017-04-01

    This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.

  15. Event-triggered Decision Propagation in Proximity Networks

    Directory of Open Access Journals (Sweden)

    Soumik eSarkar

    2014-12-01

    Full Text Available This paper proposes a novel event-triggered formulation as an extension of the recently develo-ped generalized gossip algorithm for decision/awareness propagation in mobile sensor networksmodeled as proximity networks. The key idea is to expend energy for communication (messagetransmission and reception only when there is any event of interest in the region of surveillance.The idea is implemented by using an agent’s belief about presence of a hotspot as feedback tochange its probability of (communication activity. In the original formulation, the evolution ofnetwork topology and the dynamics of decision propagation were completely decoupled whichis no longer the case as a consequence of this feedback policy. Analytical results and numeri-cal experiments are presented to show a significant gain in energy savings with no change inthe first moment characteristics of decision propagation. However, numerical experiments showthat the second moment characteristics may change and theoretical results are provided forupper and lower bounds for second moment characteristics. Effects of false alarms on networkformation and communication activity are also investigated.

  16. Management of a Complex Open Channel Network During Flood Events

    Science.gov (United States)

    Franchini, M.; Valiani, A.; Schippa, L.; Mascellani, G.

    2003-04-01

    Most part of the area around Ferrara (Italy) is below the mean sea level and an extensive drainage system combined with several pump stations allows the use of this area for both urban development and industrial and agricultural activities. The three main channels of this hydraulic system constitute the Ferrara Inland Waterway (total length approximately 70 km), which connects the Po river near Ferrara to the sea. Because of the level difference between the upstream and dowstream ends of the waterway, three locks are located along it, each of them combined with a set of gates to control the water levels. During rainfall events, most of the water of the basin flows into the waterway and heavy precipitations sometimes cause flooding in several areas. This is due to the insufficiency of the channel network dimensions and an inadequate manual operation of the gates. This study presents a hydrological-hydraulic model for the entire Ferrara basin and a system of rules in order to operate the gates. In particular, their opening is designed to be regulated in real time by monitoring the water level in several sections along the channels. Besides flood peak attenuation, this operation strategy contributes also to the maintenance of a constant water level for irrigation and fluvial navigation during the dry periods. With reference to the flood event of May 1996, it is shown that this floodgate operation policy, unlike that which was actually adopted during that event, would lead to a significant flood peak attenuation, avoiding flooding in the area upstream of Ferrara.

  17. Event building in an intelligent network interface card for the LHCb readout network

    CERN Document Server

    Dufey, J P; Neufeld, N; Zuin, M

    2001-01-01

    LHCb is an experiment being constructed at CERN's LHC accelerator for the purpose of studying precisely the CP violation parameters in the B-B system. Triggering poses special problems since the interesting events containing B-mesons are immersed in a large background of inelastic p-p reactions. Therefore, a 4 Level Triggering scheme (Level 0 to Level 3) has been implemented. Powerful embedded processors, used in modern intelligent Network Interface Cards (smart NICs), make it attractive to use them to handle the event building protocol in the high-speed data acquisition system of the LHCb experiment. The implementation of an event building algorithm developed for a specific Gigabit Ethernet NIC is presented and performance data are discussed. 5 Refs.

  18. Multi-modular neural networks for the classification of e+e- hadronic events

    International Nuclear Information System (INIS)

    Proriol, J.

    1994-01-01

    Some multi-modular neural network methods of classifying e + e - hadronic events are presented. We compare the performances of the following neural networks: MLP (multilayer perceptron), MLP and LVQ (learning vector quantization) trained sequentially, and MLP and RBF (radial basis function) trained sequentially. We introduce a MLP-RBF cooperative neural network. Our last study is a multi-MLP neural network. (orig.)

  19. Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.

    Science.gov (United States)

    Rueckauer, Bodo; Lungu, Iulia-Alexandra; Hu, Yuhuang; Pfeiffer, Michael; Liu, Shih-Chii

    2017-01-01

    Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs) can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.

  20. Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification

    Directory of Open Access Journals (Sweden)

    Bodo Rueckauer

    2017-12-01

    Full Text Available Spiking neural networks (SNNs can potentially offer an efficient way of doing inference because the neurons in the networks are sparsely activated and computations are event-driven. Previous work showed that simple continuous-valued deep Convolutional Neural Networks (CNNs can be converted into accurate spiking equivalents. These networks did not include certain common operations such as max-pooling, softmax, batch-normalization and Inception-modules. This paper presents spiking equivalents of these operations therefore allowing conversion of nearly arbitrary CNN architectures. We show conversion of popular CNN architectures, including VGG-16 and Inception-v3, into SNNs that produce the best results reported to date on MNIST, CIFAR-10 and the challenging ImageNet dataset. SNNs can trade off classification error rate against the number of available operations whereas deep continuous-valued neural networks require a fixed number of operations to achieve their classification error rate. From the examples of LeNet for MNIST and BinaryNet for CIFAR-10, we show that with an increase in error rate of a few percentage points, the SNNs can achieve more than 2x reductions in operations compared to the original CNNs. This highlights the potential of SNNs in particular when deployed on power-efficient neuromorphic spiking neuron chips, for use in embedded applications.

  1. Sensor Fusion-based Event Detection in Wireless Sensor Networks

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Havinga, Paul J.M.

    2009-01-01

    Recently, Wireless Sensor Networks (WSN) community has witnessed an application focus shift. Although, monitoring was the initial application of wireless sensor networks, in-network data processing and (near) real-time actuation capability have made wireless sensor networks suitable candidate for

  2. Distributed Topological Convex Hull Estimation of Event Region in Wireless Sensor Networks without Location Information

    NARCIS (Netherlands)

    Guo, Peng; Cao, Jiannong; Zhang, Kui

    2015-01-01

    In critical event (e.g., fire or gas) monitoring applications of wireless sensor networks (WSNs), convex hull of the event region is an efficient tool in handling the usual tasks like event report, routes reconstruction and human motion planning. Existing works on estimating convex hull of event

  3. Conditions for extinction events in chemical reaction networks with discrete state spaces.

    Science.gov (United States)

    Johnston, Matthew D; Anderson, David F; Craciun, Gheorghe; Brijder, Robert

    2018-05-01

    We study chemical reaction networks with discrete state spaces and present sufficient conditions on the structure of the network that guarantee the system exhibits an extinction event. The conditions we derive involve creating a modified chemical reaction network called a domination-expanded reaction network and then checking properties of this network. Unlike previous results, our analysis allows algorithmic implementation via systems of equalities and inequalities and suggests sequences of reactions which may lead to extinction events. We apply the results to several networks including an EnvZ-OmpR signaling pathway in Escherichia coli.

  4. Artificial intelligence based event detection in wireless sensor networks

    NARCIS (Netherlands)

    Bahrepour, M.

    2013-01-01

    Wireless sensor networks (WSNs) are composed of large number of small, inexpensive devices, called sensor nodes, which are equipped with sensing, processing, and communication capabilities. While traditional applications of wireless sensor networks focused on periodic monitoring, the focus of more

  5. Event-based simulation of networks with pulse delayed coupling

    Science.gov (United States)

    Klinshov, Vladimir; Nekorkin, Vladimir

    2017-10-01

    Pulse-mediated interactions are common in networks of different nature. Here we develop a general framework for simulation of networks with pulse delayed coupling. We introduce the discrete map governing the dynamics of such networks and describe the computation algorithm for its numerical simulation.

  6. Multitask Learning-Based Security Event Forecast Methods for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Hui He

    2016-01-01

    Full Text Available Wireless sensor networks have strong dynamics and uncertainty, including network topological changes, node disappearance or addition, and facing various threats. First, to strengthen the detection adaptability of wireless sensor networks to various security attacks, a region similarity multitask-based security event forecast method for wireless sensor networks is proposed. This method performs topology partitioning on a large-scale sensor network and calculates the similarity degree among regional subnetworks. The trend of unknown network security events can be predicted through multitask learning of the occurrence and transmission characteristics of known network security events. Second, in case of lacking regional data, the quantitative trend of unknown regional network security events can be calculated. This study introduces a sensor network security event forecast method named Prediction Network Security Incomplete Unmarked Data (PNSIUD method to forecast missing attack data in the target region according to the known partial data in similar regions. Experimental results indicate that for an unknown security event forecast the forecast accuracy and effects of the similarity forecast algorithm are better than those of single-task learning method. At the same time, the forecast accuracy of the PNSIUD method is better than that of the traditional support vector machine method.

  7. Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control.

    Science.gov (United States)

    Wen, Shiping; Zeng, Zhigang; Chen, Michael Z Q; Huang, Tingwen

    2017-10-01

    This paper addresses the issue of synchronization of switched delayed neural networks with communication delays via event-triggered control. For synchronizing coupled switched neural networks, we propose a novel event-triggered control law which could greatly reduce the number of control updates for synchronization tasks of coupled switched neural networks involving embedded microprocessors with limited on-board resources. The control signals are driven by properly defined events, which depend on the measurement errors and current-sampled states. By using a delay system method, a novel model of synchronization error system with delays is proposed with the communication delays and event-triggered control in the unified framework for coupled switched neural networks. The criteria are derived for the event-triggered synchronization analysis and control synthesis of switched neural networks via the Lyapunov-Krasovskii functional method and free weighting matrix approach. A numerical example is elaborated on to illustrate the effectiveness of the derived results.

  8. Marketing Career Speed Networking: A Classroom Event to Foster Career Awareness

    Science.gov (United States)

    Buff, Cheryl L.; O'Connor, Suzanne

    2012-01-01

    This paper describes the design, implementation, and evaluation of a marketing career speed networking event held during class time in two sections of the consumer behavior class. The event was coordinated through a partnering effort with marketing faculty and the college's Career Center. A total of 57 students participated in the event, providing…

  9. Contribution of past and future self-defining event networks to personal identity.

    Science.gov (United States)

    Demblon, Julie; D'Argembeau, Arnaud

    2017-05-01

    Personal identity is nourished by memories of significant past experiences and by the imagination of meaningful events that one anticipates to happen in the future. The organisation of such self-defining memories and prospective thoughts in the cognitive system has received little empirical attention, however. In the present study, our aims were to investigate to what extent self-defining memories and future projections are organised in networks of related events, and to determine the nature of the connections linking these events. Our results reveal the existence of self-defining event networks, composed of both memories and future events of similar centrality for identity and characterised by similar identity motives. These self-defining networks expressed a strong internal coherence and frequently organised events in meaningful themes and sequences (i.e., event clusters). Finally, we found that the satisfaction of identity motives in represented events and the presence of clustering across events both contributed to increase in the perceived centrality of events for the sense of identity. Overall, these findings suggest that personal identity is not only nourished by representations of significant past and future events, but also depends on the formation of coherent networks of related events that provide an overarching meaning to specific life experiences.

  10. Tagging b quark events in ALEPH with neural networks

    International Nuclear Information System (INIS)

    Proriol, J.; Jousset, J.; Guicheney, C.; Falvard, A.; Henrard, P.; Pallin, D.; Perret, P.; Brandl, B.

    1991-01-01

    Comparison of different methods to tag b quark events are presented: multilayered perceptron (MLP), Learning Vector Quantization (LVQ), discriminant analysis, combination of any two of the above methods. The sample events come from the ALEPH Monte Carlo and data, from the 1990 ALEPH runs. (authors) 12 refs., 16 figs., 5 tabs

  11. On Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Suresh, Mahima Agumbe; Stoleru, Radu; Zechman, Emily M.; Shihada, Basem

    2013-01-01

    Acyclic flow networks, present in many infrastructures of national importance (e.g., oil and gas and water distribution systems), have been attracting immense research interest. Existing solutions for detecting and locating attacks against

  12. Epidemiologic Considerations in Network Modeling of Theoretical Disease Events

    National Research Council Canada - National Science Library

    Lem, Marcus

    2006-01-01

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

  13. Detecting impacts of extreme events with ecological in situ monitoring networks

    Directory of Open Access Journals (Sweden)

    M. D. Mahecha

    2017-09-01

    Full Text Available Extreme hydrometeorological conditions typically impact ecophysiological processes on land. Satellite-based observations of the terrestrial biosphere provide an important reference for detecting and describing the spatiotemporal development of such events. However, in-depth investigations of ecological processes during extreme events require additional in situ observations. The question is whether the density of existing ecological in situ networks is sufficient for analysing the impact of extreme events, and what are expected event detection rates of ecological in situ networks of a given size. To assess these issues, we build a baseline of extreme reductions in the fraction of absorbed photosynthetically active radiation (FAPAR, identified by a new event detection method tailored to identify extremes of regional relevance. We then investigate the event detection success rates of hypothetical networks of varying sizes. Our results show that large extremes can be reliably detected with relatively small networks, but also reveal a linear decay of detection probabilities towards smaller extreme events in log–log space. For instance, networks with  ≈  100 randomly placed sites in Europe yield a  ≥  90 % chance of detecting the eight largest (typically very large extreme events; but only a  ≥  50 % chance of capturing the 39 largest events. These findings are consistent with probability-theoretic considerations, but the slopes of the decay rates deviate due to temporal autocorrelation and the exact implementation of the extreme event detection algorithm. Using the examples of AmeriFlux and NEON, we then investigate to what degree ecological in situ networks can capture extreme events of a given size. Consistent with our theoretical considerations, we find that today's systematically designed networks (i.e. NEON reliably detect the largest extremes, but that the extreme event detection rates are not higher than would

  14. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments

    International Nuclear Information System (INIS)

    Calvet, D.

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers (∼1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  15. Towards Optimal Event Detection and Localization in Acyclic Flow Networks

    KAUST Repository

    Agumbe Suresh, Mahima; Stoleru, Radu; Denton, Ron; Zechman, Emily; Shihada, Basem

    2012-01-01

    infrastructure (i.e., minimizing the number of sensor and beacon nodes deployed), while ensuring a degree of sensing coverage in a zone of interest and a required accuracy in locating events. We propose algorithms for solving these problems and demonstrate

  16. Cough event classification by pretrained deep neural network.

    Science.gov (United States)

    Liu, Jia-Ming; You, Mingyu; Wang, Zheng; Li, Guo-Zheng; Xu, Xianghuai; Qiu, Zhongmin

    2015-01-01

    Cough is an essential symptom in respiratory diseases. In the measurement of cough severity, an accurate and objective cough monitor is expected by respiratory disease society. This paper aims to introduce a better performed algorithm, pretrained deep neural network (DNN), to the cough classification problem, which is a key step in the cough monitor. The deep neural network models are built from two steps, pretrain and fine-tuning, followed by a Hidden Markov Model (HMM) decoder to capture tamporal information of the audio signals. By unsupervised pretraining a deep belief network, a good initialization for a deep neural network is learned. Then the fine-tuning step is a back propogation tuning the neural network so that it can predict the observation probability associated with each HMM states, where the HMM states are originally achieved by force-alignment with a Gaussian Mixture Model Hidden Markov Model (GMM-HMM) on the training samples. Three cough HMMs and one noncough HMM are employed to model coughs and noncoughs respectively. The final decision is made based on viterbi decoding algorihtm that generates the most likely HMM sequence for each sample. A sample is labeled as cough if a cough HMM is found in the sequence. The experiments were conducted on a dataset that was collected from 22 patients with respiratory diseases. Patient dependent (PD) and patient independent (PI) experimental settings were used to evaluate the models. Five criteria, sensitivity, specificity, F1, macro average and micro average are shown to depict different aspects of the models. From overall evaluation criteria, the DNN based methods are superior to traditional GMM-HMM based method on F1 and micro average with maximal 14% and 11% error reduction in PD and 7% and 10% in PI, meanwhile keep similar performances on macro average. They also surpass GMM-HMM model on specificity with maximal 14% error reduction on both PD and PI. In this paper, we tried pretrained deep neural network in

  17. A robust neural network-based approach for microseismic event detection

    KAUST Repository

    Akram, Jubran; Ovcharenko, Oleg; Peter, Daniel

    2017-01-01

    We present an artificial neural network based approach for robust event detection from low S/N waveforms. We use a feed-forward network with a single hidden layer that is tuned on a training dataset and later applied on the entire example dataset

  18. A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation

    OpenAIRE

    Dongmei Huang; Chenyixuan Xu; Danfeng Zhao; Wei Song; Qi He

    2017-01-01

    Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertice...

  19. A model of spreading of sudden events on social networks

    Science.gov (United States)

    Wu, Jiao; Zheng, Muhua; Zhang, Zi-Ke; Wang, Wei; Gu, Changgui; Liu, Zonghua

    2018-03-01

    Information spreading has been studied for decades, but its underlying mechanism is still under debate, especially for those ones spreading extremely fast through the Internet. By focusing on the information spreading data of six typical events on Sina Weibo, we surprisingly find that the spreading of modern information shows some new features, i.e., either extremely fast or slow, depending on the individual events. To understand its mechanism, we present a susceptible-accepted-recovered model with both information sensitivity and social reinforcement. Numerical simulations show that the model can reproduce the main spreading patterns of the six typical events. By this model, we further reveal that the spreading can be speeded up by increasing either the strength of information sensitivity or social reinforcement. Depending on the transmission probability and information sensitivity, the final accepted size can change from continuous to discontinuous transition when the strength of the social reinforcement is large. Moreover, an edge-based compartmental theory is presented to explain the numerical results. These findings may be of significance on the control of information spreading in modern society.

  20. Collaborative Event-Driven Coverage and Rate Allocation for Event Miss-Ratio Assurances in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ozgur Sanli H

    2010-01-01

    Full Text Available Wireless sensor networks are often required to provide event miss-ratio assurance for a given event type. To meet such assurances along with minimum energy consumption, this paper shows how a node's activation and rate assignment is dependent on its distance to event sources, and proposes a practical coverage and rate allocation (CORA protocol to exploit this dependency in realistic environments. Both uniform event distribution and nonuniform event distribution are considered and the notion of ideal correlation distance around a clusterhead is introduced for on-duty node selection. In correlation distance guided CORA, rate assignment assists coverage scheduling by determining which nodes should be activated for minimizing data redundancy in transmission. Coverage scheduling assists rate assignment by controlling the amount of overlap among sensing regions of neighboring nodes, thereby providing sufficient data correlation for rate assignment. Extensive simulation results show that CORA meets the required event miss-ratios in realistic environments. CORA's joint coverage scheduling and rate allocation reduce the total energy expenditure by 85%, average battery energy consumption by 25%, and the overhead of source coding up to 90% as compared to existing rate allocation techniques.

  1. Recognition of power quality events by using multiwavelet-based neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kaewarsa, Suriya; Attakitmongcol, Kitti; Kulworawanichpong, Thanatchai [School of Electrical Engineering, Suranaree University of Technology, 111 University Avenue, Muang District, Nakhon Ratchasima 30000 (Thailand)

    2008-05-15

    Recognition of power quality events by analyzing the voltage and current waveform disturbances is a very important task for the power system monitoring. This paper presents a novel approach for the recognition of power quality disturbances using multiwavelet transform and neural networks. The proposed method employs the multiwavelet transform using multiresolution signal decomposition techniques working together with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, such as voltage sag, swell, interruption, notching, impulsive transient, and harmonic distortion show that the classifier can detect and classify different power quality signal types efficiency. (author)

  2. Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

    Science.gov (United States)

    Oliker, Nurit; Ostfeld, Avi

    2015-09-01

    Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. E-njoy the first CERN Global Network e-vent!

    CERN Multimedia

    CERN Bulletin

    2010-01-01

    Empowered by the considerable interest it received after it was launched, the CERN Global Network takes off and organizes the first e-vent, which will be a special talk on science communication that will be held on 29 June at 4.30 p.m. in the Council Chamber. You can experience it live on the Global Network site and, if you are a Member, provide feedback. Stay linked!   On the CERN Global Network webpage, you will be able to choose the topic of the next e-vents. Seven weeks after its launch, about 600 people have already joined the CERN Global Network and six thematic groups have been created. The whole idea of joining the Network is to stay connected or reconnect with life at CERN where seminars, talks and discussions are undoubtedly a very important and much appreciated part of it. This is where the e-vents come into play. “The e-vents enable members of the Global Network to participate in selected events taking place at CERN, such as lectures or panel discussions. They will...

  4. A robust neural network-based approach for microseismic event detection

    KAUST Repository

    Akram, Jubran

    2017-08-17

    We present an artificial neural network based approach for robust event detection from low S/N waveforms. We use a feed-forward network with a single hidden layer that is tuned on a training dataset and later applied on the entire example dataset for event detection. The input features used include the average of absolute amplitudes, variance, energy-ratio and polarization rectilinearity. These features are calculated in a moving-window of same length for the entire waveform. The output is set as a user-specified relative probability curve, which provides a robust way of distinguishing between weak and strong events. An optimal network is selected by studying the weight-based saliency and effect of number of neurons on the predicted results. Using synthetic data examples, we demonstrate that this approach is effective in detecting weaker events and reduces the number of false positives.

  5. 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.

  6. Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

    Science.gov (United States)

    Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

    2017-04-01

    Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

  7. Event classification with the electronic detectors of the OPERA experiment using neural networks

    International Nuclear Information System (INIS)

    Hierholzer, Martin C.

    2012-02-01

    The OPERA experiment searches for ν μ ν τ oscillations in appearance mode. It uses the emulsion cloud chamber (ECC) technique for a high spatial resolution combined with on-line components for event localisation and muon identification. The analysis of events in an ECC detector takes considerable time, especially in case of ν τ /ν e candidate events. A ranking of events by a probability for being a ν τ /ν e event can speed up the analysis of the OPERA experiment. An algorithm for such an event ranking based on a classification-type neural network is presented in this thesis. Almost all candidate events can be found within the first 30% of the analysed events if the described ranking is applied. This event ranking is currently applied for testing purposes by the OPERA collaboration, a decision on a full application for the whole analysis is pending. A similar neural network is used for discrimination between neutral and charged current events. This is used to observe neutrino oscillations in disappearance mode with the on-line components of the OPERA detector by measuring the energy dependence of the fraction of neutral current interactions. The confidence level of the observed oscillation effect is 87%. Assuming full mixing, the mass splitting has been determined to vertical stroke Δm 2 32 vertical stroke =2.8 -1.7 +1.4 .10 -3 eV 2 .

  8. Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation

    Directory of Open Access Journals (Sweden)

    Mengdi Wang

    2017-01-01

    Full Text Available Abnormal event detection is one of the vital tasks in wireless sensor networks. However, the faults of nodes and the poor deployment environment have brought great challenges to abnormal event detection. In a typical event detection technique, spatiotemporal correlations are collected to detect an event, which is susceptible to noises and errors. To improve the quality of detection results, we propose a novel approach for abnormal event detection in wireless sensor networks. This approach considers not only spatiotemporal correlations but also the correlations among observed attributes. A dependency model of observed attributes is constructed based on Bayesian network. In this model, the dependency structure of observed attributes is obtained by structure learning, and the conditional probability table of each node is calculated by parameter learning. We propose a new concept named attribute correlation confidence to evaluate the fitting degree between the sensor reading and the abnormal event pattern. On the basis of time correlation detection and space correlation detection, the abnormal events are identified. Experimental results show that the proposed algorithm can reduce the impact of interference factors and the rate of the false alarm effectively; it can also improve the accuracy of event detection.

  9. Modeling a Million-Node Slim Fly Network Using Parallel Discrete-Event Simulation

    Energy Technology Data Exchange (ETDEWEB)

    Wolfe, Noah; Carothers, Christopher; Mubarak, Misbah; Ross, Robert; Carns, Philip

    2016-05-15

    As supercomputers close in on exascale performance, the increased number of processors and processing power translates to an increased demand on the underlying network interconnect. The Slim Fly network topology, a new lowdiameter and low-latency interconnection network, is gaining interest as one possible solution for next-generation supercomputing interconnect systems. In this paper, we present a high-fidelity Slim Fly it-level model leveraging the Rensselaer Optimistic Simulation System (ROSS) and Co-Design of Exascale Storage (CODES) frameworks. We validate our Slim Fly model with the Kathareios et al. Slim Fly model results provided at moderately sized network scales. We further scale the model size up to n unprecedented 1 million compute nodes; and through visualization of network simulation metrics such as link bandwidth, packet latency, and port occupancy, we get an insight into the network behavior at the million-node scale. We also show linear strong scaling of the Slim Fly model on an Intel cluster achieving a peak event rate of 36 million events per second using 128 MPI tasks to process 7 billion events. Detailed analysis of the underlying discrete-event simulation performance shows that a million-node Slim Fly model simulation can execute in 198 seconds on the Intel cluster.

  10. Event-Triggered Distributed Average Consensus Over Directed Digital Networks With Limited Communication Bandwidth.

    Science.gov (United States)

    Li, Huaqing; Chen, Guo; Huang, Tingwen; Dong, Zhaoyang; Zhu, Wei; Gao, Lan

    2016-12-01

    In this paper, we consider the event-triggered distributed average-consensus of discrete-time first-order multiagent systems with limited communication data rate and general directed network topology. In the framework of digital communication network, each agent has a real-valued state but can only exchange finite-bit binary symbolic data sequence with its neighborhood agents at each time step due to the digital communication channels with energy constraints. Novel event-triggered dynamic encoder and decoder for each agent are designed, based on which a distributed control algorithm is proposed. A scheme that selects the number of channel quantization level (number of bits) at each time step is developed, under which all the quantizers in the network are never saturated. The convergence rate of consensus is explicitly characterized, which is related to the scale of network, the maximum degree of nodes, the network structure, the scaling function, the quantization interval, the initial states of agents, the control gain and the event gain. It is also found that under the designed event-triggered protocol, by selecting suitable parameters, for any directed digital network containing a spanning tree, the distributed average consensus can be always achieved with an exponential convergence rate based on merely one bit information exchange between each pair of adjacent agents at each time step. Two simulation examples are provided to illustrate the feasibility of presented protocol and the correctness of the theoretical results.

  11. A comparison between Markovian models and Bayesian networks for treating some dependent events in reliability evaluations

    Energy Technology Data Exchange (ETDEWEB)

    Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e, E-mail: julianapduarte@poli.ufrj.br, E-mail: victor.coppo.leite@poli.ufrj.br, E-mail: frutuoso@nuclear.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil)

    2013-07-01

    Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)

  12. A comparison between Markovian models and Bayesian networks for treating some dependent events in reliability evaluations

    International Nuclear Information System (INIS)

    Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e

    2013-01-01

    Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)

  13. Dyadic Event Attribution in Social Networks with Mixtures of Hawkes Processes.

    Science.gov (United States)

    Li, Liangda; Zha, Hongyuan

    2013-01-01

    In many applications in social network analysis, it is important to model the interactions and infer the influence between pairs of actors, leading to the problem of dyadic event modeling which has attracted increasing interests recently. In this paper we focus on the problem of dyadic event attribution, an important missing data problem in dyadic event modeling where one needs to infer the missing actor-pairs of a subset of dyadic events based on their observed timestamps. Existing works either use fixed model parameters and heuristic rules for event attribution, or assume the dyadic events across actor-pairs are independent. To address those shortcomings we propose a probabilistic model based on mixtures of Hawkes processes that simultaneously tackles event attribution and network parameter inference, taking into consideration the dependency among dyadic events that share at least one actor. We also investigate using additive models to incorporate regularization to avoid overfitting. Our experiments on both synthetic and real-world data sets on international armed conflicts suggest that the proposed new method is capable of significantly improve accuracy when compared with the state-of-the-art for dyadic event attribution.

  14. OSCAR experiment high-density network data report: Event 3 - April 16-17, 1981

    Energy Technology Data Exchange (ETDEWEB)

    Dana, M.T.; Easter, R.C.; Thorp, J.M.

    1984-12-01

    The OSCAR (Oxidation and Scavenging Characteristics of April Rains) experiment, conducted during April 1981, was a cooperative field investigation of wet removal in cyclonic storm systems. The high-density component of OSCAR was located in northeast Indiana and included sequential precipitation chemistry measurements on a 100 by 100 km network, as well as airborne air chemistry and cloud chemistry measurements, surface air chemistry measurements, and supporting meteorological measurements. Four separate storm events were studied during the experiment. This report summarizes data taken by Pacific Northwest Laboratory (PNL) during the third storm event, April 16-17. The report contains the high-density network precipitation chemistry data, air chemistry and cloud chemistry data from the PNL aircraft, and meteorological data for the event, including standard National Weather Service products and radar and rawindsonde data from the network. 4 references, 76 figures, 6 tables.

  15. OSCAR experiment high-density network data report: Event 1 - April 8-9, 1981

    Energy Technology Data Exchange (ETDEWEB)

    Dana, M.T.; Easter, R.C.; Thorp, J.M.

    1984-12-01

    The OSCAR (Oxidation and Scavenging Characteristics of April Rains) experiment, conducted during April 1981, was a cooperative field investigation of wet removal in cyclonic storm systems. The high-densiy component of OSCAR was located in northeast Indiana and included sequential precipitation chemistry measurements on a 100 by 100 km network, as well as airborne air chemistry and cloud chemistry measurements, surface air chemistry measurements, and supporting meteorological measurements. Four separate storm events were studied during the experiment. This report summarizes data taken by Pacific Northwest Laboratory (PNL) during the first storm event, April 8-9. The report contains the high-density network precipitation chemistry data, air chemistry data from the PNL aircraft, and meteorological data for the event, including standard National Weather Service products and radar data from the network. 4 references, 72 figures, 5 tables.

  16. A Hybrid Adaptive Routing Algorithm for Event-Driven Wireless Sensor Networks

    Science.gov (United States)

    Figueiredo, Carlos M. S.; Nakamura, Eduardo F.; Loureiro, Antonio A. F.

    2009-01-01

    Routing is a basic function in wireless sensor networks (WSNs). For these networks, routing algorithms depend on the characteristics of the applications and, consequently, there is no self-contained algorithm suitable for every case. In some scenarios, the network behavior (traffic load) may vary a lot, such as an event-driven application, favoring different algorithms at different instants. This work presents a hybrid and adaptive algorithm for routing in WSNs, called Multi-MAF, that adapts its behavior autonomously in response to the variation of network conditions. In particular, the proposed algorithm applies both reactive and proactive strategies for routing infrastructure creation, and uses an event-detection estimation model to change between the strategies and save energy. To show the advantages of the proposed approach, it is evaluated through simulations. Comparisons with independent reactive and proactive algorithms show improvements on energy consumption. PMID:22423207

  17. Quality of service on Linux for the Atlas TDAQ event building network

    International Nuclear Information System (INIS)

    Yasu, Y.; Manabe, A.; Fujii, H.; Watase, Y.; Nagasaka, Y.; Hasegawa, Y.; Shimojima, M.; Nomachi, M.

    2001-01-01

    Congestion control for packets sent on a network is important for DAQ systems that contain an event builder using switching network technologies. Quality of Service (QoS) is a technique for congestion control. Recent Linux releases provide QoS in the kernel to manage network traffic. The authors have analyzed the packet-loss and packet distribution for the event builder prototype of the Atlas TDAQ system. The authors used PC/Linux with Gigabit Ethernet network as the testbed. The results showed that QoS using CBQ and TBF eliminated packet loss on UDP/IP transfer while the UDP/IP transfer in best effort made lots of packet loss. The result also showed that the QoS overhead was small. The authors concluded that QoS on Linux performed efficiently in TCP/IP and UDP/IP and will have an important role of the Atlas TDAQ system

  18. A Markovian event-based framework for stochastic spiking neural networks.

    Science.gov (United States)

    Touboul, Jonathan D; Faugeras, Olivier D

    2011-11-01

    In spiking neural networks, the information is conveyed by the spike times, that depend on the intrinsic dynamics of each neuron, the input they receive and on the connections between neurons. In this article we study the Markovian nature of the sequence of spike times in stochastic neural networks, and in particular the ability to deduce from a spike train the next spike time, and therefore produce a description of the network activity only based on the spike times regardless of the membrane potential process. To study this question in a rigorous manner, we introduce and study an event-based description of networks of noisy integrate-and-fire neurons, i.e. that is based on the computation of the spike times. We show that the firing times of the neurons in the networks constitute a Markov chain, whose transition probability is related to the probability distribution of the interspike interval of the neurons in the network. In the cases where the Markovian model can be developed, the transition probability is explicitly derived in such classical cases of neural networks as the linear integrate-and-fire neuron models with excitatory and inhibitory interactions, for different types of synapses, possibly featuring noisy synaptic integration, transmission delays and absolute and relative refractory period. This covers most of the cases that have been investigated in the event-based description of spiking deterministic neural networks.

  19. A Distributed and Energy-Efficient Algorithm for Event K-Coverage in Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Peng Jiang

    2017-01-01

    Full Text Available For event dynamic K-coverage algorithms, each management node selects its assistant node by using a greedy algorithm without considering the residual energy and situations in which a node is selected by several events. This approach affects network energy consumption and balance. Therefore, this study proposes a distributed and energy-efficient event K-coverage algorithm (DEEKA. After the network achieves 1-coverage, the nodes that detect the same event compete for the event management node with the number of candidate nodes and the average residual energy, as well as the distance to the event. Second, each management node estimates the probability of its neighbor nodes’ being selected by the event it manages with the distance level, the residual energy level, and the number of dynamic coverage event of these nodes. Third, each management node establishes an optimization model that uses expectation energy consumption and the residual energy variance of its neighbor nodes and detects the performance of the events it manages as targets. Finally, each management node uses a constrained non-dominated sorting genetic algorithm (NSGA-II to obtain the Pareto set of the model and the best strategy via technique for order preference by similarity to an ideal solution (TOPSIS. The algorithm first considers the effect of harsh underwater environments on information collection and transmission. It also considers the residual energy of a node and a situation in which the node is selected by several other events. Simulation results show that, unlike the on-demand variable sensing K-coverage algorithm, DEEKA balances and reduces network energy consumption, thereby prolonging the network’s best service quality and lifetime.

  20. Modeling a cold-air drainage event with a wireless sensor network

    OpenAIRE

    Brian R. Zutta; Eric A. Graham; Philip W. Rundel

    2005-01-01

    A wireless network of sensors was used to characterize a cold-air drainage event in the canyon surrounding the James Reserve. The flow of cold air at night and the first hours of sunrise have major ecological consequences by limiting the vegetation types to those tolerant of freeze and thaw cycles. A network of wireless sensors provides the opportunity to track this event in real time and fully characterize the cold air flow down the canyon, which may last 1.5 hours, and the pooling of cold a...

  1. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    International Nuclear Information System (INIS)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.

    2017-01-01

    Here, we present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. Lastly, we also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  2. Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber

    Energy Technology Data Exchange (ETDEWEB)

    Acciarri, R.; Adams, C.; An, R.; Asaadi, J.; Auger, M.; Bagby, L.; Baller, B.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Bugel, L.; Camilleri, L.; Caratelli, D.; Carls, B.; Fernandez, R. Castillo; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anad?n, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Sanchez, L. Escudero; Esquivel, J.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; James, C.; de Vries, J. Jan; Jen, C. -M.; Jiang, L.; Johnson, R. A.; Jones, B. J. P.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Caicedo, D. A. Martinez; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; von Rohr, C. Rudolf; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Snider, E. L.; Soderberg, M.; S?ldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y. -T.; Tufanli, S.; Usher, T.; Van de Water, R. G.; Viren, B.; Weber, M.; Weston, J.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Zeller, G. P.; Zennamo, J.; Zhang, C.

    2017-03-01

    We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

  3. Neural dynamics of event segmentation in music: converging evidence for dissociable ventral and dorsal networks.

    Science.gov (United States)

    Sridharan, Devarajan; Levitin, Daniel J; Chafe, Chris H; Berger, Jonathan; Menon, Vinod

    2007-08-02

    The real world presents our sensory systems with a continuous stream of undifferentiated information. Segmentation of this stream at event boundaries is necessary for object identification and feature extraction. Here, we investigate the neural dynamics of event segmentation in entire musical symphonies under natural listening conditions. We isolated time-dependent sequences of brain responses in a 10 s window surrounding transitions between movements of symphonic works. A strikingly right-lateralized network of brain regions showed peak response during the movement transitions when, paradoxically, there was no physical stimulus. Model-dependent and model-free analysis techniques provided converging evidence for activity in two distinct functional networks at the movement transition: a ventral fronto-temporal network associated with detecting salient events, followed in time by a dorsal fronto-parietal network associated with maintaining attention and updating working memory. Our study provides direct experimental evidence for dissociable and causally linked ventral and dorsal networks during event segmentation of ecologically valid auditory stimuli.

  4. A Database of Tornado Events as Perceived by the USArray Transportable Array Network

    Science.gov (United States)

    Tytell, J. E.; Vernon, F.; Reyes, J. C.

    2015-12-01

    Over the course of the deployment of Earthscope's USArray Transportable Array (TA) network there have numerous tornado events that have occurred within the changing footprint of its network. The Array Network Facility based in San Diego, California, has compiled a database of these tornado events based on data provided by the NOAA Storm Prediction Center (SPC). The SPC data itself consists of parameters such as start-end point track data for each event, maximum EF intensities, and maximum track widths. Our database is Antelope driven and combines these data from the SPC with detailed station information from the TA network. We are now able to list all available TA stations during any specific tornado event date and also provide a single calculated "nearest" TA station per individual tornado event. We aim to provide this database as a starting resource for those with an interest in investigating tornado signatures within surface pressure and seismic response data. On a larger scale, the database may be of particular interest to the infrasound research community

  5. How to model mutually exclusive events based on independent causal pathways in Bayesian network models

    OpenAIRE

    Fenton, N.; Neil, M.; Lagnado, D.; Marsh, W.; Yet, B.; Constantinou, A.

    2016-01-01

    We show that existing Bayesian network (BN) modelling techniques cannot capture the correct intuitive reasoning in the important case when a set of mutually exclusive events need to be modelled as separate nodes instead of states of a single node. A previously proposed ‘solution’, which introduces a simple constraint node that enforces mutual exclusivity, fails to preserve the prior probabilities of the events, while other proposed solutions involve major changes to the original model. We pro...

  6. Event-Driven Control for Networked Control Systems With Quantization and Markov Packet Losses.

    Science.gov (United States)

    Yang, Hongjiu; Xu, Yang; Zhang, Jinhui

    2016-05-23

    In this paper, event-driven is used in a networked control system (NCS) which is subjected to the effect of quantization and packet losses. A discrete event-detector is used to monitor specific events in the NCS. Both an arbitrary region quantizer and Markov jump packet losses are also considered for the NCS. Based on zoom strategy and Lyapunov theory, a complete proof is given to guarantee mean square stability of the closed-loop system. Stabilization of the NCS is ensured by designing a feedback controller. Lastly, an inverted pendulum model is given to show the advantages and effectiveness of the proposed results.

  7. Tagging b and c quark events in e+e- collisions with neural networks

    International Nuclear Information System (INIS)

    Proriol, J.; Falvard, A.; Henrard, P.; Jousset, J.; Brandl, B.

    1992-01-01

    High purity samples of b quark events and, if possible, of c quark events are attempted to produce, and the width of Γ(Z 0 → bb-bar) is measured. The different variables and the method to select the most discriminating variables are given. The physical results obtained with these methods are recalled, and new results are presented with variables connected with the impact parameter. Some neural networks used throughout this work and some results on c quark events selection are also presented. (K.A.) 9 refs.; 6 figs

  8. An Improved Forwarding of Diverse Events with Mobile Sinks in Underwater Wireless Sensor Networks.

    Science.gov (United States)

    Raza, Waseem; Arshad, Farzana; Ahmed, Imran; Abdul, Wadood; Ghouzali, Sanaa; Niaz, Iftikhar Azim; Javaid, Nadeem

    2016-11-04

    In this paper, a novel routing strategy to cater the energy consumption and delay sensitivity issues in deep underwater wireless sensor networks is proposed. This strategy is named as ESDR: Event Segregation based Delay sensitive Routing. In this strategy sensed events are segregated on the basis of their criticality and, are forwarded to their respective destinations based on forwarding functions. These functions depend on different routing metrics like: Signal Quality Index, Localization free Signal to Noise Ratio, Energy Cost Function and Depth Dependent Function. The problem of incomparable values of previously defined forwarding functions causes uneven delays in forwarding process. Hence forwarding functions are redefined to ensure their comparable values in different depth regions. Packet forwarding strategy is based on the event segregation approach which forwards one third of the generated events (delay sensitive) to surface sinks and two third events (normal events) are forwarded to mobile sinks. Motion of mobile sinks is influenced by the relative distribution of normal nodes. We have also incorporated two different mobility patterns named as; adaptive mobility and uniform mobility for mobile sinks. The later one is implemented for collecting the packets generated by the normal nodes. These improvements ensure optimum holding time, uniform delay and in-time reporting of delay sensitive events. This scheme is compared with the existing ones and outperforms the existing schemes in terms of network lifetime, delay and throughput.

  9. Applying Bayesian neural networks to separate neutrino events from backgrounds in reactor neutrino experiments

    International Nuclear Information System (INIS)

    Xu, Y; Meng, Y X; Xu, W W

    2008-01-01

    A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The samples of neutrino events and three major backgrounds from the Monte-Carlo simulation of the toy detector are generated in the signal region. The Bayesian Neural Networks (BNN) are applied to separate neutrino events from backgrounds in reactor neutrino experiments. As a result, the most neutrino events and uncorrelated background events in the signal region can be identified with BNN, and the part events each of the fast neutron and 8 He/ 9 Li backgrounds in the signal region can be identified with BNN. Then, the signal to noise ratio in the signal region is enhanced with BNN. The neutrino discrimination increases with the increase of the neutrino rate in the training sample. However, the background discriminations decrease with the decrease of the background rate in the training sample

  10. Use of wireless sensor networks for distributed event detection in disaster management applications

    NARCIS (Netherlands)

    Bahrepour, M.; Meratnia, Nirvana; Poel, Mannes; Taghikhaki, Zahra; Havinga, Paul J.M.

    Recently, wireless sensor networks (WSNs) have become mature enough to go beyond being simple fine-grained continuous monitoring platforms and have become one of the enabling technologies for early-warning disaster systems. Event detection functionality of WSNs can be of great help and importance

  11. CoreFlow: Enriching Bro security events using network traffic monitoring data

    NARCIS (Netherlands)

    Koning, R.; Buraglio, N.; de Laat, C.; Grosso, P.

    Attacks against network infrastructures can be detected by Intrusion Detection Systems (IDS). Still reaction to these events are often limited by the lack of larger contextual information in which they occurred. In this paper we present CoreFlow, a framework for the correlation and enrichment of IDS

  12. Performance Evaluation of Wireless Sensor Networks for Event-Detection with Shadowing-Induced Radio Irregularities

    Directory of Open Access Journals (Sweden)

    Giuseppe De Marco

    2007-01-01

    Full Text Available In this paper, we study a particular application of wireless sensor networks for event-detection and tracking. In this kind of application, the transport of data is simplified, and guaranteeing a minimum number of packets at the monitoring node is the only constraint on the performance of the sensor network. This minimum number of packets is called event-reliability. Contrary to other studies on the subject, here we consider the behavior of such a network in presence of a realistic radio model, such as the shadowing of the radio signal. With this setting, we extend our previous analysis of the event-reliability approach for the transport of data. In particular, both regular and random networks are considered. The contribute of this work is to show via simulations that, in the presence of randomness or irregularities in the radio channel, the event-reliability can be jeopardized, that is the constraint on the minimum number of packets at the sink node could not be satisfied.

  13. SME Innovation and Learning: The Role of Networks and Crisis Events

    Science.gov (United States)

    Saunders, Mark N. K.; Gray, David E; Goregaokar, Harshita

    2014-01-01

    Purpose: The purpose of this paper is to contribute to the literature on innovation and entrepreneurial learning by exploring how SMEs learn and innovate, how they use both formal and informal learning and in particular the role of networks and crisis events within their learning experience. Design/methodology/approach: Mixed method study,…

  14. Robustness Assessment of Urban Road Network with Consideration of Multiple Hazard Events.

    Science.gov (United States)

    Zhou, Yaoming; Sheu, Jiuh-Biing; Wang, Junwei

    2017-08-01

    Robustness measures a system's ability of being insensitive to disturbances. Previous studies assessed the robustness of transportation networks to a single disturbance without considering simultaneously happening multiple events. The purpose of this article is to address this problem and propose a new framework to assess the robustness of an urban transportation network. The framework consists of two layers. The upper layer is to define the robustness index based on the impact evaluation in different scenarios obtained from the lower layer, whereas the lower layer is to evaluate the performance of each hypothetical disrupted road network given by the upper layer. The upper layer has two varieties, that is, robustness against random failure and robustness against intentional attacks. This robustness measurement framework is validated by application to a real-world urban road network in Hong Kong. The results show that the robustness of a transport network with consideration of multiple events is quite different from and more comprehensive than that with consideration of only a single disruption. We also propose a Monte Carlo method and a heuristic algorithm to handle different scenarios with multiple hazard events, which is proved to be quite efficient. This methodology can also be applied to conduct risk analysis of other systems where multiple failures or disruptions exist. © 2017 Society for Risk Analysis.

  15. A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation

    Directory of Open Access Journals (Sweden)

    Dongmei Huang

    2017-09-01

    Full Text Available Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

  16. A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

    Science.gov (United States)

    Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

    2017-09-21

    Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

  17. Event classification with the electronic detectors of the OPERA experiment using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hierholzer, Martin C.

    2012-02-15

    The OPERA experiment searches for {nu}{sub {mu}} <-> {nu}{sub {tau}} oscillations in appearance mode. It uses the emulsion cloud chamber (ECC) technique for a high spatial resolution combined with on-line components for event localisation and muon identification. The analysis of events in an ECC detector takes considerable time, especially in case of {nu}{sub {tau}}/{nu}{sub e} candidate events. A ranking of events by a probability for being a {nu}{sub {tau}}/{nu}{sub e} event can speed up the analysis of the OPERA experiment. An algorithm for such an event ranking based on a classification-type neural network is presented in this thesis. Almost all candidate events can be found within the first 30% of the analysed events if the described ranking is applied. This event ranking is currently applied for testing purposes by the OPERA collaboration, a decision on a full application for the whole analysis is pending. A similar neural network is used for discrimination between neutral and charged current events. This is used to observe neutrino oscillations in disappearance mode with the on-line components of the OPERA detector by measuring the energy dependence of the fraction of neutral current interactions. The confidence level of the observed oscillation effect is 87%. Assuming full mixing, the mass splitting has been determined to vertical stroke {delta}m{sup 2}{sub 32} vertical stroke =2.8{sub -1.7}{sup +1.4}.10{sup -3}eV{sup 2}.

  18. Climate network analysis of regional precipitation extremes: The true story told by event synchronization

    Science.gov (United States)

    Odenweller, Adrian; Donner, Reik V.

    2017-04-01

    Over the last decade, complex network methods have been frequently used for characterizing spatio-temporal patterns of climate variability from a complex systems perspective, yielding new insights into time-dependent teleconnectivity patterns and couplings between different components of the Earth climate. Among the foremost results reported, network analyses of the synchronicity of extreme events as captured by the so-called event synchronization have been proposed to be powerful tools for disentangling the spatio-temporal organization of particularly extreme rainfall events and anticipating the timing of monsoon onsets or extreme floodings. Rooted in the analysis of spike train synchrony analysis in the neurosciences, event synchronization has the great advantage of automatically classifying pairs of events arising at two distinct spatial locations as temporally close (and, thus, possibly statistically - or even dynamically - interrelated) or not without the necessity of selecting an additional parameter in terms of a maximally tolerable delay between these events. This consideration is conceptually justified in case of the original application to spike trains in electroencephalogram (EEG) recordings, where the inter-spike intervals show relatively narrow distributions at high temporal sampling rates. However, in case of climate studies, precipitation extremes defined by daily precipitation sums exceeding a certain empirical percentile of their local distribution exhibit a distinctively different type of distribution of waiting times between subsequent events. This raises conceptual concerns if event synchronization is still appropriate for detecting interlinkages between spatially distributed precipitation extremes. In order to study this problem in more detail, we employ event synchronization together with an alternative similarity measure for event sequences, event coincidence rates, which requires a manual setting of the tolerable maximum delay between two

  19. The effect of social networks and social support on common mental disorders following specific life events.

    Science.gov (United States)

    Maulik, P K; Eaton, W W; Bradshaw, C P

    2010-08-01

    This study examined the association between life events and common mental disorders while accounting for social networks and social supports. Participants included 1920 adults in the Baltimore Epidemiologic Catchment Area Cohort who were interviewed in 1993-1996, of whom 1071 were re-interviewed in 2004-2005. Generalized estimating equations were used to analyze the data. Social support from friends, spouse or relatives was associated with significantly reduced odds of panic disorder and psychological distress, after experiencing specific life events. Social networks or social support had no significant stress-buffering effect. Social networks and social support had almost no direct or buffering effect on major depressive disorder, and no effect on generalized anxiety disorder and alcohol abuse or dependence disorder. The significant association between social support and psychological distress, rather than diagnosable mental disorders, highlights the importance of social support, especially when the severity of a mental health related problem is low.

