Science.gov

Sample records for event builder networks

  1. Network Performance Testing for the BaBar Event Builder

    SciTech Connect

    Pavel, Tomas J

    1998-11-17

    We present an overview of the design of event building in the BABAR Online, based upon TCP/IP and commodity networking technology. BABAR is a high-rate experiment to study CP violation in asymmetric e{sup +}e{sup {minus}} collisions. In order to validate the event-builder design, an extensive program was undertaken to test the TCP performance delivered by various machine types with both ATM OC-3 and Fast Ethernet networks. The buffering characteristics of several candidate switches were examined and found to be generally adequate for our purposes. We highlight the results of this testing and present some of the more significant findings.

  2. CMS DAQ event builder based on gigabit ethernet

    SciTech Connect

    Pieri, M.; Maron, G.; Brett, A.; Cano, E.; Cittolin, S.; Erhan, S.; Gigi, D.; Glege, F.; Gomez-Reino Garrido, R.; Gulmini, M.; Gutleber, J.; Jacobs, C.; Meijers, F.; Meschi, E.; Oh, A.; Orsini, L.; Pollet, L.; Racz, A.; Rosinsky, P.; Sakulin, H.; Schwick, C.; /UC, San Diego /INFN, Legnaro /CERN /UCLA /Santiago de Compostela U. /Lisbon, LIFEP /Fermilab /MIT /Boskovic Inst., Zagreb

    2006-06-01

    The CMS Data Acquisition system is designed to build and filter events originating from approximately 500 data sources from the detector at a maximum Level 1 trigger rate of 100 kHz and with an aggregate throughput of 100 GByte/s. For this purpose different architectures and switch technologies have been evaluated. Events will be built in two stages: the first stage, the FED Builder, will be based on Myrinet technology and will pre-assemble groups of about 8 data sources. The next stage, the Readout Builder, will perform the building of full events. The requirement of one Readout Builder is to build events at 12.5 kHz with average size of 16 kBytes from 64 sources. In this paper we present the prospects of a Readout Builder based on TCP/IP over Gigabit Ethernet. Various Readout Builder architectures that we are considering are discussed. The results of throughput measurements and scaling performance are outlined as well as the preliminary estimates of the final performance. All these studies have been carried out at our test-bed farms that are made up of a total of 130 dual Xeon PCs interconnected with Myrinet and Gigabit Ethernet networking and switching technologies.

  3. A New Event Builder for CMS Run II

    NASA Astrophysics Data System (ADS)

    Albertsson, K.; Andre, J.-M.; Andronidis, A.; Behrens, U.; Branson, J.; Chaze, O.; Cittolin, S.; Darlea, G.-L.; Deldicque, C.; Dobson, M.; Dupont, A.; Erhan, S.; Gigi, D.; Glege, F.; Gomez-Ceballos, G.; Hegeman, J.; Holzner, A.; Jimenez-Estupiñán, R.; Masetti, L.; Meijers, F.; Meschi, E.; Mommsen, R. K.; Morovic, S.; Nunez-Barranco-Fernandez, C.; O'Dell, V.; Orsini, L.; Paus, C.; Petrucci, A.; Pieri, M.; Racz, A.; Roberts, P.; Sakulin, H.; Schwick, C.; Stieger, B.; Sumorok, K.; Veverka, J.; Zaza, S.; Zejdl, P.

    2015-12-01

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of 100GB/s to the high-level trigger (HLT) farm. The DAQ system has been redesigned during the LHC shutdown 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 Gbps 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 Gbps Infiniband FDR CLOS network has been chosen for the event builder. This paper discusses the software design, protocols, and optimizations for exploiting the hardware capabilities. We present performance measurements from small-scale prototypes and from the full-scale production system.

  4. A new event builder for CMS Run II

    SciTech Connect

    Albertsson, K.; Andre, J-M; Andronidis, A.; Behrens, U.; Branson, J.; Chaze, O.; Cittolin, S.; Darlea, G-L; Deldicque, C.; Dobson, M.; Dupont, A.; Erhan, S.; Gigi, D.; Glege, F.; Gomez-Ceballos, G.; Hegeman, J.; Holzner, A.; Jimenez-Estupiñán, R.; Masetti, L.; Meijers, F.; Meschi, E.; Mommsen, R. K.; Morovic, S.; Nunez-Barranco-Fernandez, C.; O'Dell, V.; Orsini, L.; Paus, C.; Petrucci, A.; Pieri, M.; Racz, A.; Roberts, P.; Sakulin, H.; Schwick, C.; Stieger, B.; Sumorok, K.; Veverka, J.; Zaza, S.; Zejdl, P.

    2015-01-01

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of 100 GB/s to the high-level trigger (HLT) farm. The DAQ system has been redesigned during the LHC shutdown 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 Gbps 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 Gbps Inniband FDR CLOS network has been chosen for the event builder. This paper discusses the software design, protocols, and optimizations for exploiting the hardware capabilities. In conclusion, ee present performance measurements from small-scale prototypes and from the full-scale production system.

  5. A New Event Builder for CMS Run II

    SciTech Connect

    Albertsson, K.; et al.

    2015-12-23

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of 100 GB/s to the high-level trigger (HLT) farm. The DAQ system has been redesigned during the LHC shutdown 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 Gbps 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 Gbps Inniband FDR CLOS network has been chosen for the event builder. This paper discusses the software design, protocols, and optimizations for exploiting the hardware capabilities. We present performance measurements from small-scale prototypes and from the full-scale production system.

  6. CMS DAQ event builder based on Gigabit Ethernet

    SciTech Connect

    Bauer, G.; Boyer, V.; Branson, J.; Brett, A.; Cano, E.; Carboni, A.; Ciganek, M.; Cittolin, S.; Erhan, Samim; Gigi, D.; Glege, F.; /CERN /INFN, Legnaro /CERN /CERN /Kyungpook Natl. U. /MIT /UC, San Diego /CERN

    2007-04-01

    The CMS Data Acquisition System is designed to build and filter events originating from 476 detector data sources at a maximum trigger rate of 100 KHz. Different architectures and switch technologies have been evaluated to accomplish this purpose. Events will be built in two stages: the first stage will be a set of event builders called FED Builders. These will be based on Myrinet technology and will pre-assemble groups of about 8 data sources. The second stage will be a set of event builders called Readout Builders. These will perform the building of full events. A single Readout Builder will build events from 72 sources of 16 KB fragments at a rate of 12.5 KHz. In this paper we present the design of a Readout Builder based on TCP/IP over Gigabit Ethernet and the optimization that was required to achieve the design throughput. This optimization includes architecture of the Readout Builder, the setup of TCP/IP, and hardware selection.

