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.

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.

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.

Zoology: Molluscs All Beneath the Sun, One Shell, Two Shells, More, or None.

Science.gov (United States)

Sigwart, Julia D

2017-07-24

One great remaining problem in evolutionary biology is to understand which common ancestor could have given rise to descendants as different as giant squid and microscopic pea clams. Two new papers provide important insights into molluscan body plan disparity. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

The necessity of recognizing all events in X-ray detection.

Science.gov (United States)

Papp, T; Maxwell, J A; Papp, A T

2010-01-01

In our work in studying properties of inner shell ionization, we are troubled that the experimental data used to determine the basic parameters of X-ray physics have a large and unexplainable scatter. As we looked into the problems we found that many of them contradict simple logic, elemental arithmetic, even parity and angular momentum conservation laws. We have identified that the main source of the problems, other than the human factor, is rooted in the signal processing electronics. To overcome these problems we have developed a fully digital signal processor, which not only has excellent resolution and line shape, but also allows proper accounting of all events. This is achieved by processing all events and separating them into two or more spectra (maximum 16), where the first spectrum is the accepted or good spectrum and the second spectrum is the spectrum of all rejected events. The availability of all the events allows one to see the other part of the spectrum. To our surprise the total information explains many of the shortcomings and contradictions of the X-ray database. The data processing methodology cannot be established on the partial and fractional information offered by other approaches. Comparing Monte Carlo detector modeling results with the partial spectra is ambiguous. It suggests that the metrology of calibration by radioactive sources as well as other X-ray measurements could be improved by the availability of the proper accounting of all events. It is not enough to know that an event was rejected and increment the input counter, it is necessary to know, what was rejected and why it happened, whether it was a noise or a disturbed event, a retarded event or a true event, or any pile up combination of these events. Such information is supplied by our processor reporting the events rejected by each discriminator in separate spectra. Several industrial applications of this quality assurance capable signal processor are presented. Copyright 2009

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

77 FR 70428 - Bar None Ranch LLC; Notice of Declaration of Intention and Soliciting Comments, Protests, and/or...

Science.gov (United States)

2012-11-26

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. DI13-2-000] Bar None Ranch LLC; Notice of Declaration of Intention and Soliciting Comments, Protests, and/or Motions To Intervene...: November 2, 2012. d. Applicant: Bar None Ranch LLC. e. Name of Project: Snodgrass Springs Micro Hydro...

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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

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.

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.

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.

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.

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

Computing all hybridization networks for multiple binary phylogenetic input trees.

Science.gov (United States)

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

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.

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.

Detection and localization of crosstalk in an all-optical network

International Nuclear Information System (INIS)

Jedidi, Ahmed; Abid, Mohamed; Rejeb, Ridha

2011-01-01

The all-optical network (AON) has been considered as promising technology for next-generation optical networks. AONs are attractive because they promise very high rates, flexible switching and broad application support. However, AONs are susceptible to malicious attacks as the signals remain in the optical domain within the network and are difficult to monitor closely. One of the serious problems with AONs is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole network may be more nefarious than a single point of crosstalk. Crosstalk attacks can spread rapidly through the network, causing additional awkward failures and triggering multiple undesirable alarms. Therefore, these attacks must be detected and identified at any point in the network where they may occur. This results in the continuous monitoring and identification of the impairments becoming challenging in the event of transmission failures. This paper proposes a novel approach for detecting and localizing crosstalk in AONs, offering the benefit of relaxing the high cost and management complexity

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

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.

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.

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

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.)

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.

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.

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.

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

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.

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

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.

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

A Book for None? Teaching Biblical Studies to Millennial Nones

Science.gov (United States)

Reed, Randall

2016-01-01

The millennial generation is distinctive for several reasons, not the least is its growing religious disaffiliation. Given a growing disinterest in religion in general and the Bible in particular especially among the fast growing group of millennial "nones" how can biblical studies classes still be seen as appealing and relevant? This…

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).

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.

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.

An improved algorithm for searching all minimal cuts in modified networks

International Nuclear Information System (INIS)

Yeh, W.-C.

2008-01-01

A modified network is an updated network after inserting a branch string (a special path) between two nodes in the original network. Modifications are common for network expansion or reinforcement evaluation and planning. The problem of searching all minimal cuts (MCs) in a modified network is discussed and solved in this study. The existing best-known methods for solving this problem either needed extensive comparison and verification or failed to solve some special but important cases. Therefore, a more efficient, intuitive and generalized method for searching all MCs without an extensive research procedure is proposed. In this study, we first develop an intuitive algorithm based upon the reformation of all MCs in the original network to search for all MCs in a modified network. Next, the correctness of the proposed algorithm will be analyzed and proven. The computational complexity of the proposed algorithm is analyzed and compared with the existing best-known methods. Finally, two examples illustrate how all MCs are generated in a modified network using the information of all of the MCs in the corresponding original network

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

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

Local seismic network at the Olkiluoto site. Annual report 2002-2004

Energy Technology Data Exchange (ETDEWEB)

Saari, J. [Enprima Oy, Vantaa (Finland)

2005-09-15

In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. In the beginning, the network consisted of six seismic stations. Later, in June 2004, the seismic network was expanded with two new seismic stations. At that time started the excavation of the underground characterisation facility (the ONKALO) and the basic operation procedure was changed more suitable for the demands of the new situation. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. This report gives the results of microseismic monitoring during the years 2002 - 2004. Also the changes in the structure and the operation procedure of the network are described. The network has operated nearly continuously. The longest interruption occurred 16.-17.6.2004, when two new seismic stations were installed in the network and the operation procedure was changed. Altogether 757 events have been located in the Olkiluoto area. The magnitudes of the observed events range from ML = -3.5 to ML = 1.2. All of them are explosions or other artificial events. So far, none of the 757 observed events can be classified as microearthquakes. Five of the events have characteristics that make the origin of the recorded signal uncertain. They are quite unlikely microearthquakes, but they are not typical examples of artificial seismic signals either. When the experience and the data set of the Olkiluoto microearthquakes increase the identification of events will be more definite. Evidence of activity that would has influence on the safety of the ONKALO, have not found. (orig.)

Local seismic network at the Olkiluoto site. Annual report 2002-2004

International Nuclear Information System (INIS)

Saari, J.

2005-09-01

In Olkiluoto, Posiva Oy has operated a local seismic network since February 2002. In the beginning, the network consisted of six seismic stations. Later, in June 2004, the seismic network was expanded with two new seismic stations. At that time started the excavation of the underground characterisation facility (the ONKALO) and the basic operation procedure was changed more suitable for the demands of the new situation. The purpose of the microearthquake measurements at Olkiluoto is to improve understanding of the structure, behaviour and long term stability of the bedrock. The studies include both tectonic and excavation-induced microearthquakes. An additional task of monitoring is related to safeguarding of the ONKALO. This report gives the results of microseismic monitoring during the years 2002 - 2004. Also the changes in the structure and the operation procedure of the network are described. The network has operated nearly continuously. The longest interruption occurred 16.-17.6.2004, when two new seismic stations were installed in the network and the operation procedure was changed. Altogether 757 events have been located in the Olkiluoto area. The magnitudes of the observed events range from ML = -3.5 to ML = 1.2. All of them are explosions or other artificial events. So far, none of the 757 observed events can be classified as microearthquakes. Five of the events have characteristics that make the origin of the recorded signal uncertain. They are quite unlikely microearthquakes, but they are not typical examples of artificial seismic signals either. When the experience and the data set of the Olkiluoto microearthquakes increase the identification of events will be more definite. Evidence of activity that would has influence on the safety of the ONKALO, have not found. (orig.)

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

None

OpenAIRE

杉田 健一郎; Dershowitz, W.

2005-01-01

During Heisei-16, Golder Associates provided support for JNC Tokai through discrete fracture network data analysis and simulation of the Mizunami Underground Research Laboratory (MIU), participation in Task 6 of the Aspo Task Force on Modeling of Groundwater Flow and Transport, and development of methodologies for analysis of repository site characterization strategies and safety assessment. MIU support during H-16 involved updating the H-15 FracMan discrete fracture network (DFN) models for ...

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 .

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)

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)

Divisible Atoms or None at All? Facing the European Contributions to Developments of Chemistry and Physics in China.

Science.gov (United States)

Južnič, Stanislav

2016-12-01

One of the most important Mid-European professor with more than six thousand academic descendants was the leading Slovenian erudite Jurij Vega. In broader sense, Vega's and other applied sciences of the south of Holy Roman Empire of German Nationality were connected with the mercury mine of Idrija during the last half of millennia. The Idrija Mine used to be one of the two top European producers of mercury, the basic substance of atomistic alchemists. Idrija Mine contributions to the history of techniques, their examinations and approbations is comparable to the other Mid-European achievements. The peculiarities of Idrija mining environment where people valued mostly the applicative knowhow is put into the limelight. The applicative abilities of Idrija employers affected the broader surroundings including Vega's Jesuit teachers in nearby Ljubljana and the phenomena of comparatively many China-Based Jesuits connected with the area of modern Slovenia. The Jesuits' Mid-European education and networks are put into the limelight, as well as their adopted Chinese networks used for their bridging between Eastern and Western Sciences. The Western origin of the scientific-technologic-industrial revolution(s) with causes for their apparent nonexistence in Chinese frames is discussed as another Eurocentric rhetorical racist question which presumes the scientific-technologic-industrial revolution(s) as something good, positive, and therefore predominantly European. The Chinese ways into progress without those troublemaking revolutions is focused for the first time in historiography from combined scientific, moral, religious, and economic viewpoints. The Chinese contributions to particular areas of research in chemistry and physics is focused to find out the preferences and most frequent stages of (European) paradigms involved in the Chinese networks. Some predictions of future interests of Chinese chemistry and physics are provided. The Chinese Holistic Confucian distrust in

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.

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

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.

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.

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.

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.

The necessity of recognizing all events in x-ray detection

International Nuclear Information System (INIS)

Papp, T.; Maxwell, J.A.; Papp, A.T.

2008-01-01

Full text: In our work in studying properties of inner shell ionization, we stumbled upon the problems that the basic parameters of x-ray physics have a large and unexplainable scatter. If we look deep into the problems many of them contradict simple logic, elemental arithmetic, even parity and angular conservation laws. We have identified that the main source of the problems, other than the human factor, is rooted in the signal processing electronics. To overcome these problems, we have developed a fully digital signal processor, which not only has excellent resolution and line shape but also allows proper accounting. It is achieved by processing all events and separating them into two or more spectra, maximum sixteen, where the first spectrum is the accepted or good spectrum and the second spectrum is the rejected spectrum. Depending on the request of the analysis further spectra can be generated to supply all the information needed for the analysis. It is not enough to know that an event was rejected, and increment the input counter, it is necessary to know, what why and when it happened, whether it was a noise, noisy or disturbed event, or an event, and any pile up combination of them, accounting properly as input and at the dead time as well. This can be determined from the spectra of properly processed rejected events. We will demonstrate that the direct comparison of the results of the detector simulation model with a partial spectrum, what the various signal recognition and discrimination methods of the signal processor have created, is ambiguous. We will present the difference between pile up and sum peaks, demonstrate the proper accounting of pile up, dead time and what compromises are made in general to warrant the good resolution. We will demonstrate why it is mandatory to recognize all the events, how to interpret the rejected spectrum, what advantage it has in training the industrial analyst, and how it reduces the demands for human expertise in x

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}.

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.

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.

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)

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.

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.

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.

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.

Cisco Networking All-in-One For Dummies

CERN Document Server

Tetz, Edward

2011-01-01

A helpful guide on all things Cisco Do you wish that the complex topics of routers, switches, and networking could be presented in a simple, understandable presentation? With Cisco Networking All-in-One For Dummies, they are! This expansive reference is packed with all the information you need to learn to use Cisco routers and switches to develop and manage secure Cisco networks. This straightforward-by-fun guide offers expansive coverage of Cisco and breaks down intricate subjects such as networking, virtualization, and database technologies into easily digestible pieces. Drills down complex

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

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.

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.

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.

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...

Metropolitan all-pass and inter-city quantum communication network.

Science.gov (United States)

Chen, Teng-Yun; Wang, Jian; Liang, Hao; Liu, Wei-Yue; Liu, Yang; Jiang, Xiao; Wang, Yuan; Wan, Xu; Cai, Wei-Qi; Ju, Lei; Chen, Luo-Kan; Wang, Liu-Jun; Gao, Yuan; Chen, Kai; Peng, Cheng-Zhi; Chen, Zeng-Bing; Pan, Jian-Wei

2010-12-20

We have demonstrated a metropolitan all-pass quantum communication network in field fiber for four nodes. Any two nodes of them can be connected in the network to perform quantum key distribution (QKD). An optical switching module is presented that enables arbitrary 2-connectivity among output ports. Integrated QKD terminals are worked out, which can operate either as a transmitter, a receiver, or even both at the same time. Furthermore, an additional link in another city of 60 km fiber (up to 130 km) is seamless integrated into this network based on a trusted relay architecture. On all the links, we have implemented protocol of decoy state scheme. All of necessary electrical hardware, synchronization, feedback control, network software, execution of QKD protocols are made by tailored designing, which allow a completely automatical and stable running. Our system has been put into operation in Hefei in August 2009, and publicly demonstrated during an evaluation conference on quantum network organized by the Chinese Academy of Sciences on August 29, 2009. Real-time voice telephone with one-time pad encoding between any two of the five nodes (four all-pass nodes plus one additional node through relay) is successfully established in the network within 60 km.

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.

Habitual sleep duration and insomnia and the risk of cardiovascular events and all-cause death: report from a community-based cohort.

Science.gov (United States)

Chien, Kuo-Liong; Chen, Pei-Chung; Hsu, Hsiu-Ching; Su, Ta-Chen; Sung, Fung-Chang; Chen, Ming-Fong; Lee, Yuan-Teh

2010-02-01

To investigate the relationship between sleep duration and insomnia severity and the risk of all-cause death and cardiovascular disease (CVD) events. Prospective cohort study. Community-based. A total of 3,430 adults aged 35 years or older. None. During a median 15.9 year (interquartile range, 13.1 to 16.9) follow-up period, 420 cases developed cardiovascular disease and 901 cases died. A U-shape association between sleep duration and all-cause death was found: the age and gender-adjusted relative risks (95% confidence interval [CI]) of all-cause death (with 7 h of daily sleep being considered for the reference group) for individuals reporting or = 9 h were 1.15 (0.91-1.45), 1.02 (0.85-1.25), 1.05 (0.88-1.27), and 1.43 (1.16-1.75); P for trend, 0.019. However, the relationship between sleep duration and risk of CVD were linear. The multivariate-adjusted relative risk (95% CI) for all-cause death (using individuals without insomnia) were 1.02 (0.86-1.20) for occasional insomnia, 1.15 (0.92-1.42) for frequent insomnia, and 1.70 (1.16-2.49) for nearly everyday insomnia (P for trend, 0.028). The multivariate adjusted relative risk (95% CI) was 2.53 (1.71-3.76) for all-cause death and 2.07 (1.11-3.85) for CVD rate in participants sleeping > or = 9 h and for those with frequent insomnia. Sleep duration and insomnia severity were associated with all-cause death and CVD events among ethnic Chinese in Taiwan. Our data indicate that an optimal sleep duration (7-8 h) predicted fewer deaths.

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)

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

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.

A kinematic fit method for all-photon events

International Nuclear Information System (INIS)

Du Shuxian; Yuan Changzheng; Chinese Academy of Sciences, Beijing

2006-01-01

An improved kinematic fit method is developed for analyzing all-photon events, where the interaction point is unknown. The fitting algorithm is checked with Monte Carlo samples to ensure that the fitting program works properly. This is applied to the Monte Carlo simulated ψ(2S) decays. A higher efficiency is achieved. This method can be generally applied to analyzing all-photon events at electron-positron collider. (authors)

A study on Optical Labelling Techniques for All-Optical Networks

DEFF Research Database (Denmark)

Holm-Nielsen, Pablo Villanueva

2005-01-01

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

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

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.

Comparative study on individual aromatase inhibitors on cardiovascular safety profile: a network meta-analysis

Science.gov (United States)

Zhao, Xihe; Liu, Lei; Li, Kai; Li, Wusheng; Zhao, Li; Zou, Huawei

2015-01-01

The third-generation aromatase inhibitors (AIs: anastrozole, letrozole, and exemestane) have now become standard adjuvant endocrine treatment for postmenopausal estrogen receptor-positive breast cancer complementing chemotherapy and surgery. Because of the absence of direct head-to-head comparisons of these AIs, an indirect comparison is needed for individual treatment choice. In this network systemic assessment, the cardiovascular (CV) side effects in using anastrozole, letrozole, and exemestane based on original studies on AIs vs placebo or tamoxifen were compared. We integrated all available direct and indirect evidences. The odds ratio (OR) of severe CV events for indirect comparisons between exemestane and anastrozole was 1.41 (95% confidence interval [CI] =0.49–2.78), letrozole and anastrozole was 1.80 (95% CI =0.40–3.92), and letrozole and exemestane was 1.46 (95% CI =0.34–3.4). OR of subgroup risk for AIs and tamoxifen were all >1 except for thrombolism risk subgroup. The results showed that the total and severe CV risk ranking is letrozole, exemestane, and anastrozole in descending order. None of the AIs showed advantages in CV events than tamoxifen except for thromboembolism event incidence. PMID:26491345

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)

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.