  20. Changes in event-related potential functional networks predict traumatic brain injury in piglets.

    Science.gov (United States)

    Atlan, Lorre S; Lan, Ingrid S; Smith, Colin; Margulies, Susan S

    2018-06-01

    Traumatic brain injury is a leading cause of cognitive and behavioral deficits in children in the US each year. None of the current diagnostic tools, such as quantitative cognitive and balance tests, have been validated to identify mild traumatic brain injury in infants, adults and animals. In this preliminary study, we report a novel, quantitative tool that has the potential to quickly and reliably diagnose traumatic brain injury and which can track the state of the brain during recovery across multiple ages and species. Using 32 scalp electrodes, we recorded involuntary auditory event-related potentials from 22 awake four-week-old piglets one day before and one, four, and seven days after two different injury types (diffuse and focal) or sham. From these recordings, we generated event-related potential functional networks and assessed whether the patterns of the observed changes in these networks could distinguish brain-injured piglets from non-injured. Piglet brains exhibited significant changes after injury, as evaluated by five network metrics. The injury prediction algorithm developed from our analysis of the changes in the event-related potentials functional networks ultimately produced a tool with 82% predictive accuracy. This novel approach is the first application of auditory event-related potential functional networks to the prediction of traumatic brain injury. The resulting tool is a robust, objective and predictive method that offers promise for detecting mild traumatic brain injury, in particular because collecting event-related potentials data is noninvasive and inexpensive. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Discrete Event Modeling and Simulation-Driven Engineering for the ATLAS Data Acquisition Network

    CERN Document Server

    Bonaventura, Matias Alejandro; The ATLAS collaboration; Castro, Rodrigo Daniel

    2016-01-01

    We present an iterative and incremental development methodology for simulation models in network engineering projects. Driven by the DEVS (Discrete Event Systems Specification) formal framework for modeling and simulation we assist network design, test, analysis and optimization processes. A practical application of the methodology is presented for a case study in the ATLAS particle physics detector, the largest scientific experiment built by man where scientists around the globe search for answers about the origins of the universe. The ATLAS data network convey real-time information produced by physics detectors as beams of particles collide. The produced sub-atomic evidences must be filtered and recorded for further offline scrutiny. Due to the criticality of the transported data, networks and applications undergo careful engineering processes with stringent quality of service requirements. A tight project schedule imposes time pressure on design decisions, while rapid technology evolution widens the palett...

  2. A Probabilistic Approach to Network Event Formation from Pre-Processed Waveform Data

    Science.gov (United States)

    Kohl, B. C.; Given, J.

    2017-12-01

    The current state of the art for seismic event detection still largely depends on signal detection at individual sensor stations, including picking accurate arrivals times and correctly identifying phases, and relying on fusion algorithms to associate individual signal detections to form event hypotheses. But increasing computational capability has enabled progress toward the objective of fully utilizing body-wave recordings in an integrated manner to detect events without the necessity of previously recorded ground truth events. In 2011-2012 Leidos (then SAIC) operated a seismic network to monitor activity associated with geothermal field operations in western Nevada. We developed a new association approach for detecting and quantifying events by probabilistically combining pre-processed waveform data to deal with noisy data and clutter at local distance ranges. The ProbDet algorithm maps continuous waveform data into continuous conditional probability traces using a source model (e.g. Brune earthquake or Mueller-Murphy explosion) to map frequency content and an attenuation model to map amplitudes. Event detection and classification is accomplished by combining the conditional probabilities from the entire network using a Bayesian formulation. This approach was successful in producing a high-Pd, low-Pfa automated bulletin for a local network and preliminary tests with regional and teleseismic data show that it has promise for global seismic and nuclear monitoring applications. The approach highlights several features that we believe are essential to achieving low-threshold automated event detection: Minimizes the utilization of individual seismic phase detections - in traditional techniques, errors in signal detection, timing, feature measurement and initial phase ID compound and propagate into errors in event formation, Has a formalized framework that utilizes information from non-detecting stations, Has a formalized framework that utilizes source information, in

  3. Discrimination of panti p → tanti t events by a neural network classifier

    International Nuclear Information System (INIS)

    Cherubini, A.; Odorico, R.

    1992-01-01

    Neural network and conventional statistical techniques are compared in the problem of discriminating panti p→tanti t events, with top quarks decaying into anything, from the associated hadronic background at the energy of the Fermilab collider. The NN we develop for this sake is an improved version of Kohonen's learning vector quantization scheme. Performance of the NN as a tanti t event classifier is found to be less satisfactory than that achievable by statistical methods. We conclude that the probable reasons for that are: i) The NN approach presents advantages only when dealing with event distributions in the feature space which substantially differ from Gaussians; ii) NN's require much larger training sets of events than statistical discrimination in order to give comparable results. (orig.)

  4. Sampled-data consensus in switching networks of integrators based on edge events

    Science.gov (United States)

    Xiao, Feng; Meng, Xiangyu; Chen, Tongwen

    2015-02-01

    This paper investigates the event-driven sampled-data consensus in switching networks of multiple integrators and studies both the bidirectional interaction and leader-following passive reaction topologies in a unified framework. In these topologies, each information link is modelled by an edge of the information graph and assigned a sequence of edge events, which activate the mutual data sampling and controller updates of the two linked agents. Two kinds of edge-event-detecting rules are proposed for the general asynchronous data-sampling case and the synchronous periodic event-detecting case. They are implemented in a distributed fashion, and their effectiveness in reducing communication costs and solving consensus problems under a jointly connected topology condition is shown by both theoretical analysis and simulation examples.

  5. Event-triggered Kalman-consensus filter for two-target tracking sensor networks.

    Science.gov (United States)

    Su, Housheng; Li, Zhenghao; Ye, Yanyan

    2017-11-01

    This paper is concerned with the problem of event-triggered Kalman-consensus filter for two-target tracking sensor networks. According to the event-triggered protocol and the mean-square analysis, a suboptimal Kalman gain matrix is derived and a suboptimal event-triggered distributed filter is obtained. Based on the Kalman-consensus filter protocol, all sensors which only depend on its neighbors' information can track their corresponding targets. Furthermore, utilizing Lyapunov method and matrix theory, some sufficient conditions are presented for ensuring the stability of the system. Finally, a simulation example is presented to verify the effectiveness of the proposed event-triggered protocol. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Detection of rain events in radiological early warning networks with spectro-dosimetric systems

    Science.gov (United States)

    Dąbrowski, R.; Dombrowski, H.; Kessler, P.; Röttger, A.; Neumaier, S.

    2017-10-01

    Short-term pronounced increases of the ambient dose equivalent rate, due to rainfall are a well-known phenomenon. Increases in the same order of magnitude or even below may also be caused by a nuclear or radiological event, i.e. by artificial radiation. Hence, it is important to be able to identify natural rain events in dosimetric early warning networks and to distinguish them from radiological events. Novel spectrometric systems based on scintillators may be used to differentiate between the two scenarios, because the measured gamma spectra provide significant nuclide-specific information. This paper describes three simple, automatic methods to check whether an dot H*(10) increase is caused by a rain event or by artificial radiation. These methods were applied to measurements of three spectrometric systems based on CeBr3, LaBr3 and SrI2 scintillation crystals, investigated and tested for their practicability at a free-field reference site of PTB.

  7. Automatic Classification of volcano-seismic events based on Deep Neural Networks.

    Science.gov (United States)

    Titos Luzón, M.; Bueno Rodriguez, A.; Garcia Martinez, L.; Benitez, C.; Ibáñez, J. M.

    2017-12-01

    Seismic monitoring of active volcanoes is a popular remote sensing technique to detect seismic activity, often associated to energy exchanges between the volcano and the environment. As a result, seismographs register a wide range of volcano-seismic signals that reflect the nature and underlying physics of volcanic processes. Machine learning and signal processing techniques provide an appropriate framework to analyze such data. In this research, we propose a new classification framework for seismic events based on deep neural networks. Deep neural networks are composed by multiple processing layers, and can discover intrinsic patterns from the data itself. Internal parameters can be initialized using a greedy unsupervised pre-training stage, leading to an efficient training of fully connected architectures. We aim to determine the robustness of these architectures as classifiers of seven different types of seismic events recorded at "Volcán de Fuego" (Colima, Mexico). Two deep neural networks with different pre-training strategies are studied: stacked denoising autoencoder and deep belief networks. Results are compared to existing machine learning algorithms (SVM, Random Forest, Multilayer Perceptron). We used 5 LPC coefficients over three non-overlapping segments as training features in order to characterize temporal evolution, avoid redundancy and encode the signal, regardless of its duration. Experimental results show that deep architectures can classify seismic events with higher accuracy than classical algorithms, attaining up to 92% recognition accuracy. Pre-training initialization helps these models to detect events that occur simultaneously in time (such explosions and rockfalls), increase robustness against noisy inputs, and provide better generalization. These results demonstrate deep neural networks are robust classifiers, and can be deployed in real-environments to monitor the seismicity of restless volcanoes.

  8. A High-Efficiency Uneven Cluster Deployment Algorithm Based on Network Layered for Event Coverage in UWSNs

    Directory of Open Access Journals (Sweden)

    Shanen Yu

    2016-12-01

    Full Text Available Most existing deployment algorithms for event coverage in underwater wireless sensor networks (UWSNs usually do not consider that network communication has non-uniform characteristics on three-dimensional underwater environments. Such deployment algorithms ignore that the nodes are distributed at different depths and have different probabilities for data acquisition, thereby leading to imbalances in the overall network energy consumption, decreasing the network performance, and resulting in poor and unreliable late network operation. Therefore, in this study, we proposed an uneven cluster deployment algorithm based network layered for event coverage. First, according to the energy consumption requirement of the communication load at different depths of the underwater network, we obtained the expected value of deployment nodes and the distribution density of each layer network after theoretical analysis and deduction. Afterward, the network is divided into multilayers based on uneven clusters, and the heterogeneous communication radius of nodes can improve the network connectivity rate. The recovery strategy is used to balance the energy consumption of nodes in the cluster and can efficiently reconstruct the network topology, which ensures that the network has a high network coverage and connectivity rate in a long period of data acquisition. Simulation results show that the proposed algorithm improves network reliability and prolongs network lifetime by significantly reducing the blind movement of overall network nodes while maintaining a high network coverage and connectivity rate.

  9. Minimizing cache misses in an event-driven network server: A case study of TUX

    DEFF Research Database (Denmark)

    Bhatia, Sapan; Consel, Charles; Lawall, Julia Laetitia

    2006-01-01

    We analyze the performance of CPU-bound network servers and demonstrate experimentally that the degradation in the performance of these servers under high-concurrency workloads is largely due to inefficient use of the hardware caches. We then describe an approach to speeding up event-driven network...... servers by optimizing their use of the L2 CPU cache in the context of the TUX Web server, known for its robustness to heavy load. Our approach is based on a novel cache-aware memory allocator and a specific scheduling strategy that together ensure that the total working data set of the server stays...

  10. Identification of pp→K±π-+ K0(K0) events using artificial neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.; Polivka, G.; Vlachos, S.; Wendler, H.

    1995-01-01

    An artificial neural network classifier has been developed in order to separate on-line events containing a decaying neutral kaon. The proposed system performs better than classical selection methods in real-time applications. The biases due to the on-line selection are smaller than few per cent and are known. The system is robust against calibration variations and missing information. A hardware implementation of the algorithm allows an event selection in less than 40 μs and provides a considerable on-line rate reduction in tagged neutral kaon experiments. This classifier has been developed within the framework of the CPLEAR experiment. (orig.)

  11. The participation of Interactors in Social Network Sites as a News Event Dimension

    Directory of Open Access Journals (Sweden)

    Gabriela da Silva Zago

    2013-07-01

    Full Text Available Normal 0 21 false false false MicrosoftInternetExplorer4 The article discusses the possibility of considering the participation of interactors in social network sites as a news event dimension, to the extent that, by the recirculation, interactors can assign different and unexpected meanings to the event. We take as a starting point for the discussion, in an exploratory nature, the inauguration of the first stretch of the bike path from the Avenida Ipiranga, in Porto Alegre, Brazil, in May 2012.

  12. Early adverse life events are associated with altered brain network architecture in a sex- dependent manner

    Directory of Open Access Journals (Sweden)

    Arpana Gupta, PhD

    2017-12-01

    Full Text Available Introduction: Early adverse life events (EALs increase the risk for chronic medical and psychiatric disorders by altering early neurodevelopment. The aim of this study was to examine associations between EALs and network properties of core brain regions in the emotion regulation and salience networks, and to test the influence of sex on these associations. Methods: Resting-state functional and diffusion tensor magnetic resonance imaging were obtained in healthy individuals (61 men, 63 women. Functional and anatomical network properties of centrality and segregation were calculated for the core regions of the two networks using graph theory. Moderator analyses were applied to test hypotheses. Results: The type of adversity experienced influences brain wiring differently, as higher general EALs were associated with decreased functional and anatomical centrality in salience and emotion regulation regions, while physical and emotional EALs were associated with increased anatomical centrality and segregation in emotion regulation regions. Sex moderated the associations between EALs and measures of centrality; with decreased centrality of salience and emotion regulation regions with increased general EALs in females, and increased centrality in salience regions with higher physical and emotional EALs in males. Increased segregation of salience regions was associated with increased general EALs in males. Centrality of the amygdala was associated with physical symptoms, and segregation of salience regions was correlated with higher somatization in men only. Conclusions: Emotion regulation and salience regions are susceptible to topological brain restructuring associated with EALs. The male and female brains appear to be differently affected by specific types of EALs. Keywords: Early adverse traumatic life events, Centrality, Segregation, Network metrics, Moderating effects of sex, Emotion regulation network, Salience network

  13. The Convolutional Visual Network for Identification and Reconstruction of NOvA Events

    Energy Technology Data Exchange (ETDEWEB)

    Psihas, Fernanda [Indiana U.

    2017-11-22

    In 2016 the NOvA experiment released results for the observation of oscillations in the vμ and ve channels as well as ve cross section measurements using neutrinos from Fermilab’s NuMI beam. These and other measurements in progress rely on the accurate identification and reconstruction of the neutrino flavor and energy recorded by our detectors. This presentation describes the first application of convolutional neural network technology for event identification and reconstruction in particle detectors like NOvA. The Convolutional Visual Network (CVN) Algorithm was developed for identification, categorization, and reconstruction of NOvA events. It increased the selection efficiency of the ve appearance signal by 40% and studies show potential impact to the vμ disappearance analysis.

  14. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  15. Networked Estimation for Event-Based Sampling Systems with Packet Dropouts

    Directory of Open Access Journals (Sweden)

    Young Soo Suh

    2009-04-01

    Full Text Available This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen.

  16. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

    Directory of Open Access Journals (Sweden)

    Young Yoon

    Full Text Available Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users.

  17. A computational approach to extinction events in chemical reaction networks with discrete state spaces.

    Science.gov (United States)

    Johnston, Matthew D

    2017-12-01

    Recent work of Johnston et al. has produced sufficient conditions on the structure of a chemical reaction network which guarantee that the corresponding discrete state space system exhibits an extinction event. The conditions consist of a series of systems of equalities and inequalities on the edges of a modified reaction network called a domination-expanded reaction network. In this paper, we present a computational implementation of these conditions written in Python and apply the program on examples drawn from the biochemical literature. We also run the program on 458 models from the European Bioinformatics Institute's BioModels Database and report our results. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

    Science.gov (United States)

    Yoon, Young; Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users.

  19. Virtualization of Event Sources in Wireless Sensor Networks for the Internet of Things

    Science.gov (United States)

    Martínez, Néstor Lucas; Martínez, José-Fernán; Díaz, Vicente Hernández

    2014-01-01

    Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model. PMID:25470489

  20. Virtualization of Event Sources in Wireless Sensor Networks for the Internet of Things

    Directory of Open Access Journals (Sweden)

    Néstor Lucas Martínez

    2014-12-01

    Full Text Available Wireless Sensor Networks (WSNs are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.

  1. Virtualization of event sources in wireless sensor networks for the internet of things.

    Science.gov (United States)

    Lucas Martínez, Néstor; Martínez, José-Fernán; Hernández Díaz, Vicente

    2014-12-01

    Wireless Sensor Networks (WSNs) are generally used to collect information from the environment. The gathered data are delivered mainly to sinks or gateways that become the endpoints where applications can retrieve and process such data. However, applications would also expect from a WSN an event-driven operational model, so that they can be notified whenever occur some specific environmental changes instead of continuously analyzing the data provided periodically. In either operational model, WSNs represent a collection of interconnected objects, as outlined by the Internet of Things. Additionally, in order to fulfill the Internet of Things principles, Wireless Sensor Networks must have a virtual representation that allows indirect access to their resources, a model that should also include the virtualization of event sources in a WSN. Thus, in this paper a model for a virtual representation of event sources in a WSN is proposed. They are modeled as internet resources that are accessible by any internet application, following an Internet of Things approach. The model has been tested in a real implementation where a WSN has been deployed in an open neighborhood environment. Different event sources have been identified in the proposed scenario, and they have been represented following the proposed model.

  2. Dynamic sensing model for accurate delectability of environmental phenomena using event wireless sensor network

    Science.gov (United States)

    Missif, Lial Raja; Kadhum, Mohammad M.

    2017-09-01

    Wireless Sensor Network (WSN) has been widely used for monitoring where sensors are deployed to operate independently to sense abnormal phenomena. Most of the proposed environmental monitoring systems are designed based on a predetermined sensing range which does not reflect the sensor reliability, event characteristics, and the environment conditions. Measuring of the capability of a sensor node to accurately detect an event within a sensing field is of great important for monitoring applications. This paper presents an efficient mechanism for even detection based on probabilistic sensing model. Different models have been presented theoretically in this paper to examine their adaptability and applicability to the real environment applications. The numerical results of the experimental evaluation have showed that the probabilistic sensing model provides accurate observation and delectability of an event, and it can be utilized for different environment scenarios.

  3. Energy-Efficient Fault-Tolerant Dynamic Event Region Detection in Wireless Sensor Networks

    DEFF Research Database (Denmark)

    Enemark, Hans-Jacob; Zhang, Yue; Dragoni, Nicola

    2015-01-01

    to a hybrid algorithm for dynamic event region detection, such as real-time tracking of chemical leakage regions. Considering the characteristics of the moving away dynamic events, we propose a return back condition for the hybrid algorithm from distributed neighborhood collaboration, in which a node makes......Fault-tolerant event detection is fundamental to wireless sensor network applications. Existing approaches usually adopt neighborhood collaboration for better detection accuracy, while need more energy consumption due to communication. Focusing on energy efficiency, this paper makes an improvement...... its detection decision based on decisions received from its spatial and temporal neighbors, to local non-communicative decision making. The simulation results demonstrate that the improved algorithm does not degrade the detection accuracy of the original algorithm, while it has better energy...

  4. Cryogenic dark matter search (CDMS II): Application of neural networks and wavelets to event analysis

    Energy Technology Data Exchange (ETDEWEB)

    Attisha, Michael J. [Brown U.

    2006-01-01

    The Cryogenic Dark Matter Search (CDMS) experiment is designed to search for dark matter in the form of Weakly Interacting Massive Particles (WIMPs) via their elastic scattering interactions with nuclei. This dissertation presents the CDMS detector technology and the commissioning of two towers of detectors at the deep underground site in Soudan, Minnesota. CDMS detectors comprise crystals of Ge and Si at temperatures of 20 mK which provide ~keV energy resolution and the ability to perform particle identification on an event by event basis. Event identification is performed via a two-fold interaction signature; an ionization response and an athermal phonon response. Phonons and charged particles result in electron recoils in the crystal, while neutrons and WIMPs result in nuclear recoils. Since the ionization response is quenched by a factor ~ 3(2) in Ge(Si) for nuclear recoils compared to electron recoils, the relative amplitude of the two detector responses allows discrimination between recoil types. The primary source of background events in CDMS arises from electron recoils in the outer 50 µm of the detector surface which have a reduced ionization response. We develop a quantitative model of this ‘dead layer’ effect and successfully apply the model to Monte Carlo simulation of CDMS calibration data. Analysis of data from the two tower run March-August 2004 is performed, resulting in the world’s most sensitive limits on the spin-independent WIMP-nucleon cross-section, with a 90% C.L. upper limit of 1.6 × 10-43 cm2 on Ge for a 60 GeV WIMP. An approach to performing surface event discrimination using neural networks and wavelets is developed. A Bayesian methodology to classifying surface events using neural networks is found to provide an optimized method based on minimization of the expected dark matter limit. The discrete wavelet analysis of CDMS phonon pulses improves surface event discrimination in conjunction with the neural

  5. Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

    Science.gov (United States)

    Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

    2015-03-01

    Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula , in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

  6. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2016-02-01

    Full Text Available The 9th ARRCN Symposium 2015 was held during 21st–25th October 2015 at the Novotel Hotel, Chumphon, Thailand, one of the most favored travel destinations in Asia. The 10th ARRCN Symposium 2017 will be held during October 2017 in the Davao, Philippines. International Symposium on the Montagu's Harrier (Circus pygargus «The Montagu's Harrier in Europe. Status. Threats. Protection», organized by the environmental organization «Landesbund für Vogelschutz in Bayern e.V.» (LBV was held on November 20-22, 2015 in Germany. The location of this event was the city of Wurzburg in Bavaria.

  7. Events

    Directory of Open Access Journals (Sweden)

    Igor V. Karyakin

    2016-04-01

    Full Text Available VII International Conference on research and conservation of raptors in North Eurasia will be hold in Sochi (Russia on the basis of the Sochi National Park in 19–24 September 2016. Annual Meeting of the Raptor Research Foundation will be hold in 16–20 October 2016 in the Cape May (New Jersey, USA supported by the New Jersey Audubon Society’s Cape May Bird Observatory. IV Neotropical Raptor Network Conference will be hold in La Fortuna (Costa Rica in 10th–13th October 2016. la Fundacion Rapaces Costa Rica. V World Owl Conference will be hold in Venaus (Italy in 22–26 March 2017. 4th International Peregrine Conference will be hold in Budapest (Hungary in 27 September – 1st October 2017. Webcams on nests of Goshawk (Accipiter gentilis and Tawny Owl (Strix aluco are installed in Nizhny Novgorod (Russia in 2016. Hour broadcast has been organized since April on the website of the Russian Raptor Research Network and on the website of the Ivideon company. The equipment and technical solutions from Ivideon. MTS has provided communication.

  8. An event- and network-level analysis of college students' maximum drinking day.

    Science.gov (United States)

    Meisel, Matthew K; DiBello, Angelo M; Balestrieri, Sara G; Ott, Miles Q; DiGuiseppi, Graham T; Clark, Melissa A; Barnett, Nancy P

    2018-04-01

    Heavy episodic drinking is common among college students and remains a serious public health issue. Previous event-level research among college students has examined behaviors and individual-level characteristics that drive consumption and related consequences but often ignores the social network of people with whom these heavy drinking episodes occur. The main aim of the current study was to investigate the network of social connections between drinkers on their heaviest drinking occasions. Sociocentric network methods were used to collect information from individuals in the first-year class (N=1342) at one university. Past-month drinkers (N=972) reported on the characteristics of their heaviest drinking occasion in the past month and indicated who else among their network connections was present during this occasion. Average max drinking day indegree, or the total number of times a participant was nominated as being present on another students' heaviest drinking occasion, was 2.50 (SD=2.05). Network autocorrelation models indicated that max drinking day indegree (e.g., popularity on heaviest drinking occassions) and peers' number of drinks on their own maximum drinking occasions were significantly associated with participant maximum number of drinks, after controlling for demographic variables, pregaming, and global network indegree (e.g., popularity in the entire first-year class). Being present at other peers' heaviest drinking occasions is associated with greater drinking quantities on one's own heaviest drinking occasion. These findings suggest the potential for interventions that target peer influences within close social networks of drinkers. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Location aware event driven multipath routing in Wireless Sensor Networks: Agent based approach

    Directory of Open Access Journals (Sweden)

    A.V. Sutagundar

    2013-03-01

    Full Text Available Wireless Sensor Networks (WSNs demand reliable and energy efficient paths for critical information delivery to sink node from an event occurrence node. Multipath routing facilitates reliable data delivery in case of critical information. This paper proposes an event triggered multipath routing in WSNs by employing a set of static and mobile agents. Every sensor node is assumed to know the location information of the sink node and itself. The proposed scheme works as follows: (1 Event node computes the arbitrary midpoint between an event node and the sink node by using location information. (2 Event node establishes a shortest path from itself to the sink node through the reference axis by using a mobile agent with the help of location information; the mobile agent collects the connectivity information and other parameters of all the nodes on the way and provides the information to the sink node. (3 Event node finds the arbitrary location of the special (middle intermediate nodes (above/below reference axis by using the midpoint location information given in step 1. (4 Mobile agent clones from the event node and the clones carry the event type and discover the path passing through special intermediate nodes; the path above/below reference axis looks like an arc. While migrating from one sensor node to another along the traversed path, each mobile agent gathers the node information (such as node id, location information, residual energy, available bandwidth, and neighbors connectivity and delivers to the sink node. (5 The sink node constructs a partial topology, connecting event and sink node by using the connectivity information delivered by the mobile agents. Using the partial topology information, sink node finds the multipath and path weight factor by using link efficiency, energy ratio, and hop distance. (6 The sink node selects the number of paths among the available paths based upon the criticalness of an event, and (7 if the event is non

  10. Alert: An Adaptive Low-Latency Event-Driven MAC Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vinod Namboodiri

    2011-01-01

    Full Text Available Collection of rare but delay-critical messages from a group of sensor nodes is a key process in many wireless sensor network applications. This is particularly important for security-related applications like intrusion detection and fire alarm systems. An event sensed by multiple sensor nodes in the network can trigger many messages to be sent simultaneously. We present Alert, a MAC protocol for collecting event-triggered urgent messages from a group of sensor nodes with minimum latency and without requiring any cooperation or prescheduling among the senders or between senders and receiver during protocol execution. Alert is designed to handle multiple simultaneous messages from different nodes efficiently and reliably, minimizing the overall delay to collect all messages along with the delay to get the first message. Moreover, the ability of the network to handle a large number of simultaneous messages does not come at the cost of excessive delays when only a few messages need to be handled. We analyze Alert and evaluate its feasibility and performance with an implementation on commodity hardware. We further compare Alert with existing approaches through simulations and show the performance improvement possible through Alert.

  11. Words analysis of online Chinese news headlines about trending events: a complex network perspective.

    Science.gov (United States)

    Li, Huajiao; Fang, Wei; An, Haizhong; Huang, Xuan

    2015-01-01

    Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines' keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words' networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly.

  12. Words analysis of online Chinese news headlines about trending events: a complex network perspective.

    Directory of Open Access Journals (Sweden)

    Huajiao Li

    Full Text Available Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines' keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words' networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly.

  13. A Cluster-Based Fuzzy Fusion Algorithm for Event Detection in Heterogeneous Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    ZiQi Hao

    2015-01-01

    Full Text Available As limited energy is one of the tough challenges in wireless sensor networks (WSN, energy saving becomes important in increasing the lifecycle of the network. Data fusion enables combining information from several sources thus to provide a unified scenario, which can significantly save sensor energy and enhance sensing data accuracy. In this paper, we propose a cluster-based data fusion algorithm for event detection. We use k-means algorithm to form the nodes into clusters, which can significantly reduce the energy consumption of intracluster communication. Distances between cluster heads and event and energy of clusters are fuzzified, thus to use a fuzzy logic to select the clusters that will participate in data uploading and fusion. Fuzzy logic method is also used by cluster heads for local decision, and then the local decision results are sent to the base station. Decision-level fusion for final decision of event is performed by base station according to the uploaded local decisions and fusion support degree of clusters calculated by fuzzy logic method. The effectiveness of this algorithm is demonstrated by simulation results.

  14. Deep Convolutional Networks for Event Reconstruction and Particle Tagging on NOvA and DUNE

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Deep Convolutional Neural Networks (CNNs) have been widely applied in computer vision to solve complex problems in image recognition and analysis. In recent years many efforts have emerged to extend the use of this technology to HEP applications, including the Convolutional Visual Network (CVN), our implementation for identification of neutrino events. In this presentation I will describe the core concepts of CNNs, the details of our particular implementation in the Caffe framework and our application to identify NOvA events. NOvA is a long baseline neutrino experiment whose main goal is the measurement of neutrino oscillations. This relies on the accurate identification and reconstruction of the neutrino flavor in the interactions we observe. In 2016 the NOvA experiment released results for the observation of oscillations in the ν μ → ν e channel, the first HEP result employing CNNs. I will also discuss our approach at event identification on NOvA as well as recent developments in the application of CNN...

  15. TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications.

    Science.gov (United States)

    Costa, Daniel G; Duran-Faundez, Cristian; Andrade, Daniel C; Rocha-Junior, João B; Peixoto, João Paulo Just

    2018-04-03

    Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter , and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

  16. TwitterSensing: An Event-Based Approach for Wireless Sensor Networks Optimization Exploiting Social Media in Smart City Applications

    Directory of Open Access Journals (Sweden)

    Daniel G. Costa

    2018-04-01

    Full Text Available Modern cities are subject to periodic or unexpected critical events, which may bring economic losses or even put people in danger. When some monitoring systems based on wireless sensor networks are deployed, sensing and transmission configurations of sensor nodes may be adjusted exploiting the relevance of the considered events, but efficient detection and classification of events of interest may be hard to achieve. In Smart City environments, several people spontaneously post information in social media about some event that is being observed and such information may be mined and processed for detection and classification of critical events. This article proposes an integrated approach to detect and classify events of interest posted in social media, notably in Twitter, and the assignment of sensing priorities to source nodes. By doing so, wireless sensor networks deployed in Smart City scenarios can be optimized for higher efficiency when monitoring areas under the influence of the detected events.

  17. Energy efficient data representation and aggregation with event region detection in wireless sensor networks

    Science.gov (United States)

    Banerjee, Torsha

    Unlike conventional networks, wireless sensor networks (WSNs) are limited in power, have much smaller memory buffers, and possess relatively slower processing speeds. These characteristics necessitate minimum transfer and storage of information in order to prolong the network lifetime. In this dissertation, we exploit the spatio-temporal nature of sensor data to approximate the current values of the sensors based on readings obtained from neighboring sensors and itself. We propose a Tree based polynomial REGression algorithm, (TREG) that addresses the problem of data compression in wireless sensor networks. Instead of aggregated data, a polynomial function (P) is computed by the regression function, TREG. The coefficients of P are then passed to achieve the following goals: (i) The sink can get attribute values in the regions devoid of sensor nodes, and (ii) Readings over any portion of the region can be obtained at one time by querying the root of the tree. As the size of the data packet from each tree node to its parent remains constant, the proposed scheme scales very well with growing network density or increased coverage area. Since physical attributes exhibit a gradual change over time, we propose an iterative scheme, UPDATE_COEFF, which obviates the need to perform the regression function repeatedly and uses approximations based on previous readings. Extensive simulations are performed on real world data to demonstrate the effectiveness of our proposed aggregation algorithm, TREG. Results reveal that for a network density of 0.0025 nodes/m2, a complete binary tree of depth 4 could provide the absolute error to be less than 6%. A data compression ratio of about 0.02 is achieved using our proposed algorithm, which is almost independent of the tree depth. In addition, our proposed updating scheme makes the aggregation process faster while maintaining the desired error bounds. We also propose a Polynomial-based scheme that addresses the problem of Event Region

  18. Teleradiology system analysis using a discrete event-driven block-oriented network simulator

    Science.gov (United States)

    Stewart, Brent K.; Dwyer, Samuel J., III

    1992-07-01

    Performance evaluation and trade-off analysis are the central issues in the design of communication networks. Simulation plays an important role in computer-aided design and analysis of communication networks and related systems, allowing testing of numerous architectural configurations and fault scenarios. We are using the Block Oriented Network Simulator (BONeS, Comdisco, Foster City, CA) software package to perform discrete, event- driven Monte Carlo simulations in capacity planning, tradeoff analysis and evaluation of alternate architectures for a high-speed, high-resolution teleradiology project. A queuing network model of the teleradiology system has been devise, simulations executed and results analyzed. The wide area network link uses a switched, dial-up N X 56 kbps inverting multiplexer where the number of digital voice-grade lines (N) can vary from one (DS-0) through 24 (DS-1). The proposed goal of such a system is 200 films (2048 X 2048 X 12-bit) transferred between a remote and local site in an eight hour period with a mean delay time less than five minutes. It is found that: (1) the DS-1 service limit is around 100 films per eight hour period with a mean delay time of 412 +/- 39 seconds, short of the goal stipulated above; (2) compressed video teleconferencing can be run simultaneously with image data transfer over the DS-1 wide area network link without impacting the performance of the described teleradiology system; (3) there is little sense in upgrading to a higher bandwidth WAN link like DS-2 or DS-3 for the current system; and (4) the goal of transmitting 200 films in an eight hour period with a mean delay time less than five minutes can be achieved simply if the laser printer interface is updated from the current DR-11W interface to a much faster SCSI interface.

  19. Disentangling the Attention Network Test: Behavioral, Event Related Potentials and neural source analyses.

    Directory of Open Access Journals (Sweden)

    Alejandro eGalvao-Carmona

    2014-10-01

    Full Text Available Background. The study of the attentional system remains a challenge for current neuroscience. The Attention Network Test (ANT was designed to study simultaneously three different attentional networks (alerting, orienting and executive based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks. In particular, it is highly relevant that several interpretations about attentional impairment have arisen from these calculations in diverse pathologies. Event Related Potentials (ERPs and neural source analysis can be applied to disentangle the relationships between these attentional networks not specifically shown by behavioural measures. Results. This study shows that there is a basic level of alerting (tonic alerting in the no cue condition, represented by a slow negative trend in the ERP trace prior to the onset of the target stimuli. A progressive increase in the CNV amplitude related to the amount of information provided by the cue conditions is also shown. Neural source analysis reveals specific modulations of the CNV related to a task-related expectancy presented in the no cue condition; a late modulation triggered by the central cue condition and probably representing a generic motor preparation; and an early and late modulation for spatial cue condition suggesting specific motor and sensory preactivation. Finally, the first component in the information processing of the target stimuli modulated by the interaction between orienting network and the executive system can be represented by N1. Conclusions. The ANT is useful as a paradigm to study specific attentional mechanisms and their interactions. However, calculation of network effects is based in subtractions with non-comparable experimental conditions, as evidenced by the present data, which can induce misinterpretations in the study of the attentional capacity in human

  20. Event-triggered synchronization for reaction-diffusion complex networks via random sampling

    Science.gov (United States)

    Dong, Tao; Wang, Aijuan; Zhu, Huiyun; Liao, Xiaofeng

    2018-04-01

    In this paper, the synchronization problem of the reaction-diffusion complex networks (RDCNs) with Dirichlet boundary conditions is considered, where the data is sampled randomly. An event-triggered controller based on the sampled data is proposed, which can reduce the number of controller and the communication load. Under this strategy, the synchronization problem of the diffusion complex network is equivalently converted to the stability of a of reaction-diffusion complex dynamical systems with time delay. By using the matrix inequality technique and Lyapunov method, the synchronization conditions of the RDCNs are derived, which are dependent on the diffusion term. Moreover, it is found the proposed control strategy can get rid of the Zeno behavior naturally. Finally, a numerical example is given to verify the obtained results.

  1. Neural network approach in multichannel auditory event-related potential analysis.

    Science.gov (United States)

    Wu, F Y; Slater, J D; Ramsay, R E

    1994-04-01

    Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

  2. A statistical framework for evaluating neural networks to predict recurrent events in breast cancer

    Science.gov (United States)

    Gorunescu, Florin; Gorunescu, Marina; El-Darzi, Elia; Gorunescu, Smaranda

    2010-07-01

    Breast cancer is the second leading cause of cancer deaths in women today. Sometimes, breast cancer can return after primary treatment. A medical diagnosis of recurrent cancer is often a more challenging task than the initial one. In this paper, we investigate the potential contribution of neural networks (NNs) to support health professionals in diagnosing such events. The NN algorithms are tested and applied to two different datasets. An extensive statistical analysis has been performed to verify our experiments. The results show that a simple network structure for both the multi-layer perceptron and radial basis function can produce equally good results, not all attributes are needed to train these algorithms and, finally, the classification performances of all algorithms are statistically robust. Moreover, we have shown that the best performing algorithm will strongly depend on the features of the datasets, and hence, there is not necessarily a single best classifier.

  3. Convolutional neural networks for event-related potential detection: impact of the architecture.

    Science.gov (United States)

    Cecotti, H

    2017-07-01

    The detection of brain responses at the single-trial level in the electroencephalogram (EEG) such as event-related potentials (ERPs) is a difficult problem that requires different processing steps to extract relevant discriminant features. While most of the signal and classification techniques for the detection of brain responses are based on linear algebra, different pattern recognition techniques such as convolutional neural network (CNN), as a type of deep learning technique, have shown some interests as they are able to process the signal after limited pre-processing. In this study, we propose to investigate the performance of CNNs in relation of their architecture and in relation to how they are evaluated: a single system for each subject, or a system for all the subjects. More particularly, we want to address the change of performance that can be observed between specifying a neural network to a subject, or by considering a neural network for a group of subjects, taking advantage of a larger number of trials from different subjects. The results support the conclusion that a convolutional neural network trained on different subjects can lead to an AUC above 0.9 by using an appropriate architecture using spatial filtering and shift invariant layers.

  4. Discrete event command and control for networked teams with multiple missions

    Science.gov (United States)

    Lewis, Frank L.; Hudas, Greg R.; Pang, Chee Khiang; Middleton, Matthew B.; McMurrough, Christopher

    2009-05-01

    During mission execution in military applications, the TRADOC Pamphlet 525-66 Battle Command and Battle Space Awareness capabilities prescribe expectations that networked teams will perform in a reliable manner under changing mission requirements, varying resource availability and reliability, and resource faults. In this paper, a Command and Control (C2) structure is presented that allows for computer-aided execution of the networked team decision-making process, control of force resources, shared resource dispatching, and adaptability to change based on battlefield conditions. A mathematically justified networked computing environment is provided called the Discrete Event Control (DEC) Framework. DEC has the ability to provide the logical connectivity among all team participants including mission planners, field commanders, war-fighters, and robotic platforms. The proposed data management tools are developed and demonstrated on a simulation study and an implementation on a distributed wireless sensor network. The results show that the tasks of multiple missions are correctly sequenced in real-time, and that shared resources are suitably assigned to competing tasks under dynamically changing conditions without conflicts and bottlenecks.

  5. Computer-Aided Analysis of Flow in Water Pipe Networks after a Seismic Event

    Directory of Open Access Journals (Sweden)

    Won-Hee Kang

    2017-01-01

    Full Text Available This paper proposes a framework for a reliability-based flow analysis for a water pipe network after an earthquake. For the first part of the framework, we propose to use a modeling procedure for multiple leaks and breaks in the water pipe segments of a network that has been damaged by an earthquake. For the second part, we propose an efficient system-level probabilistic flow analysis process that integrates the matrix-based system reliability (MSR formulation and the branch-and-bound method. This process probabilistically predicts flow quantities by considering system-level damage scenarios consisting of combinations of leaks and breaks in network pipes and significantly reduces the computational cost by sequentially prioritizing the system states according to their likelihoods and by using the branch-and-bound method to select their partial sets. The proposed framework is illustrated and demonstrated by examining two example water pipe networks that have been subjected to a seismic event. These two examples consist of 11 and 20 pipe segments, respectively, and are computationally modeled considering their available topological, material, and mechanical properties. Considering different earthquake scenarios and the resulting multiple leaks and breaks in the water pipe segments, the water flows in the segments are estimated in a computationally efficient manner.

  6. Morphogenesis in sea urchin embryos: linking cellular events to gene regulatory network states

    Science.gov (United States)

    Lyons, Deidre; Kaltenbach, Stacy; McClay, David R.

    2013-01-01

    Gastrulation in the sea urchin begins with ingression of the primary mesenchyme cells (PMCs) at the vegetal pole of the embryo. After entering the blastocoel the PMCs migrate, form a syncitium, and synthesize the skeleton of the embryo. Several hours after the PMCs ingress the vegetal plate buckles to initiate invagination of the archenteron. That morphogenetic process occurs in several steps. The non-skeletogenic cells produce the initial inbending of the vegetal plate. Endoderm cells then rearrange and extend the length of the gut across the blastocoel to a target near the animal pole. Finally, cells that will form part of the midgut and hindgut are added to complete gastrulation. Later, the stomodeum invaginates from the oral ectoderm and fuses with the foregut to complete the archenteron. In advance of, and during these morphogenetic events an increasingly complex gene regulatory network controls the specification and the cell biological events that conduct the gastrulation movements. PMID:23801438

  7. A Distributed Compressive Sensing Scheme for Event Capture in Wireless Visual Sensor Networks

    Science.gov (United States)

    Hou, Meng; Xu, Sen; Wu, Weiling; Lin, Fei

    2018-01-01

    Image signals which acquired by wireless visual sensor network can be used for specific event capture. This event capture is realized by image processing at the sink node. A distributed compressive sensing scheme is used for the transmission of these image signals from the camera nodes to the sink node. A measurement and joint reconstruction algorithm for these image signals are proposed in this paper. Make advantage of spatial correlation between images within a sensing area, the cluster head node which as the image decoder can accurately co-reconstruct these image signals. The subjective visual quality and the reconstruction error rate are used for the evaluation of reconstructed image quality. Simulation results show that the joint reconstruction algorithm achieves higher image quality at the same image compressive rate than the independent reconstruction algorithm.

  8. Timing System Solution for MedAustron; Real-time Event and Data Distribution Network

    CERN Document Server

    Štefanič, R; Dedič, J; Gutleber, J; Moser, R

    2011-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVI...

  9. Event Based Simulator for Parallel Computing over the Wide Area Network for Real Time Visualization

    Science.gov (United States)

    Sundararajan, Elankovan; Harwood, Aaron; Kotagiri, Ramamohanarao; Satria Prabuwono, Anton

    As the computational requirement of applications in computational science continues to grow tremendously, the use of computational resources distributed across the Wide Area Network (WAN) becomes advantageous. However, not all applications can be executed over the WAN due to communication overhead that can drastically slowdown the computation. In this paper, we introduce an event based simulator to investigate the performance of parallel algorithms executed over the WAN. The event based simulator known as SIMPAR (SIMulator for PARallel computation), simulates the actual computations and communications involved in parallel computation over the WAN using time stamps. Visualization of real time applications require steady stream of processed data flow for visualization purposes. Hence, SIMPAR may prove to be a valuable tool to investigate types of applications and computing resource requirements to provide uninterrupted flow of processed data for real time visualization purposes. The results obtained from the simulation show concurrence with the expected performance using the L-BSP model.

  10. Digital Learning Network Education Events for the Desert Research and Technology Studies

    Science.gov (United States)

    Paul, Heather L.; Guillory, Erika R.

    2007-01-01

    NASA s Digital Learning Network (DLN) reaches out to thousands of students each year through video conferencing and webcasting. As part of NASA s Strategic Plan to reach the next generation of space explorers, the DLN develops and delivers educational programs that reinforce principles in the areas of science, technology, engineering and mathematics. The DLN has created a series of live education videoconferences connecting the Desert Research and Technology Studies (RATS) field test to students across the United States. The programs are also extended to students around the world via live webcasting. The primary focus of the events is the Vision for Space Exploration. During the programs, Desert RATS engineers and scientists inform and inspire students about the importance of exploration and share the importance of the field test as it correlates with plans to return to the Moon and explore Mars. This paper describes the events that took place in September 2006.

  11. Applying Bayesian neural networks to event reconstruction in reactor neutrino experiments

    International Nuclear Information System (INIS)

    Xu Ye; Xu Weiwei; Meng Yixiong; Zhu Kaien; Xu Wei

    2008-01-01

    A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The electron samples from the Monte-Carlo simulation of the toy detector have been reconstructed by the method of Bayesian neural networks (BNNs) and the standard algorithm, a maximum likelihood method (MLD), respectively. The result of the event reconstruction using BNN has been compared with the one using MLD. Compared to MLD, the uncertainties of the electron vertex are not improved, but the energy resolutions are significantly improved using BNN. And the improvement is more obvious for the high energy electrons than the low energy ones

  12. Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

    Science.gov (United States)

    Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

    2010-01-01

    This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

  13. Source Space Analysis of Event-Related Dynamic Reorganization of Brain Networks

    Directory of Open Access Journals (Sweden)

    Andreas A. Ioannides

    2012-01-01

    Full Text Available How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

  14. Source space analysis of event-related dynamic reorganization of brain networks.

    Science.gov (United States)

    Ioannides, Andreas A; Dimitriadis, Stavros I; Saridis, George A; Voultsidou, Marotesa; Poghosyan, Vahe; Liu, Lichan; Laskaris, Nikolaos A

    2012-01-01

    How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

  15. Decentralized event-triggered consensus control strategy for leader-follower networked systems

    Science.gov (United States)

    Zhang, Shouxu; Xie, Duosi; Yan, Weisheng

    2017-08-01

    In this paper, the consensus problem of leader-follower networked systems is addressed. At first, a centralized and a decentralized event-triggered control strategy are proposed, which make the control actuators of followers update at aperiodic invent interval. In particular, the latter one makes each follower requires the local information only. After that, an improved triggering function that only uses the follower's own information and the neighbors' states at their latest event instants is developed to relax the requirement of the continuous state of the neighbors. In addition, the strategy does not require the information of the topology, nor the eigenvalues of the Laplacian matrix. And if the follower does not have direct connection to the leader, the leader's information is not required either. It is analytically shown that by using the proposed strategy the leader-follower networked system is able to reach consensus without continuous communication among followers. Simulation examples are given to show effectiveness of the proposed control strategy.

  16. Prediction of Increasing Production Activities using Combination of Query Aggregation on Complex Events Processing and Neural Network

    Directory of Open Access Journals (Sweden)

    Achmad Arwan

    2016-07-01

    Full Text Available AbstrakProduksi, order, penjualan, dan pengiriman adalah serangkaian event yang saling terkait dalam industri manufaktur. Selanjutnya hasil dari event tersebut dicatat dalam event log. Complex Event Processing adalah metode yang digunakan untuk menganalisis apakah terdapat pola kombinasi peristiwa tertentu (peluang/ancaman yang terjadi pada sebuah sistem, sehingga dapat ditangani secara cepat dan tepat. Jaringan saraf tiruan adalah metode yang digunakan untuk mengklasifikasi data peningkatan proses produksi. Hasil pencatatan rangkaian proses yang menyebabkan peningkatan produksi digunakan sebagai data latih untuk mendapatkan fungsi aktivasi dari jaringan saraf tiruan. Penjumlahan hasil catatan event log dimasukkan ke input jaringan saraf tiruan untuk perhitungan nilai aktivasi. Ketika nilai aktivasi lebih dari batas yang ditentukan, maka sistem mengeluarkan sinyal untuk meningkatkan produksi, jika tidak, sistem tetap memantau kejadian. Hasil percobaan menunjukkan bahwa akurasi dari metode ini adalah 77% dari 39 rangkaian aliran event.Kata kunci: complex event processing, event, jaringan saraf tiruan, prediksi peningkatan produksi, proses. AbstractProductions, orders, sales, and shipments are series of interrelated events within manufacturing industry. Further these events were recorded in the event log. Complex event processing is a method that used to analyze whether there are patterns of combinations of certain events (opportunities / threats that occur in a system, so it can be addressed quickly and appropriately. Artificial neural network is a method that we used to classify production increase activities. The series of events that cause the increase of the production used as a dataset to train the weight of neural network which result activation value. An aggregate stream of events inserted into the neural network input to compute the value of activation. When the value is over a certain threshold (the activation value results

  17. LEONA: Transient Luminous Event and Thunderstorm High Energy Emission Collaborative Network in Latin America

    Science.gov (United States)

    Sao Sabbas, F. T.

    2012-12-01

    This project has the goal of establishing the Collaborative Network LEONA, to study the electrodynamical coupling of the atmospheric layers signaled by Transient Luminous Events - TLEs and high energy emissions from thunderstorms. We will develop and install a remotely controlled network of cameras to perform TLE observations in different locations in South America and one neutron detector in southern Brazil. The camera network will allow building a continuous data set of the phenomena studied in this continent. The first two trial units of the camera network are already installed, in Brazil and Peru, and two more will be installed until December 2012, in Argentina and Brazil. We expect to determine the TLE geographic distribution, occurrence rate, morphology, and possible coupling with other geophysical phenomena in South America, such as the South Atlantic Magnetic Anomaly - SAMA. We also expect to study thunderstorm neutron emissions in a region of intense electrical activity, measuring neutron fluxes with high time resolution simultaneously with TLEs and lightning for the first time in South America. Using an intensified high-speed camera for TLE observation during 2 campaigns we expect to be able to determine the duration and spatial- temporal development of the TLEs observed, to study the structure and initiation of sprites and to measure the velocity of development of sprite structures and the sprite delay. The camera was acquired via the FAPESP project DEELUMINOS (2005-2010), which also nucleated our research group Atmospheric Electrodynamical Coupling - ACATMOS. LEONA will nucleate this research in other institutions in Brazil and other countries in South America, providing continuity for this important research in our region. The camera network will be an unique tool to perform consistent long term TLE observation, and in fact is the only way to accumulate a data set for a climatological study of South America, since satellite instrumentation turns off in

  18. Group Sex Events and HIV/STI Risk in an Urban Network

    Science.gov (United States)

    Friedman, Samuel R.; Bolyard, Melissa; Khan, Maria; Maslow, Carey; Sandoval, Milagros; Mateu-Gelabert, Pedro; Krauss, Beatrice; Aral, Sevgi O.