  7. A new event builder for CMS Run II

    DOE PAGESBeta

    Albertsson, K.; Andre, J-M; Andronidis, A.; Behrens, U.; Branson, J.; Chaze, O.; Cittolin, S.; Darlea, G-L; Deldicque, C.; Dobson, M.; et al

    2015-01-01

    The data acquisition system (DAQ) of the CMS experiment at the CERN Large Hadron Collider (LHC) assembles events at a rate of 100 kHz, transporting event data at an aggregate throughput of 100 GB/s to the high-level trigger (HLT) farm. The DAQ system has been redesigned during the LHC shutdown 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 Gbps 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 Gbps Innibandmore » FDR CLOS network has been chosen for the event builder. This paper discusses the software design, protocols, and optimizations for exploiting the hardware capabilities. In conclusion, ee present performance measurements from small-scale prototypes and from the full-scale production system.« less

  8. Event builder and level 3 at the CDF experiment

    SciTech Connect

    G. Gomez-Ceballos, A. Belloni and A. Bolshov

    2003-10-30

    The Event Builder and Level3 systems constitute critical components of the DAQ in the CDF experiment at Fermilab. These systems are responsible for collecting data fragments from the front end electronics, assembling the data into complete event records, reconstructing the events, and forming the final trigger decision. With Tevatron Run IIa in progress, the systems have been running successfully at high throughput rates, the design utilizing scalable architecture and distributed event processing to meet the requirements. A brief description current performance in Run IIa and possible upgrade for Run IIb is presented.

  9. CDF DAQ upgrade and CMS DAQ R and D: event builder tests using an ATM switch

    SciTech Connect

    Bauer, G.; Daniels, T.; Kelley, K.

    1996-12-31

    The present data acquisition system of the CDF experiment has to be upgraded for the higher luminosities expected during the Run 11 (1999+) data-taking period. The core of the system, consisting of a control network based on reflective memories will remain the same. The network used for data transfers, however, will have to be changed. We have investigated ATM as a possible replacement technology for the current Ultranet switch. We present preliminary results on this new ATM-based event builder system.

  10. Results from a data acquisition system prototype project using a switch-based event builder

    SciTech Connect

    Black, D.; Andresen, J.; Barsotti, E.; Baumbaugh, A.; Esterline, D.; Knickerbocker, K.; Kwarciany, R.; Moore, G.; Patrick, J.; Swoboda, C.; Treptow, K.; Trevizo, O.; Urish, J.; VanConant, R.; Walsh, D. ); Bowden, M.; Booth, A. ); Cancelo, G. )

    1991-11-01

    A prototype of a high bandwidth parallel event builder has been designed and tested. The architecture is based on a simple switching network and is adaptable to a wide variety of data acquisition systems. An eight channel system with a peak throughput of 160 Megabytes per second has been implemented. It is modularly expandable to 64 channels (over one Gigabyte per second). The prototype uses a number of relatively recent commercial technologies, including very high speed fiber-optic data links, high integration crossbar switches and embedded RISC processors. It is based on an open architecture which permits the installation of new technologies with little redesign effort. 5 refs., 6 figs.

  11. Portable software for distributed readout controllers and event builders in FASTBUS and VME

    SciTech Connect

    Pordes, R.; Berg, D.; Berman, E.; Bernett, M.; Brown, D.; Constanta-Fanourakis, P.; Dorries, T.; Haire, M.; Joshi, U.; Kaczar, K.; Mackinnon, B.; Moore, C.; Nicinski, T.; Oleynik, G.; Petravick, D.; Sergey, G.; Slimmer, D.; Streets, J.; Votava, M.; White, V.

    1989-12-01

    We report on software developed as part of the PAN-DA system to support the functions of front end readout controllers and event builders in multiprocessor, multilevel, distributed data acquisition systems. For the next generation data acquisition system we have undertaken to design and implement software tools that are easily transportable to new modules. The first implementation of this software is for Motorola 68K series processor boards in FASTBUS and VME and will be used in the Fermilab accelerator run at the beginning of 1990. We use a Real Time Kernel Operating System. The software provides general connectivity tools for control, diagnosis and monitoring. 17 refs., 7 figs.

  12. 76 FR 2145 - Masco Builder Cabinet Group Including On-Site Leased Workers From Reserves Network, Jackson, OH...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-12

    ... Federal Register on December 11, 2009 (74 FR 65798). The Department has received information that the... Reserves Network, Jackson, OH; Masco Builder Cabinet Group, Waverly, OH; Masco Builder Cabinet Group, Seal... workers of Masco Building Cabinet Group in Waverly, Ohio, Seal Township, Ohio, and Seaman, Ohio....

  13. RefNetBuilder: a platform for construction of integrated reference gene regulatory networks from expressed sequence tags

    PubMed Central

    2011-01-01

    Background Gene Regulatory Networks (GRNs) provide integrated views of gene interactions that control biological processes. Many public databases contain biological interactions extracted from experimentally validated literature reports, but most furnish only information for a few genetic model organisms. In order to provide a bioinformatic tool for researchers who work with non-model organisms, we developed RefNetBuilder, a new platform that allows construction of putative reference pathways or GRNs from expressed sequence tags (ESTs). Results RefNetBuilder was designed to have the flexibility to extract and archive pathway or GRN information from public databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG). It features sequence alignment tools such as BLAST to allow mapping ESTs to pathways and GRNs in model organisms. A scoring algorithm was incorporated to rank and select the best match for each query EST. We validated RefNetBuilder using DNA sequences of Caenorhabditis elegans, a model organism having manually curated KEGG pathways. Using the earthworm Eisenia fetida as an example, we demonstrated the functionalities and features of RefNetBuilder. Conclusions The RefNetBuilder provides a standalone application for building reference GRNs for non-model organisms on a number of operating system platforms with standard desktop computer hardware. As a new bioinformatic tool aimed for constructing putative GRNs for non-model organisms that have only ESTs available, RefNetBuilder is especially useful to explore pathway- or network-related information in these organisms. PMID:22166047

  14. The reef builder gastropod Dendropoma petreaum - A proxy of short and long term climatic events in the Eastern Mediterranean

    NASA Astrophysics Data System (ADS)