High speed all optical networks

Science.gov (United States)

Chlamtac, Imrich; Ganz, Aura

1990-01-01

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

Optimised Design and Analysis of All-Optical Networks

DEFF Research Database (Denmark)

Glenstrup, Arne John

2002-01-01

through various experiments and is shown to produce good results and to be able to scale up to networks of realistic sizes. A novel method, subpath wavelength grouping, for routing connections in a multigranular all-optical network where several wavelengths can be grouped and switched at band and fibre......This PhD thesis presents a suite of methods for optimising design and for analysing blocking probabilities of all-optical networks. It thus contributes methodical knowledge to the field of computer assisted planning of optical networks. A two-stage greenfield optical network design optimiser...... is developed, based on shortest-path algorithms and a comparatively new metaheuristic called simulated allocation. It is able to handle design of all-optical mesh networks with optical cross-connects, considers duct as well as fibre and node costs, and can also design protected networks. The method is assessed...

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.

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.

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…

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.

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.

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

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.

Comparative study on individual aromatase inhibitors on cardiovascular safety profile: a network meta-analysis

Directory of Open Access Journals (Sweden)

Zhao XH

2015-09-01

Full Text Available Xihe Zhao,1 Lei Liu,2 Kai Li,1 Wusheng Li,1 Li Zhao,1 Huawei Zou1 1Department of Oncology, 2Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China Abstract: The third-generation aromatase inhibitors (AIs: anastrozole, letrozole, and exemestane have now become standard adjuvant endocrine treatment for postmenopausal estrogen receptor-positive breast cancer complementing chemotherapy and surgery. Because of the absence of direct head-to-head comparisons of these AIs, an indirect comparison is needed for individual treatment choice. In this network systemic assessment, the cardiovascular (CV side effects in using anastrozole, letrozole, and exemestane based on original studies on AIs vs placebo or tamoxifen were compared. We integrated all available direct and indirect evidences. The odds ratio (OR of severe CV events for indirect comparisons between exemestane and anastrozole was 1.41 (95% confidence interval [CI] =0.49–2.78, letrozole and anastrozole was 1.80 (95% CI =0.40–3.92, and letrozole and exemestane was 1.46 (95% CI =0.34–3.4. OR of subgroup risk for AIs and tamoxifen were all >1 except for thrombolism risk subgroup. The results showed that the total and severe CV risk ranking is letrozole, exemestane, and anastrozole in descending order. None of the AIs showed advantages in CV events than tamoxifen except for thromboembolism event incidence. Keywords: CV risk, breast cancer, AI, network meta-analysis

ISISisNotIslam or DeportAllMuslims?: Predicting Unspoken Views

OpenAIRE

Magdy, Walid; Darwish, Kareem; Abokhodair, Norah; Rahimi, Afshin; Baldwin, Timothy

2016-01-01

This paper examines the effect of online social network interactions on future attitudes. Specifically, we focus on how a person's online content and network dynamics can be used to predict future attitudes and stances in the aftermath of a major event. In this study, we focus on the attitudes of US Twitter users towards Islam and Muslims subsequent to the tragic Paris terrorist attacks that occurred on November 13, 2015. We quantitatively analyze 44K users' network interactions and historica...

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.

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...

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.

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.)

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.

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.

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.

A distributed lumped active all-pass network configuration.

Science.gov (United States)

Huelsman, L. P.; Raghunath, S.

1972-01-01

In this correspondence a new and interesting distributed lumped active network configuration that realizes an all-pass network function is described. A design chart for determining the values of the network elements is included.

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.

Design and optimization of all-optical networks

Science.gov (United States)

Xiao, Gaoxi

1999-10-01

In this thesis, we present our research results on the design and optimization of all-optical networks. We divide our results into the following four parts: 1.In the first part, we consider broadcast-and-select networks. In our research, we propose an alternative and cheaper network configuration to hide the tuning time. In addition, we derive lower bounds on the optimal schedule lengths and prove that they are tighter than the best existing bounds. 2.In the second part, we consider all-optical wide area networks. We propose a set of algorithms for allocating a given number of WCs to the nodes. We adopt a simulation-based optimization approach, in which we collect utilization statistics of WCs from computer simulation and then perform optimization to allocate the WCs. Therefore, our algorithms are widely applicable and they are not restricted to any particular model and assumption. We have conducted extensive computer simulation on regular and irregular networks under both uniform and non-uniform traffic. We see that our method can get nearly the same performance as that of full wavelength conversion by using a much smaller number of WCs. Compared with the best existing method, the results show that our algorithms can significantly reduce (1)the overall blocking probability (i.e., better mean quality of service) and (2)the maximum of the blocking probabilities experienced at all the source nodes (i.e., better fairness). Equivalently, for a given performance requirement on blocking probability, our algorithms can significantly reduce the number of WCs required. 3.In the third part, we design and optimize the physical topology of all-optical wide area networks. We show that the design problem is NP-complete and we propose a heuristic algorithm called two-stage cut saturation algorithm for this problem. Simulation results show that (1)the proposed algorithm can efficiently design networks with low cost and high utilization, and (2)if wavelength converters are

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.

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

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.

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.

An improved algorithm for finding all minimal paths in a network

International Nuclear Information System (INIS)

Bai, Guanghan; Tian, Zhigang; Zuo, Ming J.

2016-01-01

Minimal paths (MPs) play an important role in network reliability evaluation. In this paper, we report an efficient recursive algorithm for finding all MPs in two-terminal networks, which consist of a source node and a sink node. A linked path structure indexed by nodes is introduced, which accepts both directed and undirected form of networks. The distance between each node and the sink node is defined, and a simple recursive algorithm is presented for labeling the distance for each node. Based on the distance between each node and the sink node, additional conditions for backtracking are incorporated to reduce the number of search branches. With the newly introduced linked node structure, the distances between each node and the sink node, and the additional backtracking conditions, an improved backtracking algorithm for searching for all MPs is developed. In addition, the proposed algorithm can be adapted to search for all minimal paths for each source–sink pair in networks consisting of multiple source nodes and/or multiple sink nodes. Through computational experiments, it is demonstrated that the proposed algorithm is more efficient than existing algorithms when the network size is not too small. The proposed algorithm becomes more advantageous as the size of the network grows. - Highlights: • A linked path structure indexed by nodes is introduced to represent networks. • Additional conditions for backtracking are proposed based on the distance of each node. • An efficient algorithm is developed to find all MPs for two-terminal networks. • The computational efficiency of the algorithm for two-terminal networks is investigated. • The computational efficiency of the algorithm for multi-terminal networks is investigated.

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.

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.

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

Analytic 3D image reconstruction using all detected events

International Nuclear Information System (INIS)

Kinahan, P.E.; Rogers, J.G.

1988-11-01

We present the results of testing a previously presented algorithm for three-dimensional image reconstruction that uses all gamma-ray coincidence events detected by a PET volume-imaging scanner. By using two iterations of an analytic filter-backprojection method, the algorithm is not constrained by the requirement of a spatially invariant detector point spread function, which limits normal analytic techniques. Removing this constraint allows the incorporation of all detected events, regardless of orientation, which improves the statistical quality of the final reconstructed image

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.

All-optical network coding for DPSK signals

DEFF Research Database (Denmark)

An, Yi; Da Ros, Francesco; Peucheret, Christophe

2013-01-01

All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB.......All-optical network coding for path protection is experimentally demonstrated using four-wave mixing in SOAs for10 Gbit/s NRZ-DPSK signals with error free performance. The total power penalty after two cascaded XOR stage is only 2 dB....

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.

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.

And Then There Were None: Winnowing the Shakespeare Claimants.

Science.gov (United States)

Elliott, Ward E. Y.; Valenza, Robert J.

1996-01-01

Applies 51 stylometric computer tests of Shakespeare play authorship and 14 of play authorship, developed by the Shakespeare Clinic, to 37 "true Shakespeares," 27 plays of the Shakespeare Apocrypha, and to several poems of unknown authorship. Finds that no claimant, and none of the apocryphal plays or poems, matched Shakespeare. (DSK)

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.

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.

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.

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

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

Science.gov (United States)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

Technologies for all-optical wavelength conversion in DWDM networks

DEFF Research Database (Denmark)

Wolfson, David; Fjelde, Tina; Kloch, Allan

2001-01-01

Different techniques for all-optical wavelength conversion are reviewed and the advantages and disadvantages seen from a system perspective are highlighted. All-optical wavelength conversion will play a major role in making cost-effective network nodes in future high-speed WDM networks, where...

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

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

The None-of-the-Above Option: An Empirical Study.

Science.gov (United States)

Frary, Robert B.

1991-01-01

The use of the "none-of-the-above" option (NOTA) in 20 college-level multiple-choice tests was evaluated for classes with 100 or more students. Eight academic disciplines were represented, and 295 NOTA and 724 regular test items were used. It appears that the NOTA can be compatible with good classroom measurement. (TJH)

Social Networks: Gated Communities or Free Cantons?

CERN Multimedia

CERN. Geneva

2017-01-01

Online social networks and other cloud-based services have concentrated the control of the web in the hands of a few corporations. Our personal data has been commodified, often without our knowledge or consent. Is there a way to retain all the benefits of social networking without giving up control of our data?

Mechanisms of Winner-Take-All and Group Selection in Neuronal Spiking Networks.

Science.gov (United States)

Chen, Yanqing

2017-01-01

A major function of central nervous systems is to discriminate different categories or types of sensory input. Neuronal networks accomplish such tasks by learning different sensory maps at several stages of neural hierarchy, such that different neurons fire selectively to reflect different internal or external patterns and states. The exact mechanisms of such map formation processes in the brain are not completely understood. Here we study the mechanism by which a simple recurrent/reentrant neuronal network accomplish group selection and discrimination to different inputs in order to generate sensory maps. We describe the conditions and mechanism of transition from a rhythmic epileptic state (in which all neurons fire synchronized and indiscriminately to any input) to a winner-take-all state in which only a subset of neurons fire for a specific input. We prove an analytic condition under which a stable bump solution and a winner-take-all state can emerge from the local recurrent excitation-inhibition interactions in a three-layer spiking network with distinct excitatory and inhibitory populations, and demonstrate the importance of surround inhibitory connection topology on the stability of dynamic patterns in spiking neural network.

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.

Organization Virtual or Networked?

Directory of Open Access Journals (Sweden)

Rūta Tamošiūnaitė

2013-08-01

Full Text Available Purpose—to present distinction between “virtual organization” and “networked organization”; giving their definitions.Design/methodology/approach—review of previous researches, systemic analyses of their findings and synthesis of distinctive characteristics of ”virtual organization” and “networked organization.”Findings—the main result of the research is key diverse features separating ”virtual organization” and ”networked organization.” Definitions of “virtual organization” and “networked organization” are presented.Originality/Value—distinction between “virtual organization” and “networked organization” creates possibilities to use all advantages of those types of organizations and gives foundation for deeper researches in this field.Research type: general review.

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.

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.

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

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.

Green Measures... or, none of us are green until all of us are green

Directory of Open Access Journals (Sweden)

Brian Szymanik

2013-03-01

Full Text Available This paper introduces a re-consideration of the tenets of the ‘triple bottom line’ (economy, environment, and society to contemplate the societal implications of the current successes enjoyed by the environmentally-sensitive design movement. Considering the tools that we use to gauge the successes of sustainable ambitions, this work proposes the ways in which we apply sustainable design metrics are fundamentally working against the tenets of the triple bottom line. When considered through the lens of society, and in particular the urban poor, the current trajectory of the sustainable design movement is one that may create voids where a sustainable urban future can not exist.

Monitoring burst (M-burst) — A novel framework of failure localization in all-optical mesh networks

KAUST Repository

Ali, Mohammed L.; Ho, Pin-Han; Wu, Bin; Tapolcai, Janos; Shihada, Basem

2011-01-01

Achieving instantaneous and precise failure localization in all-optical wavelength division multiplexing (WDM) networks has been an attractive feature of network fault management systems, and is particularly important when failure-dependent protection is employed. The paper introduces a novel framework of real-time failure localization in all-optical WDM mesh networks, called monitoring-burst (m-burst), which aims to initiate a graceful compromise between consumed monitoring resources and monitoring delay. Different from any previously reported solution, the proposed m-burst framework has a single monitoring node (MN) which launches optical bursts along a set of pre-defined close-loop routes, called monitoring cycles (m-cycles), to probe the links along the m-cycles. Bursts along different m-cycles are kept non-overlapping through any link of the network. By identifying the lost bursts due to single link failure events only, the MN can unambiguously localize the failed link in at least 3-connected networks. We will justify the feasibility and applicability of the proposed m-burst framework in the scenario of interest. To avoid possible collision among optical bursts launched by the MN, we define the problem of collision-free scheduling and formulate it into an integer linear program (ILP) in order to minimize the monitoring delay. Numerical results demonstrate the effectiveness of the proposed framework and the proposed solution.

Monitoring burst (M-burst) — A novel framework of failure localization in all-optical mesh networks

KAUST Repository

Ali, Mohammed L.

2011-10-10

Achieving instantaneous and precise failure localization in all-optical wavelength division multiplexing (WDM) networks has been an attractive feature of network fault management systems, and is particularly important when failure-dependent protection is employed. The paper introduces a novel framework of real-time failure localization in all-optical WDM mesh networks, called monitoring-burst (m-burst), which aims to initiate a graceful compromise between consumed monitoring resources and monitoring delay. Different from any previously reported solution, the proposed m-burst framework has a single monitoring node (MN) which launches optical bursts along a set of pre-defined close-loop routes, called monitoring cycles (m-cycles), to probe the links along the m-cycles. Bursts along different m-cycles are kept non-overlapping through any link of the network. By identifying the lost bursts due to single link failure events only, the MN can unambiguously localize the failed link in at least 3-connected networks. We will justify the feasibility and applicability of the proposed m-burst framework in the scenario of interest. To avoid possible collision among optical bursts launched by the MN, we define the problem of collision-free scheduling and formulate it into an integer linear program (ILP) in order to minimize the monitoring delay. Numerical results demonstrate the effectiveness of the proposed framework and the proposed solution.

Assessment of Adverse Events in Protocols, Clinical Study Reports, and Published Papers of Trials of Orlistat

DEFF Research Database (Denmark)

Schroll, Jeppe Bennekou; Penninga, Elisabeth I; Gøtzsche, Peter C

2016-01-01

BACKGROUND: Little is known about how adverse events are summarised and reported in trials, as detailed information is usually considered confidential. We have acquired clinical study reports (CSRs) from the European Medicines Agency through the Freedom of Information Act. The CSRs describe......Med and adverse event data were extracted from this source as well. All three sources were compared. Individual adverse events from one trial were summed and compared to the totals in the summary report. None of the protocols or CSRs contained instructions for investigators on how to question participants about...

Optimal cost for strengthening or destroying a given network

Science.gov (United States)

Patron, Amikam; Cohen, Reuven; Li, Daqing; Havlin, Shlomo

2017-05-01

Strengthening or destroying a network is a very important issue in designing resilient networks or in planning attacks against networks, including planning strategies to immunize a network against diseases, viruses, etc. Here we develop a method for strengthening or destroying a random network with a minimum cost. We assume a correlation between the cost required to strengthen or destroy a node and the degree of the node. Accordingly, we define a cost function c (k ) , which is the cost of strengthening or destroying a node with degree k . Using the degrees k in a network and the cost function c (k ) , we develop a method for defining a list of priorities of degrees and for choosing the right group of degrees to be strengthened or destroyed that minimizes the total price of strengthening or destroying the entire network. We find that the list of priorities of degrees is universal and independent of the network's degree distribution, for all kinds of random networks. The list of priorities is the same for both strengthening a network and for destroying a network with minimum cost. However, in spite of this similarity, there is a difference between their pc, the critical fraction of nodes that has to be functional to guarantee the existence of a giant component in the network.

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.

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.

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.

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.

Advanced Optoelectronic Components for All-Optical Networks

National Research Council Canada - National Science Library

Shapiro, Jeffrey H

2002-01-01

Under APOSR Grant F49620-96-1-0126, 'Advanced Optoelectronic Components for All-Optical Networks', we have worked to develop key technologies and components to substantially improve the performance...

Routing and wavelength assignment based on normalized resource and constraints for all-optical network

Science.gov (United States)

Joo, Seong-Soon; Nam, Hyun-Soon; Lim, Chang-Kyu

2003-08-01

With the rapid growth of the Optical Internet, high capacity pipes is finally destined to support end-to-end IP on the WDM optical network. Newly launched 2D MEMS optical switching module in the market supports that expectations of upcoming a transparent optical cross-connect in the network have encouraged the field applicable research on establishing real all-optical transparent network. To open up a customer-driven bandwidth services, design of the optical transport network becomes more challenging task in terms of optimal network resource usage. This paper presents a practical approach to finding a route and wavelength assignment for wavelength routed all-optical network, which has λ-plane OXC switches and wavelength converters, and supports that optical paths are randomly set up and released by dynamic wavelength provisioning to create bandwidth between end users with timescales on the order of seconds or milliseconds. We suggest three constraints to make the RWA problem become more practical one on deployment for wavelength routed all-optical network in network view: limitation on maximum hop of a route within bearable optical network impairments, limitation on minimum hops to travel before converting a wavelength, and limitation on calculation time to find all routes for connections requested at once. We design the NRCD (Normalized Resource and Constraints for All-Optical Network RWA Design) algorithm for the Tera OXC: network resource for a route is calculated by the number of internal switching paths established in each OXC nodes on the route, and is normalized by ratio of number of paths established and number of paths equipped in a node. We show that it fits for the RWA algorithm of the wavelength routed all-optical network through real experiments on the distributed objects platform.