    2012-01-01

    Objectives To describe: a. the prevalence and individual and network characteristics of group sex events (GSE) and GSE attendees; and b. HIV/STI discordance among respondents who said they went to a GSE together. Methods and Design In a sociometric network study of risk partners (defined as sexual partners, persons with whom respondents attended a GSE, or drug-injection partners) in Brooklyn, NY, we recruited a high-risk sample of 465 adults. Respondents reported on GSE attendance, the characteristics of GSEs, and their own and others’ behaviors at GSEs. Sera and urines were collected and STI prevalence was assayed. Results Of the 465 participants, 36% had attended a GSE in the last year, 26% had sex during the most recent of these GSEs, and 13% had unprotected sex there. Certain subgroups (hard drug users, men who have sex with men, women who have sex with women, and sex workers) were more likely to attend and more likely to engage in risk behaviors at these events. Among 90 GSE dyads in which at least one partner named the other as someone with whom they attended a GSE in the previous three months, STI/HIV discordance was common (HSV-2: 45% of dyads, HIV: 12% of dyads, Chlamydia: 21% of dyads). Many GSEs had 10 or more participants, and multiple partnerships at GSEs were common. High attendance rates at GSEs among members of large networks may increase community vulnerability to STI/HIV, particularly since network data show that almost all members of a large sociometric risk network either had sex with a GSE attendee or had sex with someone who had sex with a GSE attended. Conclusions Self-reported GSE attendance and participation was common among this high-risk sample. STI/HIV discordance among GSE attendees was high, highlighting the potential transmission risk associated with GSEs. Research on sexual behaviors should incorporate measures of GSE behaviors as standard research protocol. Interventions should be developed to reduce transmission at GSEs. PMID

  19. A discrete event simulation model for evaluating time delays in a pipeline network

    Energy Technology Data Exchange (ETDEWEB)

    Spricigo, Deisi; Muggiati, Filipe V.; Lueders, Ricardo; Neves Junior, Flavio [Federal University of Technology of Parana (UTFPR), Curitiba, PR (Brazil)

    2009-07-01

    Currently in the oil industry the logistic chain stands out as a strong candidate to obtain highest profit, since recent studies have pointed out to a cost reduction by adoption of better policies for distribution of oil derivatives, particularly those where pipelines are used to transport products. Although there are models to represent transfers of oil derivatives in pipelines, they are quite complex and computationally burden. In this paper, we are interested on models that are less detailed in terms of fluid dynamics but provide more information about operational decisions in a pipeline network. We propose a discrete event simulation model in ARENA that allows simulating a pipeline network based on average historical data. Time delays for transferring different products can be evaluated through different routes. It is considered that transport operations follow a historical behavior and average time delays can thus be estimated within certain bounds. Due to its stochastic nature, time quantities are characterized by average and dispersion measures. This allows comparing different operational scenarios for product transportation. Simulation results are compared to data obtained from a real world pipeline network and different scenarios of production and demand are analyzed. (author)

  20. A Community-Based Event Delivery Protocol in Publish/Subscribe Systems for Delay Tolerant Sensor Networks

    Directory of Open Access Journals (Sweden)

    Haigang Gong

    2009-09-01

    Full Text Available The basic operation of a Delay Tolerant Sensor Network (DTSN is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

  1. A community-based event delivery protocol in publish/subscribe systems for delay tolerant sensor networks.

    Science.gov (United States)

    Liu, Nianbo; Liu, Ming; Zhu, Jinqi; Gong, Haigang

    2009-01-01

    The basic operation of a Delay Tolerant Sensor Network (DTSN) is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short) paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

  2. Acoustic Event Detection in Multichannel Audio Using Gated Recurrent Neural Networks with High‐Resolution Spectral Features

    Directory of Open Access Journals (Sweden)

    Hyoung‐Gook Kim

    2017-12-01

    Full Text Available Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception‐based spatial and spectral‐domain noise‐reduced harmonic features are extracted from multichannel audio and used as high‐resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short‐term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

  3. Digital Learning Network Education Events of NASA's Extreme Environments Mission Operations

    Science.gov (United States)

    Paul, Heather; Guillory, Erika

    2007-01-01

    NASA's Digital Learning Network (DLN) reaches out to thousands of students each year through video conferencing and web casting. The DLN has created a series of live education videoconferences connecting NASA s Extreme Environment Missions Operations (NEEMO) team to students across the United States. The programs are also extended to students around the world live web casting. The primary focus of the events is the vision for space exploration. During the programs, NEEMO Crewmembers including NASA astronauts, engineers and scientists inform and inspire students about the importance of exploration and share the impact of the project as it correlates with plans to return to the moon and explore the planet Mars. These events highlight interactivity. Students talk live with the aquanauts in Aquarius, the National Oceanic and Atmospheric Administration s underwater laboratory. With this program, NASA continues the Agency s tradition of investing in the nation's education programs. It is directly tied to the Agency's major education goal of attracting and retaining students in science, technology, and engineering disciplines. Before connecting with the aquanauts, the students conduct experiments of their own designed to coincide with mission objectives. This paper describes the events that took place in September 2006.

  4. Under-Frequency Load Shedding Technique Considering Event-Based for an Islanded Distribution Network

    Directory of Open Access Journals (Sweden)

    Hasmaini Mohamad

    2016-06-01

    Full Text Available One of the biggest challenge for an islanding operation is to sustain the frequency stability. A large power imbalance following islanding would cause under-frequency, hence an appropriate control is required to shed certain amount of load. The main objective of this research is to develop an adaptive under-frequency load shedding (UFLS technique for an islanding system. The technique is designed considering an event-based which includes the moment system is islanded and a tripping of any DG unit during islanding operation. A disturbance magnitude is calculated to determine the amount of load to be shed. The technique is modeled by using PSCAD simulation tool. A simulation studies on a distribution network with mini hydro generation is carried out to evaluate the UFLS model. It is performed under different load condition: peak and base load. Results show that the load shedding technique have successfully shed certain amount of load and stabilized the system frequency.

  5. DECISION WITH ARTIFICIAL NEURAL NETWORKS IN DISCRETE EVENT SIMULATION MODELS ON A TRAFFIC SYSTEM

    Directory of Open Access Journals (Sweden)

    Marília Gonçalves Dutra da Silva

    2016-04-01

    Full Text Available ABSTRACT This work aims to demonstrate the use of a mechanism to be applied in the development of the discrete-event simulation models that perform decision operations through the implementation of an artificial neural network. Actions that involve complex operations performed by a human agent in a process, for example, are often modeled in simplified form with the usual mechanisms of simulation software. Therefore, it was chosen a traffic system controlled by a traffic officer with a flow of vehicles and pedestrians to demonstrate the proposed solution. From a module built in simulation software itself, it was possible to connect the algorithm for intelligent decision to the simulation model. The results showed that the model elaborated responded as expected when it was submitted to actions, which required different decisions to maintain the operation of the system with changes in the flow of people and vehicles.

  6. Timing system solution for MedAustron; Real-time event and data distribution network

    International Nuclear Information System (INIS)

    Stefanic, R.; Tavcar, R.; Dedic, J.; Gutleber, J.; Moser, R.

    2012-01-01

    MedAustron is an ion beam research and therapy centre under construction in Wiener Neustadt, Austria. The facility features a synchrotron particle accelerator for light ions. The timing system for this class of accelerators has been developed in close collaboration between MedAustron and Cosylab. Mitigating economical and technological risks, we have chosen a proven, widely used Micro Research Finland (MRF) timing equipment and redesigned its FPGA firmware, extending its high-logic services above transport layer, as required by machine specifics. We obtained a generic real-time broadcast network for coordinating actions of a compact, pulse-to-pulse modulation based particle accelerator. High-level services include support for virtual accelerators and a rich selection of event response mechanisms. The system uses a combination of a real-time link for downstream events and a non-real-time link for upstream messaging and non time-critical communication. It comes with National Instruments LabVIEW-based software support, ready to be integrated into PXIe based front-end controllers. This article explains the high level logic services provided by the real-time link, describes the non-real-time interfaces and presents the software configuration mechanisms. (authors)

  7. Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

    Directory of Open Access Journals (Sweden)

    Andrzej Pawlowski

    2009-01-01

    Full Text Available Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

  8. Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

    Science.gov (United States)

    Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

    2009-01-01

    Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

  9. Sentiment Diffusion of Public Opinions about Hot Events: Based on Complex Network.

    Directory of Open Access Journals (Sweden)

    Xiaoqing Hao

    Full Text Available To study the sentiment diffusion of online public opinions about hot events, we collected people's posts through web data mining techniques. We calculated the sentiment value of each post based on a sentiment dictionary. Next, we divided those posts into five different orientations of sentiments: strongly positive (P, weakly positive (p, neutral (o, weakly negative (n, and strongly negative (N. These sentiments are combined into modes through coarse graining. We constructed sentiment mode complex network of online public opinions (SMCOP with modes as nodes and the conversion relation in chronological order between different types of modes as edges. We calculated the strength, k-plex clique, clustering coefficient and betweenness centrality of the SMCOP. The results show that the strength distribution obeys power law. Most posts' sentiments are weakly positive and neutral, whereas few are strongly negative. There are weakly positive subgroups and neutral subgroups with ppppp and ooooo as the core mode, respectively. Few modes have larger betweenness centrality values and most modes convert to each other with these higher betweenness centrality modes as mediums. Therefore, the relevant person or institutes can take measures to lead people's sentiments regarding online hot events according to the sentiment diffusion mechanism.

  10. An efficient routing algorithm for event based monitoring in a plant using virtual sink nodes in a wireless sensor network

    International Nuclear Information System (INIS)

    Jain, Sanjay Kumar; Vietla, Srinivas; Roy, D.A.; Biswas, B.B.; Pithawa, C.K.

    2010-01-01

    A Wireless Sensor Network is a collection of wireless sensor nodes arranged in a self-forming network without aid of any infrastructure or administration. The individual nodes have limited resources and hence efficient communication mechanisms between the nodes have to be devised for continued operation of the network in a plant environment. In wireless sensor networks a sink node or base station at one end acts as the recipient of information gathered by all other sensor nodes in the network and the information arrives at the sink through multiple hops across the nodes of the network. A routing algorithm has been developed in which a virtual sink node is generated whenever hop count of an ordinary node crosses a certain specified value. The virtual sink node acts as a recipient node for data of all neighboring nodes. This virtual sink helps in reducing routing overhead, especially when the sensor network is scaled to a larger network. The advantages with this scheme are less energy consumption, reduced congestion in the network and longevity of the network. The above algorithm is suitable for event based or interval based monitoring systems in nuclear plants. This paper describes the working of the proposed algorithm and provides its implementation details. (author)

  11. Towards a whole-network risk assessment for railway bridge failures caused by scour during flood events

    Directory of Open Access Journals (Sweden)

    Lamb Rob

    2016-01-01

    Full Text Available Localised erosion (scour during flood flow conditions can lead to costly damage or catastrophic failure of bridges, and in some cases loss of life or significant disruption to transport networks. Here, we take a broad scale view to assess risk associated with bridge scour during flood events over an entire infrastructure network, illustrating the analysis with data from the British railways. There have been 54 recorded events since 1846 in which scour led to the failure of railway bridges in Britain. These events tended to occur during periods of extremely high river flow, although there is uncertainty about the precise conditions under which failures occur, which motivates a probabilistic analysis of the failure events. We show how data from the historical bridge failures, combined with hydrological analysis, have been used to construct fragility curves that quantify the conditional probability of bridge failure as a function of river flow, accompanied by estimates of the associated uncertainty. The new fragility analysis is tested using flood events simulated from a national, spatial joint probability model for extremes in river flows. The combined models appear robust in comparison with historical observations of the expected number of bridge failures in a flood event, and provide an empirical basis for further broad-scale network risk analysis.

  12. Discrete event simulation methods applied to advanced importance measures of repairable components in multistate network flow systems

    International Nuclear Information System (INIS)

    Huseby, Arne B.; Natvig, Bent

    2013-01-01

    Discrete event models are frequently used in simulation studies to model and analyze pure jump processes. A discrete event model can be viewed as a system consisting of a collection of stochastic processes, where the states of the individual processes change as results of various kinds of events occurring at random points of time. We always assume that each event only affects one of the processes. Between these events the states of the processes are considered to be constant. In the present paper we use discrete event simulation in order to analyze a multistate network flow system of repairable components. In order to study how the different components contribute to the system, it is necessary to describe the often complicated interaction between component processes and processes at the system level. While analytical considerations may throw some light on this, a simulation study often allows the analyst to explore more details. By producing stable curve estimates for the development of the various processes, one gets a much better insight in how such systems develop over time. These methods are particulary useful in the study of advanced importancez measures of repairable components. Such measures can be very complicated, and thus impossible to calculate analytically. By using discrete event simulations, however, this can be done in a very natural and intuitive way. In particular significant differences between the Barlow–Proschan measure and the Natvig measure in multistate network flow systems can be explored

  13. Cardiovascular events in patients with mild autonomous cortisol secretion: analysis with artificial neural networks.

    Science.gov (United States)

    Morelli, Valentina; Palmieri, Serena; Lania, Andrea; Tresoldi, Alberto; Corbetta, Sabrina; Cairoli, Elisa; Eller-Vainicher, Cristina; Arosio, Maura; Copetti, Massimiliano; Grossi, Enzo; Chiodini, Iacopo

    2017-07-01

    The independent role of mild autonomous cortisol secretion (ACS) in influencing the cardiovascular event (CVE) occurrence is a topic of interest. We investigated the role of mild ACS in the CVE occurrence in patients with adrenal incidentaloma (AI) by standard statistics and artificial neural networks (ANNs). We analyzed a retrospective record of 518 AI patients. Data regarding cortisol levels after 1 mg dexamethasone suppression (1 mg DST) and the presence of obesity (OB), hypertension (AH), type-2 diabetes (T2DM), dyslipidemia (DL), familial CVE history, smoking habit and CVE were collected. The receiver-operating characteristic curve analysis suggested that 1 mg DST, at a cut-off of 1.8 µg/dL, had the best accuracy for detecting patients with increased CVE risk. In patients with 1 mg-DST ≥1.8 µg/dL (DST+, n  = 223), age and prevalence of AH, T2DM, DL and CVE (66 years, 74.5, 25.9, 41.4 and 26.8% respectively) were higher than that of patients with 1 mg-DST ≤1.8 µg/dL (61.9 years, 60.7, 18.5, 32.9 and 10%, respectively, P  Cortisol after 1 mg-DST is independently associated with the CVE occurrence. The ANNs might help for assessing the CVE risk in AI patients. © 2017 European Society of Endocrinology.

  14. VA Suicide Prevention Applications Network: A National Health Care System-Based Suicide Event Tracking System.

    Science.gov (United States)

    Hoffmire, Claire; Stephens, Brady; Morley, Sybil; Thompson, Caitlin; Kemp, Janet; Bossarte, Robert M

    2016-11-01

    The US Department of Veterans Affairs' Suicide Prevention Applications Network (SPAN) is a national system for suicide event tracking and case management. The objective of this study was to assess data on suicide attempts among people using Veterans Health Administration (VHA) services. We assessed the degree of data overlap on suicide attempters reported in SPAN and the VHA's medical records from October 1, 2010, to September 30, 2014-overall, by year, and by region. Data on suicide attempters in the VHA's medical records consisted of diagnoses documented with E95 codes from the International Classification of Diseases, Ninth Revision . Of 50 518 VHA patients who attempted suicide during the 4-year study period, data on fewer than half (41%) were reported in both SPAN and the medical records; nearly 65% of patients whose suicide attempt was recorded in SPAN had no data on attempted suicide in the VHA's medical records. Evaluation of administrative data suggests that use of SPAN substantially increases the collection of data on suicide attempters as compared with the use of medical records alone, but neither SPAN nor the VHA's medical records identify all suicide attempters. Further research is needed to better understand the strengths and limitations of both systems and how to best combine information across systems.

  15. Cooperative Control of Mobile Sensor Networks for Environmental Monitoring: An Event-Triggered Finite-Time Control Scheme.

    Science.gov (United States)

    Lu, Qiang; Han, Qing-Long; Zhang, Botao; Liu, Dongliang; Liu, Shirong

    2017-12-01

    This paper deals with the problem of environmental monitoring by developing an event-triggered finite-time control scheme for mobile sensor networks. The proposed control scheme can be executed by each sensor node independently and consists of two parts: one part is a finite-time consensus algorithm while the other part is an event-triggered rule. The consensus algorithm is employed to enable the positions and velocities of sensor nodes to quickly track the position and velocity of a virtual leader in finite time. The event-triggered rule is used to reduce the updating frequency of controllers in order to save the computational resources of sensor nodes. Some stability conditions are derived for mobile sensor networks with the proposed control scheme under both a fixed communication topology and a switching communication topology. Finally, simulation results illustrate the effectiveness of the proposed control scheme for the problem of environmental monitoring.

  16. Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks.

    Science.gov (United States)

    Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

    2017-10-27

    In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor's mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay.

  17. Trail-Based Search for Efficient Event Report to Mobile Actors in Wireless Sensor and Actor Networks

    Science.gov (United States)

    Xu, Zhezhuang; Liu, Guanglun; Yan, Haotian; Cheng, Bin; Lin, Feilong

    2017-01-01

    In wireless sensor and actor networks, when an event is detected, the sensor node needs to transmit an event report to inform the actor. Since the actor moves in the network to execute missions, its location is always unavailable to the sensor nodes. A popular solution is the search strategy that can forward the data to a node without its location information. However, most existing works have not considered the mobility of the node, and thus generate significant energy consumption or transmission delay. In this paper, we propose the trail-based search (TS) strategy that takes advantage of actor’s mobility to improve the search efficiency. The main idea of TS is that, when the actor moves in the network, it can leave its trail composed of continuous footprints. The search packet with the event report is transmitted in the network to search the actor or its footprints. Once an effective footprint is discovered, the packet will be forwarded along the trail until it is received by the actor. Moreover, we derive the condition to guarantee the trail connectivity, and propose the redundancy reduction scheme based on TS (TS-R) to reduce nontrivial transmission redundancy that is generated by the trail. The theoretical and numerical analysis is provided to prove the efficiency of TS. Compared with the well-known expanding ring search (ERS), TS significantly reduces the energy consumption and search delay. PMID:29077017

  18. Onset and Offset of Aversive Events Establish Distinct Memories Requiring Fear and Reward Networks

    Science.gov (United States)

    Andreatta, Marta; Fendt, Markus; Muhlberger, Andreas; Wieser, Matthias J.; Imobersteg, Stefan; Yarali, Ayse; Gerber, Bertram; Pauli, Paul

    2012-01-01

    Two things are worth remembering about an aversive event: What made it happen? What made it cease? If a stimulus precedes an aversive event, it becomes a signal for threat and will later elicit behavior indicating conditioned fear. However, if the stimulus is presented upon cessation of the aversive event, it elicits behavior indicating…

  19. International Networking for Young Scientists Event with Jenny Simanowitz and Symposium Gender and Science: Women Making Difference?

    Czech Academy of Sciences Publication Activity Database

    Červinková, Alice; Linková, Marcela

    2005-01-01

    Roč. 4, 1-2 (2005), s. 23-31 ISSN 1214-1909. [International Networking for Young Scientists Event with Jenny Simanowitz and . Vídeň, 28.02.05-01.03.05] R&D Projects: GA MŠk(CZ) 1P05OK459 Institutional research plan: CEZ:AV0Z70280505 Keywords : young women researchers * networking Subject RIV: AO - Sociology, Demography http://www.zenyaveda.cz/html/index.php?s1=1&s2=3&s3=4&lng=12&PHPSESSID=f20860b9711b5929d6c2a4dbc16511bb

  20. Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Wenbing [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Wang, Zidong [Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH (United Kingdom); Liu, Yurong, E-mail: yrliu@yzu.edu.cn [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia); Ding, Derui [Shanghai Key Lab of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093 (China); Alsaadi, Fuad E. [Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia)

    2017-01-05

    The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator. - Highlights: • An event-triggered estimator is designed for complex networks with time-varying delays. • A novel event generator function is proposed to reduce the communication burden. • The comparison principle is utilized to derive the sufficient conditions. • The designed triggering condition is shown to be free of the Zeno behavior.

  1. Performance Analysis with Network-Enhanced Complexities: On Fading Measurements, Event-Triggered Mechanisms, and Cyber Attacks

    Directory of Open Access Journals (Sweden)

    Derui Ding

    2014-01-01

    Full Text Available Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1 examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2 develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.

  2. Discrimination Analysis of Earthquakes and Man-Made Events Using ARMA Coefficients Determination by Artificial Neural Networks

    International Nuclear Information System (INIS)

    AllamehZadeh, Mostafa

    2011-01-01

    A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neural system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0–6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.

  3. Discrimination Analysis of Earthquakes and Man-Made Events Using ARMA Coefficients Determination by Artificial Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    AllamehZadeh, Mostafa, E-mail: dibaparima@yahoo.com [International Institute of Earthquake Engineering and Seismology (Iran, Islamic Republic of)

    2011-12-15

    A Quadratic Neural Networks (QNNs) model has been developed for identifying seismic source classification problem at regional distances using ARMA coefficients determination by Artificial Neural Networks (ANNs). We have devised a supervised neural system to discriminate between earthquakes and chemical explosions with filter coefficients obtained by windowed P-wave phase spectra (15 s). First, we preprocess the recording's signals to cancel out instrumental and attenuation site effects and obtain a compact representation of seismic records. Second, we use a QNNs system to obtain ARMA coefficients for feature extraction in the discrimination problem. The derived coefficients are then applied to the neural system to train and classification. In this study, we explore the possibility of using single station three-component (3C) covariance matrix traces from a priori-known explosion sites (learning) for automatically recognizing subsequent explosions from the same site. The results have shown that this feature extraction gives the best classifier for seismic signals and performs significantly better than other classification methods. The events have been tested, which include 36 chemical explosions at the Semipalatinsk test site in Kazakhstan and 61 earthquakes (mb = 5.0-6.5) recorded by the Iranian National Seismic Network (INSN). The 100% correct decisions were obtained between site explosions and some of non-site events. The above approach to event discrimination is very flexible as we can combine several 3C stations.

  4. Combining Neural Networks with Existing Methods to Estimate 1 in 100-Year Flood Event Magnitudes

    Science.gov (United States)

    Newson, A.; See, L.

    2005-12-01

    Over the last fifteen years artificial neural networks (ANN) have been shown to be advantageous for the solution of many hydrological modelling problems. The use of ANNs for flood magnitude estimation in ungauged catchments, however, is a relatively new and under researched area. In this paper ANNs are used to make estimates of the magnitude of the 100-year flood event (Q100) for a number of ungauged catchments. The data used in this study were provided by the Centre for Ecology and Hydrology's Flood Estimation Handbook (FEH), which contains information on catchments across the UK. Sixteen catchment descriptors for 719 catchments were used to train an ANN, which was split into a training, validation and test data set. The goodness-of-fit statistics on the test data set indicated good model performance, with an r-squared value of 0.8 and a coefficient of efficiency of 79 percent. Data for twelve ungauged catchments were then put through the trained ANN to produce estimates of Q100. Two other accepted methodologies were also employed: the FEH statistical method and the FSR (Flood Studies Report) design storm technique, both of which are used to produce flood frequency estimates. The advantage of developing an ANN model is that it provides a third figure to aid a hydrologist in making an accurate estimate. For six of the twelve catchments, there was a relatively low spread between estimates. In these instances, an estimate of Q100 could be made with a fair degree of certainty. Of the remaining six catchments, three had areas greater than 1000km2, which means the FSR design storm estimate cannot be used. Armed with the ANN model and the FEH statistical method the hydrologist still has two possible estimates to consider. For these three catchments, the estimates were also fairly similar, providing additional confidence to the estimation. In summary, the findings of this study have shown that an accurate estimation of Q100 can be made using the catchment descriptors of

  5. Enriched Encoding: Reward Motivation Organizes Cortical Networks for Hippocampal Detection of Unexpected Events

    OpenAIRE

    Murty, Vishnu P.; Adcock, R. Alison

    2013-01-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expec...

  6. Validation of the Revised Stressful Life Event Questionnaire Using a Hybrid Model of Genetic Algorithm and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Rasoul Sali

    2013-01-01

    Full Text Available Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12. A hybrid model of genetic algorithm (GA and artificial neural networks (ANNs was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale and the GHQ score as a response variable. In this model, GA is used in order to set some parameter of ANN for achieving more accurate results. Results. For each stressful life event, the number is defined as weight. Among all stressful life events, death of parents, spouse, or siblings is the most important and impactful stressor in the studied population. Sensitivity of 83% and specificity of 81% were obtained for the cut point 100. Conclusion. The SLE-revised (SLE-R questionnaire despite simplicity is a high-performance screening tool for investigating the stress level of life events and its management in both community and primary care settings. The SLE-R questionnaire is user-friendly and easy to be self-administered. This questionnaire allows the individuals to be aware of their own health status.

  7. How partnership behaviour evolves in networks : path dependency, social figuration and life events

    NARCIS (Netherlands)

    Romme, A.G.L.; Akkermans, H.A.

    2008-01-01

    Networks have become the dominant life form in many organizational settings. Most studies of relationships in networks focus on the dyadic interaction between two agents. However, work on enactment, sensemaking, path dependency, and social figuration processes (e.g. by Weick and Elias) suggests

  8. Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern United States

    Science.gov (United States)

    Garcia, Matthew; Peters-Lidard, Christa D.; Goodrich, David C.

    2008-05-01

    Inaccuracy in spatially distributed precipitation fields can contribute significantly to the uncertainty of hydrological states and fluxes estimated from land surface models. This paper examines the results of selected interpolation methods for both convective and mixed/stratiform events that occurred during the North American monsoon season over a dense gauge network at the U.S. Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed in the southwestern United States. The spatial coefficient of variation for the precipitation field is employed as an indicator of event morphology, and a gauge clustering factor CF is formulated as a new, scale-independent measure of network organization. We consider that CF 0 (clustering in the gauge network) will produce errors because of reduced areal representation of the precipitation field. Spatial interpolation is performed using both inverse-distance-weighted (IDW) and multiquadric-biharmonic (MQB) methods. We employ ensembles of randomly selected network subsets for the statistical evaluation of interpolation errors in comparison with the observed precipitation. The magnitude of interpolation errors and differences in accuracy between interpolation methods depend on both the density and the geometrical organization of the gauge network. Generally, MQB methods outperform IDW methods in terms of interpolation accuracy under all conditions, but it is found that the order of the IDW method is important to the results and may, under some conditions, be just as accurate as the MQB method. In almost all results it is demonstrated that the inverse-distance-squared method for spatial interpolation, commonly employed in operational analyses and for engineering assessments, is inferior to the ID-cubed method, which is also more computationally efficient than the MQB method in studies of large networks.

  9. Event-Based Impulsive Control of Continuous-Time Dynamic Systems and Its Application to Synchronization of Memristive Neural Networks.

    Science.gov (United States)

    Zhu, Wei; Wang, Dandan; Liu, Lu; Feng, Gang

    2017-08-18

    This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.

  10. Multiple Event Localization in a Sparse Acoustic Sensor Network Using UAVs as Data Mules

    Science.gov (United States)

    2012-12-01

    the events to arrive in different orders at the sensors. Consequently , simple rules to group the ToAs from an event at different sensors, such as...a Microhard radio to forward the ToAs to the mule-UAV. Two Procerus Unicorn UAVs were used with different payloads. The imaging- UAV was equipped

  11. Using wireless sensor networks to improve understanding of rain-on-snow events across the Sierra Nevada

    Science.gov (United States)

    Maurer, T.; Avanzi, F.; Oroza, C.; Malek, S. A.; Glaser, S. D.; Bales, R. C.; Conklin, M. H.

    2017-12-01

    We use data gathered from Wireless Sensor Networks (WSNs) between 2008 and 2017 to investigate the temporal/spatial patterns of rain-on-snow events in three river basins of California's Sierra Nevada. Rain-on-snow transitions occur across a broad elevation range (several hundred meters), both between storms and within a given storm, creating an opportunity to use spatially and temporally dense data to forecast and study them. WSNs collect snow depth; meteorological data; and soil moisture and temperature data across relatively dense sensor clusters. Ten to twelve measurement nodes per cluster are placed across 1-km2 areas in locations representative of snow patterns at larger scales. Combining precipitation and snow data from snow-pillow and climate stations with an estimation of dew-point temperature from WSNs, we determine the frequency, timing, and geographic extent of rain-on-snow events. We compare these results to WSN data to evaluate the impact of rain-on-snow events on snowpack energy balance, density, and depth as well as on soil moisture. Rain-on-snow events are compared to dry warm-weather days to identify the relative importance of rain and radiation as the primary energy input to the snowpack for snowmelt generation. An intercomparison of rain-on-snow events for the WSNs in the Feather, American, and Kings River basins captures the behavior across a 2° latitudinal range of the Sierra Nevada. Rain-on-snow events are potentially a more important streamflow generation mechanism in the lower-elevation Feather River basin. Snowmelt response to rain-on-snow events changes throughout the wet season, with later events resulting in more melt due to snow isothermal conditions, coarser grain size, and more-homogeneous snow stratigraphy. Regardless of snowmelt response, rain-on-snow events tend to result in decreasing snow depth and a corresponding increase in snow density. Our results demonstrate that strategically placed WSNs can provide the necessary data at

  12. An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data

    Directory of Open Access Journals (Sweden)

    Evangelos Stromatias

    2017-06-01

    Full Text Available This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS chips. The proposed supervised method uses the spiking activity provided by an arbitrary topology of prior SNN layers to build histograms and train the classifier in the frame domain using the stochastic gradient descent algorithm. In addition, this approach can cope with leaky integrate-and-fire neuron models within the SNN, a desirable feature for real-world SNN applications, where neural activation must fade away after some time in the absence of inputs. Consequently, this way of building histograms captures the dynamics of spikes immediately before the classifier. We tested our method on the MNIST data set using different synthetic encodings and real DVS sensory data sets such as N-MNIST, MNIST-DVS, and Poker-DVS using the same network topology and feature maps. We demonstrate the effectiveness of our approach by achieving the highest classification accuracy reported on the N-MNIST (97.77% and Poker-DVS (100% real DVS data sets to date with a spiking convolutional network. Moreover, by using the proposed method we were able to retrain the output layer of a previously reported spiking neural network and increase its performance by 2%, suggesting that the proposed classifier can be used as the output layer in works where features are extracted using unsupervised spike-based learning methods. In addition, we also analyze SNN performance figures such as total event activity and network latencies, which are relevant for eventual hardware implementations. In summary, the paper aggregates unsupervised-trained SNNs with a supervised-trained SNN classifier, combining and applying them to heterogeneous sets of benchmarks, both synthetic and from real DVS chips.

  13. An Event-Driven Classifier for Spiking Neural Networks Fed with Synthetic or Dynamic Vision Sensor Data.

    Science.gov (United States)

    Stromatias, Evangelos; Soto, Miguel; Serrano-Gotarredona, Teresa; Linares-Barranco, Bernabé

    2017-01-01

    This paper introduces a novel methodology for training an event-driven classifier within a Spiking Neural Network (SNN) System capable of yielding good classification results when using both synthetic input data and real data captured from Dynamic Vision Sensor (DVS) chips. The proposed supervised method uses the spiking activity provided by an arbitrary topology of prior SNN layers to build histograms and train the classifier in the frame domain using the stochastic gradient descent algorithm. In addition, this approach can cope with leaky integrate-and-fire neuron models within the SNN, a desirable feature for real-world SNN applications, where neural activation must fade away after some time in the absence of inputs. Consequently, this way of building histograms captures the dynamics of spikes immediately before the classifier. We tested our method on the MNIST data set using different synthetic encodings and real DVS sensory data sets such as N-MNIST, MNIST-DVS, and Poker-DVS using the same network topology and feature maps. We demonstrate the effectiveness of our approach by achieving the highest classification accuracy reported on the N-MNIST (97.77%) and Poker-DVS (100%) real DVS data sets to date with a spiking convolutional network. Moreover, by using the proposed method we were able to retrain the output layer of a previously reported spiking neural network and increase its performance by 2%, suggesting that the proposed classifier can be used as the output layer in works where features are extracted using unsupervised spike-based learning methods. In addition, we also analyze SNN performance figures such as total event activity and network latencies, which are relevant for eventual hardware implementations. In summary, the paper aggregates unsupervised-trained SNNs with a supervised-trained SNN classifier, combining and applying them to heterogeneous sets of benchmarks, both synthetic and from real DVS chips.

  14. Robust Event-Triggered Energy-to-Peak Filtering for Polytopic Uncertain Systems over Lossy Network with Quantized Measurements

    Directory of Open Access Journals (Sweden)

    Jidong Wang

    2016-01-01

    Full Text Available The event-triggered energy-to-peak filtering for polytopic discrete-time linear systems is studied with the consideration of lossy network and quantization error. Because of the communication imperfections from the packet dropout of lossy link, the event-triggered condition used to determine the data release instant at the event generator (EG can not be directly applied to update the filter input at the zero order holder (ZOH when performing filter performance analysis and synthesis. In order to balance such nonuniform time series between the triggered instant of EG and the updated instant of ZOH, two event-triggered conditions are defined, respectively, whereafter a worst-case bound on the number of consecutive packet losses of the transmitted data from EG is given, which marginally guarantees the effectiveness of the filter that will be designed based on the event-triggered updating condition of ZOH. Then, the filter performance analysis conditions are obtained under the assumption that the maximum number of packet losses is allowable for the worst-case bound. In what follows, a two-stage LMI-based alternative optimization approach is proposed to separately design the filter, which reduces the conservatism of the traditional linearization method of filter analysis conditions. Subsequently a codesign algorithm is developed to determine the communication and filter parameters simultaneously. Finally, an illustrative example is provided to verify the validity of the obtained results.

  15. Network performance measurements as part of feasibility studies on moving an ATLAS event filter to off-site institutes

    CERN Document Server

    Korcyl, K; Dobinson, Robert W; Ivanovici, M; Losada-Maia, Marcia; Meirosu, C; Sladowski, G

    2004-01-01

    We present a system for measuring network performance as part of the feasibility studies for locating the ATLAS third level trigger, the event filter (EF), in remote locations. Part of the processing power required to run the EF algorithms, the current estimate is 2000 state off the art processors, can be provided in remote, CERN-affiliated institutes, if a suitable network connection between CERN and the remote site could be achieved. The system is composed of two PCs equipped with GPS systems, CERN-designed clock cards and Alteon gigabit programmable network interface cards. In the first set of measurements we plan to quantify connection in terms of end-to-end latency, throughput, jitter and packet loss. Running streaming tests and study throughput, IP QoS, routing testing and traffic shaping follows this. Finally, we plan to install the event filter software in a remote location and feed it with data from test beams at CERN. Each of these tests should be preformed with the test traffic treated in the netwo...

  16. Social networks and inference about unknown events: A case of the match between Google's AlphaGo and Sedol Lee.

    Directory of Open Access Journals (Sweden)

    Jonghoon Bae

    Full Text Available This study examines whether the way that a person makes inferences about unknown events is associated with his or her social relations, more precisely, those characterized by ego network density that reflects the structure of a person's immediate social relation. From the analysis of individual predictions over the Go match between AlphaGo and Sedol Lee in March 2016 in Seoul, Korea, this study shows that the low-density group scored higher than the high-density group in the accuracy of the prediction over a future state of a social event, i.e., the outcome of the first game. We corroborated this finding with three replication tests that asked the participants to predict the following: film awards, President Park's impeachment in Korea, and the counterfactual assessment of the US presidential election. Taken together, this study suggests that network density is negatively associated with vision advantage, i.e., the ability to discover and forecast an unknown aspect of a social event.

  17. ELIMINATION OF THE DISADVANTAGES OF SCHEDULING-NETWORK PLANNING BY APPLYING THE MATRIX OF KEY PROJECT EVENTS

    Directory of Open Access Journals (Sweden)

    Morozenko Andrey Aleksandrovich

    2017-07-01

    Full Text Available The article discusses the current disadvantages of the scheduling-network planning in the management of the terms of investment-construction project. Problems associated with the construction of the schedule and the definitions of the duration of the construction project are being studied. The problems of project management for the management apparatus are shown, which consists in the absence of mechanisms for prompt response to deviations in the parameters of the scheduling-network diagram. A new approach to planning the implementation of an investment-construction project based on a matrix of key events and a rejection of the current practice of determining the duration based on inauthentic regulatory data. An algorithm for determining the key events of the project is presented. For increase the reliability of the organizational structure, the load factor of the functional block in the process of achieving the key event is proposed. Recommendations for improving the interaction of the participants in the investment-construction project are given.

  18. Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

    Science.gov (United States)

    Dean, Danielle O.; Bauer, Daniel J.; Prinstein, Mitchell J.

    2018-01-01

    A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common—as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed. PMID:28463022

  19. DETERMINATION OF THE FOREST ROAD NETWORK INFLUENCE ON THE SUPPLY CHAIN FOR FIREWOOD PRODUCTION BY DISCRETE EVENT SIMULATION

    Directory of Open Access Journals (Sweden)

    Raffaele Cavalli

    2012-06-01

    Full Text Available In this study a Discrete-event simulation (D-es has been developed to analyze the wood supply chain for firewood production in a mountain area in North-eastern Italy. The D-es is applied in the modeling of extraction (Full Tree System, processing of roundwood into wood assortments (cross-cut and sorting, offroad and on-road transport. In order to estimate the productivity functions and parameters, field studies were conducted to gather data about the different operations linked in the model. Also a GIS network analysis was developed to integrate the spatial information onthe covered distance to the D-es model for each of the supposed Scenarios. The results indicats that an increment of 5 m ha-1 of the forest road network could significantly increase the productivity of the wood supply chain up to 2%.

  20. A replica exchange transition interface sampling method with multiple interface sets for investigating networks of rare events

    Science.gov (United States)

    Swenson, David W. H.; Bolhuis, Peter G.

    2014-07-01

    The multiple state transition interface sampling (TIS) framework in principle allows the simulation of a large network of complex rare event transitions, but in practice suffers from convergence problems. To improve convergence, we combine multiple state TIS [J. Rogal and P. G. Bolhuis, J. Chem. Phys. 129, 224107 (2008)] with replica exchange TIS [T. S. van Erp, Phys. Rev. Lett. 98, 268301 (2007)]. In addition, we introduce multiple interface sets, which allow more than one order parameter to be defined for each state. We illustrate the methodology on a model system of multiple independent dimers, each with two states. For reaction networks with up to 64 microstates, we determine the kinetics in the microcanonical ensemble, and discuss the convergence properties of the sampling scheme. For this model, we find that the kinetics depend on the instantaneous composition of the system. We explain this dependence in terms of the system's potential and kinetic energy.

  1. Decision Trajectories in Dementia Care Networks: Decisions and Related Key Events.

    Science.gov (United States)

    Groen-van de Ven, Leontine; Smits, Carolien; Oldewarris, Karen; Span, Marijke; Jukema, Jan; Eefsting, Jan; Vernooij-Dassen, Myrra

    2017-10-01

    This prospective multiperspective study provides insight into the decision trajectories of people with dementia by studying the decisions made and related key events. This study includes three waves of interviews, conducted between July 2010 and July 2012, with 113 purposefully selected respondents (people with beginning to advanced stages of dementia and their informal and professional caregivers) completed in 12 months (285 interviews). Our multilayered qualitative analysis consists of content analysis, timeline methods, and constant comparison. Four decision themes emerged-managing daily life, arranging support, community living, and preparing for the future. Eight key events delineate the decision trajectories of people with dementia. Decisions and key events differ between people with dementia living alone and living with a caregiver. Our study clarifies that decisions relate not only to the disease but to living with the dementia. Individual differences in decision content and sequence may effect shared decision-making and advance care planning.

  2. Reconstruction of t anti tH (H → bb) events using deep neural networks with the CMS detector

    Energy Technology Data Exchange (ETDEWEB)

    Rieger, Marcel; Erdmann, Martin; Fischer, Benjamin; Fischer, Robert; Heidemann, Fabian; Quast, Thorben; Rath, Yannik [III. Physikalisches Institut A, RWTH Aachen University (Germany)

    2016-07-01

    The measurement of Higgs boson production in association with top-quark pairs (t anti tH) is an important goal of Run 2 of the LHC as it allows for a direct measurement of the underlying Yukawa coupling. Due to the complex final state, however, the analysis of semi-leptonic t anti tH events with the Higgs boson decaying into a pair of bottom-quarks is challenging. A promising method for tackling jet parton associations are Deep Neural Networks (DNN). While being a widely spread machine learning algorithm in modern industry, DNNs are on the way to becoming established in high energy physics. We present a study on the reconstruction of the final state using DNNs, comparing to Boosted Decision Trees (BDT) as benchmark scenario. This is accomplished by generating permutations of simulated events and comparing them with truth information to extract reconstruction efficiencies.

  3. Knowledge-based network participation in destination and event marketing: A hospitality scenario analysis perspective

    NARCIS (Netherlands)

    F.M. Go; Ad Breukel

    2009-01-01

    This paper examines how enterprises may decide to bring about effective network collaboration even though present mediation forms have proven inadequate. One of the main problems of these enterprises is that they lack a clear picture of the potential future ‘‘modular business’’. The Dutch

  4. Automatic Detection of Respiratory Events During Sleep Using Bidirectional LSTM Networks

    DEFF Research Database (Denmark)

    Jacobsen, K. P.; Olesen, Alexander Neergaard; Trap, L.

    2018-01-01

    seconds overlap. Two models were developed based on bidirectional long short-term memory (bLSTM) neural networks: 1)a two-class model for classification of windows as “normal” or “event”, and 2)a four-class model for classification as “normal”, “obstructive”, “central”, or “mixed”. 1882 subjects were used...

  5. Social Network Changes and Life Events across the Life Span: A Meta-Analysis

    Science.gov (United States)

    Wrzus, Cornelia; Hanel, Martha; Wagner, Jenny; Neyer, Franz J.

    2013-01-01

    For researchers and practitioners interested in social relationships, the question remains as to how large social networks typically are, and how their size and composition change across adulthood. On the basis of predictions of socioemotional selectivity theory and social convoy theory, we conducted a meta-analysis on age-related social network…

  6. Pattern recognition based on time-frequency analysis and convolutional neural networks for vibrational events in φ-OTDR

    Science.gov (United States)

    Xu, Chengjin; Guan, Junjun; Bao, Ming; Lu, Jiangang; Ye, Wei

    2018-01-01

    Based on vibration signals detected by a phase-sensitive optical time-domain reflectometer distributed optical fiber sensing system, this paper presents an implement of time-frequency analysis and convolutional neural network (CNN), used to classify different types of vibrational events. First, spectral subtraction and the short-time Fourier transform are used to enhance time-frequency features of vibration signals and transform different types of vibration signals into spectrograms, which are input to the CNN for automatic feature extraction and classification. Finally, by replacing the soft-max layer in the CNN with a multiclass support vector machine, the performance of the classifier is enhanced. Experiments show that after using this method to process 4000 vibration signal samples generated by four different vibration events, namely, digging, walking, vehicles passing, and damaging, the recognition rates of vibration events are over 90%. The experimental results prove that this method can automatically make an effective feature selection and greatly improve the classification accuracy of vibrational events in distributed optical fiber sensing systems.

  7. Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks.

    Science.gov (United States)

    Lee, Wang Wei; Kukreja, Sunil L; Thakor, Nitish V

    2017-01-01

    This paper presents a neuromorphic tactile encoding methodology that utilizes a temporally precise event-based representation of sensory signals. We introduce a novel concept where touch signals are characterized as patterns of millisecond precise binary events to denote pressure changes. This approach is amenable to a sparse signal representation and enables the extraction of relevant features from thousands of sensing elements with sub-millisecond temporal precision. We also proposed measures adopted from computational neuroscience to study the information content within the spiking representations of artificial tactile signals. Implemented on a state-of-the-art 4096 element tactile sensor array with 5.2 kHz sampling frequency, we demonstrate the classification of transient impact events while utilizing 20 times less communication bandwidth compared to frame based representations. Spiking sensor responses to a large library of contact conditions were also synthesized using finite element simulations, illustrating an 8-fold improvement in information content and a 4-fold reduction in classification latency when millisecond-precise temporal structures are available. Our research represents a significant advance, demonstrating that a neuromorphic spatiotemporal representation of touch is well suited to rapid identification of critical contact events, making it suitable for dynamic tactile sensing in robotic and prosthetic applications.

  8. The origin of SEP events: New research collaboration and network on space weather

    Science.gov (United States)

    Miteva, Rositsa; Kashapova, Larisa; Myagkova, Irina; Meshalkina, Nataliia; Petrov, Nikola; Bogomolov, Andrey; Myshyakov, Ivan; Tsvetkov, Tsvetan; Danov, Dimitar; Zdanov, Dmitriy

    2017-11-01

    A new project on the solar energetic particles (SEPs) and their solar origins (flares and coronal mass ejections) is described here. The main aim of this project is to answer the question - whether the SEPs observed in situ are driven by flares, by CMEs or both accelerators contribute to an extent which varies from event to event - by deducing a quantitative measure of the flare vs. CME contribution, duration and efficiency. New observations (SONG/Koronas-F, Relec/Vernov) and new approaches of analysis will be utilized (e.g., magnetic topology of active regions using 3D extrapolation techniques of detailed case studies together with statistical analysis of the phenomena). In addition, the identification of the uncertainty limits of SEP injection, onset time and testing the validity of assumptions often taken for granted (association procedures, solar activity longitudinal effects, correlation analysis, etc.) are planned. The project outcomes have the capacity to contribute to other research fields for improvement of modeling schemes and forecasting methods of space weather events.

  9. Enriched encoding: reward motivation organizes cortical networks for hippocampal detection of unexpected events.

    Science.gov (United States)

    Murty, Vishnu P; Adcock, R Alison

    2014-08-01

    Learning how to obtain rewards requires learning about their contexts and likely causes. How do long-term memory mechanisms balance the need to represent potential determinants of reward outcomes with the computational burden of an over-inclusive memory? One solution would be to enhance memory for salient events that occur during reward anticipation, because all such events are potential determinants of reward. We tested whether reward motivation enhances encoding of salient events like expectancy violations. During functional magnetic resonance imaging, participants performed a reaction-time task in which goal-irrelevant expectancy violations were encountered during states of high- or low-reward motivation. Motivation amplified hippocampal activation to and declarative memory for expectancy violations. Connectivity of the ventral tegmental area (VTA) with medial prefrontal, ventrolateral prefrontal, and visual cortices preceded and predicted this increase in hippocampal sensitivity. These findings elucidate a novel mechanism whereby reward motivation can enhance hippocampus-dependent memory: anticipatory VTA-cortical-hippocampal interactions. Further, the findings integrate literatures on dopaminergic neuromodulation of prefrontal function and hippocampus-dependent memory. We conclude that during reward motivation, VTA modulation induces distributed neural changes that amplify hippocampal signals and records of expectancy violations to improve predictions-a potentially unique contribution of the hippocampus to reward learning. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  10. Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.

    Science.gov (United States)

    Xie, Jiaheng; Liu, Xiao; Dajun Zeng, Daniel

    2018-01-01

    Recent years have seen increased worldwide popularity of e-cigarette use. However, the risks of e-cigarettes are underexamined. Most e-cigarette adverse event studies have achieved low detection rates due to limited subject sample sizes in the experiments and surveys. Social media provides a large data repository of consumers' e-cigarette feedback and experiences, which are useful for e-cigarette safety surveillance. However, it is difficult to automatically interpret the informal and nontechnical consumer vocabulary about e-cigarettes in social media. This issue hinders the use of social media content for e-cigarette safety surveillance. Recent developments in deep neural network methods have shown promise for named entity extraction from noisy text. Motivated by these observations, we aimed to design a deep neural network approach to extract e-cigarette safety information in social media. Our deep neural language model utilizes word embedding as the representation of text input and recognizes named entity types with the state-of-the-art Bidirectional Long Short-Term Memory (Bi-LSTM) Recurrent Neural Network. Our Bi-LSTM model achieved the best performance compared to 3 baseline models, with a precision of 94.10%, a recall of 91.80%, and an F-measure of 92.94%. We identified 1591 unique adverse events and 9930 unique e-cigarette components (ie, chemicals, flavors, and devices) from our research testbed. Although the conditional random field baseline model had slightly better precision than our approach, our Bi-LSTM model achieved much higher recall, resulting in the best F-measure. Our method can be generalized to extract medical concepts from social media for other medical applications. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  11. A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ahmadreza Vajdi

    2018-05-01

    Full Text Available We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP. Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

  12. A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks.

    Science.gov (United States)

    Vajdi, Ahmadreza; Zhang, Gongxuan; Zhou, Junlong; Wei, Tongquan; Wang, Yongli; Wang, Tianshu

    2018-05-04

    We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach.

  13. Acoustic event location and background noise characterization on a free flying infrasound sensor network in the stratosphere

    Science.gov (United States)

    Bowman, Daniel C.; Albert, Sarah A.

    2018-06-01

    A variety of Earth surface and atmospheric sources generate low-frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth's surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphone stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while travelling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves at 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 s.

  14. A New Path-Constrained Rendezvous Planning Approach for Large-Scale Event-Driven Wireless Sensor Networks

    Science.gov (United States)

    Zhang, Gongxuan; Wang, Yongli; Wang, Tianshu

    2018-01-01

    We study the problem of employing a mobile-sink into a large-scale Event-Driven Wireless Sensor Networks (EWSNs) for the purpose of data harvesting from sensor-nodes. Generally, this employment improves the main weakness of WSNs that is about energy-consumption in battery-driven sensor-nodes. The main motivation of our work is to address challenges which are related to a network’s topology by adopting a mobile-sink that moves in a predefined trajectory in the environment. Since, in this fashion, it is not possible to gather data from sensor-nodes individually, we adopt the approach of defining some of the sensor-nodes as Rendezvous Points (RPs) in the network. We argue that RP-planning in this case is a tradeoff between minimizing the number of RPs while decreasing the number of hops for a sensor-node that needs data transformation to the related RP which leads to minimizing average energy consumption in the network. We address the problem by formulating the challenges and expectations as a Mixed Integer Linear Programming (MILP). Henceforth, by proving the NP-hardness of the problem, we propose three effective and distributed heuristics for RP-planning, identifying sojourn locations, and constructing routing trees. Finally, experimental results prove the effectiveness of our approach. PMID:29734718

  15. Transformations of the journalism event in social networks: from the mobilizations against homophobia to the crisis of a country music duo

    Directory of Open Access Journals (Sweden)

    Ronaldo César Henn

    2012-06-01

    Full Text Available This paper presents the preliminary results of a research that investigates the creation of events through social networking sites on the Internet. There is already a specific type of event that serves the logic of these networks, especially those whose production and distribution take place based on online platforms and digital tools. This paper investigates two cases: the first concerns the duo of Brazilian country music singers, Zezé di Camargo and Luciano, who, after an argument that occurred in a concert in the city of Curitiba, announced the end of the partnership. The video was posted on YouTube and was immediately spread through the social networks, which generated intense conversation about the episode until it became a journalistic event in the traditional media. This paper also examines the organization of a protest against the attack on a homoaffective couple in a street of São Paulo in 2011, completely worked on by Facebook. Based on Charles Sanders Peirce’s concept of semiosis, a map of the construction of these events is drawn with its various ramifications, from the articulations within the network to the production of meanings that they develop. The events studied have as an element in common the leading role that social networks had in their constitution. They possess the nature of the network and are framed in what is understood now as cyberevents, a category that poses new challenges to the practice of journalism.