    Sisma-Ventura, Guy; Guzner, Barak; Yam, Ruth; Fine, Maoz; Shemesh, Aldo

    2009-08-01

    High-resolution δ 18O and δ 13C records obtained from seven cores were drilled from ledges of the reef builder gastropod Dendropomapetreaum and used to reconstruct variations in the Levantine basin sea surface temperature, hydrology and productivity during the past 500 years. The δ 18O of the aragonite shell of living D . petreaum indicate that skeletal deposition occurs under isotopic equilibrium and faithfully record the temperature and surface water δ 18O during summer and autumn. The mean down core δ 18O record clearly captures global and local climatic events, such as the Little Ice Age (LIA) and the recent warming of surface waters in the Eastern Mediterranean. Comparison to the Western Mediterranean vermetid δ 18O record reveals changes in the freshwater/evaporation budgets of the two basins during cold and warm periods. The Eastern basin had lower surface temperatures and excess evaporation during the LIA and experienced a relatively larger warming and/or a decrease in freshwater/evaporation during the past 70 years. The D . petraeum δ 13C is strongly related to δ 13C of dissolved inorganic carbon and to the primary productivity of the surface water. The mean down core δ 13C record exhibits enrichment during the LIA maximum and a strong depletion trend during the last century. The LIA δ 13C enrichment is attributed to an increase in primary production and high nutrient levels which resulted from increased vertical mixing and upwelling. The last century δ 13C depletion is mostly related to the increased anthropogenic emissions of 13C depleted carbon dioxide and to a certain decrease in primary production. The data indicate that D. petraeum isotopic signatures are unique proxies for last 500 years high-resolution reconstruction of paleo-oceanographic environments in the Mediterranean and potentially in the sub-tropical Atlantic regions.

  15. Host Event Based Network Monitoring

    SciTech Connect

    Jonathan Chugg

    2013-01-01

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

  16. Climate Networks and Extreme Events

    NASA Astrophysics Data System (ADS)

    Kurths, J.

    2014-12-01

    We analyse some climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. The global scale view on climate networks offers promising new perspectives for detecting dynamical structures based on nonlinear physical processes in the climate system. Moreover, we evaluate different regional climate models from this aspect. This concept is also applied to Monsoon data in order to characterize the regional occurrence of extreme rain events and its impact on predictability. Changing climatic conditions have led to a significant increase in magnitude and frequency of spatially extensive extreme rainfall events in the eastern Central Andes of South America. These events impose substantial natural hazards for population, economy, and ecology by floods and landslides. For example, heavy floods in Bolivia in early 2007 affected more than 133.000 households and produced estimated costs of 443 Mio. USD. Here, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. We apply our method to real-time satellite-derived rainfall data and are able to predict a large amount of extreme rainfall events. Our study reveals a linkage between polar and subtropical regimes as responsible mechanism: Extreme rainfall in the eastern Central Andes is caused by the interplay of northward migrating frontal systems and a low-level wind channel from the western Amazon to the subtropics, providing additional moisture. Frontal systems from the Antarctic thus play a key role for sub-seasonal variability of the South American Monsoon System.

  17. Controlling extreme events on complex networks

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

  18. e-Stars Template Builder

    NASA Technical Reports Server (NTRS)

    Cox, Brian

    2003-01-01

    e-Stars Template Builder is a computer program that implements a concept of enabling users to rapidly gain access to information on projects of NASA's Jet Propulsion Laboratory. The information about a given project is not stored in a data base, but rather, in a network that follows the project as it develops. e-Stars Template Builder resides on a server computer, using Practical Extraction and Reporting Language (PERL) scripts to create what are called "e-STARS node templates," which are software constructs that allow for project-specific configurations. The software resides on the server and does not require specific software on the user machine except for an Internet browser. A user's computer need not be equipped with special software (other than an Internet-browser program). e-Stars Template Builder is compatible with Windows, Macintosh, and UNIX operating systems. A user invokes e-Stars Template Builder from a browser window. Operations that can be performed by the user include the creation of child processes and the addition of links and descriptions of documentation to existing pages or nodes. By means of this addition of "child processes" of nodes, a network that reflects the development of a project is generated.

  19. Drastic events make evolving networks

    NASA Astrophysics Data System (ADS)

    Ausloos, M.; Lambiotte, R.

    2007-05-01

    Co-authorship networks of neighbouring scientific disciplines, i.e. granular (G) media and networks (N) are studied in order to observe drastic structural changes in evolving networks. The data is taken from arXives. The system is described as coupled networks. By considering the 1995-2005 time interval and scanning the author-article network evolution with a mobile time window, we focus on the properties of the links, as well as on the time evolution of the nodes. They can be in three states, N, G or multi-disciplinary (M). This leads to drastic jumps in a so-called order parameter, i.e. the link proportion of a given type, forming the main island, that reminds of features appearing at percolation and during metastable (aggregation-desaggregation) processes. The data analysis also focuses on the way different kinds (N, G or M) of authors collaborate, and on the kind of the resulting collaboration.

  20. Controlling extreme events on complex networks

    PubMed Central

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

    2014-01-01

    Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network “mobile” can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed. PMID:25131344

  1. Controlling extreme events on complex networks.

    PubMed

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

    2014-01-01

    Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network "mobile" can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed. PMID:25131344

  2. Emergence of event cascades in inhomogeneous networks.

    PubMed

    Onaga, Tomokatsu; Shinomoto, Shigeru

    2016-01-01

    There is a commonality among contagious diseases, tweets, and neuronal firings that past events facilitate the future occurrence of events. The spread of events has been extensively studied such that the systems exhibit catastrophic chain reactions if the interaction represented by the ratio of reproduction exceeds unity; however, their subthreshold states are not fully understood. Here, we report that these systems are possessed by nonstationary cascades of event-occurrences already in the subthreshold regime. Event cascades can be harmful in some contexts, when the peak-demand causes vaccine shortages, heavy traffic on communication lines, but may be beneficial in other contexts, such that spontaneous activity in neural networks may be used to generate motion or store memory. Thus it is important to comprehend the mechanism by which such cascades appear, and consider controlling a system to tame or facilitate fluctuations in the event-occurrences. The critical interaction for the emergence of cascades depends greatly on the network structure in which individuals are connected. We demonstrate that we can predict whether cascades may emerge, given information about the interactions between individuals. Furthermore, we develop a method of reallocating connections among individuals so that event cascades may be either impeded or impelled in a network. PMID:27625183

  3. Acoustic network event classification using swarm optimization

    NASA Astrophysics Data System (ADS)

    Burman, Jerry

    2013-05-01

    Classifying acoustic signals detected by distributed sensor networks is a difficult problem due to the wide variations that can occur in the transmission of terrestrial, subterranean, seismic and aerial events. An acoustic event classifier was developed that uses particle swarm optimization to perform a flexible time correlation of a sensed acoustic signature to reference data. In order to mitigate the effects from interference such as multipath, the classifier fuses signatures from multiple sensors to form a composite sensed acoustic signature and then automatically matches the composite signature with reference data. The approach can classify all types of acoustic events but is particularly well suited to explosive events such as gun shots, mortar blasts and improvised explosive devices that produce an acoustic signature having a shock wave component that is aperiodic and non-linear. The classifier was applied to field data and yielded excellent results in terms of reconstructing degraded acoustic signatures from multiple sensors and in classifying disparate acoustic events.