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.

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.

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.

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

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

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

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.

Pollination networks of oil-flowers: a tiny world within the smallest of all worlds.

Science.gov (United States)

Bezerra, Elisângela L S; Machado, Isabel C; Mello, Marco A R

2009-09-01

1. In the Neotropics, most plants depend on animals for pollination. Solitary bees are the most important vectors, and among them members of the tribe Centridini depend on oil from flowers (mainly Malpighiaceae) to feed their larvae. This specialized relationship within 'the smallest of all worlds' (a whole pollination network) could result in a 'tiny world' different from the whole system. This 'tiny world' would have higher nestedness, shorter path lengths, lower modularity and higher resilience if compared with the whole pollination network. 2. In the present study, we contrasted a network of oil-flowers and their visitors from a Brazilian steppe ('caatinga') to whole pollination networks from all over the world. 3. A network approach was used to measure network structure and, finally, to test fragility. The oil-flower network studied was more nested (NODF = 0.84, N = 0.96) than all of the whole pollination networks studied. Average path lengths in the two-mode network were shorter (one node, both for bee and plant one-mode network projections) and modularity was lower (M = 0.22 and four modules) than in all of the whole pollination networks. Extinctions had no or small effects on the network structure, with an average change in nestedness smaller than 2% in most of the cases studied; and only two species caused coextinctions. The higher the degree of the removed species, the stronger the effect and the higher the probability of a decrease in nestedness. 4. We conclude that the oil-flower subweb is more cohesive and resilient than whole pollination networks. Therefore, the Malpighiaceae have a robust pollination service in the Neotropics. Our findings reinforce the hypothesis that each ecological service is in fact a mosaic of different subservices with a hierarchical structure ('webs within webs').

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...

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.

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.

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.

The All-or-Nothing Anti-Theft Policy - Theft Protection for Pervasive Computing

DEFF Research Database (Denmark)

Pedersen, Michael Østergaard; Pagter, Jakob Illeborg

2007-01-01

In many application scenarios for pervasive computing, theft is a serious security threat. In this paper we present the All-Or-Nothing anti-theft policy aimed at providing theft protection for pervasive computing. The overall idea behind the All-Or-Nothing anti-theft policy is to chain devices...... together in friendly networks so that any device will only work when it can see all of its friends. Thus a thief will have to keep the network of friendly devices together even if he only desires to steal one of the devices. Otherwise the device will not work. We provide a detailed security policy, present...... the required cryptographic protocols, provide three different applications, and finally we document that the policy is suitable for implementation on typical pervasive computing devices....

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

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,…

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.

New all-passive 4x4 planar optical phase diversity network

NARCIS (Netherlands)

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

1991-01-01

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

26 CFR 25.2515-4 - Termination of tenancy by entirety; cases in which none, or a portion only, of value of gift is...

Science.gov (United States)

2010-04-01

... the value of the respective interests of the spouses at the time of the creation of a tenancy by the... creation of the tenancy. In 1955, at which time the fair market value of the property was the same as at... which none, or a portion only, of value of gift is determined under section 2515(b). 25.2515-4 Section...

A national seismographic network for assessing seismic hazards

International Nuclear Information System (INIS)

Masse, R.P.; Murphy, A.J.

1989-01-01

To access the seismic hazard of a region and to establish the design and construction criteria for critical facilities such as nuclear power plants, detailed information is required on the frequency of occurrence, geographical distribution, magnitude, and energy spectra of earthquakes. Also important is information on the frequency-dependent attenuation of seismic waves. This information can all be obtained from data recorded by networks of seismograph stations. A new seismograph network for the US which takes advantage of advances in technology is currently under development. This network is the US National Seismograph Network (USNSN). The USNSN is a cooperative effort between the National Earthquake Information Center (NEIC) of the US Geological survey and the Nuclear Regulatory Commission. The USNSN will be installed and operated by the NEIC. The network will consist of approximately 150 seismograph stations distributed across the lower 48 states and across Alaska, Hawaii, Puerto Rico, and the Virgin Islands. The design goal for the network is the on-scale recording by at least five well-distributed stations of any event of magnitude 2.5 or larger in the continental US, Hawaii, and Puerto Rico, and of any event of magnitude 3.5 or larger in Alaska. The rapid access to all USNSN data will be provided by the NEIC. This will be accomplished both via a dial-up capability to the event waveform data base and by satellite transmission in a broadcast mode. All earthquake data will also be distributed on compact disk with read only memory (CD-ROM) to all institutions having an interest in the seismic data

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.

THE INTERPLANETARY NETWORK RESPONSE TO LIGO GW150914

Energy Technology Data Exchange (ETDEWEB)

Hurley, K. [University of California, Berkeley, Space Sciences Laboratory, 7 Gauss Way, Berkeley, CA 94720-7450 (United States); Svinkin, D. S.; Aptekar, R. L.; Golenetskii, S. V.; Frederiks, D. D. [Ioffe Physical Technical Institute, Politekhnicheskaya 26, St. Petersburg 194021 (Russian Federation); Boynton, W. [University of Arizona, Department of Planetary Sciences, Tucson, AZ 85721 (United States); Mitrofanov, I. G.; Golovin, D. V.; Kozyrev, A. S.; Litvak, M. L.; Sanin, A. B. [Space Research Institute, 84/32, Profsoyuznaya, Moscow 117997 (Russian Federation); Rau, A.; Kienlin, A. von; Zhang, X. [Max-Planck-Institut für extraterrestrische Physik, Giessenbachstrasse, Postfach 1312, Garching, D-85748 Germany (Germany); Connaughton, V.; Meegan, C. [University of Alabama in Huntsville, NSSTC, 320 Sparkman Drive, Huntsville, AL 35805 (United States); Cline, T.; Gehrels, N., E-mail: khurley@ssl.berkeley.edu [NASA Goddard Space Flight Center, Code 661, Greenbelt, MD 20771 (United States)

2016-09-20

We have performed a blind search for a gamma-ray transient of arbitrary duration and energy spectrum around the time of the LIGO gravitational-wave event GW150914 with the six-spacecraft interplanetary network (IPN). Four gamma-ray bursts were detected between 30 hr prior to the event and 6.1 hr after it, but none could convincingly be associated with GW150914. No other transients were detected down to limiting 15–150 keV fluences of roughly 5 ×10{sup −8}–5 × 10{sup −7} erg cm{sup −2}. We discuss the search strategies and temporal coverage of the IPN on the day of the event and compare the spatial coverage to the region where GW150914 originated. We also report the negative result of a targeted search for the Fermi -GBM event reported in conjunction with GW150914.

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...

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.

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.

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...

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.

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.)

All-optical signal processing for optical packet switching networks

NARCIS (Netherlands)

Liu, Y.; Hill, M.T.; Calabretta, N.; Tangdiongga, E.; Geldenhuys, R.; Zhang, S.; Li, Z.; Waardt, de H.; Khoe, G.D.; Dorren, H.J.S.; Iftekharuddin, K.M.; awwal, A.A.S.

2005-01-01

We discuss how all-optical signal processing might play a role in future all-optical packet switched networks. We introduce a concept of optical packet switches that employ entirely all-optical signal processing technology. The optical packet switch is made out of three functional blocks: the

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.

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.

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...

Troponin T or troponin I or CK-MB (or none?).

Science.gov (United States)

Collinson, P O

1998-11-01

patients, thrombolysis is the treatment of choice. Patients presenting with ST segment elevation represents the minority of patients with probable ACS 9.6% of all patients presenting to our hospital. The majority require risk stratification into high- and low-risk groups. It is here that cardiac troponins have a major role. The measurement of cTnT has been shown in a large number of studies to enable risk stratification of patients with unstable angina. The combination of cTnT, admission ECG and stress ECG can be used for a comprehensive risk stratification of patients with unstable angina. The combination of cTnT, admission ECG and stress ECG can be used for a comprehensive risk stratification which can be completed by 24 h from admission, as well as allowing a safe discharge policy from the ED. Measurements of cardiac troponins can also be used to predict prognosis in patients with other diagnostic categories. Patients with cardiac failure can be risk stratified according to cTnT status. cTnT status on admission allows subdivision into high- and low-risk groups in patients presenting with ST segment elevation. Certainly, cTnT measurement can be incorporated into a clinical decision-making strategy to assign patients to investigation and management pathways. There is evidence that cTnT may be useful to guide therapeutic options. The major issue is one of cost. In the U.K. model of managed care with undemanding diagnostic standards, the role of cTnT will be to enhance clinical decision-making strategies, to provide accurate diagnosis and to reduce lengths of stay. This can be shown to have potential for major improvements in cost efficiency. Improvements in diagnostic accuracy can reduce inappropriate long-term drug therapy. In systems with a more aggressive laboratory investigation strategy, rationalization of test numbers will provide an immediate cost reduction while improving quality. Finally, use of point-of-care testing (POCT) means that biochemical testing can be pe

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

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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

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.

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.

Event-triggered cooperative target tracking in wireless sensor networks

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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.

The "None of the Above" Option in Multiple-Choice Testing: An Experimental Study

Science.gov (United States)

DiBattista, David; Sinnige-Egger, Jo-Anne; Fortuna, Glenda

2014-01-01

The authors assessed the effects of using "none of the above" as an option in a 40-item, general-knowledge multiple-choice test administered to undergraduate students. Examinees who selected "none of the above" were given an incentive to write the correct answer to the question posed. Using "none of the above" as the…

Light fidelity (Li-Fi): towards all-optical networking

Science.gov (United States)

Tsonev, Dobroslav; Videv, Stefan; Haas, Harald

2013-12-01

Motivated by the looming radio frequency (RF) spectrum crisis, this paper aims at demonstrating that optical wireless communication (OWC) has now reached a state where it can demonstrate that it is a viable and matured solution to this fundamental problem. In particular, for indoor communications where most mobile data traffic is consumed, light fidelity (Li-Fi) which is related to visible light communication (VLC) offers many key advantages, and effective solutions to the issues that have been posed in the last decade. This paper discusses all key component technologies required to realize optical cellular communication systems referred to here as optical attocell networks. Optical attocells are the next step in the progression towards ever smaller cells, a progression which is known to be the most significant contributor to the improvements in network spectral efficiencies in RF wireless networks.

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

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

Search for all MCs in networks with unreliable nodes and arcs

International Nuclear Information System (INIS)

Yeh, W.-C.

2003-01-01

A simple method is proposed to search for all minimal cutsets (MCs ) for imperfect networks reliability subject to both arc and node failures under the condition that all of the MCs in the network with perfect nodes are given in advance. The proposed method does not require re-enumeration for all of the MCs for additional node failure consideration. All of the MC candidates found in the proposed algorithm are actual MCs without any need for further verification. This algorithm is more effective than the existing algorithm in which every MC candidate is not verified as a MC. No identical MCs are found using the proposed algorithm, which does not duplicate MCs and is more efficient than the existing methods. Only simple concepts are used to implement the proposed algorithm, which makes it easier to understand and implement. With considering unreliable nodes, the proposed method is also more realistic and valuable for reliability analysis in an existing network. The correctness of the proposed algorithm will be analyzed and proven. One example is used to illustrate how all MCs are generated in a network with arc and node failures solved using the proposed algorithm

Security Situation Assessment of All-Optical Network Based on Evidential Reasoning Rule

Directory of Open Access Journals (Sweden)

Zhong-Nan Zhao

2016-01-01

Full Text Available It is important to determine the security situations of the all-optical network (AON, which is more vulnerable to hacker attacks and faults than other networks in some cases. A new approach of the security situation assessment to the all-optical network is developed in this paper. In the new assessment approach, the evidential reasoning (ER rule is used to integrate various evidences of the security factors including the optical faults and the special attacks in the AON. Furthermore, a new quantification method of the security situation is also proposed. A case study of an all-optical network is conducted to demonstrate the effectiveness and the practicability of the new proposed approach.

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

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

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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.

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

All-optical virtual private network and ONUs communication in optical OFDM-based PON system.

Science.gov (United States)

Zhang, Chongfu; Huang, Jian; Chen, Chen; Qiu, Kun

2011-11-21

We propose and demonstrate a novel scheme, which enables all-optical virtual private network (VPN) and all-optical optical network units (ONUs) inter-communications in optical orthogonal frequency-division multiplexing-based passive optical network (OFDM-PON) system using the subcarrier bands allocation for the first time (to our knowledge). We consider the intra-VPN and inter-VPN communications which correspond to two different cases: VPN communication among ONUs in one group and in different groups. The proposed scheme can provide the enhanced security and a more flexible configuration for VPN users compared to the VPN in WDM-PON or TDM-PON systems. The all-optical VPN and inter-ONU communications at 10-Gbit/s with 16 quadrature amplitude modulation (16 QAM) for the proposed optical OFDM-PON system are demonstrated. These results verify that the proposed scheme is feasible. © 2011 Optical Society of America

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.

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.

To friend or not to friend? Social networking and faculty perceptions of online professionalism.

Science.gov (United States)

Chretien, Katherine C; Farnan, Jeanne M; Greysen, S Ryan; Kind, Terry

2011-12-01

To assess faculty perceptions of professional boundaries and trainee-posted content on social networking sites (SNS). In June 2010, the Clerkship Directors in Internal Medicine conducted its annual survey of U.S. and Canadian member institutions. The survey included sections on demographics and social networking. The authors used descriptive statistics and tests of association to analyze the Likert scale responses and qualitatively analyzed the free-text responses. Of 110 institutional members, 82 (75%) responded to the survey. Of the 40 respondents who reported current or past SNS use, 21 (53%) reported receiving a "friend request" from a current student and 25 (63%) from a current resident. Of these, 4 (19%) accepted the student request and 12 (48%) accepted the resident request. Sixty-three of 80 (79%) felt it was inappropriate to send a friend request to a current student, 61 (76%) to accept a current student's request, 42 (53%) to become friends with a current resident, and 61 (81%) to become friends with a current patient. Becoming friends with a former student, former resident, or colleague was perceived as more appropriate. Younger respondents were less likely to deem specific student behaviors inappropriate (odds ratio [OR] 0.18-0.79; adjusted OR 0.12-0.86, controlling for respondents' sex, rank, and SNS use), although none reached statistical significance. Some internal medicine educators are using SNSs and interacting with trainees online. Their perceptions on the appropriateness of social networking behaviors provide some consensus for professional boundaries between faculty and trainees in the digital world.

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.

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.

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.

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.

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.

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.

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...

Scalability analysis of the synchronizability for ring or chain networks with dense clusters

International Nuclear Information System (INIS)

Lu, Jun-An; Zhang, Yong; Chen, Juan; Lü, Jinhu

2014-01-01

It is well known that most real-world complex networks, such as the Internet and the World Wide Web, are evolving networks. An interesting fundamental question is: how do some important functions or dynamical behaviors of complex networks evolve with increasing network scale? This paper aims at investigating the scalability of the synchronizability for ring or chain networks with dense clusters as the network size increases. We discover some interesting phenomena as follows: (i) the synchronizability of ring or chain networks with clusters decreases with increasing network scale regardless of the inner structures of all communities; (ii) for the same network scale, the network synchronizability decreases more quickly with increasing number of cluster blocks than with increasing number of nodes within the cluster block; (iii) the number of rings or chains has a much more significant influence on the network synchronizability than the size of the rings or chains. Our results indicate that network synchronizability can be maintained with increasing network scale by avoiding ring and chain structures. (paper)

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.

Bol d'Or success for all-women crew from CERN

CERN Multimedia

2001-01-01

The boat 'Mic Mac' and its CERN's all-woman crew (left to right), Christine Theurillat, Ursula Haenger , Paola Catapano, Petra Riedler, and skipper Cristina Morone. Spectacular highlight of the Lake Leman sailing calendar is the annual Bol d'Or race. Held this year on 16 and 17 June, the event attracted nearly 500 teams who competed under extreme weather conditions for the honours. Among the competitors was an all-woman crew from the CERN Yachting Club, sailing their Surprise boat, Mic Mac. The team was not only among the 397 boats to finish, but also the first all-woman crewed single hull boat to cross the line.

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.

Information Assurance in Wireless Networks

Science.gov (United States)

Kabara, Joseph; Krishnamurthy, Prashant; Tipper, David

2001-09-01

Emerging wireless networks will contain a hybrid infrastructure based on fixed, mobile and ad hoc topologies and technologies. In such a dynamic architecture, we define information assurance as the provisions for both information security and information availability. The implications of this definition are that the wireless network architecture must (a) provide sufficient security measures, (b) be survivable under node or link attack or failure and (c) be designed such that sufficient capacity remains for all critical services (and preferably most other services) in the event of attack or component failure. We have begun a research project to investigate the provision of information assurance for wireless networks viz. survivability, security and availability and here discuss the issues and challenges therein.

All-optical OXC transition strategy from WDM optical network to elastic optical network.