  16. TRANSFORMATIONS OF THE JOURNALISM EVENT IN SOCIAL NETWORKS: FROM THE MOBILIZATIONS AGAINST HOMOPHOBIA TO THE CRISIS OF A COUNTRY MUSIC DUO

    Directory of Open Access Journals (Sweden)

    Kellen Mendes Höehr

    2012-06-01

    Full Text Available This paper presents the preliminary results of a research that investigates the creation of events through social networking sites on the Internet. There is already a specific type of event that serves the logic of these networks, especially those whose production and distribution take place based on online platforms and digital tools. This paper investigates two cases: the first concerns the duo of Brazilian country music singers, Zezé di Camargo and Luciano, who, after an argument that occurred in a concert in the city of Curitiba, announced the end of the partnership. The video was posted on YouTube and was immediately spread through the social networks, which generated intense conversation about the episode until it became a journalistic event in the traditional media. This paper also examines the organization of a protest against the attack on a homoaffective couple in a street of São Paulo in 2011, completely worked on by Facebook. Based on Charles Sanders Peirce’s concept of semiosis, a map of the construction of these events is drawn with its various ramifications, from the articulations within the network to the production of meanings that they develop. The events studied have as an element in common the leading role that social networks had in their constitution. They possess the nature of the network and are framed in what is understood now as cyberevents, a category that poses new challenges to the practice of journalism.

  17. Predictions of SEP events by means of a linear filter and layer-recurrent neural network

    Czech Academy of Sciences Publication Activity Database

    Valach, F.; Revallo, M.; Hejda, Pavel; Bochníček, Josef

    2011-01-01

    Roč. 69, č. 9-10 (2011), s. 758-766 ISSN 0094-5765 R&D Projects: GA AV ČR(CZ) IAA300120608; GA MŠk OC09070 Grant - others:VEGA(SK) 2/0015/11; VEGA(SK) 2/0022/11 Institutional research plan: CEZ:AV0Z30120515 Keywords : coronal mass ejection * X-ray flare * solar energetic particles * artificial neural network Subject RIV: DE - Earth Magnetism, Geodesy, Geography Impact factor: 0.614, year: 2011

  18. Real-time prediction of acute cardiovascular events using hardware-implemented Bayesian networks.

    Science.gov (United States)

    Tylman, Wojciech; Waszyrowski, Tomasz; Napieralski, Andrzej; Kamiński, Marek; Trafidło, Tamara; Kulesza, Zbigniew; Kotas, Rafał; Marciniak, Paweł; Tomala, Radosław; Wenerski, Maciej

    2016-02-01

    This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Citizen Science and Event-Based Science Education with the Quake-Catcher Network

    Science.gov (United States)

    DeGroot, R. M.; Sumy, D. F.; Benthien, M. L.

    2017-12-01

    The Quake-Catcher Network (QCN, quakecatcher.net) is a collaborative, citizen-science initiative to develop the world's largest, low-cost strong-motion seismic network through the utilization of sensors in laptops and smartphones or small microelectromechanical systems (MEMS) accelerometers attached to internet-connected computers. The volunteer computers monitor seismic motion and other vibrations and send the "triggers" in real-time to the QCN server hosted at the University of Southern California. The QCN servers sift through these signals and determine which ones represent earthquakes and which ones represent cultural noise. Data collected by the Quake-Catcher Network can contribute to better understanding earthquakes, provide teachable moments for students, and engage the public with authentic science experiences. QCN partners coordinate sensor installations, develop QCN's scientific tools and engagement activities, and create next generation online resources. In recent years, the QCN team has installed sensors in over 225 K-12 schools and free-choice learning institutions (e.g. museums) across the United States and Canada. One of the current goals of the program in the United States is to establish several QCN stations in K-12 schools around a local museum hub as a means to provide coordinated and sustained educational opportunities leading up to the yearly Great ShakeOut Earthquake Drill, to encourage citizen science, and enrich STEM curriculum. Several school districts and museums throughout Southern California have been instrumental in the development of QCN. For educators QCN fulfills a key component of the Next Generation Science Standards where students are provided an opportunity to utilize technology and interface with authentic scientific data and learn about emerging programs such as the ShakeAlert earthquake early warning system. For example, Sunnylands Center in Rancho Mirage, CA leads Coachella Valley Hub, which serves 31 K-12 schools, many of

  20. A twenty-first century California observing network for monitoring extreme weather events

    Science.gov (United States)

    White, A.B.; Anderson, M.L.; Dettinger, M.D.; Ralph, F.M.; Hinojosa, A.; Cayan, D.R.; Hartman, R.K.; Reynolds, D.W.; Johnson, L.E.; Schneider, T.L.; Cifelli, R.; Toth, Z.; Gutman, S.I.; King, C.W.; Gehrke, F.; Johnston, P.E.; Walls, C.; Mann, Dorte; Gottas, D.J.; Coleman, T.

    2013-01-01

    During Northern Hemisphere winters, the West Coast of North America is battered by extratropical storms. The impact of these storms is of paramount concern to California, where aging water supply and flood protection infrastructures are challenged by increased standards for urban flood protection, an unusually variable weather regime, and projections of climate change. Additionally, there are inherent conflicts between releasing water to provide flood protection and storing water to meet requirements for water supply, water quality, hydropower generation, water temperature and flow for at-risk species, and recreation. In order to improve reservoir management and meet the increasing demands on water, improved forecasts of precipitation, especially during extreme events, is required. Here we describe how California is addressing their most important and costliest environmental issue – water management – in part, by installing a state-of-the-art observing system to better track the area’s most severe wintertime storms.

  1. Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

    CERN Document Server

    Chatrchyan, Serguei; Sirunyan, Albert M; Tumasyan, Armen; Adam, Wolfgang; Aguilo, Ernest; Bergauer, Thomas; Dragicevic, Marko; Erö, Janos; Fabjan, Christian; Friedl, Markus; Fruehwirth, Rudolf; Ghete, Vasile Mihai; Hörmann, Natascha; Hrubec, Josef; Jeitler, Manfred; Kiesenhofer, Wolfgang; Knünz, Valentin; Krammer, Manfred; Krätschmer, Ilse; Liko, Dietrich; Mikulec, Ivan; Pernicka, Manfred; Rabady, Dinyar; Rahbaran, Babak; Rohringer, Christine; Rohringer, Herbert; Schöfbeck, Robert; Strauss, Josef; Taurok, Anton; Waltenberger, Wolfgang; Wulz, Claudia-Elisabeth; Mossolov, Vladimir; Shumeiko, Nikolai; Suarez Gonzalez, Juan; Bansal, Monika; Bansal, Sunil; Cornelis, Tom; De Wolf, Eddi A; Janssen, Xavier; Luyckx, Sten; Mucibello, Luca; Ochesanu, Silvia; Roland, Benoit; Rougny, Romain; Selvaggi, Michele; Van Haevermaet, Hans; Van Mechelen, Pierre; Van Remortel, Nick; Van Spilbeeck, Alex; Blekman, Freya; Blyweert, Stijn; D'Hondt, Jorgen; Gonzalez Suarez, Rebeca; Kalogeropoulos, Alexis; Maes, Michael; Olbrechts, Annik; Van Doninck, Walter; Van Mulders, Petra; Van Onsem, Gerrit Patrick; Villella, Ilaria; Clerbaux, Barbara; De Lentdecker, Gilles; Dero, Vincent; Gay, Arnaud; Hreus, Tomas; Léonard, Alexandre; Marage, Pierre Edouard; Mohammadi, Abdollah; Reis, Thomas; Thomas, Laurent; Vander Velde, Catherine; Vanlaer, Pascal; Wang, Jian; Adler, Volker; Beernaert, Kelly; Cimmino, Anna; Costantini, Silvia; Garcia, Guillaume; Grunewald, Martin; Klein, Benjamin; Lellouch, Jérémie; Marinov, Andrey; Mccartin, Joseph; Ocampo Rios, Alberto Andres; Ryckbosch, Dirk; Strobbe, Nadja; Thyssen, Filip; Tytgat, Michael; Walsh, Sinead; Yazgan, Efe; Zaganidis, Nicolas; Basegmez, Suzan; Bruno, Giacomo; Castello, Roberto; Ceard, Ludivine; Delaere, Christophe; Du Pree, Tristan; Favart, Denis; Forthomme, Laurent; Giammanco, Andrea; Hollar, Jonathan; Lemaitre, Vincent; Liao, Junhui; Militaru, Otilia; Nuttens, Claude; Pagano, Davide; Pin, Arnaud; Piotrzkowski, Krzysztof; Vizan Garcia, Jesus Manuel; Beliy, Nikita; Caebergs, Thierry; Daubie, Evelyne; Hammad, Gregory Habib; Alves, Gilvan; Correa Martins Junior, Marcos; Martins, Thiago; Pol, Maria Elena; Henrique Gomes E Souza, Moacyr; Aldá Júnior, Walter Luiz; Carvalho, Wagner; Custódio, Analu; Melo Da Costa, Eliza; De Jesus Damiao, Dilson; De Oliveira Martins, Carley; Fonseca De Souza, Sandro; Malbouisson, Helena; Malek, Magdalena; Matos Figueiredo, Diego; Mundim, Luiz; Nogima, Helio; Prado Da Silva, Wanda Lucia; Santoro, Alberto; Soares Jorge, Luana; Sznajder, Andre; Vilela Pereira, Antonio; Souza Dos Anjos, Tiago; Bernardes, Cesar Augusto; De Almeida Dias, Flavia; Tomei, Thiago; De Moraes Gregores, Eduardo; Lagana, Caio; Da Cunha Marinho, Franciole; Mercadante, Pedro G; Novaes, Sergio F; Padula, Sandra; Genchev, Vladimir; Iaydjiev, Plamen; Piperov, Stefan; Rodozov, Mircho; Stoykova, Stefka; Sultanov, Georgi; Tcholakov, Vanio; Trayanov, Rumen; Vutova, Mariana; Dimitrov, Anton; Hadjiiska, Roumyana; Kozhuharov, Venelin; Litov, Leander; Pavlov, Borislav; Petkov, Peicho; Bian, Jian-Guo; Chen, Guo-Ming; Chen, He-Sheng; Jiang, Chun-Hua; Liang, Dong; Liang, Song; Meng, Xiangwei; Tao, Junquan; Wang, Jian; Wang, Xianyou; Wang, Zheng; Xiao, Hong; Xu, Ming; Zang, Jingjing; Zhang, Zhen; Asawatangtrakuldee, Chayanit; Ban, Yong; Guo, Yifei; Li, Wenbo; Liu, Shuai; Mao, Yajun; Qian, Si-Jin; Teng, Haiyun; Wang, Dayong; Zhang, Linlin; Zou, Wei; Avila, Carlos; Gomez, Juan Pablo; Gomez Moreno, Bernardo; Osorio Oliveros, Andres Felipe; Sanabria, Juan Carlos; Godinovic, Nikola; Lelas, Damir; Plestina, Roko; Polic, Dunja; Puljak, Ivica; Antunovic, Zeljko; Kovac, Marko; Brigljevic, Vuko; Duric, Senka; Kadija, Kreso; Luetic, Jelena; Mekterovic, Darko; Morovic, Srecko; Attikis, Alexandros; Galanti, Mario; Mavromanolakis, Georgios; Mousa, Jehad; Nicolaou, Charalambos; Ptochos, Fotios; Razis, Panos A; Finger, Miroslav; Finger Jr, Michael; Assran, Yasser; Elgammal, Sherif; Ellithi Kamel, Ali; Mahmoud, Mohammed; Mahrous, Ayman; Radi, Amr; Kadastik, Mario; Müntel, Mait; Murumaa, Marion; Raidal, Martti; Rebane, Liis; Tiko, Andres; Eerola, Paula; Fedi, Giacomo; Voutilainen, Mikko; Härkönen, Jaakko; Heikkinen, Mika Aatos; Karimäki, Veikko; Kinnunen, Ritva; Kortelainen, Matti J; Lampén, Tapio; Lassila-Perini, Kati; Lehti, Sami; Lindén, Tomas; Luukka, Panja-Riina; Mäenpää, Teppo; Peltola, Timo; Tuominen, Eija; Tuominiemi, Jorma; Tuovinen, Esa; Ungaro, Donatella; Wendland, Lauri; Banzuzi, Kukka; Karjalainen, Ahti; Korpela, Arja; Tuuva, Tuure; Besancon, Marc; Choudhury, Somnath; Dejardin, Marc; Denegri, Daniel; Fabbro, Bernard; Faure, Jean-Louis; Ferri, Federico; Ganjour, Serguei; Givernaud, Alain; Gras, Philippe; Hamel de Monchenault, Gautier; Jarry, Patrick; Locci, Elizabeth; Malcles, Julie; Millischer, Laurent; Nayak, Aruna; Rander, John; Rosowsky, André; Titov, Maksym; Baffioni, Stephanie; Beaudette, Florian; Benhabib, Lamia; Bianchini, Lorenzo; Bluj, Michal; Busson, Philippe; Charlot, Claude; Daci, Nadir; Dahms, Torsten; Dalchenko, Mykhailo; Dobrzynski, Ludwik; Florent, Alice; Granier de Cassagnac, Raphael; Haguenauer, Maurice; Miné, Philippe; Mironov, Camelia; Naranjo, Ivo Nicolas; Nguyen, Matthew; Ochando, Christophe; Paganini, Pascal; Sabes, David; Salerno, Roberto; Sirois, Yves; Veelken, Christian; Zabi, Alexandre; Agram, Jean-Laurent; Andrea, Jeremy; Bloch, Daniel; Bodin, David; Brom, Jean-Marie; Cardaci, Marco; Chabert, Eric Christian; Collard, Caroline; Conte, Eric; Drouhin, Frédéric; Fontaine, Jean-Charles; Gelé, Denis; Goerlach, Ulrich; Juillot, Pierre; Le Bihan, Anne-Catherine; Van Hove, Pierre; Fassi, Farida; Mercier, Damien; Beauceron, Stephanie; Beaupere, Nicolas; Bondu, Olivier; Boudoul, Gaelle; Brochet, Sébastien; Chasserat, Julien; Chierici, Roberto; Contardo, Didier; Depasse, Pierre; El Mamouni, Houmani; Fay, Jean; Gascon, Susan; Gouzevitch, Maxime; Ille, Bernard; Kurca, Tibor; Lethuillier, Morgan; Mirabito, Laurent; Perries, Stephane; Sgandurra, Louis; Sordini, Viola; Tschudi, Yohann; Verdier, Patrice; Viret, Sébastien; Tsamalaidze, Zviad; Autermann, Christian; Beranek, Sarah; Calpas, Betty; Edelhoff, Matthias; Feld, Lutz; Heracleous, Natalie; Hindrichs, Otto; Jussen, Ruediger; Klein, Katja; Merz, Jennifer; Ostapchuk, Andrey; Perieanu, Adrian; Raupach, Frank; Sammet, Jan; Schael, Stefan; Sprenger, Daniel; Weber, Hendrik; Wittmer, Bruno; Zhukov, Valery; Ata, Metin; Caudron, Julien; Dietz-Laursonn, Erik; Duchardt, Deborah; Erdmann, Martin; Fischer, Robert; Güth, Andreas; Hebbeker, Thomas; Heidemann, Carsten; Hoepfner, Kerstin; Klingebiel, Dennis; Kreuzer, Peter; Merschmeyer, Markus; Meyer, Arnd; Olschewski, Mark; Papacz, Paul; Pieta, Holger; Reithler, Hans; Schmitz, Stefan Antonius; Sonnenschein, Lars; Steggemann, Jan; Teyssier, Daniel; Thüer, Sebastian; Weber, Martin; Bontenackels, Michael; Cherepanov, Vladimir; Erdogan, Yusuf; Flügge, Günter; Geenen, Heiko; Geisler, Matthias; Haj Ahmad, Wael; Hoehle, Felix; Kargoll, Bastian; Kress, Thomas; Kuessel, Yvonne; Lingemann, Joschka; Nowack, Andreas; Perchalla, Lars; Pooth, Oliver; Sauerland, Philip; Stahl, Achim; Aldaya Martin, Maria; Behr, Joerg; Behrenhoff, Wolf; Behrens, Ulf; Bergholz, Matthias; Bethani, Agni; Borras, Kerstin; Burgmeier, Armin; Cakir, Altan; Calligaris, Luigi; Campbell, Alan; Castro, Elena; Costanza, Francesco; Dammann, Dirk; Diez Pardos, Carmen; Eckerlin, Guenter; Eckstein, Doris; Flucke, Gero; Geiser, Achim; Glushkov, Ivan; Gunnellini, Paolo; Habib, Shiraz; Hauk, Johannes; Hellwig, Gregor; Jung, Hannes; Kasemann, Matthias; Katsas, Panagiotis; Kleinwort, Claus; Kluge, Hannelies; Knutsson, Albert; Krämer, Mira; Krücker, Dirk; Kuznetsova, Ekaterina; Lange, Wolfgang; Leonard, Jessica; Lohmann, Wolfgang; Lutz, Benjamin; Mankel, Rainer; Marfin, Ihar; Marienfeld, Markus; Melzer-Pellmann, Isabell-Alissandra; Meyer, Andreas Bernhard; Mnich, Joachim; Mussgiller, Andreas; Naumann-Emme, Sebastian; Novgorodova, Olga; Olzem, Jan; Perrey, Hanno; Petrukhin, Alexey; Pitzl, Daniel; Raspereza, Alexei; Ribeiro Cipriano, Pedro M; Riedl, Caroline; Ron, Elias; Rosin, Michele; Salfeld-Nebgen, Jakob; Schmidt, Ringo; Schoerner-Sadenius, Thomas; Sen, Niladri; Spiridonov, Alexander; Stein, Matthias; Walsh, Roberval; Wissing, Christoph; Blobel, Volker; Enderle, Holger; Erfle, Joachim; Gebbert, Ulla; Görner, Martin; Gosselink, Martijn; Haller, Johannes; Hermanns, Thomas; Höing, Rebekka Sophie; Kaschube, Kolja; Kaussen, Gordon; Kirschenmann, Henning; Klanner, Robert; Lange, Jörn; Nowak, Friederike; Peiffer, Thomas; Pietsch, Niklas; Rathjens, Denis; Sander, Christian; Schettler, Hannes; Schleper, Peter; Schlieckau, Eike; Schmidt, Alexander; Schröder, Matthias; Schum, Torben; Seidel, Markus; Sibille, Jennifer; Sola, Valentina; Stadie, Hartmut; Steinbrück, Georg; Thomsen, Jan; Vanelderen, Lukas; Barth, Christian; Berger, Joram; Böser, Christian; Chwalek, Thorsten; De Boer, Wim; Descroix, Alexis; Dierlamm, Alexander; Feindt, Michael; Guthoff, Moritz; Hackstein, Christoph; Hartmann, Frank; Hauth, Thomas; Heinrich, Michael; Held, Hauke; Hoffmann, Karl-Heinz; Husemann, Ulrich; Katkov, Igor; Komaragiri, Jyothsna Rani; Lobelle Pardo, Patricia; Martschei, Daniel; Mueller, Steffen; Müller, Thomas; Niegel, Martin; Nürnberg, Andreas; Oberst, Oliver; Oehler, Andreas; Ott, Jochen; Quast, Gunter; Rabbertz, Klaus; Ratnikov, Fedor; Ratnikova, Natalia; Röcker, Steffen; Schilling, Frank-Peter; Schott, Gregory; Simonis, Hans-Jürgen; Stober, Fred-Markus Helmut; Troendle, Daniel; Ulrich, Ralf; Wagner-Kuhr, Jeannine; Wayand, Stefan; Weiler, Thomas; Zeise, Manuel; Anagnostou, Georgios; Daskalakis, Georgios; Geralis, Theodoros; Kesisoglou, Stilianos; Kyriakis, Aristotelis; Loukas, Demetrios; Manolakos, Ioannis; Markou, Athanasios; Markou, Christos; Ntomari, Eleni; Gouskos, Loukas; Mertzimekis, Theodoros; Panagiotou, Apostolos; Saoulidou, Niki; Evangelou, Ioannis; Foudas, Costas; Kokkas, Panagiotis; Manthos, Nikolaos; Papadopoulos, Ioannis; Patras, Vaios; Bencze, Gyorgy; Hajdu, Csaba; Hidas, Pàl; Horvath, Dezso; Sikler, Ferenc; Veszpremi, Viktor; Vesztergombi, Gyorgy; Beni, Noemi; Czellar, Sandor; Molnar, Jozsef; Palinkas, Jozsef; Szillasi, Zoltan; Karancsi, János; Raics, Peter; Trocsanyi, Zoltan Laszlo; Ujvari, Balazs; Beri, Suman Bala; Bhatnagar, Vipin; Dhingra, Nitish; Gupta, Ruchi; Kaur, Manjit; Mehta, Manuk Zubin; Nishu, Nishu; Saini, Lovedeep Kaur; Sharma, Archana; Singh, Jasbir; Kumar, Ashok; Kumar, Arun; Ahuja, Sudha; Bhardwaj, Ashutosh; Choudhary, Brajesh C; Malhotra, Shivali; Naimuddin, Md; Ranjan, Kirti; Sharma, Varun; Shivpuri, Ram Krishen; Banerjee, Sunanda; Bhattacharya, Satyaki; Dutta, Suchandra; Gomber, Bhawna; Jain, Sandhya; Jain, Shilpi; Khurana, Raman; Sarkar, Subir; Sharan, Manoj; Abdulsalam, Abdulla; Dutta, Dipanwita; Kailas, Swaminathan; Kumar, Vineet; Mohanty, Ajit Kumar; Pant, Lalit Mohan; Shukla, Prashant; Aziz, Tariq; Ganguly, Sanmay; Guchait, Monoranjan; Gurtu, Atul; Maity, Manas; Majumder, Gobinda; Mazumdar, Kajari; Mohanty, Gagan Bihari; Parida, Bibhuti; Sudhakar, Katta; Wickramage, Nadeesha; Banerjee, Sudeshna; Dugad, Shashikant; Arfaei, Hessamaddin; Bakhshiansohi, Hamed; Etesami, Seyed Mohsen; Fahim, Ali; Hashemi, Majid; Hesari, Hoda; Jafari, Abideh; Khakzad, Mohsen; Mohammadi Najafabadi, Mojtaba; Paktinat Mehdiabadi, Saeid; Safarzadeh, Batool; Zeinali, Maryam; Abbrescia, Marcello; Barbone, Lucia; Calabria, Cesare; Chhibra, Simranjit Singh; Colaleo, Anna; Creanza, Donato; De Filippis, Nicola; De Palma, Mauro; Fiore, Luigi; Iaselli, Giuseppe; Maggi, Giorgio; Maggi, Marcello; Marangelli, Bartolomeo; My, Salvatore; Nuzzo, Salvatore; Pacifico, Nicola; Pompili, Alexis; Pugliese, Gabriella; Selvaggi, Giovanna; Silvestris, Lucia; Singh, Gurpreet; Venditti, Rosamaria; Verwilligen, Piet; Zito, Giuseppe; Abbiendi, Giovanni; Benvenuti, Alberto; Bonacorsi, Daniele; Braibant-Giacomelli, Sylvie; Brigliadori, Luca; Capiluppi, Paolo; Castro, Andrea; Cavallo, Francesca Romana; Cuffiani, Marco; Dallavalle, Gaetano-Marco; Fabbri, Fabrizio; Fanfani, Alessandra; Fasanella, Daniele; Giacomelli, Paolo; Grandi, Claudio; Guiducci, Luigi; Marcellini, Stefano; Masetti, Gianni; Meneghelli, Marco; Montanari, Alessandro; Navarria, Francesco; Odorici, Fabrizio; Perrotta, Andrea; Primavera, Federica; Rossi, Antonio; Rovelli, Tiziano; Siroli, Gian Piero; Tosi, Nicolò; Travaglini, Riccardo; Albergo, Sebastiano; Cappello, Gigi; Chiorboli, Massimiliano; Costa, Salvatore; Potenza, Renato; Tricomi, Alessia; Tuve, Cristina; Barbagli, Giuseppe; Ciulli, Vitaliano; Civinini, Carlo; D'Alessandro, Raffaello; Focardi, Ettore; Frosali, Simone; Gallo, Elisabetta; Gonzi, Sandro; Meschini, Marco; Paoletti, Simone; Sguazzoni, Giacomo; Tropiano, Antonio; Benussi, Luigi; Bianco, Stefano; Colafranceschi, Stefano; Fabbri, Franco; Piccolo, Davide; Fabbricatore, Pasquale; Musenich, Riccardo; Tosi, Silvano; Benaglia, Andrea; De Guio, Federico; Di Matteo, Leonardo; Fiorendi, Sara; Gennai, Simone; Ghezzi, Alessio; Malvezzi, Sandra; Manzoni, Riccardo Andrea; Martelli, Arabella; Massironi, Andrea; Menasce, Dario; Moroni, Luigi; Paganoni, Marco; Pedrini, Daniele; Ragazzi, Stefano; Redaelli, Nicola; Sala, Silvano; Tabarelli de Fatis, Tommaso; Buontempo, Salvatore; Carrillo Montoya, Camilo Andres; Cavallo, Nicola; De Cosa, Annapaola; Dogangun, Oktay; Fabozzi, Francesco; Iorio, Alberto Orso Maria; Lista, Luca; Meola, Sabino; Merola, Mario; Paolucci, Pierluigi; Azzi, Patrizia; Bacchetta, Nicola; Bisello, Dario; Branca, Antonio; Carlin, Roberto; Checchia, Paolo; Dorigo, Tommaso; Gasparini, Fabrizio; Gasparini, Ugo; Gozzelino, Andrea; Kanishchev, Konstantin; Lacaprara, Stefano; Lazzizzera, Ignazio; Margoni, Martino; Meneguzzo, Anna Teresa; Pazzini, Jacopo; Pozzobon, Nicola; Ronchese, Paolo; Simonetto, Franco; Torassa, Ezio; Tosi, Mia; Vanini, Sara; Zotto, Pierluigi; Zucchetta, Alberto; Zumerle, Gianni; Gabusi, Michele; Ratti, Sergio P; Riccardi, Cristina; Torre, Paola; Vitulo, Paolo; Biasini, Maurizio; Bilei, Gian Mario; Fanò, Livio; Lariccia, Paolo; Mantovani, Giancarlo; Menichelli, Mauro; Nappi, Aniello; Romeo, Francesco; Saha, Anirban; Santocchia, Attilio; Spiezia, Aniello; Taroni, Silvia; Azzurri, Paolo; Bagliesi, Giuseppe; Bernardini, Jacopo; Boccali, Tommaso; Broccolo, Giuseppe; Castaldi, Rino; D'Agnolo, Raffaele Tito; Dell'Orso, Roberto; Fiori, Francesco; Foà, Lorenzo; Giassi, Alessandro; Kraan, Aafke; Ligabue, Franco; Lomtadze, Teimuraz; Martini, Luca; Messineo, Alberto; Palla, Fabrizio; Rizzi, Andrea; Serban, Alin Titus; Spagnolo, Paolo; Squillacioti, Paola; Tenchini, Roberto; Tonelli, Guido; Venturi, Andrea; Verdini, Piero Giorgio; Barone, Luciano; Cavallari, Francesca; Del Re, Daniele; Diemoz, Marcella; Fanelli, Cristiano; Grassi, Marco; Longo, Egidio; Meridiani, Paolo; Micheli, Francesco; Nourbakhsh, Shervin; Organtini, Giovanni; Paramatti, Riccardo; Rahatlou, Shahram; Sigamani, Michael; Soffi, Livia; Amapane, Nicola; Arcidiacono, Roberta; Argiro, Stefano; Arneodo, Michele; Biino, Cristina; Cartiglia, Nicolo; Casasso, Stefano; Costa, Marco; Demaria, Natale; Mariotti, Chiara; Maselli, Silvia; Migliore, Ernesto; Monaco, Vincenzo; Musich, Marco; Obertino, Maria Margherita; Pastrone, Nadia; Pelliccioni, Mario; Potenza, Alberto; Romero, Alessandra; Ruspa, Marta; Sacchi, Roberto; Solano, Ada; Staiano, Amedeo; Belforte, Stefano; Candelise, Vieri; Casarsa, Massimo; Cossutti, Fabio; Della Ricca, Giuseppe; Gobbo, Benigno; Marone, Matteo; Montanino, Damiana; Penzo, Aldo; Schizzi, Andrea; Kim, Tae Yeon; Nam, Soon-Kwon; Chang, Sunghyun; Kim, Dong Hee; Kim, Gui Nyun; Kong, Dae Jung; Park, Hyangkyu; Son, Dong-Chul; Son, Taejin; Kim, Jae Yool; Kim, Zero Jaeho; Song, Sanghyeon; Choi, Suyong; Gyun, Dooyeon; Hong, Byung-Sik; Jo, Mihee; Kim, Hyunchul; Kim, Tae Jeong; Lee, Kyong Sei; Moon, Dong Ho; Park, Sung Keun; Roh, Youn; Choi, Minkyoo; Kim, Ji Hyun; Park, Chawon; Park, Inkyu; Park, Sangnam; Ryu, Geonmo; Choi, Young-Il; Choi, Young Kyu; Goh, Junghwan; Kim, Min Suk; Kwon, Eunhyang; Lee, Byounghoon; Lee, Jongseok; Lee, Sungeun; Seo, Hyunkwan; Yu, Intae; Bilinskas, Mykolas Jurgis; Grigelionis, Ignas; Janulis, Mindaugas; Juodagalvis, Andrius; Castilla-Valdez, Heriberto; De La Cruz-Burelo, Eduard; Heredia-de La Cruz, Ivan; Lopez-Fernandez, Ricardo; Martínez-Ortega, Jorge; Sánchez Hernández, Alberto; Villasenor-Cendejas, Luis Manuel; Carrillo Moreno, Salvador; Vazquez Valencia, Fabiola; Salazar Ibarguen, Humberto Antonio; Casimiro Linares, Edgar; Morelos Pineda, Antonio; Reyes-Santos, Marco A; Krofcheck, David; Bell, Alan James; Butler, Philip H; Doesburg, Robert; Reucroft, Steve; Silverwood, Hamish; Ahmad, Muhammad; Asghar, Muhammad Irfan; Butt, Jamila; Hoorani, Hafeez R; Khalid, Shoaib; Khan, Wajid Ali; Khurshid, Taimoor; Qazi, Shamona; Shah, Mehar Ali; Shoaib, Muhammad; Bialkowska, Helena; Boimska, Bozena; Frueboes, Tomasz; Górski, Maciej; Kazana, Malgorzata; Nawrocki, Krzysztof; Romanowska-Rybinska, Katarzyna; Szleper, Michal; Wrochna, Grzegorz; Zalewski, Piotr; Brona, Grzegorz; Bunkowski, Karol; Cwiok, Mikolaj; Dominik, Wojciech; Doroba, Krzysztof; Kalinowski, Artur; Konecki, Marcin; Krolikowski, Jan; Misiura, Maciej; Almeida, Nuno; Bargassa, Pedrame; David Tinoco Mendes, Andre; Faccioli, Pietro; Ferreira Parracho, Pedro Guilherme; Gallinaro, Michele; Seixas, Joao; Varela, Joao; Vischia, Pietro; Belotelov, Ivan; Bunin, Pavel; Golutvin, Igor; Gorbunov, Ilya; Kamenev, Alexey; Karjavin, Vladimir; Kozlov, Guennady; Lanev, Alexander; Malakhov, Alexander; Moisenz, Petr; Palichik, Vladimir; Perelygin, Victor; Savina, Maria; Shmatov, Sergey; Smirnov, Vitaly; Volodko, Anton; Zarubin, Anatoli; Evstyukhin, Sergey; Golovtsov, Victor; Ivanov, Yury; Kim, Victor; Levchenko, Petr; Murzin, Victor; Oreshkin, Vadim; Smirnov, Igor; Sulimov, Valentin; Uvarov, Lev; Vavilov, Sergey; Vorobyev, Alexey; Vorobyev, Andrey; Andreev, Yuri; Dermenev, Alexander; Gninenko, Sergei; Golubev, Nikolai; Kirsanov, Mikhail; Krasnikov, Nikolai; Matveev, Viktor; Pashenkov, Anatoli; Tlisov, Danila; Toropin, Alexander; Epshteyn, Vladimir; Erofeeva, Maria; Gavrilov, Vladimir; Kossov, Mikhail; Lychkovskaya, Natalia; Popov, Vladimir; Safronov, Grigory; Semenov, Sergey; Shreyber, Irina; Stolin, Viatcheslav; Vlasov, Evgueni; Zhokin, Alexander; Belyaev, Andrey; Boos, Edouard; Dubinin, Mikhail; Dudko, Lev; Ershov, Alexander; Gribushin, Andrey; Klyukhin, Vyacheslav; Kodolova, Olga; Lokhtin, Igor; Markina, Anastasia; Obraztsov, Stepan; Perfilov, Maxim; Petrushanko, Sergey; Popov, Andrey; Sarycheva, Ludmila; Savrin, Viktor; Snigirev, Alexander; Andreev, Vladimir; Azarkin, Maksim; Dremin, Igor; Kirakosyan, Martin; Leonidov, Andrey; Mesyats, Gennady; Rusakov, Sergey V; Vinogradov, Alexey; Azhgirey, Igor; Bayshev, Igor; Bitioukov, Sergei; Grishin, Viatcheslav; Kachanov, Vassili; Konstantinov, Dmitri; Krychkine, Victor; Petrov, Vladimir; Ryutin, Roman; Sobol, Andrei; Tourtchanovitch, Leonid; Troshin, Sergey; Tyurin, Nikolay; Uzunian, Andrey; Volkov, Alexey; Adzic, Petar; Djordjevic, Milos; Ekmedzic, Marko; Krpic, Dragomir; Milosevic, Jovan; Aguilar-Benitez, Manuel; Alcaraz Maestre, Juan; Arce, Pedro; Battilana, Carlo; Calvo, Enrique; Cerrada, Marcos; Chamizo Llatas, Maria; Colino, Nicanor; De La Cruz, Begona; Delgado Peris, Antonio; Domínguez Vázquez, Daniel; Fernandez Bedoya, Cristina; Fernández Ramos, Juan Pablo; Ferrando, Antonio; Flix, Jose; Fouz, Maria Cruz; Garcia-Abia, Pablo; Gonzalez Lopez, Oscar; Goy Lopez, Silvia; Hernandez, Jose M; Josa, Maria Isabel; Merino, Gonzalo; Puerta Pelayo, Jesus; Quintario Olmeda, Adrián; Redondo, Ignacio; Romero, Luciano; Santaolalla, Javier; Senghi Soares, Mara; Willmott, Carlos; Albajar, Carmen; Codispoti, Giuseppe; de Trocóniz, Jorge F; Brun, Hugues; Cuevas, Javier; Fernandez Menendez, Javier; Folgueras, Santiago; Gonzalez Caballero, Isidro; Lloret Iglesias, Lara; Piedra Gomez, Jonatan; Brochero Cifuentes, Javier Andres; Cabrillo, Iban Jose; Calderon, Alicia; Chuang, Shan-Huei; Duarte Campderros, Jordi; Felcini, Marta; Fernandez, Marcos; Gomez, Gervasio; Gonzalez Sanchez, Javier; Graziano, Alberto; Jorda, Clara; Lopez Virto, Amparo; Marco, Jesus; Marco, Rafael; Martinez Rivero, Celso; Matorras, Francisco; Munoz Sanchez, Francisca Javiela; Rodrigo, Teresa; Rodríguez-Marrero, Ana Yaiza; Ruiz-Jimeno, Alberto; Scodellaro, Luca; Vila, Ivan; Vilar Cortabitarte, Rocio; Abbaneo, Duccio; Auffray, Etiennette; Auzinger, Georg; Bachtis, Michail; Baillon, Paul; Ball, Austin; Barney, David; Benitez, Jose F; Bernet, Colin; Bianchi, Giovanni; Bloch, Philippe; Bocci, Andrea; Bonato, Alessio; Botta, Cristina; Breuker, Horst; Camporesi, Tiziano; Cerminara, Gianluca; Christiansen, Tim; Coarasa Perez, Jose Antonio; D'Enterria, David; Dabrowski, Anne; De Roeck, Albert; Di Guida, Salvatore; Dobson, Marc; Dupont-Sagorin, Niels; Elliott-Peisert, Anna; Frisch, Benjamin; Funk, Wolfgang; Georgiou, Georgios; Giffels, Manuel; Gigi, Dominique; Gill, Karl; Giordano, Domenico; Girone, Maria; Giunta, Marina; Glege, Frank; Gomez-Reino Garrido, Robert; Govoni, Pietro; Gowdy, Stephen; Guida, Roberto; Gundacker, Stefan; Hammer, Josef; Hansen, Magnus; Harris, Philip; Hartl, Christian; Harvey, John; Hegner, Benedikt; Hinzmann, Andreas; Innocente, Vincenzo; Janot, Patrick; Kaadze, Ketino; Karavakis, Edward; Kousouris, Konstantinos; Lecoq, Paul; Lee, Yen-Jie; Lenzi, Piergiulio; Lourenco, Carlos; Magini, Nicolo; Maki, Tuula; Malberti, Martina; Malgeri, Luca; Mannelli, Marcello; Masetti, Lorenzo; Meijers, Frans; Mersi, Stefano; Meschi, Emilio; Moser, Roland; Mozer, Matthias Ulrich; Mulders, Martijn; Musella, Pasquale; Nesvold, Erik; Orsini, Luciano; Palencia Cortezon, Enrique; Perez, Emmanuelle; Perrozzi, Luca; Petrilli, Achille; Pfeiffer, Andreas; Pierini, Maurizio; Pimiä, Martti; Piparo, Danilo; Polese, Giovanni; Quertenmont, Loic; Racz, Attila; Reece, William; Rodrigues Antunes, Joao; Rolandi, Gigi; Rovelli, Chiara; Rovere, Marco; Sakulin, Hannes; Santanastasio, Francesco; Schäfer, Christoph; Schwick, Christoph; Segoni, Ilaria; Sekmen, Sezen; Sharma, Archana; Siegrist, Patrice; Silva, Pedro; Simon, Michal; Sphicas, Paraskevas; Spiga, Daniele; Tsirou, Andromachi; Veres, Gabor Istvan; Vlimant, Jean-Roch; Wöhri, Hermine Katharina; Worm, Steven; Zeuner, Wolfram Dietrich; Bertl, Willi; Deiters, Konrad; Erdmann, Wolfram; Gabathuler, Kurt; Horisberger, Roland; Ingram, Quentin; Kaestli, Hans-Christian; König, Stefan; Kotlinski, Danek; Langenegger, Urs; Meier, Frank; Renker, Dieter; Rohe, Tilman; Bäni, Lukas; Bortignon, Pierluigi; Buchmann, Marco-Andrea; Casal, Bruno; Chanon, Nicolas; Deisher, Amanda; Dissertori, Günther; Dittmar, Michael; Donegà, Mauro; Dünser, Marc; Eller, Philipp; Eugster, Jürg; Freudenreich, Klaus; Grab, Christoph; Hits, Dmitry; Lecomte, Pierre; Lustermann, Werner; Marini, Andrea Carlo; Martinez Ruiz del Arbol, Pablo; Mohr, Niklas; Moortgat, Filip; Nägeli, Christoph; Nef, Pascal; Nessi-Tedaldi, Francesca; Pandolfi, Francesco; Pape, Luc; Pauss, Felicitas; Peruzzi, Marco; Ronga, Frederic Jean; Rossini, Marco; Sala, Leonardo; Sanchez, Ann - Karin; Starodumov, Andrei; Stieger, Benjamin; Takahashi, Maiko; Tauscher, Ludwig; Thea, Alessandro; Theofilatos, Konstantinos; Treille, Daniel; Urscheler, Christina; Wallny, Rainer; Weber, Hannsjoerg Artur; Wehrli, Lukas; Amsler, Claude; Chiochia, Vincenzo; De Visscher, Simon; Favaro, Carlotta; Ivova Rikova, Mirena; Kilminster, Benjamin; Millan Mejias, Barbara; Otiougova, Polina; Robmann, Peter; Snoek, Hella; Tupputi, Salvatore; Verzetti, Mauro; Chang, Yuan-Hann; Chen, Kuan-Hsin; Ferro, Cristina; Kuo, Chia-Ming; Li, Syue-Wei; Lin, Willis; Lu, Yun-Ju; Singh, Anil; Volpe, Roberta; Yu, Shin-Shan; Bartalini, Paolo; Chang, Paoti; Chang, You-Hao; Chang, Yu-Wei; Chao, Yuan; Chen, Kai-Feng; Dietz, Charles; Grundler, Ulysses; Hou, George Wei-Shu; Hsiung, Yee; Kao, Kai-Yi; Lei, Yeong-Jyi; Lu, Rong-Shyang; Majumder, Devdatta; Petrakou, Eleni; Shi, Xin; Shiu, Jing-Ge; Tzeng, Yeng-Ming; Wan, Xia; Wang, Minzu; Asavapibhop, Burin; Srimanobhas, Norraphat; Adiguzel, Aytul; Bakirci, Mustafa Numan; Cerci, Salim; Dozen, Candan; Dumanoglu, Isa; Eskut, Eda; Girgis, Semiray; Gokbulut, Gul; Gurpinar, Emine; Hos, Ilknur; Kangal, Evrim Ersin; Karaman, Turker; Karapinar, Guler; Kayis Topaksu, Aysel; Onengut, Gulsen; Ozdemir, Kadri; Ozturk, Sertac; Polatoz, Ayse; Sogut, Kenan; Sunar Cerci, Deniz; Tali, Bayram; Topakli, Huseyin; Vergili, Latife Nukhet; Vergili, Mehmet; Akin, Ilina Vasileva; Aliev, Takhmasib; Bilin, Bugra; Bilmis, Selcuk; Deniz, Muhammed; Gamsizkan, Halil; Guler, Ali Murat; Ocalan, Kadir; Ozpineci, Altug; Serin, Meltem; Sever, Ramazan; Surat, Ugur Emrah; Yalvac, Metin; Yildirim, Eda; Zeyrek, Mehmet; Gülmez, Erhan; Isildak, Bora; Kaya, Mithat; Kaya, Ozlem; Ozkorucuklu, Suat; Sonmez, Nasuf; Cankocak, Kerem; Levchuk, Leonid; Brooke, James John; Clement, Emyr; Cussans, David; Flacher, Henning; Frazier, Robert; Goldstein, Joel; Grimes, Mark; Heath, Greg P; Heath, Helen F; Kreczko, Lukasz; Metson, Simon; Newbold, Dave M; Nirunpong, Kachanon; Poll, Anthony; Senkin, Sergey; Smith, Vincent J; Williams, Thomas; Basso, Lorenzo; Bell, Ken W; Belyaev, Alexander; Brew, Christopher; Brown, Robert M; Cockerill, David JA; Coughlan, John A; Harder, Kristian; Harper, Sam; Jackson, James; Kennedy, Bruce W; Olaiya, Emmanuel; Petyt, David; Radburn-Smith, Benjamin Charles; Shepherd-Themistocleous, Claire; Tomalin, Ian R; Womersley, William John; Bainbridge, Robert; Ball, Gordon; Beuselinck, Raymond; Buchmuller, Oliver; Colling, David; Cripps, Nicholas; Cutajar, Michael; Dauncey, Paul; Davies, Gavin; Della Negra, Michel; Ferguson, William; Fulcher, Jonathan; Futyan, David; Gilbert, Andrew; Guneratne Bryer, Arlo; Hall, Geoffrey; Hatherell, Zoe; Hays, Jonathan; Iles, Gregory; Jarvis, Martyn; Karapostoli, Georgia; Lyons, Louis; Magnan, Anne-Marie; Marrouche, Jad; Mathias, Bryn; Nandi, Robin; Nash, Jordan; Nikitenko, Alexander; Pela, Joao; Pesaresi, Mark; Petridis, Konstantinos; Pioppi, Michele; Raymond, David Mark; Rogerson, Samuel; Rose, Andrew; Ryan, Matthew John; Seez, Christopher; Sharp, Peter; Sparrow, Alex; Stoye, Markus; Tapper, Alexander; Vazquez Acosta, Monica; Virdee, Tejinder; Wakefield, Stuart; Wardle, Nicholas; Whyntie, Tom; Chadwick, Matthew; Cole, Joanne; Hobson, Peter R; Khan, Akram; Kyberd, Paul; Leggat, Duncan; Leslie, Dawn; Martin, William; Reid, Ivan; Symonds, Philip; Teodorescu, Liliana; Turner, Mark; Hatakeyama, Kenichi; Liu, Hongxuan; Scarborough, Tara; Charaf, Otman; Henderson, Conor; Rumerio, Paolo; Avetisyan, Aram; Bose, Tulika; Fantasia, Cory; Heister, Arno; St John, Jason; Lawson, Philip; Lazic, Dragoslav; Rohlf, James; Sperka, David; Sulak, Lawrence; Alimena, Juliette; Bhattacharya, Saptaparna; Christopher, Grant; Cutts, David; Demiragli, Zeynep; Ferapontov, Alexey; Garabedian, Alex; Heintz, Ulrich; Jabeen, Shabnam; Kukartsev, Gennadiy; Laird, Edward; Landsberg, Greg; Luk, Michael; Narain, Meenakshi; Nguyen, Duong; Segala, Michael; Sinthuprasith, Tutanon; Speer, Thomas; Breedon, Richard; Breto, Guillermo; Calderon De La Barca Sanchez, Manuel; Chauhan, Sushil; Chertok, Maxwell; Conway, John; Conway, Rylan; Cox, Peter Timothy; Dolen, James; Erbacher, Robin; Gardner, Michael; Houtz, Rachel; Ko, Winston; Kopecky, Alexandra; Lander, Richard; Mall, Orpheus; Miceli, Tia; Pellett, Dave; Ricci-Tam, Francesca; Rutherford, Britney; Searle, Matthew; Smith, John; Squires, Michael; Tripathi, Mani; Vasquez Sierra, Ricardo; Yohay, Rachel; Andreev, Valeri; Cline, David; Cousins, Robert; Duris, Joseph; Erhan, Samim; Everaerts, Pieter; Farrell, Chris; Hauser, Jay; Ignatenko, Mikhail; Jarvis, Chad; Rakness, Gregory; Schlein, Peter; Traczyk, Piotr; Valuev, Vyacheslav; Weber, Matthias; Babb, John; Clare, Robert; Dinardo, Mauro Emanuele; Ellison, John Anthony; Gary, J William; Giordano, Ferdinando; Hanson, Gail; Liu, Hongliang; Long, Owen Rosser; Luthra, Arun; Nguyen, Harold; Paramesvaran, Sudarshan; Sturdy, Jared; Sumowidagdo, Suharyo; Wilken, Rachel; Wimpenny, Stephen; Andrews, Warren; Branson, James G; Cerati, Giuseppe Benedetto; Cittolin, Sergio; Evans, David; Holzner, André; Kelley, Ryan; Lebourgeois, Matthew; Letts, James; Macneill, Ian; Mangano, Boris; Padhi, Sanjay; Palmer, Christopher; Petrucciani, Giovanni; Pieri, Marco; Sani, Matteo; Sharma, Vivek; Simon, Sean; Sudano, Elizabeth; Tadel, Matevz; Tu, Yanjun; Vartak, Adish; Wasserbaech, Steven; Würthwein, Frank; Yagil, Avraham; Yoo, Jaehyeok; Barge, Derek; Bellan, Riccardo; Campagnari, Claudio; D'Alfonso, Mariarosaria; Danielson, Thomas; Flowers, Kristen; Geffert, Paul; Golf, Frank; Incandela, Joe; Justus, Christopher; Kalavase, Puneeth; Kovalskyi, Dmytro; Krutelyov, Vyacheslav; Lowette, Steven; Magaña Villalba, Ricardo; Mccoll, Nickolas; Pavlunin, Viktor; Ribnik, Jacob; Richman, Jeffrey; Rossin, Roberto; Stuart, David; To, Wing; West, Christopher; Apresyan, Artur; Bornheim, Adolf; Chen, Yi; Di Marco, Emanuele; Duarte, Javier; Gataullin, Marat; Ma, Yousi; Mott, Alexander; Newman, Harvey B; Rogan, Christopher; Spiropulu, Maria; Timciuc, Vladlen; Veverka, Jan; Wilkinson, Richard; Xie, Si; Yang, Yong; Zhu, Ren-Yuan; Azzolini, Virginia; Calamba, Aristotle; Carroll, Ryan; Ferguson, Thomas; Iiyama, Yutaro; Jang, Dong Wook; Liu, Yueh-Feng; Paulini, Manfred; Vogel, Helmut; Vorobiev, Igor; Cumalat, John Perry; Drell, Brian Robert; Ford, William T; Gaz, Alessandro; Luiggi Lopez, Eduardo; Smith, James; Stenson, Kevin; Ulmer, Keith; Wagner, Stephen Robert; Alexander, James; Chatterjee, Avishek; Eggert, Nicholas; Gibbons, Lawrence Kent; Heltsley, Brian; Hopkins, Walter; Khukhunaishvili, Aleko; Kreis, Benjamin; Mirman, Nathan; Nicolas Kaufman, Gala; Patterson, Juliet Ritchie; Ryd, Anders; Salvati, Emmanuele; Sun, Werner; Teo, Wee Don; Thom, Julia; Thompson, Joshua; Tucker, Jordan; Vaughan, Jennifer; Weng, Yao; Winstrom, Lucas; Wittich, Peter; Winn, Dave; Abdullin, Salavat; Albrow, Michael; Anderson, Jacob; Bauerdick, Lothar AT; Beretvas, Andrew; Berryhill, Jeffrey; Bhat, Pushpalatha C; Burkett, Kevin; Butler, Joel Nathan; Chetluru, Vasundhara; Cheung, Harry; Chlebana, Frank; Elvira, Victor Daniel; Fisk, Ian; Freeman, Jim; Gao, Yanyan; Green, Dan; Gutsche, Oliver; Hanlon, Jim; Harris, Robert M; Hirschauer, James; Hooberman, Benjamin; Jindariani, Sergo; Johnson, Marvin; Joshi, Umesh; Klima, Boaz; Kunori, Shuichi; Kwan, Simon; Leonidopoulos, Christos; Linacre, Jacob; Lincoln, Don; Lipton, Ron; Lykken, Joseph; Maeshima, Kaori; Marraffino, John Michael; Maruyama, Sho; Mason, David; McBride, Patricia; Mishra, Kalanand; Mrenna, Stephen; Musienko, Yuri; Newman-Holmes, Catherine; O'Dell, Vivian; Prokofyev, Oleg; Sexton-Kennedy, Elizabeth; Sharma, Seema; Spalding, William J; Spiegel, Leonard; Taylor, Lucas; Tkaczyk, Slawek; Tran, Nhan Viet; Uplegger, Lorenzo; Vaandering, Eric Wayne; Vidal, Richard; Whitmore, Juliana; Wu, Weimin; Yang, Fan; Yun, Jae Chul; Acosta, Darin; Avery, Paul; Bourilkov, Dimitri; Chen, Mingshui; Cheng, Tongguang; Das, Souvik; De Gruttola, Michele; Di Giovanni, Gian Piero; Dobur, Didar; Drozdetskiy, Alexey; Field, Richard D; Fisher, Matthew; Fu, Yu; Furic, Ivan-Kresimir; Gartner, Joseph; Hugon, Justin; Kim, Bockjoo; Konigsberg, Jacobo; Korytov, Andrey; Kropivnitskaya, Anna; Kypreos, Theodore; Low, Jia Fu; Matchev, Konstantin; Milenovic, Predrag; Mitselmakher, Guenakh; Muniz, Lana; Park, Myeonghun; Remington, Ronald; Rinkevicius, Aurelijus; Sellers, Paul; Skhirtladze, Nikoloz; Snowball, Matthew; Yelton, John; Zakaria, Mohammed; Gaultney, Vanessa; Hewamanage, Samantha; Lebolo, Luis Miguel; Linn, Stephan; Markowitz, Pete; Martinez, German; Rodriguez, Jorge Luis; Adams, Todd; Askew, Andrew; Bochenek, Joseph; Chen, Jie; Diamond, Brendan; Gleyzer, Sergei V; Haas, Jeff; Hagopian, Sharon; Hagopian, Vasken; Jenkins, Merrill; Johnson, Kurtis F; Prosper, Harrison; Veeraraghavan, Venkatesh; Weinberg, Marc; Baarmand, Marc M; Dorney, Brian; Hohlmann, Marcus; Kalakhety, Himali; Vodopiyanov, Igor; Yumiceva, Francisco; Adams, Mark Raymond; Anghel, Ioana Maria; Apanasevich, Leonard; Bai, Yuting; Bazterra, Victor Eduardo; Betts, Russell Richard; Bucinskaite, Inga; Callner, Jeremy; Cavanaugh, Richard; Evdokimov, Olga; Gauthier, Lucie; Gerber, Cecilia Elena; Hofman, David Jonathan; Khalatyan, Samvel; Lacroix, Florent; O'Brien, Christine; Silkworth, Christopher; Strom, Derek; Turner, Paul; Varelas, Nikos; Akgun, Ugur; Albayrak, Elif Asli; Bilki, Burak; Clarida, Warren; Duru, Firdevs; Griffiths, Scott; Merlo, Jean-Pierre; Mermerkaya, Hamit; Mestvirishvili, Alexi; Moeller, Anthony; Nachtman, Jane; Newsom, Charles Ray; Norbeck, Edwin; Onel, Yasar; Ozok, Ferhat; Sen, Sercan; Tan, Ping; Tiras, Emrah; Wetzel, James; Yetkin, Taylan; Yi, Kai; Barnett, Bruce Arnold; Blumenfeld, Barry; Bolognesi, Sara; Fehling, David; Giurgiu, Gavril; Gritsan, Andrei; Guo, Zijin; Hu, Guofan; Maksimovic, Petar; Swartz, Morris; Whitbeck, Andrew; Baringer, Philip; Bean, Alice; Benelli, Gabriele; Kenny Iii, Raymond Patrick; Murray, Michael; Noonan, Daniel; Sanders, Stephen; Stringer, Robert; Tinti, Gemma; Wood, Jeffrey Scott; Barfuss, Anne-Fleur; Bolton, Tim; Chakaberia, Irakli; Ivanov, Andrew; Khalil, Sadia; Makouski, Mikhail; Maravin, Yurii; Shrestha, Shruti; Svintradze, Irakli; Gronberg, Jeffrey; Lange, David; Rebassoo, Finn; Wright, Douglas; Baden, Drew; Calvert, Brian; Eno, Sarah Catherine; Gomez, Jaime; Hadley, Nicholas John; Kellogg, Richard G; Kirn, Malina; Kolberg, Ted; Lu, Ying; Marionneau, Matthieu; Mignerey, Alice; Pedro, Kevin; Peterman, Alison; Skuja, Andris; Temple, Jeffrey; Tonjes, Marguerite; Tonwar, Suresh C; Apyan, Aram; Bauer, Gerry; Bendavid, Joshua; Busza, Wit; Butz, Erik; Cali, Ivan Amos; Chan, Matthew; Dutta, Valentina; Gomez Ceballos, Guillelmo; Goncharov, Maxim; Kim, Yongsun; Klute, Markus; Krajczar, Krisztian; Levin, Andrew; Luckey, Paul David; Ma, Teng; Nahn, Steve; Paus, Christoph; Ralph, Duncan; Roland, Christof; Roland, Gunther; Rudolph, Matthew; Stephans, George; Stöckli, Fabian; Sumorok, Konstanty; Sung, Kevin; Velicanu, Dragos; Wenger, Edward Allen; Wolf, Roger; Wyslouch, Bolek; Yang, Mingming; Yilmaz, Yetkin; Yoon, Sungho; Zanetti, Marco; Zhukova, Victoria; Cooper, Seth; Dahmes, Bryan; De Benedetti, Abraham; Franzoni, Giovanni; Gude, Alexander; Kao, Shih-Chuan; Klapoetke, Kevin; Kubota, Yuichi; Mans, Jeremy; Pastika, Nathaniel; Rusack, Roger; Sasseville, Michael; Singovsky, Alexander; Tambe, Norbert; Turkewitz, Jared; Cremaldi, Lucien Marcus; Kroeger, Rob; Perera, Lalith; Rahmat, Rahmat; Sanders, David A; Avdeeva, Ekaterina; Bloom, Kenneth; Bose, Suvadeep; Claes, Daniel R; Dominguez, Aaron; Eads, Michael; Keller, Jason; Kravchenko, Ilya; Lazo-Flores, Jose; Malik, Sudhir; Snow, Gregory R; Godshalk, Andrew; Iashvili, Ia; Jain, Supriya; Kharchilava, Avto; Kumar, Ashish; Rappoccio, Salvatore; Alverson, George; Barberis, Emanuela; Baumgartel, Darin; Chasco, Matthew; Haley, Joseph; Nash, David; Orimoto, Toyoko; Trocino, Daniele; Wood, Darien; Zhang, Jinzhong; Anastassov, Anton; Hahn, Kristan Allan; Kubik, Andrew; Lusito, Letizia; Mucia, Nicholas; Odell, Nathaniel; Ofierzynski, Radoslaw Adrian; Pollack, Brian; Pozdnyakov, Andrey; Schmitt, Michael Henry; Stoynev, Stoyan; Velasco, Mayda; Won, Steven; Antonelli, Louis; Berry, Douglas; Brinkerhoff, Andrew; Chan, Kwok Ming; Hildreth, Michael; Jessop, Colin; Karmgard, Daniel John; Kolb, Jeff; Lannon, Kevin; Luo, Wuming; Lynch, Sean; Marinelli, Nancy; Morse, David Michael; Pearson, Tessa; Planer, Michael; Ruchti, Randy; Slaunwhite, Jason; Valls, Nil; Wayne, Mitchell; Wolf, Matthias; Bylsma, Ben; Durkin, Lloyd Stanley; Hill, Christopher; Hughes, Richard; Kotov, Khristian; Ling, Ta-Yung; Puigh, Darren; Rodenburg, Marissa; Vuosalo, Carl; Williams, Grayson; Winer, Brian L; Berry, Edmund; Elmer, Peter; Halyo, Valerie; Hebda, Philip; Hegeman, Jeroen; Hunt, Adam; Jindal, Pratima; Koay, Sue Ann; Lopes Pegna, David; Lujan, Paul; Marlow, Daniel; Medvedeva, Tatiana; Mooney, Michael; Olsen, James; Piroué, Pierre; Quan, Xiaohang; Raval, Amita; Saka, Halil; Stickland, David; Tully, Christopher; Werner, Jeremy Scott; Zuranski, Andrzej; Brownson, Eric; Lopez, Angel; Mendez, Hector; Ramirez Vargas, Juan Eduardo; Alagoz, Enver; Barnes, Virgil E; Benedetti, Daniele; Bolla, Gino; Bortoletto, Daniela; De Mattia, Marco; Everett, Adam; Hu, Zhen; Jones, Matthew; Koybasi, Ozhan; Kress, Matthew; Laasanen, Alvin T; Leonardo, Nuno; Maroussov, Vassili; Merkel, Petra; Miller, David Harry; Neumeister, Norbert; Shipsey, Ian; Silvers, David; Svyatkovskiy, Alexey; Vidal Marono, Miguel; Yoo, Hwi Dong; Zablocki, Jakub; Zheng, Yu; Guragain, Samir; Parashar, Neeti; Adair, Antony; Akgun, Bora; Boulahouache, Chaouki; Ecklund, Karl Matthew; Geurts, Frank JM; Li, Wei; Padley, Brian Paul; Redjimi, Radia; Roberts, Jay; Zabel, James; Betchart, Burton; Bodek, Arie; Chung, Yeon Sei; Covarelli, Roberto; de Barbaro, Pawel; Demina, Regina; Eshaq, Yossof; Ferbel, Thomas; Garcia-Bellido, Aran; Goldenzweig, Pablo; Han, Jiyeon; Harel, Amnon; Miner, Daniel Carl; Vishnevskiy, Dmitry; Zielinski, Marek; Bhatti, Anwar; Ciesielski, Robert; Demortier, Luc; Goulianos, Konstantin; Lungu, Gheorghe; Malik, Sarah; Mesropian, Christina; Arora, Sanjay; Barker, Anthony; Chou, John Paul; Contreras-Campana, Christian; Contreras-Campana, Emmanuel; Duggan, Daniel; Ferencek, Dinko; Gershtein, Yuri; Gray, Richard; Halkiadakis, Eva; Hidas, Dean; Lath, Amitabh; Panwalkar, Shruti; Park, Michael; Patel, Rishi; Rekovic, Vladimir; Robles, Jorge; Rose, Keith; Salur, Sevil; Schnetzer, Steve; Seitz, Claudia; Somalwar, Sunil; Stone, Robert; Thomas, Scott; Walker, Matthew; Cerizza, Giordano; Hollingsworth, Matthew; Spanier, Stefan; Yang, Zong-Chang; York, Andrew; Eusebi, Ricardo; Flanagan, Will; Gilmore, Jason; Kamon, Teruki; Khotilovich, Vadim; Montalvo, Roy; Osipenkov, Ilya; Pakhotin, Yuriy; Perloff, Alexx; Roe, Jeffrey; Safonov, Alexei; Sakuma, Tai; Sengupta, Sinjini; Suarez, Indara; Tatarinov, Aysen; Toback, David; Akchurin, Nural; Damgov, Jordan; Dragoiu, Cosmin; Dudero, Phillip Russell; Jeong, Chiyoung; Kovitanggoon, Kittikul; Lee, Sung Won; Libeiro, Terence; Volobouev, Igor; Appelt, Eric; Delannoy, Andrés G; Florez, Carlos; Greene, Senta; Gurrola, Alfredo; Johns, Willard; Kurt, Pelin; Maguire, Charles; Melo, Andrew; Sharma, Monika; Sheldon, Paul; Snook, Benjamin; Tuo, Shengquan; Velkovska, Julia; Arenton, Michael Wayne; Balazs, Michael; Boutle, Sarah; Cox, Bradley; Francis, Brian; Goodell, Joseph; Hirosky, Robert; Ledovskoy, Alexander; Lin, Chuanzhe; Neu, Christopher; Wood, John; Gollapinni, Sowjanya; Harr, Robert; Karchin, Paul Edmund; Kottachchi Kankanamge Don, Chamath; Lamichhane, Pramod; Sakharov, Alexandre; Anderson, Michael; Belknap, Donald; Borrello, Laura; Carlsmith, Duncan; Cepeda, Maria; Dasu, Sridhara; Friis, Evan; Gray, Lindsey; Grogg, Kira Suzanne; Grothe, Monika; Hall-Wilton, Richard; Herndon, Matthew; Hervé, Alain; Klabbers, Pamela; Klukas, Jeffrey; Lanaro, Armando; Lazaridis, Christos; Loveless, Richard; Mohapatra, Ajit; Ojalvo, Isabel; Palmonari, Francesco; Pierro, Giuseppe Antonio; Ross, Ian; Savin, Alexander; Smith, Wesley H; Swanson, Joshua