  4. Neural network classification of questionable EGRET events

    NASA Technical Reports Server (NTRS)

    Meetre, C. A.; Norris, J. P.

    1992-01-01

    High energy gamma rays (greater than 20 MeV) pair producing in the spark chamber of the Energetic Gamma Ray Telescope Experiment (EGRET) give rise to a characteristic but highly variable 3-D locus of spark sites, which must be processed to decide whether the event is to be included in the database. A significant fraction (about 15 percent or 10(exp 4) events/day) of the candidate events cannot be categorized (accept/reject) by an automated rule-based procedure; they are therefore tagged, and must be examined and classified manually by a team of expert analysts. We describe a feedforward, back-propagation neural network approach to the classification of the questionable events. The algorithm computes a set of coefficients using representative exemplars drawn from the preclassified set of questionable events. These coefficients map a given input event into a decision vector that, ideally, describes the correct disposition of the event. The net's accuracy is then tested using a different subset of preclassified events. Preliminary results demonstrate the net's ability to correctly classify a large proportion of the events for some categories of questionables. Current work includes the use of much larger training sets to improve the accuracy of the net.

  5. AGU Hosts Networking Event for Female Scientists

    NASA Astrophysics Data System (ADS)

    McEntee, Chris

    2013-01-01

    At Fall Meeting this year I had the pleasure of cohosting a new event, a Networking Reception for Early Career Female Scientists and Students, with Jane Lubchenco, under secretary of Commerce for Oceans and Atmosphere and National Oceanic and Atmospheric Administration administrator, and Marcia McNutt, director of the U.S. Geological Survey. AGU recognizes the importance of having a diverse pool of new researchers who can enrich Earth and space sciences with their skills and innovation. That's why one of our four strategic goals is to help build the global talent pool and provide early-career scientists with networking opportunities like this one.

  6. eProject Builder

    Energy Science and Technology Software Center (ESTSC)

    2014-06-01

    eProject Builder enables Energy Services Companies (ESCOs) and their contracting agencies to: 1. upload and track project-level Information 2. generate basic project reports required by local, state, and/or federal agencies 3. benchmark new Energy Savings Performance Contract (ESPC) projects against historical data

  7. Algorithms for builder guidelines

    SciTech Connect

    Balcomb, J.D.; Lekov, A.B.

    1989-06-01

    The Builder Guidelines are designed to make simple, appropriate guidelines available to builders for their specific localities. Builders may select from passive solar and conservation strategies with different performance potentials. They can then compare the calculated results for their particular house design with a typical house in the same location. Algorithms used to develop the Builder Guidelines are described. The main algorithms used are the monthly solar ratio (SLR) method for winter heating, the diurnal heat capacity (DHC) method for temperature swing, and a new simplified calculation method (McCool) for summer cooling. This paper applies the algorithms to estimate the performance potential of passive solar strategies, and the annual heating and cooling loads of various combinations of conservation and passive solar strategies. The basis of the McCool method is described. All three methods are implemented in a microcomputer program used to generate the guideline numbers. Guidelines for Denver, Colorado, are used to illustrate the results. The structure of the guidelines and worksheet booklets are also presented. 5 refs., 3 tabs.

  8. TrustBuilder2

    Energy Science and Technology Software Center (ESTSC)

    2007-07-20

    TrustBuilder2 is a flexible framework for supporting research in the area trust negotiation protocols, designed to allow researchers to quickly prototype and experiment with various approaches to trust negotiation. In Trustbuilder2, the primary components of a trust negotiation system are represented using abstract interfaces. Any or all of these components can be implemented or extended by users of the TrustBuilder2 system, thereby making the system's functionality easily extensible. The TrustBuilder2 configuration files can be modifiedmore » to load these custom components in place of the default system components; this facilitates the use of new features without modifications to the underlying runtime system. In our implementation, we provide support for one negotiation strategy, a policy compliance checker based on Jess (the Java Expert System Shell), query interfaces enabling access to disk-based credential and policy repositories, a credential chain construction algorithm, two credential chain verification routines, and both graphical and text-based logging facilities. Trustbuilder2 also supports the interposition of user-defined plug-ins at communication points between system components to allow for easy monitoring of system activity or the modification of messages passed between components.« less

  9. Digital Learning Network Event with Robotics Engineer Jonathan Rogers

    NASA Video Gallery

    Robotics engineer Jonathan Rogers and Public Affairs Officer Kylie Clem participate in a Digital Learning Network educational event, answering questions from students at Montgomery Middle School in...

  10. Composite beam builder

    NASA Technical Reports Server (NTRS)

    Poveromo, L. M.; Muench, W. K.; Marx, W.; Lubin, G.

    1981-01-01

    The building block approach to large space structures is discussed, and the progress made in constructing aluminum beams is noted. It is pointed out that composites will also be required in space structures because they provide minimal distortion characteristics during thermal transients. A composite beam builder currently under development is discussed, with attention given to cap forming and the fastening of cross-braces. The various composite materials being considered are listed, along with certain of their properties. The need to develop continuous forming stock up to 300 m long is stressed.

  11. Man-machine interface builders at the Advanced Photon Source

    SciTech Connect

    Anderson, M.D.

    1991-12-31

    Argonne National Laboratory is constructing a 7-GeV Advanced Photon Source for use as a synchrotron radiation source in basic and applied research. The controls and computing environment for this accelerator complex includes graphical operator interfaces to the machine based on Motif, X11, and PHIGS/PEX. Construction and operation of the control system for this accelerator relies upon interactive interface builder and diagram/editor type tools, as well as a run-time environment for the constructed displays which communicate with the physical machine via network connections. This paper discusses our experience with several commercial CUI builders, the inadequacies found in these, motivation for the development of an application- specific builder, and design and implementation strategies employed in the development of our own Man-Machine Interface builder. 5 refs.