Science.gov (United States)

Chen, Xin; Li, Juhao; Guo, Bingli; Zhu, Paikun; Tang, Ruizhi; Chen, Zhangyuan; He, Yongqi

2016-02-22

Elastic optical network (EON) has been proposed recently as a spectrum-efficient optical layer to adapt to rapidly-increasing traffic demands instead of current deployed wavelength-division-multiplexing (WDM) optical network. In contrast with conventional WDM optical cross-connect (OXCs) based on wavelength selective switches (WSSs), the EON OXCs are based on spectrum selective switches (SSSs) which are much more expensive than WSSs, especially for large-scale switching architectures. So the transition cost from WDM OXCs to EON OXCs is a major obstacle to realizing EON. In this paper, we propose and experimentally demonstrate a transition OXC (TOXC) structure based on 2-stage cascading switching architectures, which make full use of available WSSs in current deployed WDM OXCs to reduce number and port count of required SSSs. Moreover, we propose a contention-aware spectrum allocation (CASA) scheme for EON built with the proposed TOXCs. We show by simulation that the TOXCs reduce the network capital expenditure transiting from WDM optical network to EON about 50%, with a minor traffic blocking performance degradation and about 10% accommodated traffic number detriment compared with all-SSS EON OXC architectures.

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

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…

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.

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.

Novel approach for all-optical packet switching in wide-area networks

Science.gov (United States)

Chlamtac, Imrich; Fumagalli, Andrea F.; Wedzinga, Gosse

1998-09-01

All-optical Wavelength Division Multiplexing (WDM) networks are believed to be a fundamental component in future high speed backbones. However, while wavelength routing made circuit switching in WDM feasible the reality of extant optical technology does not yet provide the necessary devices to achieve individual optical packet switching. This paper proposes to achieve all-optical packet switching in WDM Wide Area Networks (WANs) via a novel technique, called slot routing. Using slot routing, entire slots, each carrying multiple packets on distinct wavelengths, are switched transparently and individually. As a result packets can be optically transmitted and switched in the network using available fast and wavelength non-sensitive devices. The proposed routing technique leads to an optical packet switching solution, that is simple, practical, and unique as it makes it possible to build a WDM all-optical WAN with optical devices based on proven technologies.

Fiscalidad de los cánones en el comercio electrónico

Directory of Open Access Journals (Sweden)

Alejandro García Heredia

2014-06-01

Full Text Available

El presente trabajo analiza en qué casos los pagos derivados del comercio electrónico se califican como cánones a efectos de la aplicación de los convenios para eliminar la doble imposición internacional. En primer lugar, se analizan las características generales y los problemas de calificación que plantean los cánones en la fiscalidad internacional para comprender la relevancia que dichas rentas tienen en el ámbito del comercio electrónico. En segundo lugar, se abordan dos cuestiones que afectan directamente al comercio electrónico: por un lado, la calificación de los pagos por programas de ordenador; por otro lado, la calificación de los pagos derivados de la descarga de productos digitales. El análisis de la naturaleza jurídica de estas transacciones resulta fundamental para determinar si las rentas del comercio electrónico se pueden calificar como cánones. En tercer lugar, se expone la posición española respecto de los cánones y el comercio electrónico para poner de manifiesto la diferencia entre el criterio internacionalmente consensuado de la OCDE y los particulares intereses españoles. Por último, a modo de reflexión, se apuntan algunas conclusiones con respecto al tratamiento de los cánones del comercio electrónico y el enfoque de la OCDE.

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.

All optical OFDM transmission for passive optical networks

Science.gov (United States)

Kachare, Nitin; Ashik T., J.; Bai, K. Kalyani; Kumar, D. Sriram

2017-06-01

This paper demonstrates the idea of data transmission at a very higher rate (Tbits/s) through optical fibers in a passive optical network using the most efficient data transmission technique widely used in wireless communication that is orthogonal frequency division multiplexing. With an increase in internet users, data traffic has also increased significantly and the current dense wavelength division multiplexing (DWDM) systems may not support the next generation passive optical networks (PONs) requirements. The approach discussed in this paper allows to increase the downstream data rate per user and extend the standard single-mode fiber reach for future long-haul applications. All-optical OFDM is a promising solution for terabit per second capable single wavelength transmission, with high spectral efficiency and high tolerance to chromatic dispersion.

75 FR 49870 - Effects on Broadband Communications Networks of Damage to or Failure of Network Equipment or...

Science.gov (United States)

2010-08-16

... FEDERAL COMMUNICATIONS COMMISSION 47 CFR Chapter I [PS Docket No. 10-92; DA 10-1357] Effects on Broadband Communications Networks of Damage to or Failure of Network Equipment or Severe Overload AGENCY... with rubber bands or fasteners. Any envelopes must be disposed of before entering the building...

7 CFR 201.36 - The words “free” and “none.”

Science.gov (United States)

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false The words âfreeâ and ânone.â 201.36 Section 201.36 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards... REGULATIONS Labeling in General § 201.36 The words “free” and “none.” The words “free” and “none” shall be...

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

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

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.

75 FR 26180 - Effects on Broadband Communications Networks of Damage To or Failure of Network Equipment or...

Science.gov (United States)

2010-05-11

... FEDERAL COMMUNICATIONS COMMISSION 47 CFR Chapter I [PS Docket No. 10-92; FCC 10-62] Effects on... the National Broadband Plan, the Federal Communications Commission (Commission or FCC) adopted this... networks and to explore potential measures to reduce network vulnerability to failures in network equipment...

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...

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...

Memory and disenchantment in Nadine Gordimer's None to ...

African Journals Online (AJOL)

Le but de cet article est de montrer comment Nadine Gordimer, à None pour moi et Zoe Wicomb Accompagner, en jouant dans la Lumière ont représenté le passé dans leurs romans postapartheid et comment il a influencé la situation ontologique des personnages de ce qui précède textes en question. Ce document est ...

A computer aided treatment event recognition system in radiation therapy

International Nuclear Information System (INIS)

Xia, Junyi; Mart, Christopher; Bayouth, John

2014-01-01

Purpose: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. Methods: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012–November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors’ clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. Results: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when

A computer aided treatment event recognition system in radiation therapy

Energy Technology Data Exchange (ETDEWEB)

Xia, Junyi, E-mail: junyi-xia@uiowa.edu; Mart, Christopher [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 (United States); Bayouth, John [Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa 52242 and Department of Human Oncology, University of Wisconsin - Madison, 600 Highland Avenue, K4/B55, Madison, Wisconsin 53792-0600 (United States)

2014-01-15

Purpose: To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. Methods: CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012–November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors’ clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. Results: All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when

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.

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.

Enabling parallel simulation of large-scale HPC network systems

International Nuclear Information System (INIS)

Mubarak, Misbah; Carothers, Christopher D.; Ross, Robert B.; Carns, Philip

2016-01-01

Here, with the increasing complexity of today’s high-performance computing (HPC) architectures, simulation has become an indispensable tool for exploring the design space of HPC systems—in particular, networks. In order to make effective design decisions, simulations of these systems must possess the following properties: (1) have high accuracy and fidelity, (2) produce results in a timely manner, and (3) be able to analyze a broad range of network workloads. Most state-of-the-art HPC network simulation frameworks, however, are constrained in one or more of these areas. In this work, we present a simulation framework for modeling two important classes of networks used in today’s IBM and Cray supercomputers: torus and dragonfly networks. We use the Co-Design of Multi-layer Exascale Storage Architecture (CODES) simulation framework to simulate these network topologies at a flit-level detail using the Rensselaer Optimistic Simulation System (ROSS) for parallel discrete-event simulation. Our simulation framework meets all the requirements of a practical network simulation and can assist network designers in design space exploration. First, it uses validated and detailed flit-level network models to provide an accurate and high-fidelity network simulation. Second, instead of relying on serial time-stepped or traditional conservative discrete-event simulations that limit simulation scalability and efficiency, we use the optimistic event-scheduling capability of ROSS to achieve efficient and scalable HPC network simulations on today’s high-performance cluster systems. Third, our models give network designers a choice in simulating a broad range of network workloads, including HPC application workloads using detailed network traces, an ability that is rarely offered in parallel with high-fidelity network simulations

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

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

Versatile Networks of Simulated Spiking Neurons Displaying Winner-Take-All Behavior

Directory of Open Access Journals (Sweden)

Yanqing eChen

2013-03-01

Full Text Available We describe simulations of large-scale networks of excitatory and inhibitory spiking neurons that can generate dynamically stable winner-take-all (WTA behavior. The network connectivity is a variant of center-surround architecture that we call center-annular-surround (CAS. In this architecture each neuron is excited by nearby neighbors and inhibited by more distant neighbors in an annular-surround region. The neural units of these networks simulate conductance-based spiking neurons that interact via mechanisms susceptible to both short-term synaptic plasticity and STDP. We show that such CAS networks display robust WTA behavior unlike the center-surround networks and other control architectures that we have studied. We find that a large-scale network of spiking neurons with separate populations of excitatory and inhibitory neurons can give rise to smooth maps of sensory input. In addition, we show that a humanoid Brain-Based-Device (BBD under the control of a spiking WTA neural network can learn to reach to target positions in its visual field, thus demonstrating the acquisition of sensorimotor coordination.

Versatile networks of simulated spiking neurons displaying winner-take-all behavior.

Science.gov (United States)

Chen, Yanqing; McKinstry, Jeffrey L; Edelman, Gerald M

2013-01-01

We describe simulations of large-scale networks of excitatory and inhibitory spiking neurons that can generate dynamically stable winner-take-all (WTA) behavior. The network connectivity is a variant of center-surround architecture that we call center-annular-surround (CAS). In this architecture each neuron is excited by nearby neighbors and inhibited by more distant neighbors in an annular-surround region. The neural units of these networks simulate conductance-based spiking neurons that interact via mechanisms susceptible to both short-term synaptic plasticity and STDP. We show that such CAS networks display robust WTA behavior unlike the center-surround networks and other control architectures that we have studied. We find that a large-scale network of spiking neurons with separate populations of excitatory and inhibitory neurons can give rise to smooth maps of sensory input. In addition, we show that a humanoid brain-based-device (BBD) under the control of a spiking WTA neural network can learn to reach to target positions in its visual field, thus demonstrating the acquisition of sensorimotor coordination.

Real-time detection and classification of anomalous events in streaming data

Science.gov (United States)

Ferragut, Erik M.; Goodall, John R.; Iannacone, Michael D.; Laska, Jason A.; Harrison, Lane T.

2016-04-19

A system is described for receiving a stream of events and scoring the events based on anomalousness and maliciousness (or other classification). The events can be displayed to a user in user-defined groupings in an animated fashion. 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 atypical traffic patterns can then be classified as being of interest or not. In one particular example, in a network environment, the classification can be whether the network traffic is malicious or not.

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.

A Kohonen neural network controlled all-optical router system

NARCIS (Netherlands)

Frietman, E.E.E.; Hill, M.T.; Khoe, G.D.

2001-01-01

The internet is composed of thousands of networks, linking millions of users at academic, industrial and governmental institutions all over the world, offering opportunities to collaborate and to share resources, such as documents, software and data. The ever-increasing number of users confronts the

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

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...

Range-Based Localization in Mobile Sensor Networks

NARCIS (Netherlands)

Dil, B.J.; Dil, B.; Dulman, S.O.; Havinga, Paul J.M.; Romer, K.; Karl, H.; Mattern, F.

2006-01-01

Localization schemes for wireless sensor networks can be classified as range-based or range-free. They differ in the information used for localization. Range-based methods use range measurements, while range-free techniques only use the content of the messages. None of the existing algorithms

High speed all-optical networks

Science.gov (United States)

Chlamtac, Imrich

1993-01-01

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

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.)

Russian women emigrées in psychology: informal Jewish networks.

Science.gov (United States)

Woodward, William R

2010-05-01

This paper uses archival sources and autobiographies to give a fuller account of the lives of three Russian women psychologists, each of whom voluntarily emigrated several years before the Third Reich. As such, their stories contribute to gender history, emigration history, and ethnic history. The characteristics of second-generation women in psychology seem to apply to this sample; they accepted applied or secondary positions in psychology or allied fields and came late to tenure-track positions. Some first-generation characteristics fit them also: choosing career over marriage, accepting the "family claim," and living "fractured lives." Emigrée history reveals that these women found careers in the United States that could not have happened in the smaller, more restricted higher education networks of Europe. Female friendships and family ties to the Old World sustained them. All struggled with professional networking and had varying success, depending heavily upon the patronage of sympathetic male psychologists. Ethnic history shows that none identified strongly with Judaism, yet all benefited from Jewish mentors and networks of patronage. Evidence of gendered or racial discrimination in hiring practices is sparse, though it surely existed.

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.

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.

Radiation monitoring network of the Czech Republic

International Nuclear Information System (INIS)

Kuca, P.; Novak, L.; Rulik, P.; Tecl, J.

2003-01-01

The Radiation Monitoring Network (RMN) of the Czech Republic was established after the Chernobyl accident in 1986 and it is developed all the time. It is co-ordinated by the State Office for Nuclear Safety in co-operation with the National Radiation Protection Institute. Czech RMN consists of the several sub-networks, which include selected or all permanent parts of RMN. The sub-networks are following: the Early Warning Network (EWN), the TLD Territorial Network, the Network of the Measuring Sites of Air Contamination, the Network of Laboratories Equipped with Gamma-spectrometric and Radiochemical Analytical Instrumentation, the Ground and Airborne Mobile Groups. The Laboratory of Monitoring of Internal Contamination and the information system (IS) are a significant part of RMN, too. The data of RMN resulting from monitoring are transferred to the central database of CRMN, processed by the information system (IS). They are used in normal and emergency situations for an evaluation of radiation situation and for preparation of recommendations for protection of the public and the environment. In 2002 any extraordinary radioactivity in the environment was not detected and also none of the measuring points recorded any exceeding of established investigation levels. In components of environment and also in human beings a very low activity of 137 Cs was still measurable, that had been released into environment after the Chernobyl accident and by the nuclear weapon tests in sixties of the last century. (authors)

A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation.

Science.gov (United States)

Liu, Qingshan; Dang, Chuangyin; Cao, Jinde

2010-07-01

In this paper, based on a one-neuron recurrent neural network, a novel k-winners-take-all ( k -WTA) network is proposed. Finite time convergence of the proposed neural network is proved using the Lyapunov method. The k-WTA operation is first converted equivalently into a linear programming problem. Then, a one-neuron recurrent neural network is proposed to get the kth or (k+1)th largest inputs of the k-WTA problem. Furthermore, a k-WTA network is designed based on the proposed neural network to perform the k-WTA operation. Compared with the existing k-WTA networks, the proposed network has simple structure and finite time convergence. In addition, simulation results on numerical examples show the effectiveness and performance of the proposed k-WTA network.

Artificial Neural Network applied to lightning flashes

Science.gov (United States)

Gin, R. B.; Guedes, D.; Bianchi, R.

2013-05-01

The development of video cameras enabled cientists to study lightning discharges comportment with more precision. The main goal of this project is to create a system able to detect images of lightning discharges stored in videos and classify them using an Artificial Neural Network (ANN)using C Language and OpenCV libraries. The developed system, can be split in two different modules: detection module and classification module. The detection module uses OpenCV`s computer vision libraries and image processing techniques to detect if there are significant differences between frames in a sequence, indicating that something, still not classified, occurred. Whenever there is a significant difference between two consecutive frames, two main algorithms are used to analyze the frame image: brightness and shape algorithms. These algorithms detect both shape and brightness of the event, removing irrelevant events like birds, as well as detecting the relevant events exact position, allowing the system to track it over time. The classification module uses a neural network to classify the relevant events as horizontal or vertical lightning, save the event`s images and calculates his number of discharges. The Neural Network was implemented using the backpropagation algorithm, and was trained with 42 training images , containing 57 lightning events (one image can have more than one lightning). TheANN was tested with one to five hidden layers, with up to 50 neurons each. The best configuration achieved a success rate of 95%, with one layer containing 20 neurons (33 test images with 42 events were used in this phase). This configuration was implemented in the developed system to analyze 20 video files, containing 63 lightning discharges previously manually detected. Results showed that all the lightning discharges were detected, many irrelevant events were unconsidered, and the event's number of discharges was correctly computed. The neural network used in this project achieved a

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

"None of the above" as a correct and incorrect alternative on a multiple-choice test: implications for the testing effect.

Science.gov (United States)

Odegard, Timothy N; Koen, Joshua D

2007-11-01

Both positive and negative testing effects have been demonstrated with a variety of materials and paradigms (Roediger & Karpicke, 2006b). The present series of experiments replicate and extend the research of Roediger and Marsh (2005) with the addition of a "none-of-the-above" response option. Participants (n=32 in both experiments) read a set of passages, took an initial multiple-choice test, completed a filler task, and then completed a final cued-recall test (Experiment 1) or multiple-choice test (Experiment 2). Questions were manipulated on the initial multiple-choice test by adding a "none-of-the-above" response alternative (choice "E") that was incorrect ("E" Incorrect) or correct ("E" Correct). The results from both experiments demonstrated that the positive testing effect was negated when the "none-of-the-above" alternative was the correct response on the initial multiple-choice test, but was still present when the "none-of-the-above" alternative was an incorrect response.