    2013-04-02

    In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98 inverse femtobarns of proton-proton collisions at the center of mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (missing ET > 40 GeV) and total hadronic transverse energy (HT > 120 GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observation, yielding limits in the context of the constrained mininal supersymmetric standard model and on a set of simplified models.

  2. Fast oscillations in cortical-striatal networks switch frequency following rewarding events and stimulant drugs.

    Science.gov (United States)

    Berke, J D

    2009-09-01

    Oscillations may organize communication between components of large-scale brain networks. Although gamma-band oscillations have been repeatedly observed in cortical-basal ganglia circuits, their functional roles are not yet clear. Here I show that, in behaving rats, distinct frequencies of ventral striatal local field potential oscillations show coherence with different cortical inputs. The approximately 50 Hz gamma oscillations that normally predominate in awake ventral striatum are coherent with piriform cortex, whereas approximately 80-100 Hz high-gamma oscillations are coherent with frontal cortex. Within striatum, entrainment to gamma rhythms is selective to fast-spiking interneurons, with distinct fast-spiking interneuron populations entrained to different gamma frequencies. Administration of the psychomotor stimulant amphetamine or the dopamine agonist apomorphine causes a prolonged decrease in approximately 50 Hz power and increase in approximately 80-100 Hz power. The same frequency switch is observed for shorter epochs spontaneously in awake, undrugged animals and is consistently provoked for reward receipt. Individual striatal neurons can participate in these brief high-gamma bursts with, or without, substantial changes in firing rate. Switching between discrete oscillatory states may allow different modes of information processing during decision-making and reinforcement-based learning, and may also be an important systems-level process by which stimulant drugs affect cognition and behavior.

  3. Modeling the energy performance of event-driven wireless sensor network by using static sink and mobile sink.

    Science.gov (United States)

    Chen, Jiehui; Salim, Mariam B; Matsumoto, Mitsuji

    2010-01-01

    Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations.

  4. Modeling the Energy Performance of Event-Driven Wireless Sensor Network by Using Static Sink and Mobile Sink

    Science.gov (United States)

    Chen, Jiehui; Salim, Mariam B.; Matsumoto, Mitsuji

    2010-01-01

    Wireless Sensor Networks (WSNs) designed for mission-critical applications suffer from limited sensing capacities, particularly fast energy depletion. Regarding this, mobile sinks can be used to balance the energy consumption in WSNs, but the frequent location updates of the mobile sinks can lead to data collisions and rapid energy consumption for some specific sensors. This paper explores an optimal barrier coverage based sensor deployment for event driven WSNs where a dual-sink model was designed to evaluate the energy performance of not only static sensors, but Static Sink (SS) and Mobile Sinks (MSs) simultaneously, based on parameters such as sensor transmission range r and the velocity of the mobile sink v, etc. Moreover, a MS mobility model was developed to enable SS and MSs to effectively collaborate, while achieving spatiotemporal energy performance efficiency by using the knowledge of the cumulative density function (cdf), Poisson process and M/G/1 queue. The simulation results verified that the improved energy performance of the whole network was demonstrated clearly and our eDSA algorithm is more efficient than the static-sink model, reducing energy consumption approximately in half. Moreover, we demonstrate that our results are robust to realistic sensing models and also validate the correctness of our results through extensive simulations. PMID:22163503

  5. Using additional external inputs to forecast water quality with an artificial neural network for contamination event detection in source water

    Science.gov (United States)

    Schmidt, F.; Liu, S.

    2016-12-01

    Source water quality plays an important role for the safety of drinking water and early detection of its contamination is vital to taking appropriate countermeasures. However, compared to drinking water, it is more difficult to detect contamination events because its environment is less controlled and numerous natural causes contribute to a high variability of the background values. In this project, Artificial Neural Networks (ANNs) and a Contamination Event Detection Process (CED Process) were used to identify events in river water. The ANN models the response of basic water quality sensors obtained in laboratory experiments in an off-line learning stage and continuously forecasts future values of the time line in an on-line forecasting step. During this second stage, the CED Process compares the forecast to the measured value and classifies it as regular background or event value, which modifies the ANN's continuous learning and influences its forecasts. In addition to this basic setup, external information is fed to the CED Process: A so-called Operator Input (OI) is provided to inform about unusual water quality levels that are unrelated to the presence of contamination, for example due to cooling water discharge from a nearby power plant. This study's primary goal is to evaluate how well the OI fits into the design of the combined forecasting ANN and CED Process and to understand its effects on the online forecasting stage. To test this, data from laboratory experiments conducted previously at the School of Environment, Tsinghua University, have been used to perform simulations highlighting features and drawbacks of this method. Applying the OI has been shown to have a positive influence on the ANN's ability to handle a sudden change in background values, which is unrelated to contamination. However, it might also mask the presence of an event, an issue that underlines the necessity to have several instances of the algorithm run in parallel. Other difficulties

  6. Gastrointestinal Adverse Events of Dipeptidyl Peptidase 4 Inhibitors in Type 2 Diabetes: A Systematic Review and Network Meta-analysis.

    Science.gov (United States)

    Wu, Shanshan; Chai, Sanbao; Yang, Jun; Cai, Ting; Xu, Yang; Yang, Zhirong; Zhang, Yuan; Ji, Linong; Sun, Feng; Zhan, Siyan

    2017-09-01

    The purpose of this study was to systematically evaluate the effect of dipeptidyl peptidase 4 inhibitors on gastrointestinal adverse events in patients with type 2 diabetes. MEDLINE, Embase, the Cochrane Library, and ClinicalTrials.gov were searched from inception through April 28, 2016. Randomized controlled trials that compared dipeptidyl peptidase 4 inhibitor-based therapies with placebo and other hypoglycemic agents in type 2 diabetes were included. The duration of studies was at least 4 weeks. A total of 165 randomized controlled trials and 122,072 patients were included in the study. Dipeptidyl peptidase 4 inhibitors did not increase the incidence of gastrointestinal adverse events after the treatment with alogliptin (odds ratio [OR] = 0.83; 95% CI, 0.59-1.15), linagliptin (OR = 1.11; 95% CI, 0.92-1.35), saxagliptin (OR = 0.96; 95% CI, 0.80-1.15), sitagliptin (OR = 0.95; 95% CI, 0.64-1.14), teneligliptin (OR = 1.50; 95% CI, 0.81-2.77), and vildagliptin (OR = 0.80; 95% CI, 0.63-1.01) compared with placebo. Compared with glucagon-like peptide 1 receptor agonists, dipeptidyl peptidase 4 inhibitors significantly decreased the incidence of gastrointestinal adverse events with alogliptin (OR = 0.26; 95% CI, 0.15-0.44), linagliptin (OR = 0.43; 95% CI, 0.25-0.74), saxagliptin (OR = 0.28; 95% CI, 0.17-0.46), sitagliptin (OR = 0.24; 95% CI, 0.17-0.35), and vildagliptin (OR = 0.27; 95% CI, 0.18-0.41). Dipeptidyl peptidase 4 inhibitors were not associated with an increased risk of gastrointestinal adverse events relative to metformin and α-glucosidase inhibitors, respectively. The network meta-analysis found that compared with glucagon-like peptide 1 receptor agonists, metformin, and α-glucosidase inhibitor, dipeptidyl peptidase 4 inhibitors are associated with a lower incidence of gastrointestinal adverse events. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

  7. Automated Detection of Obstructive Sleep Apnea Events from a Single-Lead Electrocardiogram Using a Convolutional Neural Network.

    Science.gov (United States)

    Urtnasan, Erdenebayar; Park, Jong-Uk; Joo, Eun-Yeon; Lee, Kyoung-Joung

    2018-04-23

    In this study, we propose a method for the automated detection of obstructive sleep apnea (OSA) from a single-lead electrocardiogram (ECG) using a convolutional neural network (CNN). A CNN model was designed with six optimized convolution layers including activation, pooling, and dropout layers. One-dimensional (1D) convolution, rectified linear units (ReLU), and max pooling were applied to the convolution, activation, and pooling layers, respectively. For training and evaluation of the CNN model, a single-lead ECG dataset was collected from 82 subjects with OSA and was divided into training (including data from 63 patients with 34,281 events) and testing (including data from 19 patients with 8571 events) datasets. Using this CNN model, a precision of 0.99%, a recall of 0.99%, and an F 1 -score of 0.99% were attained with the training dataset; these values were all 0.96% when the CNN was applied to the testing dataset. These results show that the proposed CNN model can be used to detect OSA accurately on the basis of a single-lead ECG. Ultimately, this CNN model may be used as a screening tool for those suspected to suffer from OSA.

  8. Distributed Event-Based Set-Membership Filtering for a Class of Nonlinear Systems With Sensor Saturations Over Sensor Networks.

    Science.gov (United States)

    Ma, Lifeng; Wang, Zidong; Lam, Hak-Keung; Kyriakoulis, Nikos

    2017-11-01

    In this paper, the distributed set-membership filtering problem is investigated for a class of discrete time-varying system with an event-based communication mechanism over sensor networks. The system under consideration is subject to sector-bounded nonlinearity, unknown but bounded noises and sensor saturations. Each intelligent sensing node transmits the data to its neighbors only when certain triggering condition is violated. By means of a set of recursive matrix inequalities, sufficient conditions are derived for the existence of the desired distributed event-based filter which is capable of confining the system state in certain ellipsoidal regions centered at the estimates. Within the established theoretical framework, two additional optimization problems are formulated: one is to seek the minimal ellipsoids (in the sense of matrix trace) for the best filtering performance, and the other is to maximize the triggering threshold so as to reduce the triggering frequency with satisfactory filtering performance. A numerically attractive chaos algorithm is employed to solve the optimization problems. Finally, an illustrative example is presented to demonstrate the effectiveness and applicability of the proposed algorithm.

  9. HIV-1 subtype F1 epidemiological networks among Italian heterosexual males are associated with introduction events from South America.

    Science.gov (United States)

    Lai, Alessia; Simonetti, Francesco R; Zehender, Gianguglielmo; De Luca, Andrea; Micheli, Valeria; Meraviglia, Paola; Corsi, Paola; Bagnarelli, Patrizia; Almi, Paolo; Zoncada, Alessia; Paolucci, Stefania; Gonnelli, Angela; Colao, Grazia; Tacconi, Danilo; Franzetti, Marco; Ciccozzi, Massimo; Zazzi, Maurizio; Balotta, Claudia

    2012-01-01

    About 40% of the Italian HIV-1 epidemic due to non-B variants is sustained by F1 clade, which circulates at high prevalence in South America and Eastern Europe. Aim of this study was to define clade F1 origin, population dynamics and epidemiological networks through phylogenetic approaches. We analyzed pol sequences of 343 patients carrying F1 subtype stored in the ARCA database from 1998 to 2009. Citizenship of patients was as follows: 72.6% Italians, 9.3% South Americans and 7.3% Rumanians. Heterosexuals, Homo-bisexuals, Intravenous Drug Users accounted for 58.1%, 24.0% and 8.8% of patients, respectively. Phylogenetic analysis indicated that 70% of sequences clustered in 27 transmission networks. Two distinct groups were identified; the first clade, encompassing 56 sequences, included all Rumanian patients. The second group involved the remaining clusters and included 10 South American Homo-bisexuals in 9 distinct clusters. Heterosexual modality of infection was significantly associated with the probability to be detected in transmission networks. Heterosexuals were prevalent either among Italians (67.2%) or Rumanians (50%); by contrast, Homo-bisexuals accounted for 71.4% of South Americans. Among patients with resistant strains the proportion of clustering sequences was 57.1%, involving 14 clusters (51.8%). Resistance in clusters tended to be higher in South Americans (28.6%) compared to Italian (17.7%) and Rumanian patients (14.3%). A striking proportion of epidemiological networks could be identified in heterosexuals carrying F1 subtype residing in Italy. Italian Heterosexual males predominated within epidemiological clusters while foreign patients were mainly Heterosexual Rumanians, both males and females, and South American Homo-bisexuals. Tree topology suggested that F1 variant from South America gave rise to the Italian F1 epidemic through multiple introduction events. The contact tracing also revealed an unexpected burden of resistance in epidemiological

  10. A study of epileptogenic network structures in rat hippocampal cultures using first spike latencies during synchronization events

    International Nuclear Information System (INIS)

    Raghavan, Mohan; Amrutur, Bharadwaj; Srinivas, Kalyan V; Sikdar, Sujit K

    2012-01-01

    Study of hypersynchronous activity is of prime importance for combating epilepsy. Studies on network structure typically reconstruct the network by measuring various aspects of the interaction between neurons and subsequently measure the properties of the reconstructed network. In sub-sampled networks such methods lead to significant errors in reconstruction. Using rat hippocampal neurons cultured on a multi-electrode array dish and a glutamate injury model of epilepsy in vitro, we studied synchronous activity in neuronal networks. Using the first spike latencies in various neurons during a network burst, we extract various recurring spatio-temporal onset patterns in the networks. Comparing the patterns seen in control and injured networks, we observe that injured networks express a wide diversity in their foci (origin) and activation pattern, while control networks show limited diversity. Furthermore, we note that onset patterns in glutamate injured networks show a positive correlation between synchronization delay and physical distance between neurons, while control networks do not. (paper)

  11. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments; Reseau a multiplexage statistique pour les systemes de selection et de reconstruction d'evenements dans les experiences de physique des hautes energies

    Energy Technology Data Exchange (ETDEWEB)

    Calvet, D

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers ({approx}1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  12. Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events : the case of HSR (high speed rail)

    NARCIS (Netherlands)

    Janic, M.

    2018-01-01

    This paper deals with modelling the dynamic resilience of rail passenger transport networks affected by large-scale disruptive events whose impacts deteriorate the networks’ planned infrastructural, operational, economic, and social-economic performances represented by the selected indicators.

  13. Neural network approach to the prediction of seismic events based on low-frequency signal monitoring of the Kuril-Kamchatka and Japanese regions

    Directory of Open Access Journals (Sweden)

    Irina Popova

    2013-08-01

    Full Text Available Very-low-frequency/ low-frequency (VLF/LF sub-ionospheric radiowave monitoring has been widely used in recent years to analyze earthquake preparatory processes. The connection between earthquakes with M ≥5.5 and nighttime disturbances of signal amplitude and phase has been established. Thus, it is possible to use nighttime anomalies of VLF/LF signals as earthquake precursors. Here, we propose a method for estimation of the VLF/LF signal sensitivity to seismic processes using a neural network approach. We apply the error back-propagation technique based on a three-level perceptron to predict a seismic event. The back-propagation technique involves two main stages to solve the problem; namely, network training, and recognition (the prediction itself. To train a neural network, we first create a so-called ‘training set’. The ‘teacher’ specifies the correspondence between the chosen input and the output data. In the present case, a representative database includes both the LF data received over three years of monitoring at the station in Petropavlovsk-Kamchatsky (2005-2007, and the seismicity parameters of the Kuril-Kamchatka and Japanese regions. At the first stage, the neural network established the relationship between the characteristic features of the LF signal (the mean and dispersion of a phase and an amplitude at nighttime for a few days before a seismic event and the corresponding level of correlation with a seismic event, or the absence of a seismic event. For the second stage, the trained neural network was applied to predict seismic events from the LF data using twelve time intervals in 2004, 2005, 2006 and 2007. The results of the prediction are discussed.

  14. A new strategy for weak events in sparse networks: the first-motion polarity solutions constrained by single-station waveform inversion

    Czech Academy of Sciences Publication Activity Database

    Fojtíková, Lucia; Zahradník, J.

    2014-01-01

    Roč. 85, č. 6 (2014), s. 1265-1274 ISSN 0895-0695 R&D Projects: GA ČR GAP210/12/2336 Institutional support: RVO:67985891 Keywords : weak events * sparse networks * focal mechanism * waveform inversion Subject RIV: DC - Siesmology, Volcanology, Earth Structure Impact factor: 2.156, year: 2014 http://srl.geoscienceworld.org/content/85/6/1265.full

  15. Reliable Maintanace of Wireless Sensor Networks for Event-detection Applications%事件检测型传感器网络的可靠性维护

    Institute of Scientific and Technical Information of China (English)

    胡四泉; 杨金阳; 王俊峰

    2011-01-01

    The reliability maintannace of the wireless sensor network is a key point to keep the alarm messages delivered reliably to the monitor center on time in a event-detection application. Based on the unreliable links in the wireless sensor network and the network charateristics of an event detection application,MPRRM,a multiple path redundant reliability maintanace algoritm was proposed in this paper. Both analytical and simulation results show that the MPRRM algorithm is superior to the previous published solutions in the metrics of reliability, false positive rate, latency and message overhead.%传感器网络(Wireless Sensor Networks,WSN)的事件检测型应用中,如何通过可靠性维护来保证在检测到事件时报警信息能及时、可靠地传输到监控主机至关重要.通过对不可靠的无线链路和网络传输的分析,提出多路冗余可靠性维护算法MPRRM.通过解析方法和仿真分析证明,该算法在可靠性、误报率、延迟和消息开销量上比同类算法具有优势.

  16. STRATEGIES FOCUSING ON VALUE NETWORK: AN ANALYSIS OF EVENT PRODUCTION COMPANIEShttp://dx.doi.org/10.5585/riae.v9i1.1658

    Directory of Open Access Journals (Sweden)

    Marcos Roberto Piscopo

    2010-07-01

    Full Text Available The purpose of this article was to demonstrate that companies which compete within dynamic industries do not only adopt a single strategy. Instead, they pursue a number of strategies focusing on the value net rather than on the value chain. We carried out a survey with 47 event-planning firms based in the City of Sao Paulo and we have discovered five distinct groups of firms pursuing different strategies. Our findings support our hypothesis for the searched companies and also demonstrate how the Delta Model by Hax and Wilde II (2001 is useful to explain companies’ strategic configuration. Particularly within the event industry, we have observed that companies are migrating to strategies based upon the value net. This study contributes to managing approaches concerning the challenges faced by event firms when learning how to adopt different strategic positions based upon both the value network and the value chain, in order to obtain and sustain competitive advantages in dynamic markets.

  17. Behavioral control blunts reactions to contemporaneous and future adverse events: Medial prefrontal cortex plasticity and a corticostriatal network

    Directory of Open Access Journals (Sweden)

    Steven F. Maier

    2015-01-01

    Full Text Available It has been known for many years that the ability to exert behavioral control over an adverse event blunts the behavioral and neurochemical impact of the event. More recently, it has become clear that the experience of behavioral control over adverse events also produces enduring changes that reduce the effects of subsequent negative events, even if they are uncontrollable and quite different from the original event controlled. This review focuses on the mechanism by which control both limits the impact of the stressor being experienced and produces enduring, trans-situational “immunization”. The evidence will suggest that control is detected by a corticostriatal circuit involving the ventral medial prefrontal cortex (mPFC and the posterior dorsomedial striatum (DMS. Once control is detected, other mPFC neurons that project to stress-responsive brainstem (dorsal raphe nucleus, DRN and limbic (amygdala structures exert top–down inhibitory control over the activation of these structures that is produced by the adverse event. These structures, such as the DRN and amygdala, in turn regulate the proximate mediators of the behavioral and physiological responses produced by adverse events, and so control blunts these responses. Importantly, the joint occurrence of control and adverse events seems to produce enduring plastic changes in the top–down inhibitory mPFC system such that this system is now activated by later adverse events even if they are uncontrollable, thereby reducing the impact of these events. Other issues are discussed that include a whether other processes such as safety signals and exercise, that lead to resistance/resilience, also use the mPFC circuitry or do so in other ways; b whether control has similar effects and neural mediation in humans, and c the relationship of this work to clinical phenomena.

  18. ELIMINATION OF THE DISADVANTAGES OF SCHEDULING-NETWORK PLANNING BY APPLYING THE MATRIX OF KEY PROJECT EVENTS

    OpenAIRE

    Morozenko Andrey Aleksandrovich; Krasovskiy Dmitriy Viktorovich

    2017-01-01

    The article discusses the current disadvantages of the scheduling-network planning in the management of the terms of investment-construction project. Problems associated with the construction of the schedule and the definitions of the duration of the construction project are being studied. The problems of project management for the management apparatus are shown, which consists in the absence of mechanisms for prompt response to deviations in the parameters of the scheduling-network diagram. ...

  19. Report related to the mitigation of the impact of major climate events on the operation of electricity distribution networks

    International Nuclear Information System (INIS)

    2010-01-01

    After a presentation of the main characteristics of the French electricity distribution network, this report discusses the lessons learnt from recent tempests which occurred in 1999, 2008, 2009 and 2010. It identifies measures and technologies to be implemented to improve the network security. Then, it shows that the present institutional context does not lend itself to an optimisation of investment choices in terms of security. The last part discusses the security plan sizing which needs a better assessment of tempest-related risks

  20. The Unconstrained Event Bulletin (UEB) for the IMS Seismic Network Spaning the Period May 15-28, 2010: a New Resource for Algorithm Development and Testing

    Science.gov (United States)

    Brogan, R.; Young, C. J.; Ballard, S.

    2017-12-01

    A major problem with developing new data processing algorithms for seismic event monitoring is the lack of standard, high-quality "ground-truth" data sets to test against. The unfortunate effect of this is that new algorithms are often developed and tested with new data sets, making comparison of algorithms difficult and subjective. In an effort towards resolving this problem, we have developed the Unconstrained Event Bulletin (UEB), a ground-truth data set from the International Monitoring System (IMS) primary and auxiliary seismic networks for a two-week period in May 2010. All UEB analysis was performed by the same expert, who has more than 30 years of experience analyzing seismic data for nuclear explosion monitoring. We used the most complete International Data Centre (IDC) analyst-review event bulletin (the Late Event Bulletin or LEB) as a starting point for this analysis. To make the UEB more complete, we relaxed the minimum event definite criteria to the level of a pair of P-type and an S-type phases at a single station and using azimuth/slowness as defining. To add even more events that our analyst recognized and didn't want to omit, in rare cases, events were constructed using only 1 P-phase. Perhaps most importantly, on average our analyst spent more than 60 hours per day of data, far more than was possible in the production of the LEB. The result of all this was that while the LEB had 2,101 LEB events for the 2-week time period, we ended up with 11,435 events in the UEB, an increase of over 400%. New events are located all over the world and include both earthquakes and manmade events such as mining explosions. Our intent is to make our UEB data set openly available for all researchers to use for testing detection, correlation, and location algorithms, thus making it much easier to objectively compare different research efforts. Acknowledgement: Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and

  1. Event-Triggered Asynchronous Guaranteed Cost Control for Markov Jump Discrete-Time Neural Networks With Distributed Delay and Channel Fading.

    Science.gov (United States)

    Yan, Huaicheng; Zhang, Hao; Yang, Fuwen; Zhan, Xisheng; Peng, Chen

    2017-08-18

    This paper is concerned with the guaranteed cost control problem for a class of Markov jump discrete-time neural networks (NNs) with event-triggered mechanism, asynchronous jumping, and fading channels. The Markov jump NNs are introduced to be close to reality, where the modes of the NNs and guaranteed cost controller are determined by two mutually independent Markov chains. The asynchronous phenomenon is considered, which increases the difficulty of designing required mode-dependent controller. The event-triggered mechanism is designed by comparing the relative measurement error with the last triggered state at the process of data transmission, which is used to eliminate dispensable transmission and reduce the networked energy consumption. In addition, the signal fading is considered for the effect of signal reflection and shadow in wireless networks, which is modeled by the novel Rice fading models. Some novel sufficient conditions are obtained to guarantee that the closed-loop system reaches a specified cost value under the designed jumping state feedback control law in terms of linear matrix inequalities. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.

  2. Social networks and inference about unknown events: A case of the match between Google’s AlphaGo and Sedol Lee

    Science.gov (United States)

    Bae, Jonghoon; Cha, Young-Jae; Lee, Hyungsuk; Lee, Boyun; Baek, Sojung; Choi, Semin

    2017-01-01

    This study examines whether the way that a person makes inferences about unknown events is associated with his or her social relations, more precisely, those characterized by ego network density that reflects the structure of a person’s immediate social relation. From the analysis of individual predictions over the Go match between AlphaGo and Sedol Lee in March 2016 in Seoul, Korea, this study shows that the low-density group scored higher than the high-density group in the accuracy of the prediction over a future state of a social event, i.e., the outcome of the first game. We corroborated this finding with three replication tests that asked the participants to predict the following: film awards, President Park’s impeachment in Korea, and the counterfactual assessment of the US presidential election. Taken together, this study suggests that network density is negatively associated with vision advantage, i.e., the ability to discover and forecast an unknown aspect of a social event. PMID:28222114

  3. NEBULAS A High Performance Data-Driven Event-Building Architecture based on an Asynchronous Self-Routing Packet-Switching Network

    CERN Multimedia

    Costa, M; Letheren, M; Djidi, K; Gustafsson, L; Lazraq, T; Minerskjold, M; Tenhunen, H; Manabe, A; Nomachi, M; Watase, Y

    2002-01-01

    RD31 : The project is evaluating a new approach to event building for level-two and level-three processor farms at high rate experiments. It is based on the use of commercial switching fabrics to replace the traditional bus-based architectures used in most previous data acquisition sytems. Switching fabrics permit the construction of parallel, expandable, hardware-driven event builders that can deliver higher aggregate throughput than the bus-based architectures. A standard industrial switching fabric technology is being evaluated. It is based on Asynchronous Transfer Mode (ATM) packet-switching network technology. Commercial, expandable ATM switching fabrics and processor interfaces, now being developed for the future Broadband ISDN infrastructure, could form the basis of an implementation. The goals of the project are to demonstrate the viability of this approach, to evaluate the trade-offs involved in make versus buy options, to study the interfacing of the physics frontend data buffers to such a fabric, a...

  4. Local structural properties and attribute characteristisc in 2-mode networks: p* models to map choices of theater events

    NARCIS (Netherlands)

    Agneessens, F.; Roose, H.

    2008-01-01

    Choices of plays made by theatergoers can be considered as a 2-mode or affiliation network. In this article we illustrate how p* models (an exponential family of distributions for random graphs) can be used to uncover patterns of choices. Based on audience research in three theater institutions in

  5. Assessing loss event frequencies of smart grid cyber threats: Encoding flexibility into FAIR using Bayesian network approach

    NARCIS (Netherlands)

    Le, Anhtuan; Chen, Yue; Chai, Kok Keong; Vasenev, Alexandr; Montoya, L.

    Assessing loss event frequencies (LEF) of smart grid cyber threats is essential for planning cost-effective countermeasures. Factor Analysis of Information Risk (FAIR) is a well-known framework that can be applied to consider threats in a structured manner by using look-up tables related to a

  6. Bagging grey swans : A supply network approach to identifying and managing low-probability high-impact supply chain events

    NARCIS (Netherlands)

    Rossetti, Christian; Akkermans, Henk; Bhakoo, Vikram; Carnovale, Steven

    Over the past decade practitioners and researchers have become increasingly focused on managing risks in extended supply chains. Whether these risks involve supply disruptions, financial liabilities for a supplier’s actions, or large market shifts; Grey Swan events, defined as unforeseen

  7. Impacts of the filter clogging on the behavior of a ventilation network in the event of fire

    International Nuclear Information System (INIS)

    Laborde, J.C.; Pourprix, M.; Lopez, M.C.; Savornin, J.

    1991-01-01

    One of the main roles of ventilation in a nuclear plant is to maintain dynamic containment during normal or accidental operating conditions. Among the incidents likely to affect a nuclear installation, fire is one of those which, coming from the safety standpoint, requires the greatest attention because it is one of the most probable risks. The consequences of a fire have to be analyzed not only in the room where it breaks out, but also for the entire ventilation network. To evaluate these consequences and develop strategies against fire, the Commissariat a l'Energie Atomique uses several test rigs and calculation codes by which the impact of a fire upon the sensitive points of a network can be determined. Research and development studies currently under way give priority to the clogging of High Efficiency Particulate Air filters. Beginning with polymer fires in a 85 m 3 ventilated room, the influence of filter clogging on the characteristic parameters of the associated ventilated network is highlighted. The resultant modeling study following these experiments reveals that coupling of a ventilation code with a fire code cannot be disassociated from the development of a filter clogging model. This paper also gives the first experimental results relative to the determination of the variation, according to time and mass of deposited aerosols, of the air flow resistance of a filter clogged by aerosols derived from combustion of standard polymers used in the nuclear industry (methyl acrylate polymer, polyvinyl chloride). A methodology to extend the results obtained on the clogging test rig to any ventilation network is then described

  8. Event-Based $H_\\infty $ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.

    Science.gov (United States)

    Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E

    2017-10-01

    In this paper, the event-based finite-horizon H ∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v) -dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H ∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.

  9. Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

    Science.gov (United States)

    Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

    2017-01-01

    Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

  10. News Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

    Science.gov (United States)

    2011-09-01

    Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

  11. Prevalence of potentially traumatic events, depression, alcohol use, and social network supports among Chinese migrants: an epidemiological study in Guangzhou, China.

    Science.gov (United States)

    Hall, Brian J; Chen, Wen; Wu, Yan; Zhou, Fangjing; Latkin, Carl

    2014-01-01

    Addressing the health needs of Chinese migrants is a critical public health concern. Epidemiological studies are needed to establish the prevalence of potentially traumatic events (PTEs) and common mental disorders among Chinese migrants and identify protective community and social resources. Utilizing random household sampling, we are in the process of recruiting a representative sample of Chinese adults (N=1,000) in two districts home to a large number of internal migrants. Data are collected using face-to-face interviews and participant self-report methods. Chinese versions of the Life Events Checklist, Alcohol Use Disorders Identification Test, Patient Health Questionnaire and the Social Support Rating Scale measured exposure to PTEs, alcohol use disorder, depression, and social support networks. Preliminary results indicate a high proportion (68%) of the sample was exposed directly or indirectly to at least one PTE. The most commonly reported events were transportation accidents (43%), natural disasters (39%), and physical assault (26%). A total of 17% of the sample reported drinking consistent with having an alcohol use disorder. Moderate or severe depression was reported by 9% of the sample. The majority (75%) reported having three or more people to rely on for support, and 41% reported active participation in civic groups. Despite these strengths, only half the sample reported having trust in their community. Preliminary evidence from this population-level survey indicates high exposure to PTEs and a high potential burden of alcohol use disorders. The role of social networks will be explored as potentially useful for community-based intervention development.

  12. Prevalence of potentially traumatic events, depression, alcohol use, and social network supports among Chinese migrants: an epidemiological study in Guangzhou, China

    Directory of Open Access Journals (Sweden)

    Brian J. Hall

    2014-12-01

    Full Text Available Background: Addressing the health needs of Chinese migrants is a critical public health concern. Epidemiological studies are needed to establish the prevalence of potentially traumatic events (PTEs and common mental disorders among Chinese migrants and identify protective community and social resources. Method: Utilizing random household sampling, we are in the process of recruiting a representative sample of Chinese adults (N=1,000 in two districts home to a large number of internal migrants. Data are collected using face-to-face interviews and participant self-report methods. Chinese versions of the Life Events Checklist, Alcohol Use Disorders Identification Test, Patient Health Questionnaire and the Social Support Rating Scale measured exposure to PTEs, alcohol use disorder, depression, and social support networks. Results: Preliminary results indicate a high proportion (68% of the sample was exposed directly or indirectly to at least one PTE. The most commonly reported events were transportation accidents (43%, natural disasters (39%, and physical assault (26%. A total of 17% of the sample reported drinking consistent with having an alcohol use disorder. Moderate or severe depression was reported by 9% of the sample. The majority (75% reported having three or more people to rely on for support, and 41% reported active participation in civic groups. Despite these strengths, only half the sample reported having trust in their community. Conclusion: Preliminary evidence from this population-level survey indicates high exposure to PTEs and a high potential burden of alcohol use disorders. The role of social networks will be explored as potentially useful for community-based intervention development.

  13. Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

    Science.gov (United States)

    Gallego, C.; Costa, A.; Cuerva, A.

    2010-09-01

    Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

  14. Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

    Science.gov (United States)

    Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

    2018-03-01

    This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

  15. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  16. 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.

  17. Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

    Science.gov (United States)

    He, Yongqun

    2016-06-01

    Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

  18. The International Haemovigilance Network Database for the Surveillance of Adverse Reactions and Events in Donors and Recipients of Blood Components: technical issues and results.

    Science.gov (United States)

    Politis, C; Wiersum, J C; Richardson, C; Robillard, P; Jorgensen, J; Renaudier, P; Faber, J-C; Wood, E M

    2016-11-01

    The International Haemovigilance Network's ISTARE is an online database for surveillance of all adverse reactions (ARs) and adverse events (AEs) associated with donation of blood and transfusion of blood components, irrespective of severity or the harm caused. ISTARE aims to unify the collection and sharing of information with a view to harmonizing best practices for haemovigilance systems around the world. Adverse reactionss and adverse events are recorded by blood component, type of reaction, severity and imputability to transfusion, using internationally agreed standard definitions. From 2006 to 2012, 125 national sets of annual aggregated data were received from 25 countries, covering 132.8 million blood components issued. The incidence of all ARs was 77.5 per 100 000 components issued, of which 25% were severe (19.1 per 100 000). Of 349 deaths (0.26 per 100 000), 58% were due to the three ARs related to the respiratory system: transfusion-associated circulatory overload (TACO, 27%), transfusion-associated acute lung injury (TRALI, 19%) and transfusion-associated dyspnoea (TAD, 12%). Cumulatively, 594 477 donor complications were reported (rate 660 per 100 000), of which 2.9% were severe. ISTARE is a well-established surveillance tool offering important contributions to international efforts to maximize transfusion safety. © 2016 International Society of Blood Transfusion.

  19. Report on the events of September 28, 2003 culminating in the separation of the Italian power system from the other UCTE networks

    International Nuclear Information System (INIS)

    2004-01-01

    During the night of September 28, 2003 the European interconnected electrical system faced a series of disruptions, which started with line flashover to trees and line trips on the Swiss extra high voltage (EHV) electricity transmission grids and ended with the separation of the entire Italian peninsula from the UCTE (Union for the Coordination of Transmission of Electricity) network. Following the separation, the Italian electrical system (and part of the Swiss system, in the Ticino area), suffered an almost complete black-out. In order to investigate the reasons and attribute responsibility for the events of September 28, Autorita per l'energia elettrica e il gas (the Italian regulatory authority for electricity and gas, hereafter: AEEG), launched an inquiry into the events, based on its Order no. 112/2003 of September 29. This Order notably stipulated that the inquiry into the events leading to separation of the Italian electrical system from the European network should be carried out in co-operation with the authorities responsible for regulating the electricity sectors in the relevant neighbouring countries. On October 6, AEEG, Commission de regulation de l'energie (the French regulatory authority for energy, hereafter: CRE), and Office federal de l'energie (the Swiss federal office for energy, hereafter: SFOE) decided to carry out a joint independent investigation into the behaviour of the interconnected power systems, in order to gain a better understanding of the events leading to the separation of the Italian electrical system from the European network and to draw conclusions. The joint investigation began on October 15, when AEEG, CRE and SFOE jointly agreed on a questionnaire to be sent to the Transmission System Operators (TSOs) concerned. The questionnaire was intended to gather information on the interpretation and application of UCTE recommendations on planning and operation security, the behaviour of the electrical power system during

  20. Complex Networks Dynamics Based on Events-Phase Synchronization and Intensity Correlation Applied to The Anomaly Patterns and Extremes in The Tropical African Climate System

    Science.gov (United States)

    Oluoch, K.; Marwan, N.; Trauth, M.; Loew, A.; Kurths, J.

    2012-04-01

    The African continent lie almost entirely within the tropics and as such its (tropical) climate systems are predominantly governed by the heterogeneous, spatial and temporal variability of the Hadley and Walker circulations. The variabilities in these meridional and zonal circulations lead to intensification or suppression of the intensities, durations and frequencies of the Inter-tropical Convergence Zone (ICTZ) migration, trade winds and subtropical high-pressure regions and the continental monsoons. The above features play a central role in determining the African rainfall spatial and temporal variability patterns. The current understanding of these climate features and their influence on the rainfall patterns is not sufficiently understood. Like many real-world systems, atmospheric-oceanic processes exhibit non-linear properties that can be better explored using non-linear (NL) methods of time-series analysis. Over the recent years, the complex network approach has evolved as a powerful new player in understanding spatio-temporal dynamics and evolution of complex systems. Together with NL techniques, it is continuing to find new applications in many areas of science and technology including climate research. We would like to use these two powerful methods to understand the spatial structure and dynamics of African rainfall anomaly patterns and extremes. The method of event synchronization (ES) developed by Quiroga et al., 2002 and first applied to climate networks by Malik et al., 2011 looks at correlations with a dynamic time lag and as such, it is a more intuitive way to correlate a complex and heterogeneous system like climate networks than a fixed time delay most commonly used. On the other hand, the short comings of ES is its lack of vigorous test statistics for the significance level of the correlations, and the fact that only the events' time indices are synchronized while all information about how the relative intensities propagate within network

  1. Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts.