  12. Man-machine interface builders at the Advanced Photon Source

    SciTech Connect

    Anderson, M.D.

    1991-01-01

    Argonne National Laboratory is constructing a 7-GeV Advanced Photon Source for use as a synchrotron radiation source in basic and applied research. The controls and computing environment for this accelerator complex includes graphical operator interfaces to the machine based on Motif, X11, and PHIGS/PEX. Construction and operation of the control system for this accelerator relies upon interactive interface builder and diagram/editor type tools, as well as a run-time environment for the constructed displays which communicate with the physical machine via network connections. This paper discusses our experience with several commercial CUI builders, the inadequacies found in these, motivation for the development of an application- specific builder, and design and implementation strategies employed in the development of our own Man-Machine Interface builder. 5 refs.

  13. Synthetic Event Reconstruction Experiments for Defining Sensor Network Characteristics

    SciTech Connect

    Lundquist, J K; Kosovic, B; Belles, R

    2005-12-15

    An event reconstruction technology system has been designed and implemented at Lawrence Livermore National Laboratory (LLNL). This system integrates sensor observations, which may be sparse and/or conflicting, with transport and dispersion models via Bayesian stochastic sampling methodologies to characterize the sources of atmospheric releases of hazardous materials. We demonstrate the application of this event reconstruction technology system to designing sensor networks for detecting and responding to atmospheric releases of hazardous materials. The quantitative measure of the reduction in uncertainty, or benefit of a given network, can be utilized by policy makers to determine the cost/benefit of certain networks. Herein we present two numerical experiments demonstrating the utility of the event reconstruction methodology for sensor network design. In the first set of experiments, only the time resolution of the sensors varies between three candidate networks. The most ''expensive'' sensor network offers few advantages over the moderately-priced network for reconstructing the release examined here. The second set of experiments explores the significance of the sensors detection limit, which can have a significant impact on sensor cost. In this experiment, the expensive network can most clearly define the source location and source release rate. The other networks provide data insufficient for distinguishing between two possible clusters of source locations. When the reconstructions from all networks are aggregated into a composite plume, a decision-maker can distinguish the utility of the expensive sensor network.

  14. Signaling communication events in a computer network

    DOEpatents

    Bender, Carl A.; DiNicola, Paul D.; Gildea, Kevin J.; Govindaraju, Rama K.; Kim, Chulho; Mirza, Jamshed H.; Shah, Gautam H.; Nieplocha, Jaroslaw

    2000-01-01

    A method, apparatus and program product for detecting a communication event in a distributed parallel data processing system in which a message is sent from an origin to a target. A low-level application programming interface (LAPI) is provided which has an operation for associating a counter with a communication event to be detected. The LAPI increments the counter upon the occurrence of the communication event. The number in the counter is monitored, and when the number increases, the event is detected. A completion counter in the origin is associated with the completion of a message being sent from the origin to the target. When the message is completed, LAPI increments the completion counter such that monitoring the completion counter detects the completion of the message. The completion counter may be used to insure that a first message has been sent from the origin to the target and completed before a second message is sent.

  15. Builders Challenge Quality Criteria Support Document

    SciTech Connect

    2009-06-01

    This document provides guidance to U.S. home builders participating in Builders Challenge. To qualify for the Builders Challenge, a home must score 70 or less on the EnergySmart Home Scale (E-Scale). Homes also must meet the Builders Challenge Quality Cri

  16. A convolutional neural network neutrino event classifier

    DOE PAGESBeta

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

    2016-09-01

    Here, convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology withoutmore » the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.« less

  17. Seismic event classification using Self-Organizing Neural Networks

    SciTech Connect

    Maurer, W.J.; Dowla, F.U.; Jarpe, S.P.

    1991-10-15

    In the computer interpretation of seismic data, the critical first step is to identify the general class of an unknown event. For example, the classification might be: teleseismic, regional, local, vehicular, or noise. We have studied Self Organizing Neural Networks (SONNs) for classifying such events. Both Kohonen and Adaptive Resonance Theory (ART) SONNs were developed and tested with a moderately large set of real seismic events. Given the detection of a seismic event and the corresponding signal, we compute the time-frequency distribution, its binary representation, and finally a shift-invariant representation, which is the magnitude of the two-dimensional Fourier transform (2-D FFT) of the binary time-frequency distribution. This preprocessed input is fed into the SONNs. The overall results based on 111 events (43 training and 68 test events) show that SONNs are able to group events that ``look`` similar. We also find that the ART algorithm has an advantage in that the types of cluster groups do not need to be predefined. When a new type of event is detected, the ART network is able to handle the event rather gracefully. The results from the SONNs together with an expert seismologist`s classification are then used to derive event classification probabilities. A strategy to integrate a SONN into the interpretation of seismic events is also proposed.

  18. Extreme events in multilayer, interdependent complex networks and control

    NASA Astrophysics Data System (ADS)

    Chen, Yu-Zhong; Huang, Zi-Gang; Zhang, Hai-Feng; Eisenberg, Daniel; Seager, Thomas P.; Lai, Ying-Cheng

    2015-11-01

    We investigate the emergence of extreme events in interdependent networks. We introduce an inter-layer traffic resource competing mechanism to account for the limited capacity associated with distinct network layers. A striking finding is that, when the number of network layers and/or the overlap among the layers are increased, extreme events can emerge in a cascading manner on a global scale. Asymptotically, there are two stable absorption states: a state free of extreme events and a state of full of extreme events, and the transition between them is abrupt. Our results indicate that internal interactions in the multiplex system can yield qualitatively distinct phenomena associated with extreme events that do not occur for independent network layers. An implication is that, e.g., public resource competitions among different service providers can lead to a higher resource requirement than naively expected. We derive an analytical theory to understand the emergence of global-scale extreme events based on the concept of effective betweenness. We also articulate a cost-effective control scheme through increasing the capacity of very few hubs to suppress the cascading process of extreme events so as to protect the entire multi-layer infrastructure against global-scale breakdown.

  19. Network Event Recording Device: An automated system for Network anomaly detection, and notification. Draft

    SciTech Connect

    Simmons, D.G.; Wilkins, R.