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

Attendance at cultural events, reading books or periodicals, and making music or singing in a choir as determinants for survival: Swedish interview survey of living conditions.

Science.gov (United States)

Bygren, L O; Konlaan, B B; Johansson, S E

To investigate the possible influence of attendance at cultural events, reading books or periodicals, making music or singing in a choir as determinants for survival. A simple random sample was drawn of 15,198 individuals aged 16-74 years. Of these, 85% (12,982) were interviewed by trained non-medical interviewers between 1982 and 1983 about cultural activities. They were followed up with respect to survival until 31 December 1991. Swedish interview survey of living conditions comprising a random sample of the adult Swedish population. 12,675 people interviewed between 1982 and 1983. Survival of subjects after controlling for eight confounding variables: age, sex, education level, income, long term disease, social network, smoking, and physical exercise. 6,301 men and 6,374 women were followed up; 533 men and 314 women died during this period. The control variables influenced survival in the expected directions except for social network for men; a significant negative effective was found when the analysis was made separately for men and women. We found an influence on mortality when the eight control variables were controlled for in people who rarely attended events compared with those attending most often, the relative risk being 1.57 (95% confidence interval 1.18 to 2.09). Attendance at cultural events may have a positive influence on survival. Long term follow up of large samples with confounders that are well controlled for and with the cultural stimulation more highly specified should be used to try to falsify the hypothesis before experiments start.

Redefining Religious Nones: Lessons from Chinese and Japanese American Young Adults

Directory of Open Access Journals (Sweden)

Russell Jeung

2015-07-01

Full Text Available This analysis of Chinese and Japanese American young adults, based on the Pew Research Center 2012 Asian American Survey, examines the religious nones of these ethnic groups. Rather than focusing on their beliefs and belonging to religious denominations, it highlights their spiritual practices and ethical relations using an Asian-centric liyi (ritual and righteousness discourse. Despite being religious nones, these groups have high rates of ancestor veneration and participation in ethnic religious festivals, as well as strong familial and reciprocal obligations. These findings indicate that, similar to other American Millennials, these groups may be better understood by how they do religion than in what they believe.

Network modelling methods for FMRI.

Science.gov (United States)

Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

2011-01-15

There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

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...

Cardiovascular events and mortality in patients with adrenal incidentalomas that are either non-secreting or associated with intermediate phenotype or subclinical Cushing's syndrome: a 15-year retrospective study.

Science.gov (United States)

Di Dalmazi, Guido; Vicennati, Valentina; Garelli, Silvia; Casadio, Elena; Rinaldi, Eleonora; Giampalma, Emanuela; Mosconi, Cristina; Golfieri, Rita; Paccapelo, Alexandro; Pagotto, Uberto; Pasquali, Renato

2014-05-01

associated independently with a change (from baseline to the end of follow-up) in cortisol concentrations post DST (hazard ratio 1·13, 95% CI 1·05-1·21; p=0·001). Survival rates for all-cause mortality were lower in patients with either stable intermediate phenotype adrenal incidentalomas or subclinical Cushing's syndrome compared with those with stable non-secreting masses (57·0% vs 91·2%; p=0·005). Factors associated with mortality were age (hazard ratio 1·06, 95% CI 1·01-1·12; p=0·03) and mean concentrations of cortisol post DST (1·10, 1·01-1·19; p=0·04). Compared with patients with stable non-secreting adrenal incidentalomas, unadjusted survival for cardiovascular-specific mortality was lower in patients with either a stable intermediate phenotype or subclinical Cushing's syndrome (97·5% vs 78·4%; p=0·02) and in those with worsened secreting patterns (97·5% vs 60·0%; p=0·01). Cancer mortality did not differ between groups. Even when clinical signs of overt hypercortisolism are not present, patients with adrenal incidentalomas and mild hypercortisolism have an increased risk of cardiovascular events and mortality. None. Copyright © 2014 Elsevier Ltd. All rights reserved.

An automatic microseismic or acoustic emission arrival identification scheme with deep recurrent neural networks

Science.gov (United States)

Zheng, Jing; Lu, Jiren; Peng, Suping; Jiang, Tianqi

2018-02-01

The conventional arrival pick-up algorithms cannot avoid the manual modification of the parameters for the simultaneous identification of multiple events under different signal-to-noise ratios (SNRs). Therefore, in order to automatically obtain the arrivals of multiple events with high precision under different SNRs, in this study an algorithm was proposed which had the ability to pick up the arrival of microseismic or acoustic emission events based on deep recurrent neural networks. The arrival identification was performed using two important steps, which included a training phase and a testing phase. The training process was mathematically modelled by deep recurrent neural networks using Long Short-Term Memory architecture. During the testing phase, the learned weights were utilized to identify the arrivals through the microseismic/acoustic emission data sets. The data sets were obtained by rock physics experiments of the acoustic emission. In order to obtain the data sets under different SNRs, this study added random noise to the raw experiments' data sets. The results showed that the outcome of the proposed method was able to attain an above 80 per cent hit-rate at SNR 0 dB, and an approximately 70 per cent hit-rate at SNR -5 dB, with an absolute error in 10 sampling points. These results indicated that the proposed method had high selection precision and robustness.

Scoring of late gadolinium enhancement in cardiac magnetic resonance imaging can predict cardiac events in patients with hypertrophic cardiomyopathy

International Nuclear Information System (INIS)

Nojiri, Ayumi; Hongo, Kenichi; Kawai, Makoto; Komukai, Kimiaki; Sakuma, Toru; Taniguchi, Ikuo; Yoshimura, Michihiro

2011-01-01

Late gadolinium enhancement (LGE) of cardiac magnetic resonance imaging (MRI) represents myocardial fibrosis and may be related to the clinical outcome of various heart diseases. This study evaluated the relationship between LGE and cardiac events in hypertrophic cardiomyopathy (HCM) using a new scoring method. This study retrospectively followed 46 HCM patients without heart failure symptoms for 3.8±1.8 years. Gadolinium-enhanced cardiac MRI was performed in all patients. Cardiac events including newly developed heart failure or ventricular tachyarrhythmia were evaluated during the follow-up period. We evaluated the predictive factors to identify the patients with cardiac events. None of the risk factors reported to be related to poor outcome or the existence of LGE alone could predict cardiac events, which might be due to the small number of subjects investigated in this study. A new scoring method for LGE-positive areas (LGE score) was applied and higher LGE score can predict cardiac events in this study population. The proposed LGE score for cardiac MRI is considered to be a potentially valid method for assessing cardiac events in HCM patients. (author)

High performance all-carbon composite transparent electrodes containing uniform carbon nanotube networks

Energy Technology Data Exchange (ETDEWEB)

Yun, Hyung Duk; Kwak, Jinsung; Kim, Se-Yang [School of Materials Science and Engineering & Low-Dimensional Carbon Materials Center, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); Seo, Han; Bang, In Cheol; Kim, Sung Youb [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); Kang, Seoktae [Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141 (Korea, Republic of); Kwon, Soon-Yong, E-mail: sykwon@unist.ac.kr [School of Materials Science and Engineering & Low-Dimensional Carbon Materials Center, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of); School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919 (Korea, Republic of)

2016-08-05

Indium tin oxide-free, flexible transparent electrodes (TEs) are crucial for the future commercialization of flexible and wearable electronics. While carbon-based TEs containing carbon nanotube (CNT) networks show promise, they usually exhibit poor dispersion properties, limiting their performance and practicality. In this study, we report a highly efficient and bending durable all-carbon composite TE (ac-TE) that employs uniform CNT networks on a monolayer graphene/polyethylene terephthalate (PET) substrate via a simple air spray deposition method. The air-sprayed CNT/graphene assembly was free-standing on solution, making a polymer-free transfer of carbon composites to target substrates possible. The excellent performance of the ac-TEs was attributed to the uniformly networked CNTs on the polycrystalline graphene with a well-controlled density, effectively bridging the line defects and filling the tears/voids or folds necessarily existing in the as-processed graphene. The sheet resistance of the ac-TEs was increased only 6% from its original value at a bending radius of 2.7 mm, while that of the pristine graphene/PET assembly increased 237%. Mechanical bending of the ac-TEs worsened the electrical performance by only ∼1.7% after 2000 bending cycles at a bending radius of 2.5 mm. Degradation of the performance by the bending was the result of line defects formation in the graphene, demonstrating the potential of the uniform CNT networks to achieve more efficient and flexible carbon-based TEs. Furthermore, the chemically-doped ac-TEs showed commercially suitable electronic and optical properties with much enhanced thermal stability, closer to practical TEs in flexible devices. - Highlights: • Highly efficient and bending durable all-carbon composite transparent electrodes (TEs) are designed. • The performance was strongly dependent on morphology of CNT networks on graphene. • The mechanism relies on the defect reductions in graphene by uniform CNT coating

High performance all-carbon composite transparent electrodes containing uniform carbon nanotube networks

International Nuclear Information System (INIS)

Yun, Hyung Duk; Kwak, Jinsung; Kim, Se-Yang; Seo, Han; Bang, In Cheol; Kim, Sung Youb; Kang, Seoktae; Kwon, Soon-Yong

2016-01-01

Indium tin oxide-free, flexible transparent electrodes (TEs) are crucial for the future commercialization of flexible and wearable electronics. While carbon-based TEs containing carbon nanotube (CNT) networks show promise, they usually exhibit poor dispersion properties, limiting their performance and practicality. In this study, we report a highly efficient and bending durable all-carbon composite TE (ac-TE) that employs uniform CNT networks on a monolayer graphene/polyethylene terephthalate (PET) substrate via a simple air spray deposition method. The air-sprayed CNT/graphene assembly was free-standing on solution, making a polymer-free transfer of carbon composites to target substrates possible. The excellent performance of the ac-TEs was attributed to the uniformly networked CNTs on the polycrystalline graphene with a well-controlled density, effectively bridging the line defects and filling the tears/voids or folds necessarily existing in the as-processed graphene. The sheet resistance of the ac-TEs was increased only 6% from its original value at a bending radius of 2.7 mm, while that of the pristine graphene/PET assembly increased 237%. Mechanical bending of the ac-TEs worsened the electrical performance by only ∼1.7% after 2000 bending cycles at a bending radius of 2.5 mm. Degradation of the performance by the bending was the result of line defects formation in the graphene, demonstrating the potential of the uniform CNT networks to achieve more efficient and flexible carbon-based TEs. Furthermore, the chemically-doped ac-TEs showed commercially suitable electronic and optical properties with much enhanced thermal stability, closer to practical TEs in flexible devices. - Highlights: • Highly efficient and bending durable all-carbon composite transparent electrodes (TEs) are designed. • The performance was strongly dependent on morphology of CNT networks on graphene. • The mechanism relies on the defect reductions in graphene by uniform CNT coating

Lightning and severe thunderstorms in event management.

Science.gov (United States)

Walsh, Katie M

2012-01-01

There are a few national position stands/guidelines that address environmental conditions in athletics, yet they do not govern all outdoor sports. Extreme heat and cold, lightning, and severe wind can all be fatal, yet the majority of outdoor sports have no published guidelines addressing these conditions in relation to activity. Available research on extreme heat and cold conditions in athletics provides prevention strategies, to include acclimatization. Lightning and severe wind are two environmental conditions to which humans cannot accommodate, and they both can be deadly. There are strong positions on extreme heat/cold and lightning safety in athletics, but none affiliated with severe winds. Medical personnel involved in planning large outdoor sporting events must know of the presence of nationally published weather-related documents and apply them to their event. In addition, research needs to be expanded in the realm of establishing guidelines for safety to participants and spectators in severe wind conditions.

Brain networks: small-worlds, after all?

International Nuclear Information System (INIS)

Muller, Lyle; Destexhe, Alain; Rudolph-Lilith, Michelle

2014-01-01

Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime. (paper)

Brain networks: small-worlds, after all?

Energy Technology Data Exchange (ETDEWEB)

Muller, Lyle; Destexhe, Alain; Rudolph-Lilith, Michelle [Unité de Neurosciences, Information et Complexité (UNIC), Centre National de la Recherche Scientifique (CNRS), 1 Avenue de la Terrasse, Gif-sur-Yvette (France)

2014-10-01

Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime. (paper)

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

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.

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

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.

Many multicenter trials had few events per center, requiring analysis via random-effects models or GEEs.

Science.gov (United States)

Kahan, Brennan C; Harhay, Michael O

2015-12-01

Adjustment for center in multicenter trials is recommended when there are between-center differences or when randomization has been stratified by center. However, common methods of analysis (such as fixed-effects, Mantel-Haenszel, or stratified Cox models) often require a large number of patients or events per center to perform well. We reviewed 206 multicenter randomized trials published in four general medical journals to assess the average number of patients and events per center and determine whether appropriate methods of analysis were used in trials with few patients or events per center. The median number of events per center/treatment arm combination for trials using a binary or survival outcome was 3 (interquartile range, 1-10). Sixteen percent of trials had less than 1 event per center/treatment combination, 50% fewer than 3, and 63% fewer than 5. Of the trials which adjusted for center using a method of analysis which requires a large number of events per center, 6% had less than 1 event per center-treatment combination, 25% fewer than 3, and 50% fewer than 5. Methods of analysis that allow for few events per center, such as random-effects models or generalized estimating equations (GEEs), were rarely used. Many multicenter trials contain few events per center. Adjustment for center using random-effects models or GEE with model-based (non-robust) standard errors may be beneficial in these scenarios. Copyright © 2015 Elsevier Inc. All rights reserved.

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,

Health in All Policies (HiAP) governance: lessons from network governance.

Science.gov (United States)

Khayatzadeh-Mahani, Akram; Ruckert, Arne; Labonté, Ronald; Kenis, Patrick; Akbari-Javar, Mohammad Reza

2018-05-25

The Health in All Policies (HiAP) approach requires formal and sustained governance structures and mechanisms to ensure that the policies of various non-health sectors maximize positive and minimize negative impacts on population health. In this paper, we demonstrate the usefulness of a network perspective in understanding and contributing to the effectiveness of HiAP. We undertook an exploratory, qualitative case study of a HiAP structure in Iran, the Kerman province Council of Health and Food Security (CHFS) with diverse members from health and non-health sectors. We analyzed relevant policy texts and interviewed 32 policy actors involved in the CHFS. Data were analyzed using within-case analysis and constant comparative methodology. Our findings suggest that CHFS governance from a network perspective drew in practice on elements of two competing network governance modes: the network administrative organization (NAO) and the lead organization mode. Our results also show that a shift from a hierarchical and market-based mode of interaction to a network logic within CHFS has not yet taken place. In addition, CHFS suffers from large membership and an inability to address complex 'wicked problems', as well as low trust, legitimacy and goal consensus among its members. Drawing on other HiAP studies and commentaries, insights from organization network theory, and in-depth findings from our case study, we conclude that a NAO may be the most effective mode of governance for tackling complex social problems in HiAP structures. Since similar studies are limited, and our single case study may not be transferable across all contexts, we suggest that further research be undertaken to explore HiAP structures from a network perspective in different institutional and cultural settings. With increasing emphasis given to HiAP approaches in national and international health policy discourse, it is important that comparative knowledge about the effectiveness of HiAP governance

The relationship of the factor V Leiden mutation or the deletion-deletion polymorphism of the angiotensin converting enzyme to postoperative thromboembolic events following total joint arthroplasty

Directory of Open Access Journals (Sweden)

Fang Carrie

2001-04-01

Full Text Available Abstract Background Although all patients undergoing total joint arthroplasty are subjected to similar risk factors that predispose to thromboembolism, only a subset of patients develop this complication. The objective of this study was to determine whether a specific genetic profile is associated with a higher risk of developing a postoperative thromboembolic complication. Specifically, we examined if the Factor V Leiden (FVL mutation or the deletion polymorphism of the angiotensin-converting enzyme (ACE gene increased a patient's risk for postoperative thromboembolic events. The FVL mutation has been associated with an increased risk of idiopathic thromboembolism and the deletion polymorphism of the ACE gene has been associated with increased vascular tone, attenuated fibrinolysis and increased platelet aggregation. Methods The presence of these genetic profiles was determined for 38 patients who had a postoperative symptomatic pulmonary embolus or proximal deep venous thrombosis and 241 control patients without thrombosis using molecular biological techniques. Results The Factor V Leiden mutation was present in none of the 38 experimental patients and in 3% or 8 of the 241 controls (p = 0.26. Similarly there was no difference detected in the distribution of polymorphisms for the ACE gene with the deletion-deletion genotype present in 36% or 13 of the 38 experimental patients and in 31% or 74 of the 241 controls (p = 0.32. Conclusions Our results suggest that neither of these potentially hypercoaguable states are associated with an increased risk of symptomatic thromboembolic events following total hip or knee arthroplasty in patients receiving pharmacological thromboprophylaxis.

Spatiotemporal Features for Asynchronous Event-based Data

Directory of Open Access Journals (Sweden)

Xavier eLagorce

2015-02-01

Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

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.