    Science.gov (United States)

    Li, Yunji; Peng, Li

    2018-02-28

    Wireless sensors have many new applications where remote estimation is essential. Considering that a remote estimator is located far away from the process and the wireless transmission distance of sensor nodes is limited, sensor nodes always forward data packets to the remote estimator through a series of relays over a multi-hop link. In this paper, we consider a network with sensor nodes and relay nodes where the relay nodes can forward the estimated values to the remote estimator. An event-triggered remote estimator of state and fault with the corresponding data-forwarding scheme is investigated for stochastic systems subject to both randomly occurring nonlinearity and randomly occurring packet dropouts governed by Bernoulli-distributed sequences to achieve a trade-off between estimation accuracy and energy consumption. Recursive Riccati-like matrix equations are established to calculate the estimator gain to minimize an upper bound of the estimator error covariance. Subsequently, a sufficient condition and data-forwarding scheme are presented under which the error covariance is mean-square bounded in the multi-hop links with random packet dropouts. Furthermore, implementation issues of the theoretical results are discussed where a new data-forwarding communication protocol is designed. Finally, the effectiveness of the proposed algorithms and communication protocol are extensively evaluated using an experimental platform that was established for performance evaluation with a sensor and two relay nodes.

  2. Advance Liquid Metal Reactor Discrete Dynamic Event Tree/Bayesian Network Analysis and Incident Management Guidelines (Risk Management for Sodium Fast Reactors)

    Energy Technology Data Exchange (ETDEWEB)

    Denman, Matthew R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Groth, Katrina M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Cardoni, Jeffrey N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wheeler, Timothy A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2015-04-01

    Accident management is an important component to maintaining risk at acceptable levels for all complex systems, such as nuclear power plants. With the introduction of self-correcting, or inherently safe, reactor designs the focus has shifted from management by operators to allowing the system's design to manage the accident. Inherently and passively safe designs are laudable, but nonetheless extreme boundary conditions can interfere with the design attributes which facilitate inherent safety, thus resulting in unanticipated and undesirable end states. This report examines an inherently safe and small sodium fast reactor experiencing a beyond design basis seismic event with the intend of exploring two issues : (1) can human intervention either improve or worsen the potential end states and (2) can a Bayesian Network be constructed to infer the state of the reactor to inform (1). ACKNOWLEDGEMENTS The authors would like to acknowledge the U.S. Department of Energy's Office of Nuclear Energy for funding this research through Work Package SR-14SN100303 under the Advanced Reactor Concepts program. The authors also acknowledge the PRA teams at Argonne National Laboratory, Oak Ridge National Laboratory, and Idaho National Laboratory for their continue d contributions to the advanced reactor PRA mission area.

  3. Cross-correlation analysis of 2012-2014 seismic events in Central-Northern Italy: insights from the geochemical monitoring network of Tuscany

    Science.gov (United States)

    Pierotti, Lisa; Facca, Gianluca; Gherardi, Fabrizio

    2015-04-01

    Since late 2002, a geochemical monitoring network is operating in Tuscany, Central Italy, to collect data and possibly identify geochemical anomalies that characteristically occur before regionally significant (i.e. with magnitude > 3) seismic events. The network currently consists of 6 stations located in areas already investigated in detail for their geological setting, hydrogeological and geochemical background and boundary conditions. All these stations are equipped for remote, continuous monitoring of selected physicochemical parameters (temperature, pH, redox potential, electrical conductivity), and dissolved concentrations of CO2 and CH4. Additional information are obtained through in situ discrete monitoring. Field surveys are periodically performed to guarantee maintenance and performance control of the sensors of the automatic stations, and to collect water samples for the determination of the chemical and stable isotope composition of all the springs investigated for seismic precursors. Geochemical continuous signals are numerically processed to remove outliers, monitoring errors and aseismic effects from seasonal and climatic fluctuations. The elaboration of smoothed, long-term time series (more than 200000 data available today for each station) allows for a relatively accurate definition of geochemical background values. Geochemical values out of the two-sigma relative standard deviation domain are inspected as possible indicators of physicochemical changes related to regional seismic activity. Starting on November 2011, four stations of the Tuscany network located in two separate mountainous areas of Northern Apennines separating Tuscany from Emilia-Romagna region (Equi Terme and Gallicano), and Tuscany from Emilia-Romagna and Umbria regions (Vicchio and Caprese Michelangelo), started to register anomalous values in pH and CO2 partial pressure (PCO2). Cross-correlation analysis indicates an apparent relationship between the most important seismic

  4. A Study on Network Group Events from the Conflict Theory Perspective%冲突理论视阈下的网络群体事件探析

    Institute of Scientific and Technical Information of China (English)

    胡圣方

    2011-01-01

    网络群体事件从冲突的成因看,是冲突主体在社会进程中安全感的剥离,信任感的丧失和受挫感的增强使然。从冲突的类型看,主要存在现实性和非现实性冲突。从冲突的性质看,这种冲突具有积极和消极两面。从;中突的应对看,第一,无论对于现实性冲突和非现实性7中突都应积极响应。第二,媒体应扩大正面舆论的宣传面,秉着客观、公平的理念进行舆论监督和舆论引导。第三,政府应从韧性管治的角度,强调司法调解,并秉着公开透明、公正的原则处理冲突,以此重建信任关系。、%The causes of the conflict of network group events are the sense of stripped security, the loss of trust and the enhanced sense of frustration of conflict main body in the social process. It is mainly shown as reality conflict and non-reality conflict, which have both positive and negative sides. The response of the conflict should be to respond active- ly both to the reality conflict and non-reality conflict. The media should enhance the positive publicity and the government should emnhasize judicial mediation and solve the conflict based on openness and fairness principles to rebuild trust.

  5. The effects of high-frequency oscillations in hippocampal electrical activities on the classification of epileptiform events using artificial neural networks

    Science.gov (United States)

    Chiu, Alan W. L.; Jahromi, Shokrollah S.; Khosravani, Houman; Carlen, Peter L.; Bardakjian, Berj L.

    2006-03-01

    The existence of hippocampal high-frequency electrical activities (greater than 100 Hz) during the progression of seizure episodes in both human and animal experimental models of epilepsy has been well documented (Bragin A, Engel J, Wilson C L, Fried I and Buzsáki G 1999 Hippocampus 9 137-42 Khosravani H, Pinnegar C R, Mitchell J R, Bardakjian B L, Federico P and Carlen P L 2005 Epilepsia 46 1-10). However, this information has not been studied between successive seizure episodes or utilized in the application of seizure classification. In this study, we examine the dynamical changes of an in vitro low Mg2+ rat hippocampal slice model of epilepsy at different frequency bands using wavelet transforms and artificial neural networks. By dividing the time-frequency spectrum of each seizure-like event (SLE) into frequency bins, we can analyze their burst-to-burst variations within individual SLEs as well as between successive SLE episodes. Wavelet energy and wavelet entropy are estimated for intracellular and extracellular electrical recordings using sufficiently high sampling rates (10 kHz). We demonstrate that the activities of high-frequency oscillations in the 100-400 Hz range increase as the slice approaches SLE onsets and in later episodes of SLEs. Utilizing the time-dependent relationship between different frequency bands, we can achieve frequency-dependent state classification. We demonstrate that activities in the frequency range 100-400 Hz are critical for the accurate classification of the different states of electrographic seizure-like episodes (containing interictal, preictal and ictal states) in brain slices undergoing recurrent spontaneous SLEs. While preictal activities can be classified with an average accuracy of 77.4 ± 6.7% utilizing the frequency spectrum in the range 0-400 Hz, we can also achieve a similar level of accuracy by using a nonlinear relationship between 100-400 Hz and <4 Hz frequency bands only.

  6. Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments; Reseau a multiplexage statistique pour les systemes de selection et de reconstruction d'evenements dans les experiences de physique des hautes energies

    Energy Technology Data Exchange (ETDEWEB)

    Calvet, D

    2000-03-01

    Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers ({approx}1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

  7. Geophysical events

    Science.gov (United States)

    This is a summary of SEAN Bulletin, 13(3), March 31, 1988, a publication of the Smithsonian Institution's Scientific Event Alert Network. The complete bulletin is available in the microfiche edition of Eos as a microfiche supplement or as a paper reprint. For the microfiche, order document E88-002 at $2.50 (U.S.) by writing to AGU Orders, 2000 Florida Avenue, N.W., Washington, DC 20009 or by calling toll free on 800-424-2488. For the paper reprint, order SEAN Bulletin (giving volume and issue numbers and issue date) through the same address; the price is $3.50 for one copy of each issue number for those who do not have a deposit account, $2 for those who do; additional copies of each issue number are $1. Subscriptions to SEAN Bulletin are also available from AGU-Orders; the price is $18 for 12 monthly issues mailed to a U.S. address, $28 if mailed elsewhere, and must be prepaid.

  8. Understanding the Fundamental Principles Underlying the Survival and Efficient Recovery of Multi-Scale Techno-Social Networks Following a WMD Event (A)

    Science.gov (United States)

    2016-07-01

    networked systems in human societies are composed of repeated communications between actors. A dyadic relationship made up of repeated interactions may...constraints include software limitations, communication protocols and regulations. To advance empirical applications, network models will need to address...around for a while, communication and computing infrastructure networks have been forming a dense web around those in the past two decades. All these

  9. Temporal networks

    CERN Document Server

    Saramäki, Jari

    2013-01-01

    The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach  the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and concept...

  10. Event Investigation

    International Nuclear Information System (INIS)

    Korosec, D.

    2000-01-01

    The events in the nuclear industry are investigated from the license point of view and from the regulatory side too. It is well known the importance of the event investigation. One of the main goals of such investigation is to prevent the circumstances leading to the event and the consequences of the event. The protection of the nuclear workers against nuclear hazard, and the protection of general public against dangerous effects of an event could be achieved by systematic approach to the event investigation. Both, the nuclear safety regulatory body and the licensee shall ensure that operational significant events are investigated in a systematic and technically sound manner to gather information pertaining to the probable causes of the event. One of the results should be appropriate feedback regarding the lessons of the experience to the regulatory body, nuclear industry and general public. In the present paper a general description of systematic approach to the event investigation is presented. The systematic approach to the event investigation works best where cooperation is present among the different divisions of the nuclear facility or regulatory body. By involving management and supervisors the safety office can usually improve their efforts in the whole process. The end result shall be a program which serves to prevent events and reduce the time and efforts solving the root cause which initiated each event. Selection of the proper method for the investigation and an adequate review of the findings and conclusions lead to the higher level of the overall nuclear safety. (author)

  11. Need of a disaster alert system for India through a network of real-time monitoring of sea-level and other meteorological events

    Digital Repository Service at National Institute of Oceanography (India)

    Joseph, A.; Desai, R.G.P.

    Need of a disaster alert system (DAS) capable of online transmission of real-time integrated sea-level and surface meteorological data is discussed. In addition to INSAT platform transmit terminal, VHF, etc., the ubiquitous cellular phone network...

  12. A Network of AOPs for reduced thyroid hormone synthesis derived from inhibition of Thyroperoxidase - A common Molecular Initiating Event Leading to Species-Specific Indices of Adversity.

    Science.gov (United States)

    This collection of 3 AOPs describe varying outcomes of adversity dependent upon species in response to inhibition of thyroperoxidase (TPO) during development. Chemical inhibition of TPO, the molecular-initiating event (MIE), results in decreased thyroid hormone (TH) synthesis, a...

  13. Design of robust reliable control for T-S fuzzy Markovian jumping delayed neutral type neural networks with probabilistic actuator faults and leakage delays: An event-triggered communication scheme.

    Science.gov (United States)

    Syed Ali, M; Vadivel, R; Saravanakumar, R

    2018-06-01

    This study examines the problem of robust reliable control for Takagi-Sugeno (T-S) fuzzy Markovian jumping delayed neural networks with probabilistic actuator faults and leakage terms. An event-triggered communication scheme. First, the randomly occurring actuator faults and their failures rates are governed by two sets of unrelated random variables satisfying certain probabilistic failures of every actuator, new type of distribution based event triggered fault model is proposed, which utilize the effect of transmission delay. Second, Takagi-Sugeno (T-S) fuzzy model is adopted for the neural networks and the randomness of actuators failures is modeled in a Markov jump model framework. Third, to guarantee the considered closed-loop system is exponential mean square stable with a prescribed reliable control performance, a Markov jump event-triggered scheme is designed in this paper, which is the main purpose of our study. Fourth, by constructing appropriate Lyapunov-Krasovskii functional, employing Newton-Leibniz formulation and integral inequalities, several delay-dependent criteria for the solvability of the addressed problem are derived. The obtained stability criteria are stated in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones, among them one example was supported by real-life application of the benchmark problem. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  14. SENTINEL EVENTS

    Directory of Open Access Journals (Sweden)

    Andrej Robida

    2004-09-01

    Full Text Available Background. The Objective of the article is a two year statistics on sentinel events in hospitals. Results of a survey on sentinel events and the attitude of hospital leaders and staff are also included. Some recommendations regarding patient safety and the handling of sentinel events are given.Methods. In March 2002 the Ministry of Health introduce a voluntary reporting system on sentinel events in Slovenian hospitals. Sentinel events were analyzed according to the place the event, its content, and root causes. To show results of the first year, a conference for hospital directors and medical directors was organized. A survey was conducted among the participants with the purpose of gathering information about their view on sentinel events. One hundred questionnaires were distributed.Results. Sentinel events. There were 14 reports of sentinel events in the first year and 7 in the second. In 4 cases reports were received only after written reminders were sent to the responsible persons, in one case no reports were obtained. There were 14 deaths, 5 of these were in-hospital suicides, 6 were due to an adverse event, 3 were unexplained. Events not leading to death were a suicide attempt, a wrong side surgery, a paraplegia after spinal anaesthesia, a fall with a femoral neck fracture, a damage of the spleen in the event of pleural space drainage, inadvertent embolization with absolute alcohol into a femoral artery and a physical attack on a physician by a patient. Analysis of root causes of sentinel events showed that in most cases processes were inadequate.Survey. One quarter of those surveyed did not know about the sentinel events reporting system. 16% were having actual problems when reporting events and 47% beleived that there was an attempt to blame individuals. Obstacles in reporting events openly were fear of consequences, moral shame, fear of public disclosure of names of participants in the event and exposure in mass media. The majority of

  15. Event Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2001-01-01

    The purpose of this chapter is to discuss conceptual event modeling within a context of information modeling. Traditionally, information modeling has been concerned with the modeling of a universe of discourse in terms of information structures. However, most interesting universes of discourse...... are dynamic and we present a modeling approach that can be used to model such dynamics.We characterize events as both information objects and change agents (Bækgaard 1997). When viewed as information objects events are phenomena that can be observed and described. For example, borrow events in a library can...

  16. Molecular initiating events of the intersex phenotype: Low-dose exposure to 17α-ethinylestradiol rapidly regulates molecular networks associated with gonad differentiation in the adult fathead minnow testis

    International Nuclear Information System (INIS)

    Feswick, April; Loughery, Jennifer R.; Isaacs, Meghan A.; Munkittrick, Kelly R.; Martyniuk, Christopher J.

    2016-01-01

    Highlights: • Male fathead minnow were exposed to 17alpha ethinylestradiol (EE2). • Both 11-ketotestosterone and testosterone production was decreased relative to controls. • A gene network associated with doublesex and mab-3 related transcription factor 1 were suppressed. • Genes involved in granulosa cell development were increased and sensitive to EE2 exposure. • Molecular initiating events that may be related to the intersex condition were identified. - Abstract: Intersex, or the presence of oocytes in the testes, has been documented in fish following exposure to wastewater effluent and estrogenic compounds. However, the molecular networks underlying the intersex condition are not completely known. To address this, we exposed male fathead minnows to a low, environmentally-relevant concentration of 17alpha-ethinylestradiol (EE2) (15 ng/L) and measured the transcriptome response in the testis after 96 h to identify early molecular initiating events that may proceed the intersex condition. The short-term exposure to EE2 did not affect gonadosomatic index and proportion of gametes within the testes. However, the production of 11-ketotestosterone and testosterone from the testis in vitro was decreased relative to controls. Expression profiling using a 8 × 60 K fathead minnow microarray identified 10 transcripts that were differentially expressed in the testes, the most dramatic change being that of coagulation factor XIII A chain (20-fold increase). Transcripts that included guanine nucleotide binding protein (Beta Polypeptide 2), peroxisome proliferator-activated receptor delta, and WNK lysine deficient protein kinase 1a, were down-regulated by EE2. Subnetwork enrichment analysis revealed that EE2 suppressed transcriptional networks associated with steroid metabolism, hormone biosynthesis, and sperm mobility. Most interesting was that gene networks associated with doublesex and mab-3 related transcription factor 1 (dmrt1) were suppressed in the adult

  17. Molecular initiating events of the intersex phenotype: Low-dose exposure to 17α-ethinylestradiol rapidly regulates molecular networks associated with gonad differentiation in the adult fathead minnow testis

    Energy Technology Data Exchange (ETDEWEB)

    Feswick, April; Loughery, Jennifer R.; Isaacs, Meghan A.; Munkittrick, Kelly R.; Martyniuk, Christopher J., E-mail: cmartyni@yahoo.ca

    2016-12-15

    Highlights: • Male fathead minnow were exposed to 17alpha ethinylestradiol (EE2). • Both 11-ketotestosterone and testosterone production was decreased relative to controls. • A gene network associated with doublesex and mab-3 related transcription factor 1 were suppressed. • Genes involved in granulosa cell development were increased and sensitive to EE2 exposure. • Molecular initiating events that may be related to the intersex condition were identified. - Abstract: Intersex, or the presence of oocytes in the testes, has been documented in fish following exposure to wastewater effluent and estrogenic compounds. However, the molecular networks underlying the intersex condition are not completely known. To address this, we exposed male fathead minnows to a low, environmentally-relevant concentration of 17alpha-ethinylestradiol (EE2) (15 ng/L) and measured the transcriptome response in the testis after 96 h to identify early molecular initiating events that may proceed the intersex condition. The short-term exposure to EE2 did not affect gonadosomatic index and proportion of gametes within the testes. However, the production of 11-ketotestosterone and testosterone from the testis in vitro was decreased relative to controls. Expression profiling using a 8 × 60 K fathead minnow microarray identified 10 transcripts that were differentially expressed in the testes, the most dramatic change being that of coagulation factor XIII A chain (20-fold increase). Transcripts that included guanine nucleotide binding protein (Beta Polypeptide 2), peroxisome proliferator-activated receptor delta, and WNK lysine deficient protein kinase 1a, were down-regulated by EE2. Subnetwork enrichment analysis revealed that EE2 suppressed transcriptional networks associated with steroid metabolism, hormone biosynthesis, and sperm mobility. Most interesting was that gene networks associated with doublesex and mab-3 related transcription factor 1 (dmrt1) were suppressed in the adult

  18. DER 83: outstanding events

    International Nuclear Information System (INIS)

    1984-01-01

    The DER's activity is presented through 82 ''outstanding events''. Each one is a stage in the effort of research and development of the DER. These events concern the following fields: new applications of electric power for customers; environment protection and new energy sources; improvements of electric power production units; electrical materials; electric network planning and control; computer codes. In the production field, one deals more particularly with nuclear reactor safety studies: analysis of the behaviour of different components; reactor safety experiments; reliability of different systems (safety, communications...) [fr

  19. Geothermal heat - The second stream for geothermal sectors; Electricity production: industries are facing the geological unexpected events; Heat networks: a new boom in France

    International Nuclear Information System (INIS)

    Minster, Jean-Francois; Appert, Olivier; Moisant, Francois; Salha, Bernard; Tardieu, Bernard; Florette, Marc; Basilico, Laurent

    2013-01-01

    A first article proposes an overview of recent development in the field of geothermal power (individual heat pumps, urban heating networks, electricity production in volcanic context, and possibility of non conventional fields). These developments are notably interesting in a context of an evolving energy mix. Some benefits of geothermal power are outlined: a reliable and predictable production, and a low footprint. An installation of deep geothermal power in Alsace is presented. By evoking the construction of three high-energy geothermal power stations by GDF Suez in Sumatra, a second article outlines the high costs associated with exploration drilling which can face geological difficulties. It indicates and comments the distribution of costs among exploration, confirmation, authorizations, drilling, steam collection, electric plant, and connection to the grid. The third and last article comments the development of heat networks in France, and more particularly in the Parisian Basin which has the highest concentration of low-energy geothermal exploitations

  20. A Study on the Rate of Events and Water Loss in Water Distribution Network of Azna, Lorstan, Iran during 2008-2014 and Its Associated Factors

    Directory of Open Access Journals (Sweden)

    Mohammad Adeli

    2016-12-01

    Full Text Available Introduction and purpose: One of the problems of water distribution systems is loss of large volumes of water due to the occurrence of various events, which incurs a huge financial loss. Regarding this, the aim of the present study was to investigate the rate of events and water loss in the water distribution system and its related factors in Azna, Lorestan province, Iran, during 2008-2014. Methods: This cross-sectional study was conducted using census method, surveys, and field data collection. The amount of water production and consumption, the volumes of water loss, the number of accidents, type of pipe, pressure zone, as well as the age and length of the pipes recorded during 2008- 2014 were studied and analyzed. Results: According to the results, the highest (34.48% and lowest (20.57% amount of water losses happened in 2008 and 2014, respectively. High pressures in water systems had significant relationship with the number of events as well as the amount of water loss and water consumption. In addition, higher length and age of the pipes had a direct correlation with increased number of events and water loss. Furthermore, the maximum number of events were found to occur in the pipe embranchment and galvanized pipes. Conclusion: This study showed that of events was directly related to the length and age of the pipes, the water pressure, and number of branches. Also water loss quantity can be reduced by applying suitable management techniques in different sections. Furthermore, the water loss can be significantly controlled by taking such measures as reducing the pressure in the high-pressure zones, timely replacement of old and inappropriate pipes, appropriate fixing of the pipes, replacement of the galvanized pipe, and standard implementation of pipes and fittings.

  1. Design and development of self-powered sensors on wireless sensor network for standalone plant critical data management during SBO and beyond design basis events

    International Nuclear Information System (INIS)

    Aparna, J.; Dulera, I.V.; Rama Rao, A.; Vijayan, P.K.

    2015-01-01

    Advanced reactors are designed with an aim of maximum safety, optimized fuel utilization and effective system design. Safety aspects in reactor designs are being viewed for all possible vulnerabilities, and as a result, robust self-regulating passive safety features have been favored in Gen IV and advanced reactor designs. In addition to passive systems, the accidents scenarios at Fukushima indicate the dire need of reliable and stand-alone self-powered sensors, for monitoring plant critical parameters for effective damage control actions. There is a strong need for plant critical data management and situation awareness during the unavailability of all conventional power sources in a nuclear power plant, during extended station blackout (SBO) conditions. These self-powered sensors would assist the operators in managing events like SBO and help in containing any Beyond Design Basis Events (BDBE) conditions, well away from the public domain

  2. Prevalence of potentially traumatic events, depression, alcohol use, and social network supports among Chinese migrants: an epidemiological study in Guangzhou, China

    OpenAIRE

    Hall, Brian J.; Chen, Wen; Wu, Yan; Zhou, Fangjing; Latkin, Carl

    2014-01-01

    Background: Addressing the health needs of Chinese migrants is a critical public health concern. Epidemiological studies are needed to establish the prevalence of potentially traumatic events (PTEs) and common mental disorders among Chinese migrants and identify protective community and social resources.Method: Utilizing random household sampling, we are in the process of recruiting a representative sample of Chinese adults (N=1,000) in two districts home to a large number of internal migrant...

  3. Extensin network formation in Vitis vinifera callus cells is an essential and causal event in rapid and H2O2-induced reduction in primary cell wall hydration

    Science.gov (United States)

    2011-01-01

    Background Extensin deposition is considered important for the correct assembly and biophysical properties of primary cell walls, with consequences to plant resistance to pathogens, tissue morphology, cell adhesion and extension growth. However, evidence for a direct and causal role for the extensin network formation in changes to cell wall properties has been lacking. Results Hydrogen peroxide treatment of grapevine (Vitis vinifera cv. Touriga) callus cell walls was seen to induce a marked reduction in their hydration and thickness. An analysis of matrix proteins demonstrated this occurs with the insolubilisation of an abundant protein, GvP1, which displays a primary structure and post-translational modifications typical of dicotyledon extensins. The hydration of callus cell walls free from saline-soluble proteins did not change in response to H2O2, but fully regained this capacity after addition of extensin-rich saline extracts. To assay the specific contribution of GvP1 cross-linking and other wall matrix proteins to the reduction in hydration, GvP1 levels in cell walls were manipulated in vitro by binding selected fractions of extracellular proteins and their effect on wall hydration during H2O2 incubation assayed. Conclusions This approach allowed us to conclude that a peroxidase-mediated formation of a covalently linked network of GvP1 is essential and causal in the reduction of grapevine callus wall hydration in response to H2O2. Importantly, this approach also indicated that extensin network effects on hydration was only partially irreversible and remained sensitive to changes in matrix charge. We discuss this mechanism and the importance of these changes to primary wall properties in the light of extensin distribution in dicotyledons. PMID:21672244

  4. Detection of anomalous events

    Science.gov (United States)

    Ferragut, Erik M.; Laska, Jason A.; Bridges, Robert A.

    2016-06-07

    A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The system can include a plurality of anomaly detectors that together implement an algorithm to identify low-probability events and detect atypical traffic patterns. The anomaly detector provides for comparability of disparate sources of data (e.g., network flow data and firewall logs.) Additionally, the anomaly detector allows for regulatability, meaning that the algorithm can be user configurable to adjust a number of false alerts. The anomaly detector can be used for a variety of probability density functions, including normal Gaussian distributions, irregular distributions, as well as functions associated with continuous or discrete variables.

  5. Rapid surveillance for health events following a mass meningococcal B vaccine program in a university setting: A Canadian Immunization Research Network study.

    Science.gov (United States)

    Langley, J M; MacDougall, D M; Halperin, B A; Swain, A; Halperin, S A; Top, K A; McNeil, S A; MacKinnon-Cameron, D; Marty, K; De Serres, G; Dubé, E; Bettinger, J A

    2016-07-25

    An outbreak of Neisseria meningitidis serotype B infection occurred at a small residential university; public health announced an organizational vaccination program with the 4-component Meningococcal B (4CMenB) vaccine (Bexsero(TM), Novartis/GlaxoSmithKline Inc.) several days later. Since there were limited published data on reactogenicity of 4CMenB in persons over 17years of age, this study sought to conduct rapid surveillance of health events in vaccinees and controls using an online survey. Vaccine uptake was 84.7% for dose 1 (2967/3500) and 70% (2456/3500) for dose 2; the survey response rates were 33.0% (987/2967) and 18.7% (459/2456) in dose 1 and dose 1 recipients respectively, and 12% in unvaccinated individuals (63/533). Most students were 20-29years of age (vaccinees, 64.0%; controls, 74.0). A new health problem or worsening of an existing health problem was reported by 30.0% and 30.3% of vaccine recipients after doses 1 and 2 respectively; and by 15.9% of controls. These health problems interfered with the ability to perform normal activities in most vaccinees reporting these events (74.7% post dose 1; 62.6% post dose 2), and in 60% of controls. The health problems led to a health care provider visit (including emergency room) in 12.8% and 14.4% of vaccinees post doses 1 and 2, respectively and in 40% of controls. The most common reactions in vaccinees were injection site reactions (20.6% post dose 1, 16.1% post dose 20 and non-specific systemic complaints (22.6% post dose 1, 17.6% post dose 2). No hospitalizations were reported. An online surveillance program during an emergency meningococcal B vaccine program was successfully implemented, and detected higher rates of health events in vaccinees compared to controls, and high rates of both vaccinees and controls seeking medical attention. The types of adverse events reported by young adult vaccinees were consistent with those previously. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Fusion events

    International Nuclear Information System (INIS)

    Aboufirassi, M; Angelique, J.C.; Bizard, G.; Bougault, R.; Brou, R.; Buta, A.; Colin, J.; Cussol, D.; Durand, D.; Genoux-Lubain, A.; Horn, D.; Kerambrun, A.; Laville, J.L.; Le Brun, C.; Lecolley, J.F.; Lefebvres, F.; Lopez, O.; Louvel, M.; Meslin, C.; Metivier, V.; Nakagawa, T.; Peter, J.; Popescu, R.; Regimbart, R.; Steckmeyer, J.C.; Tamain, B.; Vient, E.; Wieloch, A.; Yuasa-Nakagawa, K.

    1998-01-01

    The fusion reactions between low energy heavy ions have a very high cross section. First measurements at energies around 30-40 MeV/nucleon indicated no residue of either complete or incomplete fusion, thus demonstrating the disappearance of this process. This is explained as being due to the high amount o energies transferred to the nucleus, what leads to its total dislocation in light fragments and particles. Exclusive analyses have permitted to mark clearly the presence of fusion processes in heavy systems at energies above 30-40 MeV/nucleon. Among the complete events of the Kr + Au reaction at 60 MeV/nucleon the majority correspond to binary collisions. Nevertheless, for the most considerable energy losses, a class of events do occur for which the detected fragments appears to be emitted from a unique source. These events correspond to an incomplete projectile-target fusion followed by a multifragmentation. Such events were singled out also in the reaction Xe + Sn at 50 MeV/nucleon. For the events in which the energy dissipation was maximal it was possible to isolate an isotropic group of events showing all the characteristics of fusion nuclei. The fusion is said to be incomplete as pre-equilibrium Z = 1 and Z = 2 particles are emitted. The cross section is of the order of 25 mb. Similar conclusions were drown for the systems 36 Ar + 27 Al and 64 Zn + nat Ti. A cross section value of ∼ 20 mb was determined at 55 MeV/nucleon in the first case, while the measurement of evaporation light residues in the last system gave an upper limit of 20-30 mb for the cross section at 50 MeV/nucleon

  7. Robust network topologies for generating switch-like cellular responses.

    Directory of Open Access Journals (Sweden)

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  8. MyHealthAssistant: an event-driven middleware for multiple medical applications on a smartphone-mediated body sensor network.

    Science.gov (United States)

    Seeger, Christian; Van Laerhoven, Kristof; Buchmann, Alejandro

    2015-03-01

    An ever-growing range of wireless sensors for medical monitoring has shown that there is significant interest in monitoring patients in their everyday surroundings. It however remains a challenge to merge information from several wireless sensors and applications are commonly built from scratch. This paper presents a middleware targeted for medical applications on smartphone-like platforms that relies on an event-based design to enable flexible coupling with changing sets of wireless sensor units, while posing only a minor overhead on the resources and battery capacity of the interconnected devices. We illustrate the requirements for such middleware with three different healthcare applications that were deployed with our middleware solution, and characterize the performance with energy consumption, overhead caused for the smartphone, and processing time under real-world circumstances. Results show that with sensing-intensive applications, our solution only minimally impacts the phone's resources, with an added CPU utilization of 3% and a memory usage under 7 MB. Furthermore, for a minimum message delivery ratio of 99.9%, up to 12 sensor readings per second are guaranteed to be handled, regardless of the number of applications using our middleware.

  9. Network Views

    Science.gov (United States)

    Alexander, Louis

    2010-01-01

    The world changed in 2008. The financial crisis brought with it a deepening sense of insecurity, and the desire to be connected to a network increased. Throughout the summer and fall of 2008, events were unfolding with alarming rapidity. The Massachusetts Institute of Technology (MIT) Alumni Association wanted to respond to this change in the…

  10. Establishing the functional connectivity of the frontotemporal network in pre-attentive change detection with Transcranial Magnetic Stimulation and event-related optical signal.

    Science.gov (United States)

    Tse, Chun-Yu; Long-Yin, Yip; Lui, Troby Ka-Yan; Xiao, Xue-Zhen; Wang, Yang; Chu, Winnie Chiu Wing; Parks, Nathan Allen; Chan, Sandra Sau-Man; Neggers, Sebastiaan Franciscus Wijnandus

    2018-06-18

    Current theories of pre-attentive deviant detection postulate that before the Superior Temporal Cortex (STC) detects a change, the Inferior Frontal Cortex (IFC) engages in stimulus analysis, which is particularly critical for ambiguous deviations (e.g., deviant preceded by a short train of standards). These theories rest on the assumption that IFC and STC are functionally connected, which has only been supported by correlational brain imaging studies. We examined this functional connectivity assumption by applying Transcranial Magnetic Stimulation (TMS) to disrupt IFC function, while measuring the later STC mismatch response with the event-related optical signal (EROS). EROS can localize brain activity in both spatial and temporal dimensions via measurement of optical property changes associated with neuronal activity, and is inert to the electromagnetic interference produced by TMS. Specifically, the STC mismatch response at 120-180 ms elicited by a deviant preceded by a short standard train when IFC TMS was applied at 80 ms was compared with the STC mismatch responses in temporal control (TMS with 200 ms delay), spatial control (sham TMS at vertex), auditory control (TMS pulse noise only), and cognitive control (deviant preceded by a long standard train) conditions. The STC mismatch response to deviants preceded by the short train was abolished by TMS of the IFC at 80 ms, while the STC responses remained intact in all other control conditions. These results confirm the involvement of the IFC in the STC mismatch response and support a functional connection between IFC and STC. Copyright © 2018. Published by Elsevier Inc.

  11. [Adverse events prevention ability].

    Science.gov (United States)

    Aparo, Ugo Luigi; Aparo, Andrea

    2007-03-01

    The issue of how to address medical errors is the key to improve the health care system performances. Operational evidence collected in the last five years shows that the solution is only partially linked to future technological developments. Cultural and organisational changes are mandatory to help to manage and drastically reduce the adverse events in health care organisations. Classical management, merely based on coordination and control, is inadequate. Proactive, self-organising network based structures must be put in place and managed using adaptive, fast evolving management tools.

  12. Event Index - a LHCb Event Search System

    CERN Document Server

    INSPIRE-00392208; Kazeev, Nikita; Redkin, Artem

    2015-12-23

    LHC experiments generate up to $10^{12}$ events per year. This paper describes Event Index - an event search system. Event Index's primary function is quickly selecting subsets of events from a combination of conditions, such as the estimated decay channel or stripping lines output. Event Index is essentially Apache Lucene optimized for read-only indexes distributed over independent shards on independent nodes.

  13. Heterodox networks

    DEFF Research Database (Denmark)

    Lala, Purnima; Kumar, Ambuj

    2016-01-01

    It is imperative for the service providers to bring innovation in the network design to meet the exponential growth of mobile subscribers for multi-technology future wireless networks. As a matter of research, studies on providing services to moving subscriber groups aka ‘Place Time Capacity (PTC......)’ have not been considered much in the literature. In this article we present Heterodox networks as an innovative and alternate approach to handle the PTC congestion. We describe two different approaches to combat the PTC congestion where the traditional terrestrial infrastructure fails to provide......-Configurable Intelligent Distributed Antenna System (SCIDAS)’ that overlays intelligence over the conventional DAS architecture and latter is in the form of a swarm of intelligent hovering base stations working in a team to cooperatively resolve the PTC congestion at the Area of Event (AoE). A suitable network...

  14. Simulating events

    Energy Technology Data Exchange (ETDEWEB)

    Ferretti, C; Bruzzone, L [Techint Italimpianti, Milan (Italy)

    2000-06-01

    The Petacalco Marine terminal on the Pacific coast in the harbour of Lazaro Carclenas (Michoacan) in Mexico, provides coal to the thermoelectric power plant at Pdte Plutarco Elias Calles in the port area. The plant is being converted from oil to burn coal to generate 2100 MW of power. The article describes the layout of the terminal and equipment employed in the unloading, coal stacking, coal handling areas and the receiving area at the power plant. The contractor Techint Italimpianti has developed a software system, MHATIS, for marine terminal management which is nearly complete. The discrete event simulator with its graphic interface provides a real-type decision support system for simulating changes to the terminal operations and evaluating impacts. The article describes how MHATIS is used. 7 figs.

  15. Event generators

    International Nuclear Information System (INIS)

    Durand, D.; Gulminelli, F.; Lopez, O.; Vient, E.

    1998-01-01

    The results concerning the heavy ion collision simulations at Fermi energies by means of phenomenological models obtained in the last two years ar presented. The event generators are essentially following the phase of elaboration of analysis methods of data obtained by INDRA or NAUTILUS 4 π multidetectors. To identify and correctly quantify a phenomenon or a physical quantity it is necessary to verify by simulation the feasibility and validity of the analysis and also to estimate the bias introduced by the experimental filter. Many studies have shown this, for instance: the determination of the collision reaction plan for flow studies, determination of kinematical characteristics of the quasi-projectiles, and the excitation energy measurement stored in the hot nuclei. To Eugene, the currently utilised generator, several improvements were added: introduction of space-time correlations between the different products emitted in the decay of excited nuclei by calculating the trajectories of the particles in the final phase of the reaction; taking into account in the decay cascade of the discrete levels of the lighter fragments; the possibility of the schematically description of the explosion of the nucleus by simultaneous emission of multi-fragments. Thus, by comparing the calculations with the data relative to heavy systems studied with the NAUTILUS assembly it was possible to extract the time scales in the nuclear fragmentation. The utilisation of these event generators was extended to the analysis of INDRA data concerning the determination of the vaporization threshold in the collisions Ar + Ni and also the research of the expansion effects in the collisions Xe + Sn at 50 MeV/u

  16. Events diary

    Science.gov (United States)

    2000-01-01

    as Imperial College, the Royal Albert Hall, the Royal College of Art, the Natural History and Science Museums and the Royal Geographical Society. Under the heading `Shaping the future together' BA2000 will explore science, engineering and technology in their wider cultural context. Further information about this event on 6 - 12 September may be obtained from Sandra Koura, BA2000 Festival Manager, British Association for the Advancement of Science, 23 Savile Row, London W1X 2NB (tel: 0171 973 3075, e-mail: sandra.koura@britassoc.org.uk ). Details of the creating SPARKS events may be obtained from creating.sparks@britassoc.org.uk or from the website www.britassoc.org.uk . Other events 3 - 7 July, Porto Alegre, Brazil VII Interamerican conference on physics education: The preparation of physicists and physics teachers in contemporary society. Info: IACPE7@if.ufrgs.br or cabbat1.cnea.gov.ar/iacpe/iacpei.htm 27 August - 1 September, Barcelona, Spain GIREP conference: Physics teacher education beyond 2000. Info: www.blues.uab.es/phyteb/index.html

  17. Performance of the CMS Event Builder

    CERN Document Server

    Andre, Jean-Marc Olivier; Branson, James; Brummer, Philipp Maximilian; Chaze, Olivier; Cittolin, Sergio; Contescu, Cristian; Craigs, Benjamin Gordon; Darlea, Georgiana Lavinia; Deldicque, Christian; Demiragli, Zeynep; Dobson, Marc; Doualot, Nicolas; Erhan, Samim; Fulcher, Jonathan Richard; Gigi, Dominique; Gladki, Maciej Szymon; Glege, Frank; Gomez Ceballos, Guillelmo; Hegeman, Jeroen Guido; Holzner, Andre Georg; Janulis, Mindaugas; Jimenez Estupinan, Raul; Masetti, Lorenzo; Meijers, Franciscus; Meschi, Emilio; Mommsen, Remigius; Morovic, Srecko; O'Dell, Vivian; Orsini, Luciano; Paus, Christoph Maria Ernst; Petrova, Petia; Pieri, Marco; Racz, Attila; Reis, Thomas; Sakulin, Hannes; Schwick, Christoph; Simelevicius, Dainius; Zejdl, Petr

    2017-01-01

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events at a rate of 100 kHz. It transports event data at an aggregate throughput of ~100 GB/s to the high-level trigger (HLT) farm. The CMS DAQ system has been completely rebuilt during the first long shutdown of the LHC in 2013/14. The new DAQ architecture is based on state-of-the-art network technologies for the event building. For the data concentration, 10/40 Gb/s Ethernet technologies are used together with a reduced TCP/IP protocol implemented in FPGA for a reliable transport between custom electronics and commercial computing hardware. A 56 Gb/s Infiniband FDR CLOS network has been chosen for the event builder. We report on the performance of the event builder system and the steps taken to exploit the full potential of the network technologies.

  18. On the usability of frequency distributions and source attribution of Cs-137 detections encountered in the IMS radio-nuclide network for radionuclide event screening and climate change monitoring

    Science.gov (United States)

    Becker, A.; Wotawa, G.; Zähringer, M.

    2009-04-01

    Under the provisions of the Comprehensive Nuclear-Test-Ban Treaty (CTBT), airborne radioactivity is measured by means of high purity Germanium gamma ray detectors deployed in a global monitoring network. Almost 60 of the scheduled 80 stations have been put in provisional operations by the end of 2008. Each station daily sends the 24 hour samples' spectroscopic data to the Vienna based Provisional Technical Secretariat (PTS) of the CTBT Organization (CTBTO) for review for treaty-relevant nuclides. Cs-137 is one of these relevant isotopes. Its typical minimum detectable concentration is in the order of a few Bq/m3. However, this isotope is also known to occur in atmospheric trace concentrations, due to known non CTBT relevant processes and sources related to, for example, the re-suspension of cesium from historic nuclear tests and/or the Chernobyl reactor disaster, temporarily enhanced by bio-mass burning (Wotawa et al. 2006). Properly attributed cesium detections can be used as a proxy to detect Aeolian dust events (Igarashi et al, 2001) that potentially carry cesium from all aforementioned sources but are also known to play an important role for the radiative forcing in the atmosphere (shadow effect), at the surface (albedo) and the carbon dioxide cycle when interacting with oceanic phytoplankton (Mikami and Shi, 2005). In this context this paper provides a systematic attribution of recent Cs-137 detections in the PTS monitoring network in order to Characterize those stations which are regularly affected by Cs-137 Provide input for procedures that distinguish CTBT relevant detection from other sources (event screening) Explore on the capability of certain stations to use their Cs-137 detections as a proxy to detect aeolian dust events and to flag the belonging filters to be relevant for further investigations in this field (-> EGU-2009 Session CL16/AS4.6/GM10.1: Aeolian dust: initiator, player, and recorder of environmental change). References Igarashi, Y., M

  19. Asynchronous networks: modularization of dynamics theorem

    Science.gov (United States)

    Bick, Christian; Field, Michael

    2017-02-01

    Building on the first part of this paper, we develop the theory of functional asynchronous networks. We show that a large class of functional asynchronous networks can be (uniquely) represented as feedforward networks connecting events or dynamical modules. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network: the modularization of dynamics theorem. We give examples to illustrate the main results.

  20. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  1. De-Virtualizing Social Events: Understanding the Gap between Online and Offline Participation for Event Invitations

    OpenAIRE

    Huang, Ai-Ju; Wang, Hao-Chuan; Yuan, Chien Wen

    2013-01-01

    One growing use of computer-based communication media is for gathering people to initiate or sustain social events. Although the use of computer-mediated communication and social network sites such as Facebook for event promotion is becoming popular, online participation in an event does not always translate to offline attendance. In this paper, we report on an interview study of 31 participants that examines how people handle online event invitations and what influences their online and offl...

  2. Network Security Visualization

    National Research Council Canada - National Science Library

    1999-01-01

    The application of interactive, three-dimensional viewing techniques to the representation of security-related, computer network status and events is expected to improve the timeliness and efficiency...

  3. Vaccine Adverse Events

    Science.gov (United States)

    ... for Biologics Evaluation & Research Vaccine Adverse Events Vaccine Adverse Events Share Tweet Linkedin Pin it More sharing ... in the primary immunization series in infants Report Adverse Event Report a Vaccine Adverse Event Contact FDA ( ...

  4. Upgrade of the CMS Event Builder

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The Data Acquisition (DAQ) system of the Compact Muon Solenoid (CMS) experiment at CERN assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of 100 GB/s. By the time the LHC restarts after the 2013/14 shut-down, the current compute nodes and networking infrastructure will have reached the end of their lifetime. We are presenting design studies for an upgrade of the CMS event builder based on advanced networking technologies such as 10 Gb/s Ethernet. We report on tests and performance measurements with small-scale test setups.

  5. Parallel discrete event simulation using shared memory

    Science.gov (United States)

    Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

    1988-01-01

    With traditional event-list techniques, evaluating a detailed discrete-event simulation-model can often require hours or even days of computation time. By eliminating the event list and maintaining only sufficient synchronization to ensure causality, parallel simulation can potentially provide speedups that are linear in the numbers of processors. A set of shared-memory experiments, using the Chandy-Misra distributed-simulation algorithm, to simulate networks of queues is presented. Parameters of the study include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential-simulation of most queueing network models.

  6. The ATLAS Event Service: A New Approach to Event Processing

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00070566; De, Kaushik; Guan, Wen; Maeno, Tadashi; Nilsson, Paul; Oleynik, Danila; Panitkin, Sergey; Tsulaia, Vakhtang; van Gemmeren, Peter; Wenaus, Torre

    2015-01-01

    The ATLAS Event Service (ES) implements a new fine grained approach to HEP event processing, designed to be agile and efficient in exploiting transient, short-lived resources such as HPC hole-filling, spot market commercial clouds, and volunteer computing. Input and output control and data flows, bookkeeping, monitoring, and data storage are all managed at the event level in an implementation capable of supporting ATLAS-scale distributed processing throughputs (about 4M CPU-hours/day). Input data flows utilize remote data repositories with no data locality or pre­staging requirements, minimizing the use of costly storage in favor of strongly leveraging powerful networks. Object stores provide a highly scalable means of remotely storing the quasi-continuous, fine grained outputs that give ES based applications a very light data footprint on a processing resource, and ensure negligible losses should the resource suddenly vanish. We will describe the motivations for the ES system, its unique features and capabi...

  7. CAISSON: Interconnect Network Simulator

    Science.gov (United States)

    Springer, Paul L.

    2006-01-01

    Cray response to HPCS initiative. Model future petaflop computer interconnect. Parallel discrete event simulation techniques for large scale network simulation. Built on WarpIV engine. Run on laptop and Altix 3000. Can be sized up to 1000 simulated nodes per host node. Good parallel scaling characteristics. Flexible: multiple injectors, arbitration strategies, queue iterators, network topologies.

  8. Heterogeneous network architectures

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann

    2006-01-01

    is flexibility. This thesis investigates such heterogeneous network architectures and how to make them flexible. A survey of algorithms for network design is presented, and it is described how using heuristics can increase the speed. A hierarchical, MPLS based network architecture is described......Future networks will be heterogeneous! Due to the sheer size of networks (e.g., the Internet) upgrades cannot be instantaneous and thus heterogeneity appears. This means that instead of trying to find the olution, networks hould be designed as being heterogeneous. One of the key equirements here...... and it is discussed that it is advantageous to heterogeneous networks and illustrated by a number of examples. Modeling and simulation is a well-known way of doing performance evaluation. An approach to event-driven simulation of communication networks is presented and mixed complexity modeling, which can simplify...

  9. Performance of the CMS Event Builder

    Energy Technology Data Exchange (ETDEWEB)

    Andre, J.M.; et al.

    2017-11-22

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of to the high-level trigger farm. The DAQ architecture is based on state-of-the-art network technologies for the event building. For the data concentration, 10/40 Gbit/s Ethernet technologies are used together with a reduced TCP/IP protocol implemented in FPGA for a reliable transport between custom electronics and commercial computing hardware. A 56 Gbit/s Infiniband FDR Clos network has been chosen for the event builder. This paper presents the implementation and performance of the event-building system.

  10. Topology of Event Horizon

    OpenAIRE

    Siino, Masaru

    1997-01-01

    The topologies of event horizons are investigated. Considering the existence of the endpoint of the event horizon, it cannot be differentiable. Then there are the new possibilities of the topology of the event horizon though they are excluded in smooth event horizons. The relation between the topology of the event horizon and the endpoint of it is revealed. A torus event horizon is caused by two-dimensional endpoints. One-dimensional endpoints provide the coalescence of spherical event horizo...

  11. Synchronization Of Parallel Discrete Event Simulations

    Science.gov (United States)

    Steinman, Jeffrey S.

    1992-01-01

    Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.

  12. Event segmentation ability uniquely predicts event memory.

    Science.gov (United States)

    Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

    2013-11-01

    Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

  13. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  14. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  15. Event dependent sampling of recurrent events

    DEFF Research Database (Denmark)

    Kvist, Tine Kajsa; Andersen, Per Kragh; Angst, Jules

    2010-01-01

    The effect of event-dependent sampling of processes consisting of recurrent events is investigated when analyzing whether the risk of recurrence increases with event count. We study the situation where processes are selected for study if an event occurs in a certain selection interval. Motivation...... retrospective and prospective disease course histories are used. We examine two methods to correct for the selection depending on which data are used in the analysis. In the first case, the conditional distribution of the process given the pre-selection history is determined. In the second case, an inverse...

  16. Attack Graph Construction for Security Events Analysis

    Directory of Open Access Journals (Sweden)

    Andrey Alexeevich Chechulin

    2014-09-01

    Full Text Available The paper is devoted to investigation of the attack graphs construction and analysis task for a network security evaluation and real-time security event processing. Main object of this research is the attack modeling process. The paper contains the description of attack graphs building, modifying and analysis technique as well as overview of implemented prototype for network security analysis based on attack graph approach.