    1994-09-01

    The goal of the Network Event Recording Device (NERD) is to provide a flexible autonomous system for network logging and notification when significant network anomalies occur. The NERD is also charged with increasing the efficiency and effectiveness of currently implemented network security procedures. While it has always been possible for network and security managers to review log files for evidence of network irregularities, the NERD provides real-time display of network activity, as well as constant monitoring and notification services for managers. Similarly, real-time display and notification of possible security breaches will provide improved effectiveness in combating resource infiltration from both inside and outside the immediate network environment.

  20. Capturing significant events with neural networks.

    PubMed

    Szu, Harold; Hsu, Charles; Jenkins, Jeffrey; Willey, Jefferson; Landa, Joseph

    2012-05-01

    Smartphone video capture and transmission to the Web contributes to data pollution. In contrast, mammalian eyes sense all, capture only significant events, allowing us vividly recall the causalities. Likewise in our videos, we wish to skip redundancies and keep only significantly differences, as determined by real-time local medium filters. We construct a Picture Index (PI) of one's (center of gravity changes) among zeros (no changes) as Motion Organized Sparseness (MOS). Only non-overlapping time-ordered PI pair is admitted in the outer-product Associative Memory (AM). Another outer product between PI and its image builds Hetero-AM (HAM) for fault tolerant retrievals. PMID:22402410

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

    PubMed

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

    2012-01-01

    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. PMID:23202191

  2. Subsurface Event Detection and Classification Using Wireless Signal Networks

    PubMed Central

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

    2012-01-01

    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. PMID:23202191

  3. System diagnostic builder

    NASA Technical Reports Server (NTRS)

    Nieten, Joseph L.; Burke, Roger

    1992-01-01

    The System Diagnostic Builder (SDB) is an automated software verification and validation tool using state-of-the-art Artificial Intelligence (AI) technologies. The SDB is used extensively by project BURKE at NASA-JSC as one component of a software re-engineering toolkit. The SDB is applicable to any government or commercial organization which performs verification and validation tasks. The SDB has an X-window interface, which allows the user to 'train' a set of rules for use in a rule-based evaluator. The interface has a window that allows the user to plot up to five data parameters (attributes) at a time. Using these plots and a mouse, the user can identify and classify a particular behavior of the subject software. Once the user has identified the general behavior patterns of the software, he can train a set of rules to represent his knowledge of that behavior. The training process builds rules and fuzzy sets to use in the evaluator. The fuzzy sets classify those data points not clearly identified as a particular classification. Once an initial set of rules is trained, each additional data set given to the SDB will be used by a machine learning mechanism to refine the rules and fuzzy sets. This is a passive process and, therefore, it does not require any additional operator time. The evaluation component of the SDB can be used to validate a single software system using some number of different data sets, such as a simulator. Moreover, it can be used to validate software systems which have been re-engineered from one language and design methodology to a totally new implementation.

  4. Comparison of Event Detection Methods for Centralized Sensor Networks

    NASA Technical Reports Server (NTRS)

    Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

    2006-01-01

    The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

  5. Communication: Analysing kinetic transition networks for rare events.

    PubMed

    Stevenson, Jacob D; Wales, David J

    2014-07-28

    The graph transformation approach is a recently proposed method for computing mean first passage times, rates, and committor probabilities for kinetic transition networks. Here we compare the performance to existing linear algebra methods, focusing on large, sparse networks. We show that graph transformation provides a much more robust framework, succeeding when numerical precision issues cause the other methods to fail completely. These are precisely the situations that correspond to rare event dynamics for which the graph transformation was introduced. PMID:25084870

  6. Automatic classification of seismic events within a regional seismograph network

    NASA Astrophysics Data System (ADS)

    Tiira, Timo; Kortström, Jari; Uski, Marja

    2015-04-01

    A fully automatic method for seismic event classification within a sparse regional seismograph network is presented. The tool is based on a supervised pattern recognition technique, Support Vector Machine (SVM), trained here to distinguish weak local earthquakes from a bulk of human-made or spurious seismic events. The classification rules rely on differences in signal energy distribution between natural and artificial seismic sources. Seismic records are divided into four windows, P, P coda, S, and S coda. For each signal window STA is computed in 20 narrow frequency bands between 1 and 41 Hz. The 80 discrimination parameters are used as a training data for the SVM. The SVM models are calculated for 19 on-line seismic stations in Finland. The event data are compiled mainly from fully automatic event solutions that are manually classified after automatic location process. The station-specific SVM training events include 11-302 positive (earthquake) and 227-1048 negative (non-earthquake) examples. The best voting rules for combining results from different stations are determined during an independent testing period. Finally, the network processing rules are applied to an independent evaluation period comprising 4681 fully automatic event determinations, of which 98 % have been manually identified as explosions or noise and 2 % as earthquakes. The SVM method correctly identifies 94 % of the non-earthquakes and all the earthquakes. The results imply that the SVM tool can identify and filter out blasts and spurious events from fully automatic event solutions with a high level of confidence. The tool helps to reduce work-load in manual seismic analysis by leaving only ~5 % of the automatic event determinations, i.e. the probable earthquakes for more detailed seismological analysis. The approach presented is easy to adjust to requirements of a denser or wider high-frequency network, once enough training examples for building a station-specific data set are available.

  7. Automatic event detection based on artificial neural networks

    NASA Astrophysics Data System (ADS)

    Doubravová, Jana; Wiszniowski, Jan; Horálek, Josef

    2015-04-01

    The proposed algorithm was developed to be used for Webnet, a local seismic network in West Bohemia. The Webnet network was built to monitor West Bohemia/Vogtland swarm area. During the earthquake swarms there is a large number of events which must be evaluated automatically to get a quick estimate of the current earthquake activity. Our focus is to get good automatic results prior to precise manual processing. With automatic data processing we may also reach a lower completeness magnitude. The first step of automatic seismic data processing is the detection of events. To get a good detection performance we require low number of false detections as well as high number of correctly detected events. We used a single layer recurrent neural network (SLRNN) trained by manual detections from swarms in West Bohemia in the past years. As inputs of the SLRNN we use STA/LTA of half-octave filter bank fed by vertical and horizontal components of seismograms. All stations were trained together to obtain the same network with the same neuron weights. We tried several architectures - different number of neurons - and different starting points for training. Networks giving the best results for training set must not be the optimal ones for unknown waveforms. Therefore we test each network on test set from different swarm (but still with similar characteristics, i.e. location, focal mechanisms, magnitude range). We also apply a coincidence verification for each event. It means that we can lower the number of false detections by rejecting events on one station only and force to declare an event on all stations in the network by coincidence on two or more stations. In further work we would like to retrain the network for each station individually so each station will have its own coefficients (neural weights) set. We would also like to apply this method to data from Reykjanet network located in Reykjanes peninsula, Iceland. As soon as we have a reliable detection, we can proceed to

  8. Drag and drop display & builder

    SciTech Connect

    Bolshakov, Timofei B.; Petrov, Andrey D.; /Fermilab

    2007-12-01

    The Drag and Drop (DnD) Display & Builder is a component-oriented system that allows users to create visual representations of data received from data acquisition systems. It is an upgrade of a Synoptic Display mechanism used at Fermilab since 2002. Components can be graphically arranged and logically interconnected in the web-startable Project Builder. Projects can be either lightweight AJAX- and SVG-based web pages, or they can be started as Java applications. The new version was initiated as a response to discussions between the LHC Controls Group and Fermilab.