Fair Secure Computation with Reputation Assumptions in the Mobile Social Networks

Directory of Open Access Journals (Sweden)

Yilei Wang

2015-01-01

Full Text Available With the rapid development of mobile devices and wireless technologies, mobile social networks become increasingly available. People can implement many applications on the basis of mobile social networks. Secure computation, like exchanging information and file sharing, is one of such applications. Fairness in secure computation, which means that either all parties implement the application or none of them does, is deemed as an impossible task in traditional secure computation without mobile social networks. Here we regard the applications in mobile social networks as specific functions and stress on the achievement of fairness on these functions within mobile social networks in the presence of two rational parties. Rational parties value their utilities when they participate in secure computation protocol in mobile social networks. Therefore, we introduce reputation derived from mobile social networks into the utility definition such that rational parties have incentives to implement the applications for a higher utility. To the best of our knowledge, the protocol is the first fair secure computation in mobile social networks. Furthermore, it finishes within constant rounds and allows both parties to know the terminal round.

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.

Search for all d-MPs for all d levels in multistate two-terminal networks

International Nuclear Information System (INIS)

Bai, Guanghan; Zuo, Ming J.; Tian, Zhigang

2015-01-01

A general method for reliability evaluation of multistate network is using minimal path vectors. A minimal path (MP) vector to system state d is called a d-MP. Most reported works on generating d-MPs are for a particular d value. However, if all d-MPs for all possible integer d values are required, we need to call such methods multiple times with respect to all d values. A more efficient method is desirable to generate all d-MPs. In this paper, we develop a recursive algorithm based on breadth-first search to search for all the d-MPs for all possible d values. The relationships among d-MPs for different d levels are revealed. Each d-MP candidate can be generated by a combination of one (d-1)-MP and the vector form of one binary minimal path. Thus, we can use binary MPs as building blocks to generate 2-MP candidates, and use 2-MPs and binary MPs as building blocks to generate 3-MP candidates … and so forth. When the d-MPs with respect to the maximum d value have been found, all the d-MPs for all possible d values are obtained. A heuristic for pre-processing the MPs is proposed to improve the efficiency of the algorithm. Through computational experiments, it is found that the proposed algorithm is more efficient than existing algorithms for finding all d-MPs for all possible d values. In addition, we show that the proposed algorithm can also be used to generate a subset of d-MPs for all or some d values given a subset of MPs. The generated subset of d-MPs can be used for lower reliability bound evaluation. - Highlights: • The relationships among d-MPs for different d levels are revealed. • An efficient algorithm is developed to search for all d-MPs for all d levels. • A heuristic for pre-processing the MPs is proposed to improve the efficiency. • The computational efficiency of the algorithm is investigated. • A method to search for subsets of d-MPs is proposed for reliability bounding

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.

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.

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.

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.

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.

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.

Experimental demonstrations of all-optical networking functions for WDM optical networks

Science.gov (United States)

Gurkan, Deniz

The deployment of optical networks will enable high capacity links between users but will introduce the problems associated with transporting and managing more channels. Many network functions should be implemented in optical domain; main reasons are: to avoid electronic processing bottlenecks, to achieve data-format and data-rate independence, to provide reliable and cost efficient control and management information, to simultaneously process multiple wavelength channel operation for wavelength division multiplexed (WDM) optical networks. The following novel experimental demonstrations of network functions in the optical domain are presented: Variable-bit-rate recognition of the header information in a data packet. The technique is reconfigurable for different header sequences and uses optical correlators as look-up tables. The header is processed and a signal is sent to the switch for a series of incoming data packets at 155 Mb/s, 622 Mb/s, and 2.5 Gb/s in a reconfigurable network. Simultaneous optical time-slot-interchange and wavelength conversion of the bits in a 2.5-Gb/s data stream to achieve a reconfigurable time/wavelength switch. The technique uses difference-frequency-generation (DFG) for wavelength conversion and fiber Bragg gratings (FBG) as wavelength-dependent optical time buffers. The WDM header recognition module simultaneously recognizing two header bits on each of two 2.5-Gbit/s WDM packet streams. The module is tunable to enable reconfigurable look-up tables. Simultaneous and independent label swapping and wavelength conversion of two WDM channels for a multi-protocol label switching (MPLS) network. Demonstration of label swapping of distinct 8-bit-long labels for two WDM data channels is presented. Two-dimensional code conversion module for an optical code-division multiple-access (O-CDMA) local area network (LAN) system. Simultaneous wavelength conversion and time shifting is achieved to enable flexible code conversion and increase code re

Network Structure and Community Evolution on Twitter: Human Behavior Change in Response to the 2011 Japanese Earthquake and Tsunami

Science.gov (United States)

Lu, Xin; Brelsford, Christa

2014-10-01

To investigate the dynamics of social networks and the formation and evolution of online communities in response to extreme events, we collected three datasets from Twitter shortly before and after the 2011 earthquake and tsunami in Japan. We find that while almost all users increased their online activity after the earthquake, Japanese speakers, who are assumed to be more directly affected by the event, expanded the network of people they interact with to a much higher degree than English speakers or the global average. By investigating the evolution of communities, we find that the behavior of joining or quitting a community is far from random: users tend to stay in their current status and are less likely to join new communities from solitary or shift to other communities from their current community. While non-Japanese speakers did not change their conversation topics significantly after the earthquake, nearly all Japanese users changed their conversations to earthquake-related content. This study builds a systematic framework for investigating human behaviors under extreme events with online social network data and our findings on the dynamics of networks and communities may provide useful insight for understanding how patterns of social interaction are influenced by extreme events.

Not all past events are equal: biased attention and emerging heuristics in children's past-to-future forecasting.

Science.gov (United States)

Lagattuta, Kristin Hansen; Sayfan, Liat

2013-01-01

Four- to 10-year-olds and adults (N = 265) responded to eight scenarios presented on an eye tracker. Each trial involved a character who encounters a perpetrator who had previously enacted positive (P), negative (N), or both types of actions toward him or her in varying sequences (NN, PP, PN, and NP). Participants predicted the character's thoughts about the likelihood of future events, emotion type and intensity, and decision to approach or avoid. All ages made more positive forecasts for PP > NP > PN > NN trials, with differentiation by past experience widening with age. Age-related increases in weighting the most recent past event also appeared in eye gaze. Individual differences in biased visual attention correlated with verbal judgments. Findings contribute to research on risk assessment, person perception, and heuristics in judgment and decision making. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Blunt splenic injury: are early adverse events related to trauma, nonoperative management, or surgery?

Science.gov (United States)

Frandon, Julien; Rodiere, Mathieu; Arvieux, Catherine; Vendrell, Anne; Boussat, Bastien; Sengel, Christian; Broux, Christophe; Bricault, Ivan; Ferretti, Gilbert; Thony, Frédéric

2015-01-01

PURPOSE We aimed to compare clinical outcomes and early adverse events of operative management (OM), nonoperative management (NOM), and NOM with splenic artery embolization (SAE) in blunt splenic injury (BSI) and identify the prognostic factors. METHODS Medical records of 136 consecutive patients with BSI admitted to a trauma center from 2005 to 2010 were retrospectively reviewed. Patients were separated into three groups: OM, NOM, and SAE. We focused on associated injuries and early adverse events. Multivariate analysis was performed on 23 prognostic factors to find predictors. RESULTS The total survival rate was 97.1%, with four deaths all occurred in the OM group. The spleen salvage rate was 91% in NOM and SAE. At least one adverse event was observed in 32.8%, 62%, and 96% of patients in NOM, SAE, and OM groups, respectively (P < 0.001). We found significantly more deaths, infectious complications, pleural drainage, acute renal failures, and pancreatitis in OM and more pseudocysts in SAE. Six prognostic factors were statistically significant for one or more adverse events: simplified acute physiology score 2 ≥25 for almost all adverse events, age ≥50 years for acute respiratory syndrome, limb fracture for secondary bleeding, thoracic injury for pleural drainage, and at least one associated injury for pseudocyst. Adverse events were not related to the type of BSI management. CONCLUSION Patients with BSI present worse outcome and more adverse events in OM, but this is related to the severity of injury. The main predictor of adverse events remains the severity of injury. PMID:26081719

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.

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

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

Science.gov (United States)

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

Science.gov (United States)

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

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...

Dynamics of pollutant discharge in combined sewer systems during rain events: chance or determinism?

Science.gov (United States)

Hannouche, A; Chebbo, G; Joannis, C

2014-01-01

A large database of continuous flow and turbidity measurements cumulating data on hundreds of rain events and dry weather days from two sites in Paris (called Quais and Clichy) and one in Lyon (called Ecully) is presented. This database is used to characterize and compare the behaviour of the three sites at the inter-events scale. The analysis is probed through three various variables: total volumes and total suspended solids (TSS) masses and concentrations during both wet and dry weather periods in addition to the contributions of diverse-origin sources to event flow volume and TSS load values. The results obtained confirm the previous findings regarding the spatial consistency of TSS fluxes and concentrations between both sites in Paris having similar land uses. Moreover, masses and concentrations are proven to be correlated between Parisian sites in a way that implies the possibility of some deterministic processes being reproducible from one catchment to another for a particular rain event. The results also demonstrate the importance of the contribution of wastewater and sewer deposits to the total events' loads and show that such contributions are not specific to Paris sewer networks.

Neural network pattern recognition of lingual-palatal pressure for automated detection of swallow.

Science.gov (United States)

Hadley, Aaron J; Krival, Kate R; Ridgel, Angela L; Hahn, Elizabeth C; Tyler, Dustin J

2015-04-01

We describe a novel device and method for real-time measurement of lingual-palatal pressure and automatic identification of the oral transfer phase of deglutition. Clinical measurement of the oral transport phase of swallowing is a complicated process requiring either placement of obstructive sensors or sitting within a fluoroscope or articulograph for recording. Existing detection algorithms distinguish oral events with EMG, sound, and pressure signals from the head and neck, but are imprecise and frequently result in false detection. We placed seven pressure sensors on a molded mouthpiece fitting over the upper teeth and hard palate and recorded pressure during a variety of swallow and non-swallow activities. Pressure measures and swallow times from 12 healthy and 7 Parkinson's subjects provided training data for a time-delay artificial neural network to categorize the recordings as swallow or non-swallow events. User-specific neural networks properly categorized 96 % of swallow and non-swallow events, while a generalized population-trained network was able to properly categorize 93 % of swallow and non-swallow events across all recordings. Lingual-palatal pressure signals are sufficient to selectively and specifically recognize the initiation of swallowing in healthy and dysphagic patients.

Staged Event-Driven Architecture As A Micro-Architecture Of Distributed And Pluginable Crawling Platform

Directory of Open Access Journals (Sweden)

Leszek Siwik

2013-01-01

Full Text Available There are many crawling systems available on the market but they are rather close systems dedicated for performing particular kind and class of tasks with predefined set of scope, strategy etc. In real life however there are meaningful groups of users (e.g. marketing, criminal or governmental analysts requiring not just a yet another crawling system dedicated for performing predefined tasks. They need rather easy-to-use, user friendly all-in-one studio for not only executing and running internet robots and crawlers, but also for (graphical (redefining and (recomposing crawlers according to dynamically changing requirements and use-cases. To realize the above-mentioned idea, Cassiopeia framework has been designed and developed. One has to remember, however, that enormous size and unimaginable structural complexity of WWW network are the reasons that, from a technical and architectural point of view, developing effective internet robots – and the more so developing a framework supporting graphical robots’ composition – becomes a really challenging task. The crucial aspect in the context of crawling efficiency and scalability is concurrency model applied. There are two the most typical concurrency management models i.e. classical concurrency based on the pool of threads and processes and event-driven concurrency. None of them are ideal approaches. That is why, research on alternative models is still conducted to propose efficient and convenient architecture for concurrent and distributed applications. One of promising models is staged event-driven architecture mixing to some extent both of above mentioned classical approaches and providing some additional benefits such as splitting application into separate stages connected by events queues – what is interesting taking requirements about crawler (recomposition into account. The goal of this paper is to present the idea and the PoC  implementation of Cassiopeia framework, with the special

Experimental Seismic Event-screening Criteria at the Prototype International Data Center

Science.gov (United States)

Fisk, M. D.; Jepsen, D.; Murphy, J. R.

- Experimental seismic event-screening capabilities are described, based on the difference of body-and surface-wave magnitudes (denoted as Ms:mb) and event depth. These capabilities have been implemented and tested at the prototype International Data Center (PIDC), based on recommendations by the IDC Technical Experts on Event Screening in June 1998. Screening scores are presented that indicate numerically the degree to which an event meets, or does not meet, the Ms:mb and depth screening criteria. Seismic events are also categorized as onshore, offshore, or mixed, based on their 90% location error ellipses and an onshore/offshore grid with five-minute resolution, although this analysis is not used at this time to screen out events.Results are presented of applications to almost 42,000 events with mb>=3.5 in the PIDC Standard Event Bulletin (SEB) and to 121 underground nuclear explosions (UNE's) at the U.S. Nevada Test Site (NTS), the Semipalatinsk and Novaya Zemlya test sites in the Former Soviet Union, the Lop Nor test site in China, and the Indian, Pakistan, and French Polynesian test sites. The screening criteria appear to be quite conservative. None of the known UNE's are screened out, while about 41 percent of the presumed earthquakes in the SEB with mb>=3.5 are screened out. UNE's at the Lop Nor, Indian, and Pakistan test sites on 8 June 1996, 11 May 1998, and 28 May 1998, respectively, have among the lowest Ms:mb scores of all events in the SEB.To assess the validity of the depth screening results, comparisons are presented of SEB depth solutions to those in other bulletins that are presumed to be reliable and independent. Using over 1600 events, the comparisons indicate that the SEB depth confidence intervals are consistent with or shallower than over 99.8 percent of the corresponding depth estimates in the other bulletins. Concluding remarks are provided regarding the performance of the experimental event-screening criteria, and plans for future

Scaling a network with positive gains to a lossy or gainy network

NARCIS (Netherlands)

Koene, J.

1979-01-01

Necessary and sufficient conditions are presented under which it is possible to scale a network with positive gains to a lossy or a gainy network. A procedure to perform such a scaling operation is given.

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)

Computing chemical organizations in biological networks.

Science.gov (United States)

Centler, Florian; Kaleta, Christoph; di Fenizio, Pietro Speroni; Dittrich, Peter

2008-07-15

Novel techniques are required to analyze computational models of intracellular processes as they increase steadily in size and complexity. The theory of chemical organizations has recently been introduced as such a technique that links the topology of biochemical reaction network models to their dynamical repertoire. The network is decomposed into algebraically closed and self-maintaining subnetworks called organizations. They form a hierarchy representing all feasible system states including all steady states. We present three algorithms to compute the hierarchy of organizations for network models provided in SBML format. Two of them compute the complete organization hierarchy, while the third one uses heuristics to obtain a subset of all organizations for large models. While the constructive approach computes the hierarchy starting from the smallest organization in a bottom-up fashion, the flux-based approach employs self-maintaining flux distributions to determine organizations. A runtime comparison on 16 different network models of natural systems showed that none of the two exhaustive algorithms is superior in all cases. Studying a 'genome-scale' network model with 762 species and 1193 reactions, we demonstrate how the organization hierarchy helps to uncover the model structure and allows to evaluate the model's quality, for example by detecting components and subsystems of the model whose maintenance is not explained by the model. All data and a Java implementation that plugs into the Systems Biology Workbench is available from http://www.minet.uni-jena.de/csb/prj/ot/tools.

Reverse engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL.

Science.gov (United States)

Della Gatta, Giusy; Palomero, Teresa; Perez-Garcia, Arianne; Ambesi-Impiombato, Alberto; Bansal, Mukesh; Carpenter, Zachary W; De Keersmaecker, Kim; Sole, Xavier; Xu, Luyao; Paietta, Elisabeth; Racevskis, Janis; Wiernik, Peter H; Rowe, Jacob M; Meijerink, Jules P; Califano, Andrea; Ferrando, Adolfo A

2012-02-26

The TLX1 and TLX3 transcription factor oncogenes have a key role in the pathogenesis of T cell acute lymphoblastic leukemia (T-ALL). Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This systems biology analysis defined T cell leukemia homeobox 1 (TLX1) and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, a network structure analysis of this hierarchical network identified RUNX1 as a key mediator of the T-ALL induced by TLX1 and TLX3 and predicted a tumor-suppressor role for RUNX1 in T cell transformation. Consistent with these results, we identified recurrent somatic loss-of-function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 at the top of an oncogenic transcriptional network controlling leukemia development, show the power of network analyses to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor-suppressor gene in T-ALL.

No increase in autism-associated genetic events in children conceived by assisted reproduction.