  17. Event generators for address event representation transmitters

    Science.gov (United States)

    Serrano-Gotarredona, Rafael; Serrano-Gotarredona, Teresa; Linares Barranco, Bernabe

    2005-06-01

    Address Event Representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with mili-seconds timings) are sampled at low frequencies. Also, neurons generate 'events' according to their activity levels. More active neurons generate more events per unit time, and access the interchip communication channel more frequently, while neurons with low activity consume less communication bandwidth. In a typical AER transmitter chip, there is an array of neurons that generate events. They send events to a peripheral circuitry (let's call it "AER Generator") that transforms those events to neurons coordinates (addresses) which are put sequentially on an interchip high speed digital bus. This bus includes a parallel multi-bit address word plus a Rqst (request) and Ack (acknowledge) handshaking signals for asynchronous data exchange. There have been two main approaches published in the literature for implementing such "AER Generator" circuits. They differ on the way of handling event collisions coming from the array of neurons. One approach is based on detecting and discarding collisions, while the other incorporates arbitration for sequencing colliding events . The first approach is supposed to be simpler and faster, while the second is able to handle much higher event traffic. In this article we will concentrate on the second arbiter-based approach. Boahen has been publishing several techniques for implementing and improving the arbiter based approach. Originally, he proposed an arbitration squeme by rows, followed by a column arbitration. In this scheme, while one neuron was selected by the arbiters to transmit his event out of the chip, the rest of neurons in the array were

  18. Using Bayesian Belief Networks and event trees for volcanic hazard assessment and decision support : reconstruction of past eruptions of La Soufrière volcano, Guadeloupe and retrospective analysis of 1975-77 unrest.

    Science.gov (United States)

    Komorowski, Jean-Christophe; Hincks, Thea; Sparks, Steve; Aspinall, Willy; Legendre, Yoann; Boudon, Georges

    2013-04-01

    Since 1992, mild but persistent seismic and fumarolic unrest at La Soufrière de Guadeloupe volcano has prompted renewed concern about hazards and risks, crisis response planning, and has rejuvenated interest in geological studies. Scientists monitoring active volcanoes frequently have to provide science-based decision support to civil authorities during such periods of unrest. In these circumstances, the Bayesian Belief Network (BBN) offers a formalized evidence analysis tool for making inferences about the state of the volcano from different strands of data, allowing associated uncertainties to be treated in a rational and auditable manner, to the extent warranted by the strength of the evidence. To illustrate the principles of the BBN approach, a retrospective analysis is undertaken of the 1975-77 crisis, providing an inferential assessment of the evolving state of the magmatic system and the probability of subsequent eruption. Conditional dependencies and parameters in the BBN are characterized quantitatively by structured expert elicitation. Revisiting data available in 1976 suggests the probability of magmatic intrusion would have been evaluated high at the time, according with subsequent thinking about the volcanological nature of the episode. The corresponding probability of a magmatic eruption therefore would have been elevated in July and August 1976; however, collective uncertainty about the future course of the crisis was great at the time, even if some individual opinions were certain. From this BBN analysis, while the more likely appraised outcome - based on observational trends at 31 August 1976 - might have been 'no eruption' (mean probability 0.5; 5-95 percentile range 0.8), an imminent magmatic eruption (or blast) could have had a probability of about 0.4, almost as substantial. Thus, there was no real scientific basis to assert one scenario was more likely than the other. This retrospective evaluation adds objective probabilistic expression to

  19. Event-by-event jet quenching

    Energy Technology Data Exchange (ETDEWEB)

    Fries, R.J.; Rodriguez, R.; Ramirez, E.

    2010-08-14

    High momentum jets and hadrons can be used as probes for the quark gluon plasma (QGP) formed in nuclear collisions at high energies. We investigate the influence of fluctuations in the fireball on jet quenching observables by comparing propagation of light quarks and gluons through averaged, smooth QGP fireballs with event-by-event jet quenching using realistic inhomogeneous fireballs. We find that the transverse momentum and impact parameter dependence of the nuclear modification factor R{sub AA} can be fit well in an event-by-event quenching scenario within experimental errors. However the transport coefficient {cflx q} extracted from fits to the measured nuclear modification factor R{sub AA} in averaged fireballs underestimates the value from event-by-event calculations by up to 50%. On the other hand, after adjusting {cflx q} to fit R{sub AA} in the event-by-event analysis we find residual deviations in the azimuthal asymmetry v{sub 2} and in two-particle correlations, that provide a possible faint signature for a spatial tomography of the fireball. We discuss a correlation function that is a measure for spatial inhomogeneities in a collision and can be constrained from data.

  20. Event-by-event jet quenching

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, R. [Cyclotron Institute and Physics Department, Texas A and M University, College Station, TX 77843 (United States); Fries, R.J., E-mail: rjfries@comp.tamu.ed [Cyclotron Institute and Physics Department, Texas A and M University, College Station, TX 77843 (United States); RIKEN/BNL Research Center, Brookhaven National Laboratory, Upton, NY 11973 (United States); Ramirez, E. [Physics Department, University of Texas El Paso, El Paso, TX 79968 (United States)

    2010-09-27

    High momentum jets and hadrons can be used as probes for the quark gluon plasma (QGP) formed in nuclear collisions at high energies. We investigate the influence of fluctuations in the fireball on jet quenching observables by comparing propagation of light quarks and gluons through averaged, smooth QGP fireballs with event-by-event jet quenching using realistic inhomogeneous fireballs. We find that the transverse momentum and impact parameter dependence of the nuclear modification factor R{sub AA} can be fit well in an event-by-event quenching scenario within experimental errors. However the transport coefficient q extracted from fits to the measured nuclear modification factor R{sub AA} in averaged fireballs underestimates the value from event-by-event calculations by up to 50%. On the other hand, after adjusting q to fit R{sub AA} in the event-by-event analysis we find residual deviations in the azimuthal asymmetry v{sub 2} and in two-particle correlations, that provide a possible faint signature for a spatial tomography of the fireball. We discuss a correlation function that is a measure for spatial inhomogeneities in a collision and can be constrained from data.

  1. Event-by-event fluctuations at SPS

    CERN Document Server

    Appelshauser, Harald; Adamova, D.; Agakichiev, G.; Belaga, V.; Braun-Munzinger, P.; Castillo, A.; Cherlin, A.; Damjanovic, S.; Dietel, T.; Dietrich, L.; Drees, A.; Esumi, S.I.; Filimonov, K.; Fomenko, K.; Fraenkel, Z.; Garabatos, C.; Glassel, P.; Hering, G.; Holeczek, J.; Kushpil, V.; Lenkeit, B.; Ludolphs, W.; Maas, A.; Marn, A.; Milosevic, J.; Milov, A.; Miskowiec, D.; Panebrattsev, Yu.; Petchenova, O.; Petracek, V.; Pfeiffer, A.; Rak, J.; Ravinovich, I.; Rehak, P.; Schmitz, W.; Schukraft, J.; Sedykh, S.; Shimansky, S.; Slvova, J.; Stachel, J.; Sumbera, M.; Tilsner, H.; Tserruya, Itzhak; Wessels, J.P.; Wienold, T.; Windelband, B.; Wurm, J.P.; Xie, W.; Yurevich, S.; Yurevich, V.; Appelshauser, Harald; Sako, Hiro

    2005-01-01

    Results on event-by-event fluctuations of the mean transverse momentum and net charge in Pb-Au collisions, measured by the CERES Collaboration at CERN-SPS, are presented. We discuss the centrality and beam energy dependence and compare our data to cascade calculations.

  2. LHCb Online event processing and filtering

    Science.gov (United States)

    Alessio, F.; Barandela, C.; Brarda, L.; Frank, M.; Franek, B.; Galli, D.; Gaspar, C.; Herwijnen, E. v.; Jacobsson, R.; Jost, B.; Köstner, S.; Moine, G.; Neufeld, N.; Somogyi, P.; Stoica, R.; Suman, S.

    2008-07-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. The entire data-flow is controlled and configured by means of a SCADA system and several databases. After an overview of the LHCb data acquisition and its design principles this paper will emphasize the LHCb event filter system, which is now implemented using the final hardware and will be ready for data-taking for the LHC startup. Control, configuration and security aspects will also be discussed.

  3. LHCb Online event processing and filtering

    International Nuclear Information System (INIS)

    Alessio, F; Barandela, C; Brarda, L; Frank, M; Gaspar, C; Herwijnen, E v; Jacobsson, R; Jost, B; Koestner, S; Moine, G; Neufeld, N; Somogyi, P; Stoica, R; Suman, S; Franek, B; Galli, D

    2008-01-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. The entire data-flow is controlled and configured by means of a SCADA system and several databases. After an overview of the LHCb data acquisition and its design principles this paper will emphasize the LHCb event filter system, which is now implemented using the final hardware and will be ready for data-taking for the LHC startup. Control, configuration and security aspects will also be discussed

  4. The CBM first-level event selector

    Energy Technology Data Exchange (ETDEWEB)

    Cuveland, Jan de; Lindenstruth, Volker [Frankfurt Institute for Advanced Studies, Goethe University, Frankfurt (Germany)

    2015-07-01

    The CBM experiment currently under construction at GSI/FAIR is designed to study QCD predictions at high baryon densities. The CBM First-Level Event Selector (FLES) is the central event selection system of the experiment. Designed as a high-performance computer cluster, its task is an online analysis of the physics data including full event reconstruction at an incoming data rate exceeding 1 TByte/s. The CBM detector systems are free-running and self-triggered, delivering time-stamped data streams. As there is no inherent event separation, traditional approaches for global event building and event selection are not directly applicable. Instead of event building, the FLES combines the data from approximately 1000 input links to self-contained, overlapping processing intervals and distributes them to compute nodes. It employs a high-bandwidth InfiniBand network as well as dedicated custom FPGA input boards providing time-addressed access to buffered data. Subsequently, specialized event selection algorithms analyze these processing intervals in 4-D, identify events, and select those relevant for storage depending on the chosen CBM setup and selection scenario. This presentation outlines the design of the CBM First-level Event Selector and summarizes the results from first prototype systems.

  5. Episodes, events, and models

    Directory of Open Access Journals (Sweden)

    Sangeet eKhemlani

    2015-10-01

    Full Text Available We describe a novel computational theory of how individuals segment perceptual information into representations of events. The theory is inspired by recent findings in the cognitive science and cognitive neuroscience of event segmentation. In line with recent theories, it holds that online event segmentation is automatic, and that event segmentation yields mental simulations of events. But it posits two novel principles as well: first, discrete episodic markers track perceptual and conceptual changes, and can be retrieved to construct event models. Second, the process of retrieving and reconstructing those episodic markers is constrained and prioritized. We describe a computational implementation of the theory, as well as a robotic extension of the theory that demonstrates the processes of online event segmentation and event model construction. The theory is the first unified computational account of event segmentation and temporal inference. We conclude by demonstrating now neuroimaging data can constrain and inspire the construction of process-level theories of human reasoning.

  6. Characterization of Background Traffic in Hybrid Network Simulation

    National Research Council Canada - National Science Library

    Lauwens, Ben; Scheers, Bart; Van de Capelle, Antoine

    2006-01-01

    .... Two approaches are common: discrete event simulation and fluid approximation. A discrete event simulation generates a huge amount of events for a full-blown battlefield communication network resulting in a very long runtime...

  7. News Education: Physics Education Networks meeting has global scale Competition: Competition seeks the next Brian Cox Experiment: New measurement of neutrino time-of-flight consistent with the speed of light Event: A day for all those who teach physics Conference: Students attend first Anglo-Japanese international science conference Celebration: Will 2015 be the 'Year of Light'? Teachers: Challenging our intuition in spectacular fashion: the fascinating world of quantum physics awaits Research: Science sharpens up sport Learning: Kittinger and Baumgartner: on a mission to the edge of space International: London International Youth Science Forum calls for leading young scientists Competition: Physics paralympian challenge needs inquisitive, analytical, artistic and eloquent pupils Forthcoming events

    Science.gov (United States)

    2012-05-01

    Education: Physics Education Networks meeting has global scale Competition: Competition seeks the next Brian Cox Experiment: New measurement of neutrino time-of-flight consistent with the speed of light Event: A day for all those who teach physics Conference: Students attend first Anglo-Japanese international science conference Celebration: Will 2015 be the 'Year of Light'? Teachers: Challenging our intuition in spectacular fashion: the fascinating world of quantum physics awaits Research: Science sharpens up sport Learning: Kittinger and Baumgartner: on a mission to the edge of space International: London International Youth Science Forum calls for leading young scientists Competition: Physics paralympian challenge needs inquisitive, analytical, artistic and eloquent pupils Forthcoming events

  8. NASA Integrated Network COOP

    Science.gov (United States)

    Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

    2012-01-01

    Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

  9. Dynamics of Charged Events

    International Nuclear Information System (INIS)

    Bachas, Constantin; Bunster, Claudio; Henneaux, Marc

    2009-01-01

    In three spacetime dimensions the world volume of a magnetic source is a single point, an event. We make the event dynamical by regarding it as the imprint of a flux-carrying particle impinging from an extra dimension. This can be generalized to higher spacetime dimensions and to extended events. We exhibit universal observable consequences of the existence of events and argue that events are as important as particles or branes. We explain how events arise on the world volume of membranes in M theory, and in a Josephson junction in superconductivity.

  10. The global event system

    International Nuclear Information System (INIS)

    Winans, J.

    1994-01-01

    The support for the global event system has been designed to allow an application developer to control the APS event generator and receiver boards. This is done by the use of four new record types. These records are customized and are only supported by the device support modules for the APS event generator and receiver boards. The use of the global event system and its associated records should not be confused with the vanilla EPICS events and the associated event records. They are very different

  11. Event by event physics in ALICE

    CERN Document Server

    Christakoglou, Panos

    2009-01-01

    Fluctuations of thermodynamic quantities are fundamental for the study of the QGP phase transition. The ALICE experiment is well suited for precise event-by-event measurements of various quantities. In this article, we review the capabilities of ALICE to study the fluctuations of several key observables such as the net charge, the temperature, and the particle ratios. Among the observables related to correlations, we review the balance functions and the long range correlations.

  12. The Fourth International Network of Twin Registries: Overview from Osaka/Research Reviews: Familial Fraternal Twinning; Twin Study of Masculine Faces; Physical Aggression and Epigenetics; Prenatal Education for Parents of Twins/Current Events: 2016 Guinness Book of World Records; Oldest Living Male Twins; Twins Reunited at Sixty-Nine; Panda Twins; Twins.com.

    Science.gov (United States)

    Segal, Nancy L

    2015-12-01

    The 4th International Network of Twin Registries (INTR) Consortium Meeting took place in Osaka, Japan, September 28-29, 2015. The venue was the Osaka Medical Center for Medical Innovation and Translational Research. An overview of presentations and other activities is provided. Next, 1930s research on familial fraternal twinning, preference for masculine faces, physical aggression and epigenetics, and a prenatal education program for parents of multiples are described. Current twin-related events include the 2016 Guinness Book of World Records (GWR), the oldest living male twins, newly reunited twins, the birth of panda twins and a controversial twin-based website.

  13. Events and the means of attention

    NARCIS (Netherlands)

    Richards, G.W.

    2013-01-01

    In the contemporary network society, attracting public attention has become more challenging as the supply of information increases. Events arguably play an essential role in synchronizing personal, social and political agendas, helping to focus attention and frame places, objects and people. The

  14. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  15. Conferences and Events

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

    André Lavoie

    2016-06-14

    Jun 14, 2016 ... Approved by the Management Executive Committee. - 1 - ... Event ‒ represents activities related to IDRC operations and may include both ... Events include business meetings; corporate, branch or divisional management.

  16. Initiating events frequency determination

    International Nuclear Information System (INIS)

    Simic, Z.; Mikulicic, V.; Vukovic, I.

    2004-01-01

    The paper describes work performed for the Nuclear Power Station (NPS). Work is related to the periodic initiating events frequency update for the Probabilistic Safety Assessment (PSA). Data for all relevant NPS initiating events (IE) were reviewed. The main focus was on events occurring during most recent operating history (i.e., last four years). The final IE frequencies were estimated by incorporating both NPS experience and nuclear industry experience. Each event was categorized according to NPS individual plant examination (IPE) initiating events grouping approach. For the majority of the IE groups, few, or no events have occurred at the NPS. For those IE groups with few or no NPS events, the final estimate was made by means of a Bayesian update with general nuclear industry values. Exceptions are rare loss-of-coolant-accidents (LOCA) events, where evaluation of engineering aspects is used in order to determine frequency.(author)

  17. Advertising Effectiveness In Events

    OpenAIRE

    Jain, Sushilkumar

    2012-01-01

    Confronted with decreasing effectiveness of the classic marketing communications, events have become an increasingly popular alternative for marketers. Events constitute one of the most exciting and fastest growing forms of leisure and business. With time, the decreasing effectiveness of classical marketing communications boosted the use of events for marketing and making brand awareness. Event marketing is seen as the unique opportunity to integrate the firm’s communication activities like p...

  18. Event detection intelligent camera development

    International Nuclear Information System (INIS)

    Szappanos, A.; Kocsis, G.; Molnar, A.; Sarkozi, J.; Zoletnik, S.

    2008-01-01

    A new camera system 'event detection intelligent camera' (EDICAM) is being developed for the video diagnostics of W-7X stellarator, which consists of 10 distinct and standalone measurement channels each holding a camera. Different operation modes will be implemented for continuous and for triggered readout as well. Hardware level trigger signals will be generated from real time image processing algorithms optimized for digital signal processor (DSP) and field programmable gate array (FPGA) architectures. At full resolution a camera sends 12 bit sampled 1280 x 1024 pixels with 444 fps which means 1.43 Terabyte over half an hour. To analyse such a huge amount of data is time consuming and has a high computational complexity. We plan to overcome this problem by EDICAM's preprocessing concepts. EDICAM camera system integrates all the advantages of CMOS sensor chip technology and fast network connections. EDICAM is built up from three different modules with two interfaces. A sensor module (SM) with reduced hardware and functional elements to reach a small and compact size and robust action in harmful environment as well. An image processing and control unit (IPCU) module handles the entire user predefined events and runs image processing algorithms to generate trigger signals. Finally a 10 Gigabit Ethernet compatible image readout card functions as the network interface for the PC. In this contribution all the concepts of EDICAM and the functions of the distinct modules are described

  19. A Mosque event

    DEFF Research Database (Denmark)

    Simonsen, Kirsten; Neergaard, Maja de; Koefoed, Lasse Martin

    2017-01-01

    and public imaginations attached to it. And they are connected to a specific event – the opening of the mosque. In the first part, a conceptual framework is presented bringing together literature on three notions: encounters, visibility and the event. Following this, the paper explores the opening event...

  20. On semirecurrent events

    International Nuclear Information System (INIS)

    Dvurechenskij, A.

    1984-01-01

    In some problems of the mathematical theory of particle counters, film or filmless measurements of track ionization in high energy physics,queueing theory, random walks, etc., the classes of emirecurrent and m-semirecurrent events, which generalize the recurrent events and the recurrent events with delay, appeared. In the paper their basic properties, and some relationships between them are shown

  1. LHCb Online event processing and filtering

    CERN Document Server

    Alessio, F; Brarda, L; Frank, M; Franek, B; Galli, D; Gaspar, C; Van Herwijnen, E; Jacobsson, R; Jost, B; Köstner, S; Moine, G; Neufeld, N; Somogyi, P; Stoica, R; Suman, S

    2008-01-01

    The first level trigger of LHCb accepts one million events per second. After preprocessing in custom FPGA-based boards these events are distributed to a large farm of PC-servers using a high-speed Gigabit Ethernet network. Synchronisation and event management is achieved by the Timing and Trigger system of LHCb. Due to the complex nature of the selection of B-events, which are the main interest of LHCb, a full event-readout is required. Event processing on the servers is parallelised on an event basis. The reduction factor is typically 1/500. The remaining events are forwarded to a formatting layer, where the raw data files are formed and temporarily stored. A small part of the events is also forwarded to a dedicated farm for calibration and monitoring. The files are subsequently shipped to the CERN Tier0 facility for permanent storage and from there to the various Tier1 sites for reconstruction. In parallel files are used by various monitoring and calibration processes running within the LHCb Online system. ...

  2. Networks model of the East Turkistan terrorism

    Science.gov (United States)

    Li, Ben-xian; Zhu, Jun-fang; Wang, Shun-guo

    2015-02-01

    The presence of the East Turkistan terrorist network in China can be traced back to the rebellions on the BAREN region in Xinjiang in April 1990. This article intends to research the East Turkistan networks in China and offer a panoramic view. The events, terrorists and their relationship are described using matrices. Then social network analysis is adopted to reveal the network type and the network structure characteristics. We also find the crucial terrorist leader. Ultimately, some results show that the East Turkistan network has big hub nodes and small shortest path, and that the network follows a pattern of small world network with hierarchical structure.

  3. 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...

  4. Nonstochastic Analysis of Manufacturing Systems Using Timed-Event Graphs

    DEFF Research Database (Denmark)

    Hulgaard, Henrik; Amon, Tod

    1996-01-01

    Using automated methods to analyze the temporal behavior ofmanufacturing systems has proven to be essential and quite beneficial.Popular methodologies include Queueing networks, Markov chains,simulation techniques, and discrete event systems (such as Petrinets). These methodologies are primarily...

  5. Event-by-Event Observables and Fluctuations

    International Nuclear Information System (INIS)

    Petersen, Hannah

    2013-01-01

    In this talk the status and open questions of the phenomenological description of all the stages of a heavy ion reaction are highlighted. Special emphasis is put on event-by-event fluctuations and associated observables. The first part is concentrated on high RHIC and LHC energies and the second part reviews the challenges for modeling heavy ion reactions at lower beam energies in a more realistic fashion. Overall, the main conclusion is that sophisticated theoretical dynamical approaches that describe many observables in the same framework are essential for the quantitative understanding of the properties of hot and dense nuclear matter

  6. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  7. Identifying jet quantum numbers event by event

    International Nuclear Information System (INIS)

    Teper, M.J.

    1979-12-01

    A method is proposed to identify the parton that gives rise to any particular jet. The method improves with the number of particles in the jet, and should indicate which of the jets in a three jet event at PETRA is the gluon jet. (author)

  8. Mobility Network and Safety

    Directory of Open Access Journals (Sweden)

    Adriana Galderisi

    2010-04-01

    Full Text Available Mobility network is crucial for ensuring territorial safety with respect to natural and technological hazards. They represent a basic support to community’s everyday life although being exposed elements often characterized by high vulnerability to different hazards and, in the meanwhile, strategic equipments for emergency management. Physical damages or the lack in functioning of those networks may greatly increase the loss of human lives caused by hazardous events as well as produce relevant economic damages at medium and long term. Although the relevance of the mobility networks in assuring territorial safety is at present largely recognized, risk analyses have been long focused on buildings’ vulnerability or, even where they have paid attention to mobility network, they have been mainly focused on the physical damages that a given hazard could may induce on individual elements of such network. It is recent the awareness that mobility network represents a system, characterized by relevant interdependences both among its elements and among network infrastructures and urban systems. Based on these assumptions, this paper points out the heterogeneous aspects of the mobility network vulnerability and their relevance in increasing the overall territorial or urban vulnerability to hazardous events. Therefore, an in-depth investigation of the concept of mobility network vulnerability is provided, in order to highlight the aspects mostly investigated and more recent research perspectives. Finally, a case study in the Campania Region is presented in order to point out how traditional risk analyses, generally referred to individual hazards, can sometimes led to invest in the mobility network improvement or development which, targeted to increase the security of a territory result, on the opposite, in an increase of the territorial vulnerability.

  9. Survey of Network Visualization Tools

    Science.gov (United States)

    2007-12-01

    programming language such as Java, C #, Delphi and Visual basic. AlgoCOMs Network also supports Visual Basic for Applications ( VBA ). Hardware: Users...AlgoCOMs Network also supports Visual Basic for Applications ( VBA ). Hardware: Users: Availability: • Commercially Available Cost $101...Application Monitoring - Constantly watch the health of your mission-critical applications: MS SQL , MS Exchange, MS IIS, Active Directory. Event

  10. The "All Sky Camera Network"

    Science.gov (United States)

    Caldwell, Andy

    2005-01-01

    In 2001, the "All Sky Camera Network" came to life as an outreach program to connect the Denver Museum of Nature and Science (DMNS) exhibit "Space Odyssey" with Colorado schools. The network is comprised of cameras placed strategically at schools throughout Colorado to capture fireballs--rare events that produce meteorites.…

  11. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  12. Soundscapes, events, resistance

    Directory of Open Access Journals (Sweden)

    Andrea Mubi Brighenti

    2008-12-01

    Full Text Available Put it bluntly, a soundscape is the sonic counterpart, or component, of landscape. From such minimal assumption, some interesting consequences follow: just as landscape is far from being a simple stage-set upon which events take place, soundscape, too, is itself evental, i.e., it consists of events. Not only because its nature, far from being acoustics is always ‘psychoacoustics’, as Murray Schafer (1977/1994 first argued. Processes of environmental perception are of course there.

  13. Structure from interaction events

    NARCIS (Netherlands)

    de Nooy, W.

    2015-01-01

    In this contribution to the colloquium, I argue why and how I lost interest in the overall structure of social networks even though Big Data techniques are increasingly simplifying the collection, organisation, and analysis of ever larger networks. The challenge that Big Data techniques pose to the

  14. Features, Events, and Processes: Disruptive Events

    International Nuclear Information System (INIS)

    J. King

    2004-01-01

    The primary purpose of this analysis is to evaluate seismic- and igneous-related features, events, and processes (FEPs). These FEPs represent areas of natural system processes that have the potential to produce disruptive events (DE) that could impact repository performance and are related to the geologic processes of tectonism, structural deformation, seismicity, and igneous activity. Collectively, they are referred to as the DE FEPs. This evaluation determines which of the DE FEPs are excluded from modeling used to support the total system performance assessment for license application (TSPA-LA). The evaluation is based on the data and results presented in supporting analysis reports, model reports, technical information, or corroborative documents that are cited in the individual FEP discussions in Section 6.2 of this analysis report

  15. Features, Events, and Processes: Disruptive Events

    Energy Technology Data Exchange (ETDEWEB)

    J. King

    2004-03-31

    The primary purpose of this analysis is to evaluate seismic- and igneous-related features, events, and processes (FEPs). These FEPs represent areas of natural system processes that have the potential to produce disruptive events (DE) that could impact repository performance and are related to the geologic processes of tectonism, structural deformation, seismicity, and igneous activity. Collectively, they are referred to as the DE FEPs. This evaluation determines which of the DE FEPs are excluded from modeling used to support the total system performance assessment for license application (TSPA-LA). The evaluation is based on the data and results presented in supporting analysis reports, model reports, technical information, or corroborative documents that are cited in the individual FEP discussions in Section 6.2 of this analysis report.

  16. Semantic reasoning in zero example video event retrieval

    NARCIS (Netherlands)

    Boer, M.H.T. de; Lu, Y.J.; Zhang, H.; Schutte, K.; Ngo, C.W.; Kraaij, W.

    2017-01-01

    Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples,

  17. In Whom Do We Trust - Sharing Security Events

    NARCIS (Netherlands)

    Steinberger, Jessica; Kuhnert, Benjamin; Sperotto, Anna; Baier, Harald; Pras, Aiko

    2016-01-01

    Security event sharing is deemed of critical importance to counteract large-scale attacks at Internet service provider (ISP) networks as these attacks have become larger, more sophisticated and frequent. On the one hand, security event sharing is regarded to speed up organization's mitigation and

  18. Safeguards summary event list (SSEL)

    International Nuclear Information System (INIS)

    Davidson, J.J.; MacMurdy, P.H.

    1980-12-01

    The List contains nine categories of events involving NRC licensed material or licensees. It is deliberately broad in scope for two main reasons. First, the list is designed to serve as a reference document. It is as complete and accurate as possible. Second, the list is intended to provide as broad a perspective of the nature of licensee-related events as possible. The nine categories of events are as follows: bomb-related events; intrusion events; missing and/or allegedly stolen events; transportation-related events; vandalism events; arson events; firearms-related events; sabotage events; and miscellaneous events

  19. Features, Events, and Processes: Disruptive Events

    Energy Technology Data Exchange (ETDEWEB)

    P. Sanchez

    2004-11-08

    The purpose of this analysis report is to evaluate and document the inclusion or exclusion of the disruptive events features, events, and processes (FEPs) with respect to modeling used to support the total system performance assessment for license application (TSPA-LA). A screening decision, either ''Included'' or ''Excluded,'' is given for each FEP, along with the technical basis for screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.114 (d), (e), and (f) [DIRS 156605]. The FEPs addressed in this report deal with both seismic and igneous disruptive events, such as fault displacements through the repository and an igneous intrusion into the repository. For included FEPs, this analysis summarizes the implementation of the FEP in TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from TSPA-LA (i.e., why the FEP is excluded). Previous versions of this report were developed to support the total system performance assessments (TSPA) for various prior repository designs. This revision addresses the repository design for the license application (LA).

  20. Features, Events, and Processes: Disruptive Events

    International Nuclear Information System (INIS)

    P. Sanchez

    2004-01-01

    The purpose of this analysis report is to evaluate and document the inclusion or exclusion of the disruptive events features, events, and processes (FEPs) with respect to modeling used to support the total system performance assessment for license application (TSPA-LA). A screening decision, either ''Included'' or ''Excluded,'' is given for each FEP, along with the technical basis for screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.114 (d), (e), and (f) [DIRS 156605]. The FEPs addressed in this report deal with both seismic and igneous disruptive events, such as fault displacements through the repository and an igneous intrusion into the repository. For included FEPs, this analysis summarizes the implementation of the FEP in TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from TSPA-LA (i.e., why the FEP is excluded). Previous versions of this report were developed to support the total system performance assessments (TSPA) for various prior repository designs. This revision addresses the repository design for the license application (LA)

  1. Seeding Event: Creating and Developing Spaces of Entrepreneurial Freedom

    Directory of Open Access Journals (Sweden)

    Gaëtan Mourmant

    2012-12-01

    Full Text Available This paper addresses the question of initiating, fostering and growing a vibrant economy by developing Spaces of Entrepreneurial Freedom (SoEF. Establishing and developing the SoEF is explained by a seeding event which is the core category of this grounded theory. In short, a seeding event leads to the patching of a potential, structural “hole”, which may prove valuable to an entrepreneurial network. Seeding events are started by an initiator who will recognize a network opportunity and exploit it. After event designing, the initiators implement the event through bold experimentation and using an adaptive structure. If the event is considered successful, the next stages are refining, growing, templating and finally replicating; these stages may occur one after the other or simultaneously. Through the development of SoEF, we suggest that entrepreneurs, governments, universities, large companies, and other players in the business world can improve the development of entrepreneurship at their respective levels.

  2. Human Performance Event Database

    International Nuclear Information System (INIS)

    Trager, E. A.

    1998-01-01

    The purpose of this paper is to describe several aspects of a Human Performance Event Database (HPED) that is being developed by the Nuclear Regulatory Commission. These include the background, the database structure and basis for the structure, the process for coding and entering event records, the results of preliminary analyses of information in the database, and plans for the future. In 1992, the Office for Analysis and Evaluation of Operational Data (AEOD) within the NRC decided to develop a database for information on human performance during operating events. The database was needed to help classify and categorize the information to help feedback operating experience information to licensees and others. An NRC interoffice working group prepared a list of human performance information that should be reported for events and the list was based on the Human Performance Investigation Process (HPIP) that had been developed by the NRC as an aid in investigating events. The structure of the HPED was based on that list. The HPED currently includes data on events described in augmented inspection team (AIT) and incident investigation team (IIT) reports from 1990 through 1996, AEOD human performance studies from 1990 through 1993, recent NRR special team inspections, and licensee event reports (LERs) that were prepared for the events. (author)

  3. The Agency of Event

    DEFF Research Database (Denmark)

    Nicholas, Paul; Tamke, Martin; Riiber, Jacob

    2014-01-01

    This paper explores the notion of agency within event-based models. We present an event-based modeling approach that links interdependent generative, analytic and decision making sub-models within a system of exchange. Two case study projects demonstrate the underlying modeling concepts and metho...

  4. Intermediate mass dimuon events

    International Nuclear Information System (INIS)

    Moser, H.-G.

    1985-01-01

    We report the observation of 67 dimuon events at the CERN p anti p collider with the UA1 detector. The events will be interpreted in terms of the Drell-Yan mechanism, J/PSI and UPSILON decays and heavy flavour production. (author)

  5. The Blayais event

    International Nuclear Information System (INIS)

    2000-01-01

    This document provides the main events occurred to the Blayais installation during the year 2000. For each events, the detailed chronology, the situation analysis, the crisis management and the public information are provided. Some recommendations are also provided by the nuclear safety authorities. (A.L.B.)

  6. Nonbinary tree-based phylogenetic networks

    OpenAIRE

    Jetten, Laura; van Iersel, Leo

    2016-01-01

    Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can for example represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and st...

  7. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago Vanderlei; Giannitsarou, Chrysi; Johnson, CR

    2017-01-01

    We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and define a network aggregator that preserves network cohesion.

  8. The ATLAS Event Service: A new approach to event processing

    Science.gov (United States)

    Calafiura, P.; De, K.; Guan, W.; Maeno, T.; Nilsson, P.; Oleynik, D.; Panitkin, S.; Tsulaia, V.; Van Gemmeren, P.; Wenaus, T.

    2015-12-01

    The ATLAS Event Service (ES) implements a new fine grained approach to HEP event processing, designed to be agile and efficient in exploiting transient, short-lived resources such as HPC hole-filling, spot market commercial clouds, and volunteer computing. Input and output control and data flows, bookkeeping, monitoring, and data storage are all managed at the event level in an implementation capable of supporting ATLAS-scale distributed processing throughputs (about 4M CPU-hours/day). Input data flows utilize remote data repositories with no data locality or pre-staging requirements, minimizing the use of costly storage in favor of strongly leveraging powerful networks. Object stores provide a highly scalable means of remotely storing the quasi-continuous, fine grained outputs that give ES based applications a very light data footprint on a processing resource, and ensure negligible losses should the resource suddenly vanish. We will describe the motivations for the ES system, its unique features and capabilities, its architecture and the highly scalable tools and technologies employed in its implementation, and its applications in ATLAS processing on HPCs, commercial cloud resources, volunteer computing, and grid resources. Notice: This manuscript has been authored by employees of Brookhaven Science Associates, LLC under Contract No. DE-AC02-98CH10886 with the U.S. Department of Energy. The publisher by accepting the manuscript for publication acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  9. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

  10. Search for the Higgs boson using neural networks in events with missing energy and b-quark jets in pp collisions at square root(s) = 1.96 TeV.

    Science.gov (United States)

    Aaltonen, T; Adelman, J; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'Orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; d'Errico, M; Di Canto, A; di Giovanni, G P; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, T; Dube, S; Ebina, K; Elagin, A; Erbacher, R; Errede, D; Errede, S; Ershaidat, N; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Group, R C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Hughes, R E; Hurwitz, M; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; LeCompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leone, S; Lewis, J D; Lin, C-J; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Lovas, L; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; MacQueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Mastrandrea, P; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Mesropian, C; Miao, T; Mietlicki, D; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramanov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Potamianos, K; Poukhov, O; Prokoshin, F; Pronko, A; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Rutherford, B; Saarikko, H; Safonov, A; Sakumoto, W K; Santi, L; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Simonenko, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Suh, J S; Sukhanov, A; Suslov, I; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Uozumi, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wolfe, H; Wright, T; Wu, X; Würthwein, F; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zhang, X; Zheng, Y; Zucchelli, S

    2010-04-09

    We report on a search for the standard model Higgs boson produced in association with a W or Z boson in pp collisions at square root(s)=1.96 TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb(-1). We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a b hadron. We find good agreement between data and background predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110 GeV/c(2) to 150 GeV/c(2). For a mass of 115 GeV/c(2) the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

  11. Parallel discrete event simulation: A shared memory approach

    Science.gov (United States)

    Reed, Daniel A.; Malony, Allen D.; Mccredie, Bradley D.

    1987-01-01

    With traditional event list techniques, evaluating a detailed discrete event simulation model can often require hours or even days of computation time. Parallel simulation mimics the interacting servers and queues of a real system by assigning each simulated entity to a processor. By eliminating the event list and maintaining only sufficient synchronization to insure causality, parallel simulation can potentially provide speedups that are linear in the number of processors. A set of shared memory experiments is presented using the Chandy-Misra distributed simulation algorithm to simulate networks of queues. Parameters include queueing network topology and routing probabilities, number of processors, and assignment of network nodes to processors. These experiments show that Chandy-Misra distributed simulation is a questionable alternative to sequential simulation of most queueing network models.

  12. News Teaching Support: New schools network launched Competition: Observatory throws open doors to a select few Festival: Granada to host 10th Ciencia en Acción Centenary: Science Museum celebrates 100 years Award: Queen's birthday honour for science communicator Teacher Training: Training goes where it's needed Conference: Physics gets creative in Christchurch Conference: Conference is packed with ideas Poster Campaign: Bus passengers learn about universe Forthcoming events

    Science.gov (United States)

    2009-09-01

    Teaching Support: New schools network launched Competition: Observatory throws open doors to a select few Festival: Granada to host 10th Ciencia en Acción Centenary: Science Museum celebrates 100 years Award: Queen's birthday honour for science communicator Teacher Training: Training goes where it's needed Conference: Physics gets creative in Christchurch Conference: Conference is packed with ideas Poster Campaign: Bus passengers learn about universe Forthcoming events

  13. Network cosmology.

    Science.gov (United States)

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

  14. Romanian seismic network

    International Nuclear Information System (INIS)

    Ionescu, Constantin; Rizescu, Mihaela; Popa, Mihaela; Grigore, Adrian

    2000-01-01

    The research in the field of seismology in Romania is mainly carried out by the National Institute for Earth Physics (NIEP). The NIEP activities are mainly concerned with the fundamental research financed by research contracts from public sources and the maintenance and operation of the Romanian seismic network. A three stage seismic network is now operating under NIEP, designed mainly to monitor the Vrancea seismic region in a magnitude range from microearthquakes to strong events: - network of 18 short-period seismometers (S13); - Teledyne Geotech Instruments (Texas); - network of 7 stations with local digital recording (PCM-5000) on magnetic tape, made up of, S13 geophone (T=2 s) on vertical component and SH1 geophone (T=5 s) on horizontal components; - network of 28 SMA-1 accelerometers and 30 digital accelerometers (Kinemetrics - K2) installed in the free field conditions in the framework of the joint German-Romanian cooperation program (CRC); the K2 instruments cover a magnitude range from 1.4 to 8.0. Since 1994, MLR (Muntele Rosu) station has become part of the GEOFON network and was provided with high performance broad band instruments. At Bucharest and Timisoara data centers, an automated and networked seismological system performs the on-line digital acquisition and processing of the telemetered data. Automatic processing includes discrimination between local and distant seismic events, earthquake location and magnitude computation, and source parameter determination for local earthquakes. The results are rapidly distributed via Internet, to several seismological services in Europe and USA, to be used in the association/confirmation procedures. Plans for new developments of the network include the upgrade from analog to digital telemetry and new stations for monitoring local seismicity. (authors)

  15. Event shape sorting

    International Nuclear Information System (INIS)

    Kopecna, Renata; Tomasik, Boris

    2016-01-01

    We propose a novel method for sorting events of multiparticle production according to the azimuthal anisotropy of their momentum distribution. Although the method is quite general, we advocate its use in analysis of ultra-relativistic heavy-ion collisions where a large number of hadrons is produced. The advantage of our method is that it can automatically sort out samples of events with histograms that indicate similar distributions of hadrons. It takes into account the whole measured histograms with all orders of anisotropy instead of a specific observable (e.g., v 2 , v 3 , q 2 ). It can be used for more exclusive experimental studies of flow anisotropies which are then more easily compared to theoretical calculations. It may also be useful in the construction of mixed-events background for correlation studies as it allows to select events with similar momentum distribution. (orig.)

  16. "Universe" event at AIMS

    Science.gov (United States)

    2008-06-01

    Report of event of 11 May 2008 held at the African Institute of Mathematical Sciences (Muizenberg, Cape), with speakers Michael Griffin (Administrator of NASA), Stephen Hawking (Cambridge), David Gross (Kavli Institute, Santa Barbara) and George Smoot (Berkeley).

  17. Event visualization in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00211497; The ATLAS collaboration; Boudreau, Joseph; Konstantinidis, Nikolaos; Martyniuk, Alex; Moyse, Edward; Thomas, Juergen; Waugh, Ben; Yallup, David

    2017-01-01

    At the beginning, HEP experiments made use of photographical images both to record and store experimental data and to illustrate their findings. Then the experiments evolved and needed to find ways to visualize their data. With the availability of computer graphics, software packages to display event data and the detector geometry started to be developed. Here, an overview of the usage of event display tools in HEP is presented. Then the case of the ATLAS experiment is considered in more detail and two widely used event display packages are presented, Atlantis and VP1, focusing on the software technologies they employ, as well as their strengths, differences and their usage in the experiment: from physics analysis to detector development, and from online monitoring to outreach and communication. Towards the end, the other ATLAS visualization tools will be briefly presented as well. Future development plans and improvements in the ATLAS event display packages will also be discussed.

  18. Analysis of extreme events

    CSIR Research Space (South Africa)

    Khuluse, S

    2009-04-01

    Full Text Available ) determination of the distribution of the damage and (iii) preparation of products that enable prediction of future risk events. The methodology provided by extreme value theory can also be a powerful tool in risk analysis...

  19. RAS Initiative - Events

    Science.gov (United States)

    The NCI RAS Initiative has organized multiple events with outside experts to discuss how the latest scientific and technological breakthroughs can be applied to discover vulnerabilities in RAS-driven cancers.

  20. Gargamelle: neutral current event

    CERN Multimedia

    1973-01-01

    This event shows real tracks of particles from the 1200 litre Gargamelle bubble chamber that ran on the PS from 1970 to 1976 and on the SPS from 1976 to 1979. In this image a neutrino passes close to a nucleon and reemerges as a neutrino. Such events are called neutral curent, as they are mediated by the Z0 boson which has no electric charge.

  1. Small Business Procurement Event

    Science.gov (United States)

    2014-08-13

    Small Business Procurement Event 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Department of the Navy,Office of Small Business Programs,720 Kennon...distribution unlimited 13. SUPPLEMENTARY NOTES NDIA 27th Navy Gold Coast Small Business Procurement Event, 12-13 Aug 2014, San Diego, CA. 14. ABSTRACT

  2. The ALEPH event builder

    International Nuclear Information System (INIS)

    Benetta, R.; Marchioro, A.; McPherson, G.; Rueden, W. von

    1986-01-01

    The data acquisition system for the ALEPH experiment at CERN is organised in a hierarchical fashion within FASTBUS. The detector consists of a number of sub-detectors whose data must be individually assembled and formatted in real time. This task of 'event building' will be performed by a FASTBUS module in which a powerful microprocessor running high level software is embedded. Such a module, called an Event Builder, has been constructed by the ALEPH Online Group at CERN. (Auth.)

  3. LHCb DAQ network upgrade tests

    CERN Document Server

    Pisani, Flavio

    2013-01-01

    My project concerned the evaluation of new technologies for the DAQ network upgrade of LHCb. The first part consisted in developing and Open Flow-based Clos network. This new technology is very interesting and powerful but, as shown by the results, it still needs further improvements. The second part consisted in testing and benchmarking 40GbE network equipment: Mellanox MT27500, Chelsio T580 and Huawei Cloud Engine 12804. An event-building simulation is currently been performed in order to check the feasibility of the DAQ network upgrade in LS2. The first results are promising.

  4. Nonbinary Tree-Based Phylogenetic Networks.

    Science.gov (United States)

    Jetten, Laura; van Iersel, Leo

    2018-01-01

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

  5. A Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and \\boldit{b}-quark Jets in $p\\bar p$ Collisions at $\\sqrt{s}=1.96$ TeV

    Energy Technology Data Exchange (ETDEWEB)

    Aaltonen, T.; /Helsinki Inst. of Phys.; Adelman, J.; /Chicago U., EFI; Alvarez Gonzalez, B.; /Cantabria Inst. of Phys.; Amerio, S.; /INFN, Padua; Amidei, D.; /Michigan U.; Anastassov, A.; /Northwestern U.; Annovi, A.; /Frascati; Antos, J.; /Comenius U.; Apollinari, G.; /Fermilab; Apresyan, A.; /Purdue U.; Arisawa, T.; /Waseda U. /Dubna, JINR

    2009-11-01

    We report on a search for the standard model Higgs boson produced in association with a W or Z boson in p{bar p} collisions at {radical}s = 1.96 TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb{sup -1}. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a b hadron. We find good agreement between data and predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110 GeV/c{sup 2} to 150 GeV/c{sup 2}. For a mass of 115 GeV/c{sup 2} the observed (expected) limit is 6.9 (5.6) times the standard model prediction.

  6. Nightside High Latitude Magnetic Impulse Events

    Science.gov (United States)

    Engebretson, M. J.; Connors, M. G.; Braun, D.; Posch, J. L.; Kaur, M.; Guillon, S.; Hartinger, M.; Kim, H.; Behlke, R.; Reiter, K.; Jackel, B. J.; Russell, C. T.

    2017-12-01

    High latitude Magnetic Impulse Events (MIEs), isolated pulses with periods 5-10 min, were first noted in ground-based magnetometer data near local noon, and are now understood to be signatures of transient pressure increases in the solar wind (sudden impulses - SIs) and/or in the ion foreshock (traveling convection vortex events - TCVs). However, solitary pulses with considerably larger amplitude (ΔB up to 1500 nT) have often been observed in the night sector at these same latitudes. These events are not directly associated with transient external pressure increases, and are often large enough to produce significant ground induced currents. Although many night sector MIEs occur in association with substorm signatures, others appear to be very isolated. We present here a survey of intense MIE events identified in magnetometer data from the AUTUMNX and MACCS arrays in eastern Arctic Canada at all local times between July 1, 2014 and June 30, 2017. We also show maps of horizontal and vertical perturbations and maximum dB/dt values, as well as sample magnetograms, for several example events using data from these and other arrays in Arctic Canada, as well as in West Greenland and Antarctica, the latter to show the conjugate nature of these events. A basic relation to GIC data in the Hydro-Québec electrical transmission network in eastern Canada has been determined and will be discussed.

  7. Rare event simulation using Monte Carlo methods

    CERN Document Server

    Rubino, Gerardo

    2009-01-01

    In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. ...

  8. A software Event Summation System for MDSplus

    International Nuclear Information System (INIS)

    Davis, W.M.; Mastrovito, D.M.; Roney, P.G.; Sichta, P.

    2008-01-01

    The MDSplus data acquisition and management system uses software events for communication among interdependent processes anywhere on the network. Actions can then be triggered, such as a data-acquisition routine, or analysis or display programs waiting for data. A small amount of data, such as a shot number, can be passed with these events. Since programs sometimes need more than one data set, we developed a system on NSTX to declare composite events using logical AND and OR operations. The system is written in the IDL language, so it can be run on Linux, Macintosh or Windows platforms. Like MDSplus, the Experimental Physics and Industrial Control System (EPICS) is a core component of the NSTX software environment. The Event Summation System provides an IDL-based interface to EPICS. This permits EPICS-aware processes to be synchronized with MDSplus-aware processes, to provide, for example, engineering operators information about physics data acquisition and analysis. Reliability was a more important design consideration than performance for this system; the system's architecture includes features to support this. The system has run for weeks at a time without requiring manual intervention. Hundreds of incoming events per second can be handled reliably. All incoming and declared events are logged with a timestamp. The system can be configured easily through a single, easy-to-read text file

  9. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  10. Advanced event reweighting using multivariate analysis

    International Nuclear Information System (INIS)

    Martschei, D; Feindt, M; Honc, S; Wagner-Kuhr, J

    2012-01-01

    Multivariate analysis (MVA) methods, especially discrimination techniques such as neural networks, are key ingredients in modern data analysis and play an important role in high energy physics. They are usually trained on simulated Monte Carlo (MC) samples to discriminate so called 'signal' from 'background' events and are then applied to data to select real events of signal type. We here address procedures that improve this work flow. This will be the enhancement of data / MC agreement by reweighting MC samples on a per event basis. Then training MVAs on real data using the sPlot technique will be discussed. Finally we will address the construction of MVAs whose discriminator is independent of a certain control variable, i.e. cuts on this variable will not change the discriminator shape.

  11. Functional asynchronous networks: Factorization of dynamics and function

    Directory of Open Access Journals (Sweden)

    Bick Christian

    2016-01-01

    Full Text Available In this note we describe the theory of functional asynchronous networks and one of the main results, the Modularization of Dynamics Theorem, which for a large class of functional asynchronous networks gives a factorization of dynamics in terms of constituent subnetworks. For these networks we can give a complete description of the network function in terms of the function of the events comprising the network and thereby answer a question originally raised by Alon in the context of biological networks.

  12. Contribution of Infrasound to IDC Reviewed Event Bulletin

    Science.gov (United States)

    Bittner, Paulina; Polich, Paul; Gore, Jane; Ali, Sherif Mohamed; Medinskaya, Tatiana; Mialle, Pierrick

    2016-04-01

    Until 2003 two waveform technologies, i.e. seismic and hydroacoustic were used to detect and locate events included in the International Data Centre (IDC) Reviewed Event Bulletin (REB). The first atmospheric event was published in the REB in 2003 but infrasound detections could not be used by the Global Association (GA) Software due to the unmanageable high number of spurious associations. Offline improvements of the automatic processing took place to reduce the number of false detections to a reasonable level. In February 2010 the infrasound technology was reintroduced to the IDC operations and has contributed to both automatic and reviewed IDC bulletins. The primary contribution of infrasound technology is to detect atmospheric events. These events may also be observed at seismic stations, which will significantly improve event location. Examples of REB events, which were detected by the International Monitoring System (IMS) infrasound network were fireballs (e.g. Bangkok fireball, 2015), volcanic eruptions (e.g. Calbuco, Chile 2015) and large surface explosions (e.g. Tjanjin, China 2015). Query blasts and large earthquakes belong to events primarily recorded at seismic stations of the IMS network but often detected at the infrasound stations. Presence of infrasound detection associated to an event from a mining area indicates a surface explosion. Satellite imaging and a database of active mines can be used to confirm the origin of such events. This presentation will summarize the contribution of 6 years of infrasound data to IDC bulletins and provide examples of events recorded at the IMS infrasound network. Results of this study may help to improve location of small events with observations on infrasound stations.