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

    PubMed Central

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    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. PMID:26694394

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

    PubMed

    Zhou, Zhangbing; Xing, Riliang; Duan, Yucong; Zhu, Yueqin; Xiang, Jianming

    2015-01-01

    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. PMID:26694394

  11. Seismic event interpretation using fuzzy logic and neural networks

    SciTech Connect

    Maurer, W.J.; Dowla, F.U.

    1994-01-01

    In the computer interpretation of seismic data, unknown sources of seismic events must be represented and reasoned about using measurements from the recorded signal. In this report, we develop the use of fuzzy logic to improve our ability to interpret weak seismic events. Processing strategies for the use of fuzzy set theory to represent vagueness and uncertainty, a phenomena common in seismic data analysis, are developed. A fuzzy-assumption based truth-maintenance-inferencing engine is also developed. Preliminary results in interpreting seismic events using the fuzzy neural network knowledge-based system are presented.

  12. Builders Challenge High Performance Builder Spotlight - Artistic Homes, Albuquerque, NM

    SciTech Connect

    2009-01-01

    Building America Builders Challenge fact sheet on Artistic Homes of Albuquerque, New Mexico. Describes the first true zero E-scale home in a hot-dry climate with ducts inside, R-50 attic insulation, roof-mounted photovoltaic power system, and solar thermal water heating.

  13. Characterizing interactions in online social networks during exceptional events

    NASA Astrophysics Data System (ADS)

    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.

  14. Forecasting solar proton event with artificial neural network

    NASA Astrophysics Data System (ADS)

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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. PMID:23522624

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

    PubMed

    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. PMID:26708304

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

    PubMed Central

    Hu, Hongzhi; Wu, Tunan

    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. PMID:24600323

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

    NASA Technical Reports Server (NTRS)

    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.

  20. Predicting adverse drug events using pharmacological network models.

    PubMed

    Cami, Aurel; Arnold, Alana; Manzi, Shannon; Reis, Ben

    2011-12-21

    Early and accurate identification of adverse drug events (ADEs) is critically important for public health. We have developed a novel approach for predicting ADEs, called predictive pharmacosafety networks (PPNs). PPNs integrate the network structure formed by known drug-ADE relationships with information on specific drugs and adverse events to predict likely unknown ADEs. Rather than waiting for sufficient post-market evidence to accumulate for a given ADE, this predictive approach relies on leveraging existing, contextual drug safety information, thereby having the potential to identify certain ADEs earlier. We constructed a network representation of drug-ADE associations for 809 drugs and 852 ADEs on the basis of a snapshot of a widely used drug safety database from 2005 and supplemented these data with additional pharmacological information. We trained a logistic regression model to predict unknown drug-ADE associations that were not listed in the 2005 snapshot. We evaluated the model's performance by comparing these predictions with the new drug-ADE associations that appeared in a 2010 snapshot of the same drug safety database. The proposed model achieved an AUROC (area under the receiver operating characteristic curve) statistic of 0.87, with a sensitivity of 0.42 given a specificity of 0.95. These findings suggest that predictive network methods can be useful for predicting unknown ADEs. PMID:22190238

  1. Event Networks and the Identification of Crime Pattern Motifs.

    PubMed

    Davies, Toby; Marchione, Elio

    2015-01-01

    In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

  2. Event Networks and the Identification of Crime Pattern Motifs

    PubMed Central

    2015-01-01

    In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

  3. Development and Evaluation of a Dynamic Moving Storm (DMS) Builder

    NASA Astrophysics Data System (ADS)

    Fang, N. Z.; Gao, S.

    2014-12-01

    The University of Texas at Arlington (UTA) developed a design rainfall generator - Dynamic Moving Storm (DMS). DMS is a unique tool because it accounts for three major factors of real rainfall events simultaneously that other tools do not: (1) spatial variability, (2) temporal variability, and (3) directional movement. The rainfall intensity distribution with a storm is normally referred to spatial variability factor. The DMS builder takes in account storm sizes, shapes, and orientations (for non-circular storms) within the spatial variability module. Given rainfall intensity within the storm always varies with respect of time, the builder has a capability of specifying temporal distributions of rainfall intensities following linear or exponential patterns. To represent the dynamic motions of real storms, the researchers at UTA developed a movement module into DMS to handle combinations of accelerations, decelerations, pause and turns. Typically, an idealized storm generated by DMS can be presented as a circular shape in 2-D and conic shape in 3-D views. While it moves across a watershed, the rainfall pattern within the storm follows a certain temporal pattern. Once various combinations of spatial, temporal, and movement factors are input into the DMS builder, it can generate corresponding elliptical-shaped rainfall contours with rainfall hyetographs for each subbasin of a particular watershed. The resulted rainfall information can then be fed into hydrologic models to evaluate the spatiotemporal impacts for any watersheds. This paper demonstrates a case study using DMS builder to access the vulnerability for the Brays Bayou watershed in Houston, Texas.

  4. Builders Challenge High Performance Builder Spotlight - Community Development Corporation of Utah

    SciTech Connect

    2008-01-01

    Building America/Builders Challenge fact sheet on Community Development Corp, an energy-efficient home builder in cold climate using advanced framing and compact duct design. Evaluates impacts to cost.

  5. Builders Challenge High Performance Builder Spotlight: Yavapai College, Chino Valley, Arizona

    SciTech Connect

    2009-12-22

    Building America Builders Challenge fact sheet on Yavapai College of Chino Valley, Arizona. These college students built a Building America Builders Challenge house that achieved the remarkably low HERS score of -3 and achieved a tight building envelope.