Science.gov (United States)

Ackerman, Sean; Wenegrat, Julia; Rettew, David; Althoff, Robert; Bernier, Raphael

2014-08-01

To understand the rate of genetic events in patients with autism spectrum disorder (ASD) who were exposed to assisted reproduction. Case control study using genetics data. Twelve collaborating data collection sites across North America as part of the Simons Simplex Collection. 2,760 children with ASD, for whom 1,994 had published copy number variation data and 424 had published gene mutation status available. None. Rates of autism-associated genetic events in children with ASD conceived with assisted reproduction versus those conceived naturally. No statistically significant differences in copy number variations or autism-associated gene-disrupting events were found when comparing ASD patients exposed to assisted reproduction with those not exposed to assisted reproduction. This is the first large genetic association to concurrently examine the genotype of individuals with ASD in relation to their exposure to ART versus natural conception, and it adds reassuring evidence to the argument that ART does not increase the risk of ASD. Copyright © 2014 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

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

the events and the type and quality of information exchanged among the parties concerned (TSOs and Swiss electric utilities), both before and during the events. Subsequently, SFOE failed to deliver any information, either written or verbal, and proposed adopting the UCTE interim report, issued by UCTE on October 27, as the sole source of information for the investigation concerning the Swiss transmission grids. Furthermore, SFOE required the French and Italian TSOs and the integrated Swiss electricity companies to take part in the inquiry. AEEG and CRE could therefore not agree on the organisation of the investigation proposed by SFOE: they believed that the aforementioned participation was not compatible with the necessary independence of their inquiry. Moreover, on November 20, SFOE independently and unilaterally issued a Report on the black-out in Italy on September 28, 2003, without previously consulting AEEG and CRE. Following the afore mentioned unilateral position AEEG and CRE therefore decided to continue the investigation without SFOE and, in a letter dated December 1, signed by respective Directors of AEEG and CRE, invited the integrated Swiss electricity companies directly to provide the same information already requested and obtained from the Italian and French TSOs. In a letter from Swiss Electric dated December 23, the integrated Swiss electricity companies refused to submit information to the regulators' enquiry and stated that all relevant information had already been released for other investigations (e.g., UCTE investigation, SFOE investigation and Italian Government investigation). In spite of the absence of data from the Swiss parties, the amount and quality of information gathered from the Italian and French TSOs however enabled AEEG and CRE to reach a good and fair understanding of the events and the operational procedures jointly adopted by all the system operators involved. The information retrieved by AEEG and CRE also provided a mean of

Assessment of Adverse Events in Protocols, Clinical Study Reports, and Published Papers of Trials of Orlistat: A Document Analysis.

Directory of Open Access Journals (Sweden)

Jeppe Bennekou Schroll

2016-08-01

Full Text Available Little is known about how adverse events are summarised and reported in trials, as detailed information is usually considered confidential. We have acquired clinical study reports (CSRs from the European Medicines Agency through the Freedom of Information Act. The CSRs describe the results of studies conducted as part of the application for marketing authorisation for the slimming pill orlistat. The purpose of this study was to study how adverse events were summarised and reported in study protocols, CSRs, and published papers of orlistat trials.We received the CSRs from seven randomised placebo controlled orlistat trials (4,225 participants submitted by Roche. The CSRs consisted of 8,716 pages and included protocols. Two researchers independently extracted data on adverse events from protocols and CSRs. Corresponding published papers were identified on PubMed and adverse event data were extracted from this source as well. All three sources were compared. Individual adverse events from one trial were summed and compared to the totals in the summary report. None of the protocols or CSRs contained instructions for investigators on how to question participants about adverse events. In CSRs, gastrointestinal adverse events were only coded if the participant reported that they were "bothersome," a condition that was not specified in the protocol for two of the trials. Serious adverse events were assessed for relationship to the drug by the sponsor, and all adverse events were coded by the sponsor using a glossary that could be updated by the sponsor. The criteria for withdrawal due to adverse events were in one case related to efficacy (high fasting glucose led to withdrawal, which meant that one trial had more withdrawals due to adverse events in the placebo group. Finally, only between 3% and 33% of the total number of investigator-reported adverse events from the trials were reported in the publications because of post hoc filters, though six of

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

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

Synchronization Algorithm for SDN-controlled All-Optical TDM Switching in a Random Length Ring Network

DEFF Research Database (Denmark)

Kamchevska, Valerija; Cristofori, Valentina; Da Ros, Francesco

2016-01-01

We propose and demonstrate an algorithm that allows for automatic synchronization of SDN-controlled all-optical TDM switching nodes connected in a ring network. We experimentally show successful WDM-SDM transmission of data bursts between all ring nodes.......We propose and demonstrate an algorithm that allows for automatic synchronization of SDN-controlled all-optical TDM switching nodes connected in a ring network. We experimentally show successful WDM-SDM transmission of data bursts between all ring nodes....

To Break or to Brake Neuronal Network Accelerated by Ammonium Ions?

Directory of Open Access Journals (Sweden)

Vladimir V Dynnik

Full Text Available The aim of present study was to investigate the effects of ammonium ions on in vitro neuronal network activity and to search alternative methods of acute ammonia neurotoxicity prevention.Rat hippocampal neuronal and astrocytes co-cultures in vitro, fluorescent microscopy and perforated patch clamp were used to monitor the changes in intracellular Ca2+- and membrane potential produced by ammonium ions and various modulators in the cells implicated in neural networks.Low concentrations of NH4Cl (0.1-4 mM produce short temporal effects on network activity. Application of 5-8 mM NH4Cl: invariably transforms diverse network firing regimen to identical burst patterns, characterized by substantial neuronal membrane depolarization at plateau phase of potential and high-amplitude Ca2+-oscillations; raises frequency and average for period of oscillations Ca2+-level in all cells implicated in network; results in the appearance of group of «run out» cells with high intracellular Ca2+ and steadily diminished amplitudes of oscillations; increases astrocyte Ca2+-signalling, characterized by the appearance of groups of cells with increased intracellular Ca2+-level and/or chaotic Ca2+-oscillations. Accelerated network activity may be suppressed by the blockade of NMDA or AMPA/kainate-receptors or by overactivation of AMPA/kainite-receptors. Ammonia still activate neuronal firing in the presence of GABA(A receptors antagonist bicuculline, indicating that «disinhibition phenomenon» is not implicated in the mechanisms of networks acceleration. Network activity may also be slowed down by glycine, agonists of metabotropic inhibitory receptors, betaine, L-carnitine, L-arginine, etc.Obtained results demonstrate that ammonium ions accelerate neuronal networks firing, implicating ionotropic glutamate receptors, having preserved the activities of group of inhibitory ionotropic and metabotropic receptors. This may mean, that ammonia neurotoxicity might be prevented by

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.

Characterizing Topology of Probabilistic Biological Networks.

Science.gov (United States)

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-09-06

Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.

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

Energy Technology Data Exchange (ETDEWEB)

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

2005-01-01

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

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

International Nuclear Information System (INIS)

Abbenseth, S; Lochmann, S I

2005-01-01

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

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.

All-optical two-way relaying free-space optical communications for HAP-based broadband backhaul networks

Science.gov (United States)

Vu, Minh Q.; Nguyen, Nga T. T.; Pham, Hien T. T.; Dang, Ngoc T.

2018-03-01

High-altitude platforms (HAPs) are flexible, non-pollutant and cost-effective infrastructures compared to satellite or old terrestrial systems. They are being researched and developed widely in Europe, USA, Japan, Korea, and so on. However, the current limited data rates and the overload of radio frequency (RF) spectrum are problems which the developers for HAPs are confronting because most of them use RF links to communicate with the ground stations (GSs) or each other. In this paper, we propose an all-optical two-way half-duplex relaying free-space optical (FSO) communication for HAP-based backhaul networks, which connect the base transceiver station (BTS) to the core network (CN) via a single HAP. Our proposed backhaul solution can be deployed quickly and flexibly for disaster relief and for serving users in both urban environments and remote areas. The key subsystem of HAP is an optical regenerate-and-forward (ORF) equipped with an optical hard-limiter (OHL) and an optical XOR gate to perform all-optical processing and help mitigate the background noise. In addition, two-way half-duplex relaying can be provided thanks to the use of network coding scheme. The closed-form expression for the bit error rate (BER) of our proposed system under the effect of path loss, atmospheric turbulence, and noise induced by the background light is formulated. The numerical results are demonstrated to prove the feasibility of our proposed system with the verification by using Monte-Carlo (M-C) simulations.

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.

System markets: Indirect network effects in action, or inaction?

NARCIS (Netherlands)

J.L.G. Binken (Jeroen)

2010-01-01

textabstractIn this dissertation, I empirically examine system markets up close. More specifically I examine indirect network effects, both demand-side and supply-side indirect network effects. Indirect network effects are the source of positive feedback in system markets, or so network effect

Small-Firm Networks: hybrid arrangement or organizational form?

OpenAIRE

Verschoore, Jorge Renato; Balestrin, Alsones; Perucia, Alexandre

2014-01-01

In the field of organizations, one relevant question is whether or not to consider networks as organizational forms. On the one hand, Williamson (1985) says that networks are hybrid arrangements. On the other, authors like Powell (1990) argue that networks constitute themselves as organizational forms. Given this dilemma, the present article proposes the analysis of organizational characteristics of small-firm networks (SFN). To reach such objective, twelve SFNs in distinct stages of developm...

M-Burst: A Framework of SRLG Failure Localization in All-Optical Networks

KAUST Repository

Ali, Mohammed L.

2012-07-27

Fast and unambiguous failure localization for shared risk link groups (SRLGs) with multiple links is essential for building a fully survivable and functional transparent all-optical mesh network. Monitoring trails (m-trails) have been proposed as an effective approach to achieve this goal. However, each m-trail traverses through each link by constantly taking a wavelength channel, causing a significant amount of resource consumption. In this paper, a novel framework of all-optical monitoring for SRLG failure localization is proposed. We investigate the feasibility of periodically launching optical bursts along each m-trail instead of assigning it a dedicated supervisory lightpath to probe the set of fiber segments along the m-trail, aiming to achieve a graceful compromise between resource consumption and failure localization latency. This paper defines the proposed framework and highlights the relevant issues regarding its feasibility. We provide theoretical justifications of the scheme. As a proof of concept, we formulate the optimal burst scheduling problem via an integer linear program (ILP) and implement the method in networks of all possible SRLGs with up to d=3 links. A heuristic method is also proposed and implemented for multiple-link SRLG failure localization, keeping all the assumptions the same as in the ILP method. Numerical results for small networks show that the scheme is able to localize single-link and multiple-link SRLG failures unambiguously with a very small amount of failure localization latency.

Computing return times or return periods with rare event algorithms

Science.gov (United States)

Lestang, Thibault; Ragone, Francesco; Bréhier, Charles-Edouard; Herbert, Corentin; Bouchet, Freddy

2018-04-01

The average time between two occurrences of the same event, referred to as its return time (or return period), is a useful statistical concept for practical applications. For instance insurances or public agencies may be interested by the return time of a 10 m flood of the Seine river in Paris. However, due to their scarcity, reliably estimating return times for rare events is very difficult using either observational data or direct numerical simulations. For rare events, an estimator for return times can be built from the extrema of the observable on trajectory blocks. Here, we show that this estimator can be improved to remain accurate for return times of the order of the block size. More importantly, we show that this approach can be generalised to estimate return times from numerical algorithms specifically designed to sample rare events. So far those algorithms often compute probabilities, rather than return times. The approach we propose provides a computationally extremely efficient way to estimate numerically the return times of rare events for a dynamical system, gaining several orders of magnitude of computational costs. We illustrate the method on two kinds of observables, instantaneous and time-averaged, using two different rare event algorithms, for a simple stochastic process, the Ornstein–Uhlenbeck process. As an example of realistic applications to complex systems, we finally discuss extreme values of the drag on an object in a turbulent flow.

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. ...

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.

Lifetime trauma exposure and prospective cardiovascular events and all-cause mortality: findings from the Heart and Soul Study.

Science.gov (United States)

Hendrickson, Carolyn M; Neylan, Thomas C; Na, Beeya; Regan, Mathilda; Zhang, Qian; Cohen, Beth E

2013-01-01

Little is known about the effect of cumulative psychological trauma on health outcomes in patients with cardiovascular disease. The objective of this study was to prospectively examine the association between lifetime trauma exposure and recurrent cardiovascular events or all-cause mortality in patients with existing cardiovascular disease. A total of 1021 men and women with cardiovascular disease were recruited in 2000 to 2002 and followed annually. Trauma history and psychiatric comorbidities were assessed at baseline using the Computerized Diagnostic Interview Schedule for DSM-IV. Health behaviors were assessed using standardized questionnaires. Outcome data were collected annually, and all medical records were reviewed by two independent, blinded physician adjudicators. We used Cox proportional hazards models to evaluate the association between lifetime trauma exposure and the composite outcome of cardiovascular events and all-cause mortality. During an average of 7.5 years of follow-up, there were 503 cardiovascular events and deaths. Compared with the 251 participants in the lowest trauma exposure quartile, the 256 participants in the highest exposure quartile had a 38% greater risk of adverse outcomes (hazard ratio = 1.38, 95% confidence interval = 1.06-1.81), adjusted for age, sex, race, income, education, depression, posttraumatic stress disorder, generalized anxiety disorder, smoking, physical inactivity, and illicit drug abuse. Cumulative exposure to psychological trauma was associated with an increased risk of recurrent cardiovascular events and mortality, independent of psychiatric comorbidities and health behaviors. These data add to a growing literature showing enduring effects of repeated trauma exposure on health that are independent of trauma-related psychiatric disorders such as depression and posttraumatic stress disorder.

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.

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.

On Event/Time Triggered and Distributed Analysis of a WSN System for Event Detection, Using Fuzzy Logic

Directory of Open Access Journals (Sweden)

Sofia Maria Dima

2016-01-01

Full Text Available Event detection in realistic WSN environments is a critical research domain, while the environmental monitoring comprises one of its most pronounced applications. Although efforts related to the environmental applications have been presented in the current literature, there is a significant lack of investigation on the performance of such systems, when applied in wireless environments. Aiming at addressing this shortage, in this paper an advanced multimodal approach is followed based on fuzzy logic. The proposed fuzzy inference system (FIS is implemented on TelosB motes and evaluates the probability of fire detection while aiming towards power conservation. Additionally to a straightforward centralized approach, a distributed implementation of the above FIS is also proposed, aiming towards network congestion reduction while optimally distributing the energy consumption among network nodes so as to maximize network lifetime. Moreover this work proposes an event based execution of the aforementioned FIS aiming to further reduce the computational as well as the communication cost, compared to a periodical time triggered FIS execution. As a final contribution, performance metrics acquired from all the proposed FIS implementation techniques are thoroughly compared and analyzed with respect to critical network conditions aiming to offer realistic evaluation and thus objective conclusions’ extraction.

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

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.

Long-running telemedicine networks delivering humanitarian services: experience, performance and scientific output

Science.gov (United States)

Geissbuhler, Antoine; Jethwani, Kamal; Kovarik, Carrie; Person, Donald A; Vladzymyrskyy, Anton; Zanaboni, Paolo; Zolfo, Maria

2012-01-01

Abstract Objective To summarize the experience, performance and scientific output of long-running telemedicine networks delivering humanitarian services. Methods Nine long-running networks – those operating for five years or more– were identified and seven provided detailed information about their activities, including performance and scientific output. Information was extracted from peer-reviewed papers describing the networks’ study design, effectiveness, quality, economics, provision of access to care and sustainability. The strength of the evidence was scored as none, poor, average or good. Findings The seven networks had been operating for a median of 11 years (range: 5–15). All networks provided clinical tele-consultations for humanitarian purposes using store-and-forward methods and five were also involved in some form of education. The smallest network had 15 experts and the largest had more than 500. The clinical caseload was 50 to 500 cases a year. A total of 59 papers had been published by the networks, and 44 were listed in Medline. Based on study design, the strength of the evidence was generally poor by conventional standards (e.g. 29 papers described non-controlled clinical series). Over half of the papers provided evidence of sustainability and improved access to care. Uncertain funding was a common risk factor. Conclusion Improved collaboration between networks could help attenuate the lack of resources reported by some networks and improve sustainability. Although the evidence base is weak, the networks appear to offer sustainable and clinically useful services. These findings may interest decision-makers in developing countries considering starting, supporting or joining similar telemedicine networks. PMID:22589567

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

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...

WIRED World Wide Web Interactive Remote Event Display

CERN Document Server

Ballaminut, A; Dönszelmann, M; Van Herwijnen, Eric; Köper, D; Korhonen, J; Litmaath, M; Perl, J; Theodorou, A; Whiteson, D; Wolff, E

2000-01-01

WIRED is a framework, written in Java, to build High Energy Physics event displays that can be used across the network. To guarantee portability across all platforms, WIRED is implemented in the Java language and uses the Swing user interface component set. It can be used as a stand-alone application or as an applet inside a WWW browser. The graphical user interface allows for multiple views and for multiple controls acting on those views. A detector tree control is available to toggle the visibility of parts of the events and detector geometry. XML (Extensible Markup Language), RMI (Remote Method Invocation) and CORBA loaders can be used to load event data as well as geometry data, and to connect to FORTRAN, C, C++ and Java reconstruction programs. Non-linear and non-Cartesian projections (e.g. fish-eye, rho-phi, rho-Z, phi-Z) provide special views to get a better understanding of events. WIRED has grown to be a framework in use and under development in several HEP experiments (ATLAS, CHORUS, DELPHI, LHCb, B...

Aftershocks of the India Republic Day Earthquake: the MAEC/ISTAR Temporary Seismograph Network

Science.gov (United States)

Bodin, P.; Horton, S.; Johnston, A.; Patterson, G.; Bollwerk, J.; Rydelek, P.; Steiner, G.; McGoldrick, C.; Budhbhatti, K. P.; Shah, R.; Macwan, N.