  13. 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.

  14. RETRIEVAL EVENTS EVALUATION

    International Nuclear Information System (INIS)

    Wilson, T.

    1999-01-01

    The purpose of this analysis is to evaluate impacts to the retrieval concept presented in the Design Analysis ''Retrieval Equipment and Strategy'' (Reference 6), from abnormal events based on Design Basis Events (DBE) and Beyond Design Basis Events (BDBE) as defined in two recent analyses: (1) DBE/Scenario Analysis for Preclosure Repository Subsurface Facilities (Reference 4); and (2) Preliminary Preclosure Design Basis Event Calculations for the Monitored Geologic Repository (Reference 5) The objective of this task is to determine what impacts the DBEs and BDBEs have on the equipment developed for retrieval. The analysis lists potential impacts and recommends changes to be analyzed in subsequent design analyses for developed equipment, or recommend where additional equipment may be needed, to allow retrieval to be performed in all DBE or BDBE situations. This analysis supports License Application design and therefore complies with the requirements of Systems Description Document input criteria comparison as presented in Section 7, Conclusions. In addition, the analysis discusses the impacts associated with not using concrete inverts in the emplacement drifts. The ''Retrieval Equipment and Strategy'' analysis was based on a concrete invert configuration in the emplacement drift. The scope of the analysis, as presented in ''Development Plan for Retrieval Events Evaluation'' (Reference 3) includes evaluation and criteria of the following: Impacts to retrieval from the emplacement drift based on DBE/BDBEs, and changes to the invert configuration for the preclosure period. Impacts to retrieval from the main drifts based on DBE/BDBEs for the preclosure period

  15. Revisiting event horizon finders

    International Nuclear Information System (INIS)

    Cohen, Michael I; Pfeiffer, Harald P; Scheel, Mark A

    2009-01-01

    Event horizons are the defining physical features of black hole spacetimes, and are of considerable interest in studying black hole dynamics. Here, we reconsider three techniques to find event horizons in numerical spacetimes: integrating geodesics, integrating a surface, and integrating a level-set of surfaces over a volume. We implement the first two techniques and find that straightforward integration of geodesics backward in time is most robust. We find that the exponential rate of approach of a null surface towards the event horizon of a spinning black hole equals the surface gravity of the black hole. In head-on mergers we are able to track quasi-normal ringing of the merged black hole through seven oscillations, covering a dynamic range of about 10 5 . Both at late times (when the final black hole has settled down) and at early times (before the merger), the apparent horizon is found to be an excellent approximation of the event horizon. In the head-on binary black hole merger, only some of the future null generators of the horizon are found to start from past null infinity; the others approach the event horizons of the individual black holes at times far before merger.

  16. 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

  17. Reporting of safeguards events

    International Nuclear Information System (INIS)

    Dwyer, P.A.; Ervin, N.E.

    1988-02-01

    On June 9, 1987, the Commission published in the Federal Register a final rule revising the reporting requirements for safeguards events. Safeguards events include actual or attempted theft of special nuclear material (SNM); actual or attempted acts or events which interrupt normal operations at power reactors due to unauthorized use of or tampering with machinery, components, or controls; certain threats made against facilities possessing SNM; and safeguards system failures impacting the effectiveness of the system. The revised rule was effective October 8, 1987. On September 14, 1987, the NRC held a workshop in Bethesda, MD, to answer affected licensees' questions on the final rule. This report documents questions discussed at the September 14 meeting, reflects a completed staff review of the answers, and supersedes previous oral comment on the topics covered

  18. Discrete-Event Simulation

    Directory of Open Access Journals (Sweden)

    Prateek Sharma

    2015-04-01

    Full Text Available Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of events in time. So this paper aims at introducing about Discrete-Event Simulation and analyzing how it is beneficial to the real world systems.

  19. First Indico Virtual Event

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    The first Indico virtual event will take place on February 4th 15:00 and will focus on two main topics The release of Indico v1.2 The migration of the OO Indico backend database (ZODB) to a more standard DBMS It will be fully virtual using the CERN Vidyo service and will foster discussions between developers and administrators of Indico servers worldwide. Connections to the virtual room will be open, but attendees are encouraged to register to the event, in order to be informed of any changes in the organisation if any. If you would like to add a topic of discussion or propose yourself a contribution, please let us know at indico-team@cern.ch. Connection to Vidyo Vidyo connection details are available here CERN Vidyo service documentation can be found here First-time users are encouraged to try the service before connecting to the real event

  20. 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.

  1. A Communication network for LHC detector readout

    International Nuclear Information System (INIS)

    Romero, L.

    1993-01-01

    This paper describe a network architecture for data taking in LHC environment. The network is composed of 64 rings of point to point links working at 100 Mbytes/s. The network connect the front end electronics, computer farms and two data switches. The efficiency of the system is discussed. Using extracted 1 Kbyte events for the 2nd level trigger and whole 1 Mbyte events for the 3rd level trigger, then the system can sustain working rates of 2 x 10''5 and 2 x 10''3 events/s going into the 2nd and 3rd level triggers. System resistance to errors is discussed. (Author) 3 refs

  2. A communication network for LHC detector readout

    International Nuclear Information System (INIS)

    Romero, L.

    1993-01-01

    This paper describe a network architecture for data taking in LHC environment. The network is composed of 64 rings of point to point links working at 100 Mbytes/s. The network connect the front end electronics, computer farms and two data switches. The efficiency of the system is discussed. Using extracted 1 kbyte events for the 2nd level trigger and whole 1 Mbyte events for the 3rd level trigger, then the system can sustain working rates of 2 x 10''5 and 2 x 10''3events/s going into the 2nd and 3rd level triggers. System resistance to errors is discussed. (Author)

  3. A Communication network for LHC detector readout

    Energy Technology Data Exchange (ETDEWEB)

    Romero, L

    1993-07-01

    This paper describe a network architecture for data taking in LHC environment. The network is composed of 64 rings of point to point links working at 100 Mbytes/s. The network connect the front end electronics, computer farms and two data switches. The efficiency of the system is discussed. Using extracted 1 Kbyte events for the 2nd level trigger and whole 1 Mbyte events for the 3rd level trigger, then the system can sustain working rates of 2 x 10''5 and 2 x 10''3 events/s going into the 2nd and 3rd level triggers. System resistance to errors is discussed. (Author) 3 refs.

  4. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...

  5. Events and Effects

    DEFF Research Database (Denmark)

    Rytter, Mikkel

    2010-01-01

    Analyzing the period of ‘intensive transnationalism’ among Pakistani migrants in Denmark precipitated by the 2005 earthquake in Kashmir, this article explores the relationship between events and effects on a global scale. One significant initiative after the disaster was the founding of an ad hoc......, and national identity politics in Denmark. Despite the medical doctors’ efforts and intentions, the out- come was framed by 9/11, which has become the major critical event of the decade—one that has supported a developing cleavage between the Danish majority and Denmark’s Muslim immigrant minority....

  6. Army Air and Missile Defense Network Design Facility (AAMDNDF)

    Data.gov (United States)

    Federal Laboratory Consortium — This facility provides JTIDS network designs and platform initialization load files for all Joint and Army-only tests, exercises, operations, and contingency events...

  7. Network maintenance

    CERN Multimedia

    GS Department

    2009-01-01

    A site-wide network maintenance operation has been scheduled for Saturday 28 February. Most of the network devices of the general purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites throughout the day. This upgrade will not affect the Computer Centre itself, Building 613, the Technical Network and the LHC experiments, dedicated networks at the pits. For further details of this intervention, please contact Netops by phone 74927 or e-mail mailto:Netops@cern.ch. IT/CS Group

  8. Network maintenance

    CERN Multimedia

    IT Department

    2009-01-01

    A site wide network maintenance has been scheduled for Saturday 28 February. Most of the network devices of the General Purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites along this day. This upgrade will not affect: the Computer centre itself, building 613, the Technical Network and the LHC experiments dedicated networks at the pits. Should you need more details on this intervention, please contact Netops by phone 74927 or email mailto:Netops@cern.ch. IT/CS Group

  9. Recurring events - Volume 2

    International Nuclear Information System (INIS)

    2003-04-01

    The feedback of operating experience from nuclear power plants (NPP) is intended to help avoid occurrence or recurrence of safety significant events. Regulatory bodies, and utilities operating nuclear power plants, have established operating experience feedback systems since the beginning of commercial nuclear power production. Well-established operating experience feedback systems exist on national and international level. An example of an international system is the Incident Reporting System (IRS) jointly operated by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency (NEA). There also are systems maintained by the operating organizations, including the World Association of Nuclear Operators (WANO), and owner groups of different NPP vendors. Committee on the Safety of Nuclear Installations (CSNI) Working Group on Operating Experience (WGOE; formerly Principal Working Group No. 1, PWG1) carried out a study on recurring events some years ago. This report, published in 1999, highlighted some areas of safety significance involving recurrent events in different NPPs around the world. Based on the important findings of this report, CSNI requested two additional studies: 1. first an international workshop should be organized and second, 2. a task group should be established to develop a second report on the topic and to evaluate the findings of the workshop. The workshop, hosted by the Swiss Regulatory Authority, HSK, was held in Switzerland in March 2002. It was attended by 32 experts representing the regulatory, nuclear power plant, vendor, and international agency communities. Several insights and recommendations were presented and are integrated in this report with respect to causes of recurring events: - Operating experience feedback processes had not always been effective, that is, the existing operating experiences had not been effectively applied, - Actions to be taken were not implemented in a timely manner, - The root cause was not

  10. LAN attack detection using Discrete Event Systems.

    Science.gov (United States)

    Hubballi, Neminath; Biswas, Santosh; Roopa, S; Ratti, Ritesh; Nandi, Sukumar

    2011-01-01

    Address Resolution Protocol (ARP) is used for determining the link layer or Medium Access Control (MAC) address of a network host, given its Internet Layer (IP) or Network Layer address. ARP is a stateless protocol and any IP-MAC pairing sent by a host is accepted without verification. This weakness in the ARP may be exploited by malicious hosts in a Local Area Network (LAN) by spoofing IP-MAC pairs. Several schemes have been proposed in the literature to circumvent these attacks; however, these techniques either make IP-MAC pairing static, modify the existing ARP, patch operating systems of all the hosts etc. In this paper we propose a Discrete Event System (DES) approach for Intrusion Detection System (IDS) for LAN specific attacks which do not require any extra constraint like static IP-MAC, changing the ARP etc. A DES model is built for the LAN under both a normal and compromised (i.e., spoofed request/response) situation based on the sequences of ARP related packets. Sequences of ARP events in normal and spoofed scenarios are similar thereby rendering the same DES models for both the cases. To create different ARP events under normal and spoofed conditions the proposed technique uses active ARP probing. However, this probing adds extra ARP traffic in the LAN. Following that a DES detector is built to determine from observed ARP related events, whether the LAN is operating under a normal or compromised situation. The scheme also minimizes extra ARP traffic by probing the source IP-MAC pair of only those ARP packets which are yet to be determined as genuine/spoofed by the detector. Also, spoofed IP-MAC pairs determined by the detector are stored in tables to detect other LAN attacks triggered by spoofing namely, man-in-the-middle (MiTM), denial of service etc. The scheme is successfully validated in a test bed. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Control theory of digitally networked dynamic systems

    CERN Document Server

    Lunze, Jan

    2013-01-01

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

  12. Business Event Notification Service (BENS)

    Data.gov (United States)

    Department of Veterans Affairs — BENS provides a notification of pre-defined business events to applications, portals, and automated business processes. Such events are defined in the Event Catalog,...

  13. Wroclaw neutrino event generator

    International Nuclear Information System (INIS)

    Nowak, J A

    2006-01-01

    A neutrino event generator developed by the Wroclaw Neutrino Group is described. The physical models included in the generator are discussed and illustrated with the results of simulations. The considered processes are quasi-elastic scattering and pion production modelled by combining the Δ resonance excitation and deep inelastic scattering

  14. The CMS Event Builder

    CERN Document Server

    Brigljevic, V; Cano, E; Cittolin, Sergio; Csilling, Akos; Gigi, D; Glege, F; Gómez-Reino, Robert; Gulmini, M; Gutleber, J; Jacobs, C; Kozlovszky, Miklos; Larsen, H; Magrans de Abril, Ildefons; Meijers, F; Meschi, E; Murray, S; Oh, A; Orsini, L; Pollet, L; Rácz, A; Samyn, D; Scharff-Hansen, P; Schwick, C; Sphicas, Paris; ODell, V; Suzuki, I; Berti, L; Maron, G; Toniolo, N; Zangrando, L; Ninane, A; Erhan, S; Bhattacharya, S; Branson, J G

    2003-01-01

    The data acquisition system of the CMS experiment at the Large Hadron Collider will employ an event builder which will combine data from about 500 data sources into full events at an aggregate throughput of 100 GByte/s. Several architectures and switch technologies have been evaluated for the DAQ Technical Design Report by measurements with test benches and by simulation. This paper describes studies of an EVB test-bench based on 64 PCs acting as data sources and data consumers and employing both Gigabit Ethernet and Myrinet technologies as the interconnect. In the case of Ethernet, protocols based on Layer-2 frames and on TCP/IP are evaluated. Results from ongoing studies, including measurements on throughput and scaling are presented. The architecture of the baseline CMS event builder will be outlined. The event builder is organised into two stages with intelligent buffers in between. The first stage contains 64 switches performing a first level of data concentration by building super-fragments from fragmen...

  15. The ATLAS event filter

    CERN Document Server

    Beck, H P; Boissat, C; Davis, R; Duval, P Y; Etienne, F; Fede, E; Francis, D; Green, P; Hemmer, F; Jones, R; MacKinnon, J; Mapelli, Livio P; Meessen, C; Mommsen, R K; Mornacchi, Giuseppe; Nacasch, R; Negri, A; Pinfold, James L; Polesello, G; Qian, Z; Rafflin, C; Scannicchio, D A; Stanescu, C; Touchard, F; Vercesi, V

    1999-01-01

    An overview of the studies for the ATLAS Event Filter is given. The architecture and the high level design of the DAQ-1 prototype is presented. The current status if the prototypes is briefly given. Finally, future plans and milestones are given. (11 refs).

  16. Negligence and Athletic Events.

    Science.gov (United States)

    Mawdsley, Ralph D.

    2001-01-01

    Although athletic events generate their share of negligence lawsuits, the relatively small number, compared with other education areas, suggests that defenses (like assumption or risk and contributory negligence) have a better fit in athletics. Implications of newer litigation trends involving coaches' misconduct and interpretation of state…

  17. On Objects and Events

    DEFF Research Database (Denmark)

    Eugster, Patrick Thomas; Guerraoui, Rachid; Damm, Christian Heide

    2001-01-01

    This paper presents linguistic primitives for publish/subscribe programming using events and objects. We integrate our primitives into a strongly typed object-oriented language through four mechanisms: (1) serialization, (2) multiple sub typing, (3) closures, and (4) deferred code evaluation. We...

  18. Load event: Aircraft crash

    International Nuclear Information System (INIS)

    Fritsch, H.

    1985-01-01

    The bibliography includes 48 quotations, up to the year 1983, on the following issues: Experiments and computational methods. Design load for the dimensioning of reinforced concrete buildings and components with respect to the dynamic load in the event of an aircraft crash. (orig./HP) [de

  19. Preparedness events in 2008

    International Nuclear Information System (INIS)

    2009-01-01

    NRPA have as Secretariat for the Crisis Committee and the nuclear preparedness organization in 2008 published several reports of incidents of radioactivity and radioactive pollution to the nuclear preparedness organization, media and the public. In addition to these events, there have been some incidents with radiation and small radioactive sources in Norway during this year. (AG)

  20. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW

  1. Traumatic events and children

    Science.gov (United States)

    ... over and over again Know the Signs of Post-traumatic Stress Disorder (PTSD) Half of the children who survive traumatic events ... team. Related MedlinePlus Health Topics Child Mental Health Post-Traumatic Stress Disorder Browse the Encyclopedia A.D.A.M., Inc. ...

  2. Network Ambivalence

    Directory of Open Access Journals (Sweden)

    Patrick Jagoda

    2015-08-01

    Full Text Available The language of networks now describes everything from the Internet to the economy to terrorist organizations. In distinction to a common view of networks as a universal, originary, or necessary form that promises to explain everything from neural structures to online traffic, this essay emphasizes the contingency of the network imaginary. Network form, in its role as our current cultural dominant, makes scarcely imaginable the possibility of an alternative or an outside uninflected by networks. If so many things and relationships are figured as networks, however, then what is not a network? If a network points towards particular logics and qualities of relation in our historical present, what others might we envision in the future? In  many ways, these questions are unanswerable from within the contemporary moment. Instead of seeking an avant-garde approach (to move beyond networks or opting out of networks (in some cases, to recover elements of pre-networked existence, this essay proposes a third orientation: one of ambivalence that operates as a mode of extreme presence. I propose the concept of "network aesthetics," which can be tracked across artistic media and cultural forms, as a model, style, and pedagogy for approaching interconnection in the twenty-first century. The following essay is excerpted from Network Ambivalence (Forthcoming from University of Chicago Press. 

  3. 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

  4. Network workshop

    DEFF Research Database (Denmark)

    Bruun, Jesper; Evans, Robert Harry

    2014-01-01

    This paper describes the background for, realisation of and author reflections on a network workshop held at ESERA2013. As a new research area in science education, networks offer a unique opportunity to visualise and find patterns and relationships in complicated social or academic network data....... These include student relations and interactions and epistemic and linguistic networks of words, concepts and actions. Network methodology has already found use in science education research. However, while networks hold the potential for new insights, they have not yet found wide use in the science education...... research community. With this workshop, participants were offered a way into network science based on authentic educational research data. The workshop was constructed as an inquiry lesson with emphasis on user autonomy. Learning activities had participants choose to work with one of two cases of networks...

  5. Network Convergence

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Network Convergence. User is interested in application and content - not technical means of distribution. Boundaries between distribution channels fade out. Network convergence leads to seamless application and content solutions.

  6. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    Companies organize in a way that involves many activities that are external to the traditional organizational boundaries. This presents challenges to operations management and managing operations involves many issues and actions dealing with external networks. Taking a network perspective changes...

  7. Network Science

    National Research Council Canada - National Science Library

    Leland, Will

    2006-01-01

    OVERVIEW: (1) A committee of technical experts, military officers and R&D managers was assembled by the National Research Council to reach consensus on the nature of networks and network research. (2...

  8. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Krigslund, Jeppe; Hansen, Jonas; Roetter, Daniel Enrique Lucani

    2015-01-01

    Software Defined Networking (SDN) and Network Coding (NC) are two key concepts in networking that have garnered a large attention in recent years. On the one hand, SDN's potential to virtualize services in the Internet allows a large flexibility not only for routing data, but also to manage....... This paper advocates for the use of SDN to bring about future Internet and 5G network services by incorporating network coding (NC) functionalities. The inherent flexibility of both SDN and NC provides a fertile ground to envision more efficient, robust, and secure networking designs, that may also...

  9. Single Event Kinetic Modelling without Explicit Generation of Large Networks: Application to Hydrocracking of Long Paraffins Modélisation cinétique par événements constitutifs sans génération explicite de grands réseaux : application à l’hydrocraquage des paraffines longues

    Directory of Open Access Journals (Sweden)

    Guillaume D.

    2011-08-01

    Full Text Available The single event modelling concept allows developing kinetic models for the simulation of refinery processes. For reaction networks with several hundreds of thousands of species, as is the case for catalytic reforming, rigorous relumping by carbon atom number and branching degree were efficiently employed by assuming chemical equilibrium in each lump. This relumping technique yields a compact lumped model without any loss of information, but requires the full detail of an explicitly generated reaction network. Classic network generation techniques become impractical when the hydrocarbon species contain more than approximately 20 carbon atoms, because of the extremely rapid growth of reaction network. Hence, implicit relumping techniques were developed in order to compute lumping coefficients without generating the detailed reaction network. Two alternative and equivalent approaches are presented, based either on structural classes or on lateral chain decomposition. These two methods are discussed and the lateral chain decomposition method is applied to the kinetic modelling of long chain paraffin hydroisomerization and hydrocracking. The lateral chain decomposition technique is exactly equivalent to the original calculation method based on the explicitly generated detailed reaction network, as long as Benson’s group contribution method is used to calculate the necessary thermodynamic data in both approaches. Le concept de modélisation par événements constitutifs permet de développer des modèles cinétiques pour la simulation des procédés de raffinage. Pour des réseaux réactionnels de centaines de milliers d'espèces, comme cela est le cas pour le reformage catalytique, le regroupement rigoureux par nombre d'atomes de carbone et degré de ramification a été utilisé efficacement en faisant l'hypothèse de l'équilibre chimique dans chaque groupe. Cette technique de regroupement conduit à un modèle regroupé compact sans perte d

  10. Network Simulation

    CERN Document Server

    Fujimoto, Richard

    2006-01-01

    "Network Simulation" presents a detailed introduction to the design, implementation, and use of network simulation tools. Discussion topics include the requirements and issues faced for simulator design and use in wired networks, wireless networks, distributed simulation environments, and fluid model abstractions. Several existing simulations are given as examples, with details regarding design decisions and why those decisions were made. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the

  11. SMOS data and extreme events

    Science.gov (United States)

    Kerr, Yann; Wigneron, Jean-Pierre; Ferrazzoli, Paolo; Mahmoodi, Ali; Al-Yaari, Amen; Parrens, Marie; Bitar, Ahmad Al; Rodriguez-Fernandez, Nemesio; Bircher, Simone; Molero-rodenas, Beatriz; Drusch, Matthias; Mecklenburg, Susanne

    2017-04-01

    The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3), vegetation water content over land, and ocean salinity. These geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches, and in particular in improving model forecasts. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. The whole data set has been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets

  12. Construction and Updating of Event Models in Auditory Event Processing

    Science.gov (United States)

    Huff, Markus; Maurer, Annika E.; Brich, Irina; Pagenkopf, Anne; Wickelmaier, Florian; Papenmeier, Frank

    2018-01-01

    Humans segment the continuous stream of sensory information into distinct events at points of change. Between 2 events, humans perceive an event boundary. Present theories propose changes in the sensory information to trigger updating processes of the present event model. Increased encoding effort finally leads to a memory benefit at event…

  13. Estimate of neutrons event-by-event in DREAM

    International Nuclear Information System (INIS)

    Hauptman, John

    2009-01-01

    We have measured the contribution of neutrons to hadronic showers in the DREAM module event-by-event as a means to estimate the event-by-event fluctuations in binding energy losses by hadrons as they break up nuclei of the Cu absorber. We make a preliminary assessment of the consequences for hadronic energy resolution in dual-readout calorimeters.

  14. Event boundaries and anaphoric reference.

    Science.gov (United States)

    Thompson, Alexis N; Radvansky, Gabriel A

    2016-06-01

    The current study explored the finding that parsing a narrative into separate events impairs anaphor resolution. According to the Event Horizon Model, when a narrative event boundary is encountered, a new event model is created. Information associated with the prior event model is removed from working memory. So long as the event model containing the anaphor referent is currently being processed, this information should still be available when there is no narrative event boundary, even if reading has been disrupted by a working-memory-clearing distractor task. In those cases, readers may reactivate their prior event model, and anaphor resolution would not be affected. Alternatively, comprehension may not be as event oriented as this account suggests. Instead, any disruption of the contents of working memory during comprehension, event related or not, may be sufficient to disrupt anaphor resolution. In this case, reading comprehension would be more strongly guided by other, more basic language processing mechanisms and the event structure of the described events would play a more minor role. In the current experiments, participants were given stories to read in which we included, between the anaphor and its referent, either the presence of a narrative event boundary (Experiment 1) or a narrative event boundary along with a working-memory-clearing distractor task (Experiment 2). The results showed that anaphor resolution was affected by narrative event boundaries but not by a working-memory-clearing distractor task. This is interpreted as being consistent with the Event Horizon Model of event cognition.

  15. Contingency Analysis of Cascading Line Outage Events

    Energy Technology Data Exchange (ETDEWEB)

    Thomas L Baldwin; Magdy S Tawfik; Miles McQueen

    2011-03-01

    As the US power systems continue to increase in size and complexity, including the growth of smart grids, larger blackouts due to cascading outages become more likely. Grid congestion is often associated with a cascading collapse leading to a major blackout. Such a collapse is characterized by a self-sustaining sequence of line outages followed by a topology breakup of the network. This paper addresses the implementation and testing of a process for N-k contingency analysis and sequential cascading outage simulation in order to identify potential cascading modes. A modeling approach described in this paper offers a unique capability to identify initiating events that may lead to cascading outages. It predicts the development of cascading events by identifying and visualizing potential cascading tiers. The proposed approach was implemented using a 328-bus simplified SERC power system network. The results of the study indicate that initiating events and possible cascading chains may be identified, ranked and visualized. This approach may be used to improve the reliability of a transmission grid and reduce its vulnerability to cascading outages.

  16. Nova Event Logging System

    International Nuclear Information System (INIS)

    Calliger, R.J.; Suski, G.J.

    1981-01-01

    Nova is a 200 terawatt, 10-beam High Energy Glass Laser currently under construction at LLNL. This facility, designed to demonstrate the feasibility of laser driven inertial confinement fusion, contains over 5000 elements requiring coordinated control, data acquisition, and analysis functions. The large amounts of data that will be generated must be maintained over the life of the facility. Often the most useful but inaccessible data is that related to time dependent events associated with, for example, operator actions or experiment activity. We have developed an Event Logging System to synchronously record, maintain, and analyze, in part, this data. We see the system as being particularly useful to the physics and engineering staffs of medium and large facilities in that it is entirely separate from experimental apparatus and control devices. The design criteria, implementation, use, and benefits of such a system will be discussed

  17. Event Ticketing Software

    Directory of Open Access Journals (Sweden)

    Maria Cristina ENACHE

    2018-05-01

    Full Text Available The evolution of the virtual world nowadays is an environment more favorable and in full up as regards the evolution of our cultural and technological development. Due to the possibility of online promotion, Internet-based business technology was born, a new, still moving process, representing companies and suppliers of goods and services a unique way to win as many potential customers as possible. The paper analyzes system requirements for online shopping in general and the specific requirements for on-line event ticket sales systems. The paper insists on the critical design and implementation issues for an Event Ticketing System and the potential problems for such a fully automated, high-availability system

  18. Terrorism as Media Event

    Directory of Open Access Journals (Sweden)

    2012-07-01

    Full Text Available Proving that terrorism should be seen as a media event (as defined by Dayan and Katzafter 9/11 and treated accordingly. We have turned to the work of Dayan and Katz and GeorgeGerbner’s for a definition of media events and of violence in the mass media. This paper is ahermeneutical interpretation of the concept of terrorism and its relation to communication. We haveput forward a better understanding of the complex concept of terrorism and its definitions in the massmedia context. Terrorism nowadays should always be defined within its inherent relation with themedia. The article is the first to define terrorism as media evenit in Dayan and Katz’s terms.

  19. The CMS event builder demonstrator and results with Myrinet

    CERN Document Server

    Antchev, G; Cittolin, Sergio; Erhan, S; Faure, B; Gigi, D; Gutleber, J; Jacobs, C; Meijers, F; Meschi, E; Ninane, A; Orsini, L; Pollet, Lucien; Rácz, A; Samyn, D; Schleifer, W; Sinanis, N; Sphicas, Paris

    2001-01-01

    The data acquisition system for the CMS experiment at the Large Hadron Collider (LHC) will require a large and high performance event building network. Several switch technologies are currently being evaluated in order to compare different architectures for the event builder. One candidate is Myrinet. This paper describes the demonstrator which has been setup to study a small-scale (16*16) event builder based on PCs running Linux connected to Myrinet and Ethernet switches. A detailed study of the Myrinet switch performance has been performed for various traffic conditions, including the behaviour of composite switches. Results from event building studies are presented, including measurements on throughput, overhead and scaling. Traffic shaping techniques have been implemented and the effect on the event building performance has been investigated. The paper reports on performances and maximum event rate obtainable using custom software, not described, for the Myrinet control program and the low-level communica...

  20. Traumatic-event headaches

    Directory of Open Access Journals (Sweden)

    Haas David C

    2004-10-01

    Full Text Available Abstract Background Chronic headaches from head trauma and whiplash injury are well-known and common, but chronic headaches from other sorts of physical traumas are not recognized. Methods Specific information was obtained from the medical records of 15 consecutive patients with chronic headaches related to physically injurious traumatic events that did not include either head trauma or whiplash injury. The events and the physical injuries produced by them were noted. The headaches' development, characteristics, duration, frequency, and accompaniments were recorded, as were the patients' use of pain-alleviative drugs. From this latter information, the headaches were classified by the diagnostic criteria of the International Headache Society as though they were naturally-occurring headaches. The presence of other post-traumatic symptoms and litigation were also recorded. Results The intervals between the events and the onset of the headaches resembled those between head traumas or whiplash injuries and their subsequent headaches. The headaches themselves were, as a group, similar to those after head trauma and whiplash injury. Thirteen of the patients had chronic tension-type headache, two had migraine. The sustained bodily injuries were trivial or unidentifiable in nine patients. Fabrication of symptoms for financial remuneration was not evident in these patients of whom seven were not even seeking payments of any kind. Conclusions This study suggests that these hitherto unrecognized post-traumatic headaches constitute a class of headaches characterized by a relation to traumatic events affecting the body but not including head or whiplash traumas. The bodily injuries per se can be discounted as the cause of the headaches. So can fabrication of symptoms for financial remuneration. Altered mental states, not systematically evaluated here, were a possible cause of the headaches. The overall resemblance of these headaches to the headaches after

  1. Sport event marketing plan

    Directory of Open Access Journals (Sweden)

    Gašović Milan

    2007-01-01

    Full Text Available A marketing plan details how an event organization will compete in the marketplace in terms of its service offerings, promotions and evaluation. During the first stage of the marketing plan process, a number of its consumers (current, former and prospective and competitors. Marketing objectives are developed and implemented using an action plan. The marketing plan objectives are evaluated using an objective-discrepancy approach to determine the extent to which they were attained.

  2. Intercorporate Security Event Correlation

    Directory of Open Access Journals (Sweden)

    D. O. Kovalev

    2010-03-01

    Full Text Available Security controls are prone to false positives and false negatives which can lead to unwanted reputation losses for the bank. The reputational database within the security operations center (SOC and intercorporate correlation of security events are offered as a solution to increase attack detection fidelity. The theses introduce the definition and structure of the reputation, architectures of reputational exchange and the place of intercorporate correlation in overall SOC correlation analysis.

  3. The Design and Analysis of Virtual Network Configuration for a Wireless Mobile ATM Network

    OpenAIRE

    Bush, Stephen F.

    1999-01-01

    This research concentrates on the design and analysis of an algorithm referred to as Virtual Network Configuration (VNC) which uses predicted future states of a system for faster network configuration and management. VNC is applied to the configuration of a wireless mobile ATM network. VNC is built on techniques from parallel discrete event simulation merged with constraints from real-time systems and applied to mobile ATM configuration and handoff. Configuration in a mobile network is a dyna...

  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. LHCb Event display

    CERN Document Server

    Trisovic, Ana

    2014-01-01

    The LHCb Event Display was made for educational purposes at the European Organization for Nuclear Research, CERN in Geneva, Switzerland. The project was implemented as a stand-alone application using C++ and ROOT, a framework developed by CERN for data analysis. This paper outlines the development and architecture of the application in detail, as well as the motivation for the development and the goals of the exercise. The application focuses on the visualization of events recorded by the LHCb detector, where an event represents a set of charged particle tracks in one proton-proton collision. Every particle track is coloured by its type and can be selected to see its essential information such as mass and momentum. The application allows students to save this information and calculate the invariant mass for any pair of particles. Furthermore, the students can use additional calculating tools in the application and build up a histogram of these invariant masses. The goal for the students is to find a $D^0$ par...

  6. Securing Major Events

    International Nuclear Information System (INIS)

    Loeoef, Susanna

    2013-01-01

    When asked why the IAEA should provide nuclear security support to countries that organize large public events, Nuclear Security Officer Sophia Miaw answers quickly and without hesitation. ''Imagine any major public event such as the Olympics, a football championship, or an Expo. If a dirty bomb were to be exploded at a site where tens of thousands of people congregate, the radioactive contamination would worsen the effects of the bomb, increase the number of casualties, impede a rapid emergency response, and cause long term disruption in the vicinity,'' she said. Avoiding such nightmarish scenarios is the driving purpose behind the assistance the IAEA offers States that host major sporting or other public events. The support can range from a single training course to a comprehensive programme that includes threat assessment, training, loaned equipment and exercises. The type and scope of assistance depends on the host country's needs. ''We incorporate nuclear security measures into their security plan. We don't create anything new,'' Miaw said

  7. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimise the management of the Technical Network (TN), to facilitate understanding of the purpose of devices connected to the TN and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive e-mails from IT/CS asking them to add the corresponding information in the network database at "network-cern-ch". Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  8. Temporal motifs in time-dependent networks

    International Nuclear Information System (INIS)

    Kovanen, Lauri; Karsai, Márton; Kaski, Kimmo; Kertész, János; Saramäki, Jari

    2011-01-01

    Temporal networks are commonly used to represent systems where connections between elements are active only for restricted periods of time, such as telecommunication, neural signal processing, biochemical reaction and human social interaction networks. We introduce the framework of temporal motifs to study the mesoscale topological–temporal structure of temporal networks in which the events of nodes do not overlap in time. Temporal motifs are classes of similar event sequences, where the similarity refers not only to topology but also to the temporal order of the events. We provide a mapping from event sequences to coloured directed graphs that enables an efficient algorithm for identifying temporal motifs. We discuss some aspects of temporal motifs, including causality and null models, and present basic statistics of temporal motifs in a large mobile call network

  9. Information Operations Innovation Network (IOIN) Demonstration

    National Research Council Canada - National Science Library

    Choo, Vic; Scheiderich, Louis

    2006-01-01

    ...; and Supplement existing/future network defense tools with additional capabilities. The actual software packages used for this effort include VIAasst, VisAlert, Flexviewer, Event Correlation for Cyber Attack Recognition (ECCARS...

  10. Spatial networks

    Science.gov (United States)

    Barthélemy, Marc

    2011-02-01

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

  11. Network science

    CERN Document Server

    Barabasi, Albert-Laszlo

    2016-01-01

    Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network sci...

  12. Vulnerability of network of networks

    Science.gov (United States)

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

    2014-10-01

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

  13. Deploying temporary networks for upscaling of sparse network stations

    Science.gov (United States)

    Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

    2016-10-01

    Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

  14. The International Nuclear Event Scale (INES) user's manual. 2001 edition

    International Nuclear Information System (INIS)

    2001-12-01

    The International Nuclear Event Scale (INES) was introduced in March 1990 jointly by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development (OECD/NEA). Its primary purpose is to facilitate communication and understanding between the nuclear community, the media and the public on the safety significance of events occurring at nuclear installations. The scale was refined in 1992 in the light of experience gained and extended to be applicable to any event associated with radioactive material and/or radiation, including the transport of radioactive materials.This edition of the INES User's Manual incorporates experience gained from applying the 1992 version of the scale and the document entitled 'Clarification of Issues Raised'. As such, it replaces those earlier publications. It does not amend the technical basis of the INES rating procedure but is expected to facilitate the task of those who are required to rate the safety significance of events using the INES scale. The INES communication network currently receives and disseminates event information to the INES National Officers of 60 Member States on special Event Rating Forms which represent official information on the events, including the rating. The INES communication process has led each participating country to set up an internal network which ensures that all events are promptly communicated and rated whenever they have to be reported outside or inside the country. The IAEA provides training services on the use of INES on request

  15. INES - The International Nuclear Event Scale. User's manual

    International Nuclear Information System (INIS)

    2005-01-01

    The International Nuclear Event Scale (INES) was introduced in March 1990 jointly by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development (OECD/NEA). Its primary purpose is to facilitate communication and understanding between the nuclear community, the media and the public on the safety significance of events occurring at nuclear installations. The scale was refined in 1992 in the light of experience gained and extended to be applicable to any event associated with radioactive material and/or radiation, including the transport of radioactive materials. This edition of the INES User's Manual incorporates experience gained from applying the 1992 version of the scale and the document entitled 'Clarification of Issues Raised'. As such, it replaces those earlier publications. It does not amend the technical basis of the INES rating procedure but is expected to facilitate the task of those who are required to rate the safety significance of events using the INES scale. The INES communication network currently receives and disseminates event information to the INES National Officers of 60 Member States on special Event Rating Forms which represent official information on the events, including the rating. The INES communication process has led each participating country to set up an internal network which ensures that all events are promptly communicated and rated whenever they have to be reported outside or inside the country. The IAEA provides training services on the use of INES on request

  16. The International Nuclear Event Scale (INES) user's manual. 2001 edition

    International Nuclear Information System (INIS)

    2001-02-01

    The International Nuclear Event Scale (INES) was introduced in March 1990 jointly by the International Atomic Energy Agency (IAEA) and the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development (OECD/NEA). Its primary purpose is to facilitate communication and understanding between the nuclear community, the media and the public on the safety significance of events occurring at nuclear installations. The scale was refined in 1992 in the light of experience gained and extended to be applicable to any event associated with radioactive material and/or radiation, including the transport of radioactive materials.This edition of the INES User's Manual incorporates experience gained from applying the 1992 version of the scale and the document entitled ''Clarification of Issues Raised''. As such, it replaces those earlier publications. It does not amend the technical basis of the INES rating procedure but is expected to facilitate the task of those who are required to rate the safety significance of events using the INES scale. The INES communication network currently receives and disseminates event information to the INES National Officers of 60 Member States on special Event Rating Forms which represent official information on the events, including the rating. The INES communication process has led each participating country to set up an internal network which ensures that all events are promptly communicated and rated whenever they have to be reported outside or inside the country. The IAEA provides training services on the use of INES on request

  17. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  18. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Hansen, Jonas; Roetter, Daniel Enrique Lucani; Krigslund, Jeppe

    2015-01-01

    Software defined networking has garnered large attention due to its potential to virtualize services in the Internet, introducing flexibility in the buffering, scheduling, processing, and routing of data in network routers. SDN breaks the deadlock that has kept Internet network protocols stagnant...... for decades, while applications and physical links have evolved. This article advocates for the use of SDN to bring about 5G network services by incorporating network coding (NC) functionalities. The latter constitutes a major leap forward compared to the state-of-the- art store and forward Internet paradigm...

  19. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  20. Communication and control for networked complex systems

    CERN Document Server

    Peng, Chen; Han, Qing-Long

    2015-01-01

    This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

  1. Discrete-Event Simulation

    OpenAIRE

    Prateek Sharma

    2015-01-01

    Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of ev...

  2. LIU 2011 event

    CERN Multimedia

    BE Department

    2011-01-01

    The LHC injectors upgrade (LIU) project was launched at the end of 2010 to coordinate the preparation of the CERN accelerator complex to meet the needs of the High Luminosity LHC (HL-LHC) until at least 2030. It should be completed by the end of the second long LHC shutdown, presently scheduled for 2018.   The goal of the LIU-2011 event is to present the status and plans of the LIU project, describing the needs and the actions foreseen in the different accelerators, from Linac4 to the PSB, PS and SPS.  

  3. CATASTROPHIC EVENTS MODELING

    Directory of Open Access Journals (Sweden)

    Ciumas Cristina

    2013-07-01

    Full Text Available This paper presents the emergence and evolution of catastrophe models (cat models. Starting with the present context of extreme weather events and features of catastrophic risk (cat risk we’ll make a chronological illustration from a theoretical point of view of the main steps taken for building such models. In this way the importance of interdisciplinary can be observed. The first cat model considered contains three modules. For each of these indentified modules: hazard, vulnerability and financial losses a detailed overview and also an exemplification of a potential case of an earthquake that measures more than 7 on Richter scale occurring nowadays in Bucharest will be provided. The key areas exposed to earthquake in Romania will be identified. Then, based on past catastrophe data and taking into account present conditions of housing stock, insurance coverage and the population of Bucharest the impact will be quantified by determining potential losses. In order to accomplish this work we consider a scenario with data representing average values for: dwelling’s surface, location, finishing works. On each step we’ll make a reference to the earthquake on March 4 1977 to see what would happen today if a similar event occurred. The value of Bucharest housing stock will be determined taking firstly the market value, then the replacement value and ultimately the real value to quantify potential damages. Through this approach we can find the insurance coverage of potential losses and also the uncovered gap. A solution that may be taken into account by public authorities, for example by Bucharest City Hall will be offered: in case such an event occurs the impossibility of paying compensations to insured people, rebuilding infrastructure and public buildings and helping the suffering persons should be avoided. An actively public-private partnership should be created between government authorities, the Natural Disaster Insurance Pool, private

  4. PERSON IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Андрей Борисович Шалимов

    2013-11-01

    Full Text Available Purpose: Our scientific purpose is creation of practical model of person’s representation in social networks (Facebook, Twitter, Classmates. As user of social networks, person is made conditional not only upon its own identity, but also upon the information about himself, which he is ready to share with his friends in contact list. Goal-setting and practical activities for their achievement mean that you should apply force, it can completely eliminates systemic factors, the system of power relations, which overwhelms human being in social networks.Methodology: The reconstruction of the model of human in the popularity of social networksResults: There is descripton of practical model of person's representation in social networks, it includes the management of own identity and the audience (the list of contacts. When person manages own identity, he answers the question, «Whom I can dare to be?». Person perceives himself in social networks' being, he understands himself and his place in the world, he identifies.Managing the way in social media means that you answer the question «What I want to tell?». Person in social media looks at events in the field of culture, economy, politics, social relations through the prism of his own attitudes, he forms and formulates his own agenda and he is going to tell about himself through them.Practical implications: Everyday people’s life, practical activities, including marketing in social networks.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-51

  5. Event storm detection and identification in communication systems

    International Nuclear Information System (INIS)

    Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

    2006-01-01

    Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

  6. Offline analysis of HEP events by ''dynamic perceptron'' neural network

    International Nuclear Information System (INIS)

    Perrone, A.L.; Basti, G.; Messi, R.; Pasqualucci, E.; Paoluzi, L.

    1997-01-01

    In this paper we start from a critical analysis of the fundamental problems of the parallel calculus in linear structures and of their extension to the partial solutions obtained with non-linear architectures. Then, we present shortly a new dynamic architecture able to solve the limitations of the previous architectures through an automatic re-definition of the topology. This architecture is applied to real-time recognition of particle tracks in high-energy accelerators. (orig.)

  7. A Framework for Event Prioritization in Cyber Network Defense

    Science.gov (United States)

    2014-07-15

    to use it by replacing the commands with divisions (e.g., human resources, payroll , R&D) within its organization, and having a table that translates...Attribute Decision Making: An Introduction (Quantitative Applications in the Social Sciences), SAGE Publications, Inc, 1995. [21] G.-H. Tzeng and...and be considered more critical than others, such as a host machine in the human resources department that contains payroll information. We map the

  8. Detection of Incidents and Events in Urban Networks

    NARCIS (Netherlands)

    Thomas, Tom; van Berkum, Eric C.; ITS,

    2008-01-01

    Although there is a large variation in traffic flow patterns, we can distinguish two main types: recurrent and non-recurrent patterns. A recurrent pattern repeats itself with a known period and is therefore predictable. An example is the rush hour peak, but also the peak in travel demand which is

  9. Discrete Event Command & Control for Networked Teams with Multiple Missions

    Science.gov (United States)

    2009-03-16

    Architecture for Unmanned Ground Systems ( JAUGS )10, and is an efficient means to realize the high-level OODA loops (observe, orient, decide, act) of 4D...for Unmanned Ground systems ( JAUGS )10, and is an efficient means to realize the OODA loops (observe, orient, decide, act) of 4D/RCS11. DEC is able to

  10. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

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

  11. Mathematical foundations of event trees

    International Nuclear Information System (INIS)

    Papazoglou, Ioannis A.

    1998-01-01

    A mathematical foundation from first principles of event trees is presented. The main objective of this formulation is to offer a formal basis for developing automated computer assisted construction techniques for event trees. The mathematical theory of event trees is based on the correspondence between the paths of the tree and the elements of the outcome space of a joint event. The concept of a basic cylinder set is introduced to describe joint event outcomes conditional on specific outcomes of basic events or unconditional on the outcome of basic events. The concept of outcome space partition is used to describe the minimum amount of information intended to be preserved by the event tree representation. These concepts form the basis for an algorithm for systematic search for and generation of the most compact (reduced) form of an event tree consistent with the minimum amount of information the tree should preserve. This mathematical foundation allows for the development of techniques for automated generation of event trees corresponding to joint events which are formally described through other types of graphical models. Such a technique has been developed for complex systems described by functional blocks and it is reported elsewhere. On the quantification issue of event trees, a formal definition of a probability space corresponding to the event tree outcomes is provided. Finally, a short discussion is offered on the relationship of the presented mathematical theory with the more general use of event trees in reliability analysis of dynamic systems

  12. ENERGY EFFICIENCY AND ROUTING IN SENSOR NETWORKS

    DEFF Research Database (Denmark)

    Cetin, Bilge Kartal

    -hoc networks, recharging or replacing of the sen- sors battery may be inconvenient, or even impossible in some monitoring environments. Therefore, the key challenge in the design of wireless sen- sor network protocols is how to maximize the network lifetime, which is limited by battery energy in sensor nodes......, while providing the application requirement. In sensor networks, there are two important energy consuming pro- cesses, the rst is transmission-reception phase and the second is listening the radio for any possible event. Therefore, there are two strategies for en- ergy saving. The rst is reducing...... for dierent network parameters is de- veloped by considering a duty-cycling mechanism in the network. Upper bound on network lifetime is sought by considering idle and sleep mode energy consumption as well as energy consumption in transmission and reception for sensor networks. The solution of the developed...

  13. Event Shape Sorting: selecting events with similar evolution

    Directory of Open Access Journals (Sweden)

    Tomášik Boris

    2017-01-01

    Full Text Available We present novel method for the organisation of events. The method is based on comparing event-by-event histograms of a chosen quantity Q that is measured for each particle in every event. The events are organised in such a way that those with similar shape of the Q-histograms end-up placed close to each other. We apply the method on histograms of azimuthal angle of the produced hadrons in ultrarelativsitic nuclear collisions. By selecting events with similar azimuthal shape of their hadron distribution one chooses events which are likely that they underwent similar evolution from the initial state to the freeze-out. Such events can more easily be compared to theoretical simulations where all conditions can be controlled. We illustrate the method on data simulated by the AMPT model.

  14. Achieving High Resolution Timer Events in Virtualized Environment.

    Science.gov (United States)

    Adamczyk, Blazej; Chydzinski, Andrzej

    2015-01-01

    Virtual Machine Monitors (VMM) have become popular in different application areas. Some applications may require to generate the timer events with high resolution and precision. This however may be challenging due to the complexity of VMMs. In this paper we focus on the timer functionality provided by five different VMMs-Xen, KVM, Qemu, VirtualBox and VMWare. Firstly, we evaluate resolutions and precisions of their timer events. Apparently, provided resolutions and precisions are far too low for some applications (e.g. networking applications with the quality of service). Then, using Xen virtualization we demonstrate the improved timer design that greatly enhances both the resolution and precision of achieved timer events.

  15. The NASA Fireball Network Database

    Science.gov (United States)

    Moser, Danielle E.

    2011-01-01

    The NASA Meteoroid Environment Office (MEO) has been operating an automated video fireball network since late-2008. Since that time, over 1,700 multi-station fireballs have been observed. A database containing orbital data and trajectory information on all these events has recently been compiled and is currently being mined for information. Preliminary results are presented here.

  16. International Symposium on Ubiquitous Networking

    CERN Document Server

    Medromi, Hicham; Sadik, Mohamed

    2016-01-01

    This volume publishes new trends and findings in hot topics related to ubiquitous computing/networking. It is the outcome of UNet - ainternational scientific event that took place on September 08-10, 2015, in the fascinating city of Casablanca, Morocco. UNet’15 is technically sponsored by IEEE Morocco Section and IEEE COMSOC Morocco Chapter.

  17. Network security

    CERN Document Server

    Perez, André

    2014-01-01

    This book introduces the security mechanisms deployed in Ethernet, Wireless-Fidelity (Wi-Fi), Internet Protocol (IP) and MultiProtocol Label Switching (MPLS) networks. These mechanisms are grouped throughout the book according to the following four functions: data protection, access control, network isolation, and data monitoring. Data protection is supplied by data confidentiality and integrity control services. Access control is provided by a third-party authentication service. Network isolation is supplied by the Virtual Private Network (VPN) service. Data monitoring consists of applying

  18. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago V. V.; Giannitsarou, Chryssi; Johnson, Charles R.

    2016-01-01

    This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00199-016-0992-1 We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and d...

  19. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimize the management of the Technical Network (TN), to ease the understanding and purpose of devices connected to the TN, and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive email notifications from IT/CS asking them to add the corresponding information in the network database. Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  20. Corporate Social Networking: Risks and Opportunities

    OpenAIRE

    Straumsheim, Jan Henrik Schou

    2011-01-01

    Social networks have seen an explosive growth over the last few years, with the most popular online services totaling over half a billion users. These networks have started permeating several aspects of our daily lives: for example by changing the ways we communicate with our friends and family, share media and organize events. Popular social networking websites like Facebook and Twitter now account for over half of the content shared on the web. Norwegian businesses are taking note, and are ...