2001-05-01

The MW=7.7 Republic Day (26 January, 2001) earthquake on the Kachchh in western India initiated a strong sequence of small aftershocks. Seventeen days following the mainshock, we deployed a network of portable digital event recorders as a cooperative project of the Mid America Earthquake Center in the US and the Institute for Scientific and Technological Advanced Research. Our network consisted of 8 event-triggered Kinemetrics K2 seismographs with 6 data channels (3 accelerometer, 3 Mark L-28/3d seismometer) sampled at 200 Hz, and one continuously-recording Guralp CMG40TD broad-band seismometer sampled at 220 Hz. This network was in place for 18 days. Underlying our network deployment was the notion that because of its tectonic and geologic setting the Republic Day earthquake and its aftershocks might have source and/or propagation characteristics common to earthquakes in stable continental plate-interiors rather than those on plate boundaries or within continental mobile belts. Thus, our goals were to provide data that could be used to compare the Republic Day earthquake with other earthquakes. In particular, the objectives of our network deployment were: (1) to characterize the spatial distribution and occurrence rates of aftershocks, (2) to examine source characteristics of the aftershocks (stress-drops, focal mechanisms), (3) to study the effect of deep unconsolidated sediment on wave propagation, and (4) to determine if other faults (notably the Allah Bundh) were simultaneously active. Most of our sites were on Jurassic bedrock, and all were either free-field, or on the floor of light structures built on rock or with a thin soil cover. However, one of our stations was on a section of unconsolidated sediments hundreds of meters thick adjacent to a site that was subjected to shaking-induced sediment liquefaction during the mainshock. The largest aftershock reported by global networks was an MW=5.9 event on January 28, prior to our deployment. The largest

Personal and Impersonal Stimuli Differentially Engage Brain Networks during Moral Reasoning

Science.gov (United States)

Xue, Shao-Wei; Wang, Yan; Tang, Yi-Yuan

2013-01-01

Moral decision making has recently attracted considerable attention as a core feature of all human endeavors. Previous functional magnetic resonance imaging studies about moral judgment have identified brain areas associated with cognitive or emotional engagement. Here, we applied graph theory-based network analysis of event-related potentials…

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.

Early Obstacle Detection and Avoidance for All to All Traffic Pattern in Wireless Sensor Networks

Science.gov (United States)

Huc, Florian; Jarry, Aubin; Leone, Pierre; Moraru, Luminita; Nikoletseas, Sotiris; Rolim, Jose

This paper deals with early obstacles recognition in wireless sensor networks under various traffic patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a constant factor of 2π + 1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.

CareTrack Kids—part 3. Adverse events in children's healthcare in Australia: study protocol for a retrospective medical record review

Science.gov (United States)

Hibbert, Peter D; Hallahan, Andrew R; Muething, Stephen E; Lachman, Peter; Hooper, Tamara D; Wiles, Louise K; Jaffe, Adam; White, Les; Wheaton, Gavin R; Runciman, William B; Dalton, Sarah; Williams, Helena M; Braithwaite, Jeffrey

2015-01-01

Introduction A high-quality health system should deliver care that is free from harm. Few large-scale studies of adverse events have been undertaken in children's healthcare internationally, and none in Australia. The aim of this study is to measure the frequency and types of adverse events encountered in Australian paediatric care in a range of healthcare settings. Methods and analysis A form of retrospective medical record review, the Institute of Healthcare Improvement's Global Trigger Tool, will be modified to collect data. Records of children aged <16 years managed during 2012 and 2013 will be reviewed. We aim to review 6000–8000 records from a sample of healthcare practices (hospitals, general practices and specialists). Ethics and dissemination Human Research Ethics Committee approvals have been received from the Sydney Children's Hospital Network, Children's Health Queensland Hospital and Health Service, and the Women's and Children's Hospital Network in South Australia. An application is under review with the Royal Australian College of General Practitioners. The authors will submit the results of the study to relevant journals and undertake national and international oral presentations to researchers, clinicians and policymakers. PMID:25854978

Post-conflict struggles as networks of problems: A network analysis of trauma, daily stressors and psychological distress among Sri Lankan war survivors.

Science.gov (United States)

Jayawickreme, Nuwan; Mootoo, Candace; Fountain, Christine; Rasmussen, Andrew; Jayawickreme, Eranda; Bertuccio, Rebecca F

2017-10-01

A growing body of literature indicates that the mental distress experienced by survivors of war is a function of both experienced trauma and stressful life events. However, the majority of these studies are limited in that they 1) employ models of psychological distress that emphasize underlying latent constructs and do not allow researchers to examine the unique associations between particular symptoms and various stressors; and 2) use one or more measures that were not developed for that particular context and thus may exclude key traumas, stressful life events and symptoms of psychopathology. The current study addresses both these limitations by 1) using a novel conceptual model, network analysis, which assumes that symptoms covary with each other not because they stem from a latent construct, but rather because they represent meaningful relationships between the symptoms; and 2) employing a locally developed measure of experienced trauma, stressful life problems and symptoms of psychopathology. Over the course of 2009-2011, 337 survivors of the Sri Lankan civil war were administered the Penn-RESIST-Peradeniya War Problems Questionnaire (PRPWPQ). Network analysis revealed that symptoms of psychopathology, problems pertaining to lack of basic needs, and social problems were central to the network relative to experienced trauma and other types of problems. After controlling for shared associations, social problems in particular were the most central, significantly more so than traumatic events and family problems. Several particular traumatic events, stressful life events and symptoms of psychopathology that were central to the network were also identified. Discussion emphasizes the utility of such network models to researchers and practitioners determining how to spend limited resources in the most impactful way possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

NOAA Weather Radio - All Hazards

Science.gov (United States)

Non-Zero All Hazards Logo Emergency Alert Description Event Codes Fact Sheet FAQ Organization Search -event information for all types of hazards: weather (e.g., tornadoes, floods), natural (e.g Management or Preparedness, civil defense, police or mayor/commissioner sets up linkages to send messages on

M-Burst: A Framework of SRLG Failure Localization in All-Optical Networks

KAUST Repository

Ali, Mohammed L.; Ho, Pin-Han; Tapolcai, Já nos; Shihada, Basem

2012-01-01

Fast and unambiguous failure localization for shared risk link groups (SRLGs) with multiple links is essential for building a fully survivable and functional transparent all-optical mesh network. Monitoring trails (m-trails) have been proposed

Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Science.gov (United States)

Pardi, Fabio; Scornavacca, Celine

2015-04-01

Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

Reconstructible phylogenetic networks: do not distinguish the indistinguishable.

Directory of Open Access Journals (Sweden)

Fabio Pardi

2015-04-01

Full Text Available Phylogenetic networks represent the evolution of organisms that have undergone reticulate events, such as recombination, hybrid speciation or lateral gene transfer. An important way to interpret a phylogenetic network is in terms of the trees it displays, which represent all the possible histories of the characters carried by the organisms in the network. Interestingly, however, different networks may display exactly the same set of trees, an observation that poses a problem for network reconstruction: from the perspective of many inference methods such networks are "indistinguishable". This is true for all methods that evaluate a phylogenetic network solely on the basis of how well the displayed trees fit the available data, including all methods based on input data consisting of clades, triples, quartets, or trees with any number of taxa, and also sequence-based approaches such as popular formalisations of maximum parsimony and maximum likelihood for networks. This identifiability problem is partially solved by accounting for branch lengths, although this merely reduces the frequency of the problem. Here we propose that network inference methods should only attempt to reconstruct what they can uniquely identify. To this end, we introduce a novel definition of what constitutes a uniquely reconstructible network. For any given set of indistinguishable networks, we define a canonical network that, under mild assumptions, is unique and thus representative of the entire set. Given data that underwent reticulate evolution, only the canonical form of the underlying phylogenetic network can be uniquely reconstructed. While on the methodological side this will imply a drastic reduction of the solution space in network inference, for the study of reticulate evolution this is a fundamental limitation that will require an important change of perspective when interpreting phylogenetic networks.

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.

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

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.

Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

Science.gov (United States)

Tavakoli, M. M.; Assadian, N.

2018-03-01

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.

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

Details of microearthquake swarms in the Columbia basin, Washington

International Nuclear Information System (INIS)

Malone, S.D.; Rothe, G.H.; Smith, S.W.

1975-01-01

Three microearthquake swarms in the Columbia River basin of eastern Washington were studied by means of a small portable seismic network. Earthquakes in this area typically occur in swarms, concentrated both temporally and spatially. One unusual characteristic of the three swarms studied was the shallow focal depths of all events. Most events located had depths less than 1 km; none were deeper than 2 km. Composite focal mechanism solutions indicate that more than one fault surface is active in any one swarm. All events had some thrust component with the axis of maximum compression oriented roughly in a north-south direction. (auth)

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.

Diet, physical activity or both for prevention or delay of type 2 diabetes mellitus and its associated complications in people at increased risk of developing type 2 diabetes mellitus.

Science.gov (United States)

Hemmingsen, Bianca; Gimenez-Perez, Gabriel; Mauricio, Didac; Roqué I Figuls, Marta; Metzendorf, Maria-Inti; Richter, Bernd

2017-12-04

The projected rise in the incidence of type 2 diabetes mellitus (T2DM) could develop into a substantial health problem worldwide. Whether diet, physical activity or both can prevent or delay T2DM and its associated complications in at-risk people is unknown. To assess the effects of diet, physical activity or both on the prevention or delay of T2DM and its associated complications in people at increased risk of developing T2DM. This is an update of the Cochrane Review published in 2008. We searched the CENTRAL, MEDLINE, Embase, ClinicalTrials.gov, ICTRP Search Portal and reference lists of systematic reviews, articles and health technology assessment reports. The date of the last search of all databases was January 2017. We continuously used a MEDLINE email alert service to identify newly published studies using the same search strategy as described for MEDLINE up to September 2017. We included randomised controlled trials (RCTs) with a duration of two years or more. We used standard Cochrane methodology for data collection and analysis. We assessed the overall quality of the evidence using GRADE. We included 12 RCTs randomising 5238 people. One trial contributed 41% of all participants. The duration of the interventions varied from two to six years. We judged none of the included trials at low risk of bias for all 'Risk of bias' domains.Eleven trials compared diet plus physical activity with standard or no treatment. Nine RCTs included participants with impaired glucose tolerance (IGT), one RCT included participants with IGT, impaired fasting blood glucose (IFG) or both, and one RCT included people with fasting glucose levels between 5.3 to 6.9 mmol/L. A total of 12 deaths occurred in 2049 participants in the diet plus physical activity groups compared with 10 in 2050 participants in the comparator groups (RR 1.12, 95% CI 0.50 to 2.50; 95% prediction interval 0.44 to 2.88; 4099 participants, 10 trials; very low-quality evidence). The definition of T2DM incidence

Exploring the evolution of node neighborhoods in Dynamic Networks

Science.gov (United States)

Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

2017-09-01

Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

Amplification or suppression: Social networks and the climate change-migration association in rural Mexico.

Science.gov (United States)

Nawrotzki, Raphael J; Riosmena, Fernando; Hunter, Lori M; Runfola, Daniel M

2015-11-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks - the ties connecting an origin and destination - may operate as "migration corridors" with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying , social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

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.

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.

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...

Event-based user classification in Weibo media.

Science.gov (United States)

Guo, Liang; Wang, Wendong; Cheng, Shiduan; Que, Xirong

2014-01-01

Weibo media, known as the real-time microblogging services, has attracted massive attention and support from social network users. Weibo platform offers an opportunity for people to access information and changes the way people acquire and disseminate information significantly. Meanwhile, it enables people to respond to the social events in a more convenient way. Much of the information in Weibo media is related to some events. Users who post different contents, and exert different behavior or attitude may lead to different contribution to the specific event. Therefore, classifying the large amount of uncategorized social circles generated in Weibo media automatically from the perspective of events has been a promising task. Under this circumstance, in order to effectively organize and manage the huge amounts of users, thereby further managing their contents, we address the task of user classification in a more granular, event-based approach in this paper. By analyzing real data collected from Sina Weibo, we investigate the Weibo properties and utilize both content information and social network information to classify the numerous users into four primary groups: celebrities, organizations/media accounts, grassroots stars, and ordinary individuals. The experiments results show that our method identifies the user categories accurately.

Asexuality: Sexual Orientation, Paraphilia, Sexual Dysfunction, or None of the Above?

Science.gov (United States)

Brotto, Lori A; Yule, Morag

2017-04-01

Although lack of sexual attraction was first quantified by Kinsey, large-scale and systematic research on the prevalence and correlates of asexuality has only emerged over the past decade. Several theories have been posited to account for the nature of asexuality. The goal of this review was to consider the evidence for whether asexuality is best classified as a psychiatric syndrome (or a symptom of one), a sexual dysfunction, or a paraphilia. Based on the available science, we believe there is not sufficient evidence to support the categorization of asexuality as a psychiatric condition (or symptom of one) or as a disorder of sexual desire. There is some evidence that a subset of self-identified asexuals have a paraphilia. We also considered evidence supporting the classification of asexuality as a unique sexual orientation. We conclude that asexuality is a heterogeneous entity that likely meets conditions for a sexual orientation, and that researchers should further explore evidence for such a categorization.

Compulsory declaration of the loss or theft of property and of serious events: New rules and reminder

CERN Document Server

2014-01-01

This notification cancels and replaces the notifications published in Bulletins Nos. 13-14/2006 and 28-29/2009 and the update of 18 November 2011.   1.     Definitions "fenced part of the CERN site" means all the different fenced areas used by the Organization, including remote buildings and underground facilities, "serious event" means any event infringing the rules designed to protect people and property (e.g. attacks, threats, acts of sabotage, vandalism).   2.   Internal declarations The loss or theft of property and serious events must be declared internally if they occur: within the fenced part of the CERN site, irrespective of the person and item concerned, outside the fenced part of the CERN site if CERN is the owner or custodian of the item concerned.   3.   Who must make the declaration? In principle, the loss or theft of property and serious events m...

Lightness : a function-virtualizable software defined data center network with all-optical circuit/packet switching

NARCIS (Netherlands)

Saridis, G.; Peng, S.; Yan, Y.; Aguado, A.; Guo, B.; Arslan, M.; Jackson, C.; Miao, W.; Calabretta, N.; Agraz, F.; Spadaro, S.; Bernini, G.; Ciulli, N.; Zervas, G.; Nejabati, R.; Simeonidou, D.

2016-01-01

Modern high-performance Data Centers are responsible for delivering a huge variety of cloud applications to the end-users, which are increasingly pushing the limits of currently deployed computing and network infrastructure. All-optical dynamic data center network (DCN) architectures are strong

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.

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.

Background rejection in NEXT using deep neural networks

CERN Document Server

Renner, J.

2017-01-01

We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

Background rejection in NEXT using deep neural networks

International Nuclear Information System (INIS)

Renner, J.; Farbin, A.; Vidal, J. Muñoz; Benlloch-Rodríguez, J. M.; Botas, A.

2017-01-01

Here, we investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

Monitoring burst (M-burst) — A novel framework of failure localization in all-optical mesh networks

KAUST Repository

Ali, Mohammed L.; Ho, Pin-Han; Wu, Bin; Tapolcai, Janos; Shihada, Basem

2011-01-01

Achieving instantaneous and precise failure localization in all-optical wavelength division multiplexing (WDM) networks has been an attractive feature of network fault management systems, and is particularly important when failure

Analyzing THE PLACE FOR THE EVENT-type Metonymies from the Perspective of Negative Evaluative Factors

Directory of Open Access Journals (Sweden)

Nami Arimitsu

Full Text Available This paper has two objectives. First, by analyzing THE PLACE FOR THE EVENT-type metonymies, this paper points out that it is mainly negative events that are expressed by this type of metonymy. Second, this paper reveals the motivations of those THE PLACE FOR THE EVENT-type metonymies that express negative events. Metonymies are widely investigated along with the views of Lakoff and Johnson (1980, and their oppositional semantic aspects are pointed out by Voßhagen (1999. However, none of the previous studies focused on the nature of THE PLACE FOR THE EVENT-type metonymies from the perspective of negative evaluation, euphemism, and politeness. "Let's not let Thailand become another Vietnam" expresses the Vietnam War and all the tragedies behind it. Speakers refrain from expressing negative evaluative aspects from a euphemistic perspective and try to behave politely through hiding the exact expression, and listeners can also easily understand THE PLACE FOR THE EVENT-type metonymies that express negative events, since negative events are much more highly marked and intensified, as well as more prominent, than are positive ones.

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

Walking through doorways causes forgetting: Event structure or updating disruption?

Science.gov (United States)

Pettijohn, Kyle A; Radvansky, Gabriel A

2016-11-01

According to event cognition theory, people segment experience into separate event models. One consequence of this segmentation is that when people transport objects from one location to another, memory is worse than if people move across a large location. In two experiments participants navigated through a virtual environment, and recognition memory was tested in either the presence or the absence of a location shift for objects that were recently interacted with (i.e., just picked up or set down). Of particular concern here is whether this location updating effect is due to (a) differences in retention intervals as a result of the navigation process, (b) a temporary disruption in cognitive processing that may occur as a result of the updating processes, or (c) a need to manage multiple event models, as has been suggested in prior research. Experiment 1 explored whether retention interval is driving this effect by recording travel times from the acquisition of an object and the probe time. The results revealed that travel times were similar, thereby rejecting a retention interval explanation. Experiment 2 explored whether a temporary disruption in processing is producing the effect by introducing a 3-second delay prior to the presentation of a memory probe. The pattern of results was not affected by adding a delay, thereby rejecting a temporary disruption account. These results are interpreted in the context of the event horizon model, which suggests that when there are multiple event models that contain common elements there is interference at retrieval, which compromises performance.