  6. Builders Challenge High Performance Builder Spotlight - Martha Rose Construction, Inc., Seattle, Washington

    SciTech Connect

    2008-01-01

    Building America/Builders Challenge fact sheet on Martha Rose Construction, an energy-efficient home builder in marine climate using the German Passiv Haus design, improved insulation, and solar photovoltaics.

  7. Event-driven approach of layered multicast to network adaptation in RED-based IP networks

    NASA Astrophysics Data System (ADS)

    Nahm, Kitae; Li, Qing; Kuo, C.-C. J.

    2003-11-01

    In this work, we investigate the congestion control problem for layered video multicast in IP networks of active queue management (AQM) using a simple random early detection (RED) queue model. AQM support from networks improves the visual quality of video streaming but makes network adaptation more di+/-cult for existing layered video multicast proticols that use the event-driven timer-based approach. We perform a simplified analysis on the response of the RED algorithm to burst traffic. The analysis shows that the primary problem lies in the weak correlation between the network feedback and the actual network congestion status when the RED queue is driven by burst traffic. Finally, a design guideline of the layered multicast protocol is proposed to overcome this problem.

  8. A novel progressive signal association algorithm for detecting teleseismic/network-outside events using regional seismic networks

    NASA Astrophysics Data System (ADS)

    Jin, Ping; Pan, Changzhou; Zhang, Chengliu; Shen, Xufeng; Wang, Hongchun; Lu, Na

    2015-06-01

    Regional seismic networks may and in some cases need to be used to monitor teleseismic or network-outside events. For detecting and localizing teleseismic events automatically and reliably in this case, in this paper we present a novel progressive association algorithm for teleseismic signals recorded by a regional seismic network. The algorithm takes triangle station arrays as the starting point to search for P waves of teleseismic events progressively by that, as detections from different stations actually are from the same teleseismic event, their arrival times should be linearly related to the average slowness vector with which the signal propagates across the network, and the slowness of direct teleseismic P wave basically is different from other major seismic phases. We have tested this algorithm using data recorded by Xinjiang Seismic Network of China (XJSN) for 16 d. The results show that the algorithm can effectively and reliably detect and localize earthquakes outside of the network. For the period of the test data, as all mb 4.0+ events with Δc < 30° and all mb 4.5+ events with Δc < 60° referring to the International Data Center-Reviewed Event Bulletin (IDC REB) were detected, where Δc is the epicentral distance relative to the network's geographical centre, the rate of false events only accounted for 2.4 per cent, suggesting that the new association algorithm has good application prospect for situations when regional seismic networks need to be used to monitor teleseismic events.

  9. Rome: sinkhole events and network of underground cavities (Italy)

    NASA Astrophysics Data System (ADS)

    Nisio, Stefania; Ciotoli, Giancarlo

    2016-04-01

    The anthropogenic sinkholes in the city of Rome are closely linked to the network of underground cavities produced by human activities in more than two thousand years of history. Over the past fifteen years the increased frequency of intense rainfall events, favors sinkhole formation. The risk assessment induced by anthropogenic sinkhole is really difficult. However, a susceptibility of the territory to sinkholes can be more easily determined as the probability that an event may occur in a given space, with unique geological-morphological characteristics, and in an infinite time. A sinkhole susceptibility map of the Rome territory, up to the ring road, has been constructed by using Geographically Weighted Regression technique and geostatistics. The spatial regression model includes the analysis of more than 2700 anthropogenic sinkholes (recorded from 1875 to 2015), as well as geological, morphological, hydrological and predisposing anthropogenic characteristics of the study area. The numerous available data (underground cavities, the ancient entrances to the quarry, bunkers, etc.) facilitate the creation of a series of maps. The density map of the cavity, updated to 2015, showed that more than 20 km2 of the Roman territory are affected by underground cavities. The census of sinkholes (over 2700) shows that over 30 km2 has been affected by sinkholes. The final susceptibility map highlights that inside the Ring Road about 40 km2 of the territory (about 11%) have a very high probability of triggering a sinkhole event. The susceptibility map was also compared with the data of ground subsidence (InSAR) to obtain a predictive model.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Wireless address event representation system for biological sensor networks

    NASA Astrophysics Data System (ADS)

    Folowosele, Fopefolu; Tapson, Jonathan; Etienne-Cummings, Ralph

    2007-05-01

    We describe wireless networking systems for close proximity biological sensors, as would be encountered in artificial skin. The sensors communicate to a "base station" that interprets the data and decodes its origin. Using a large bundle of ultra thin metal wires from the sensors to the "base station" introduces significant technological hurdles for both the construction and maintenance of the system. Fortunately, the Address Event Representation (AER) protocol provides an elegant and biomorphic method for transmitting many impulses (i.e. neural spikes) down a single wire/channel. However, AER does not communicate any sensory information within each spike, other that the address of the origination of the spike. Therefore, each sensor must provide a number of spikes to communicate its data, typically in the form of the inter-spike intervals or spike rate. Furthermore, complex circuitry is required to arbitrate access to the channel when multiple sensors communicate simultaneously, which results in spike delay. This error is exacerbated as the number of sensors per channel increases, mandating more channels and more wires. We contend that despite the effectiveness of the wire-based AER protocol, its natural evolution will be the wireless AER protocol. A wireless AER system: (1) does not require arbitration to handle multiple simultaneous access of the channel, (2) uses cross-correlation delay to encode sensor data in every spike (eliminating the error due to arbitration delay), and (3) can be reorganized and expanded with little consequence to the network. The system uses spread spectrum communications principles, implemented with a low-power integrate-and-fire neurons. This paper discusses the design, operation and capabilities of such a system. We show that integrate-and-fire neurons can be used to both decode the origination of each spike and extract the data contained within in. We also show that there are many technical obstacles to overcome before this version

  12. The CMS Remote Analysis Builder (CRAB)

    SciTech Connect

    Spiga, D.; Cinquilli, M.; Servoli, L.; Lacaprara, S.; Fanzago, F.; Dorigo, A.; Merlo, M.; Farina, F.; Fanfani, A.; Codispoti, G.; Bacchi, W.; /INFN, Bologna /Bologna U /CERN /INFN, CNAF /INFN, Trieste /Fermilab

    2008-01-22

    The CMS experiment will produce several Pbytes of data every year, to be distributed over many computing centers geographically distributed in different countries. Analysis of this data will be also performed in a distributed way, using grid infrastructure. CRAB (CMS Remote Analysis Builder) is a specific tool, designed and developed by the CMS collaboration, that allows a transparent access to distributed data to end physicist. Very limited knowledge of underlying technicalities are required to the user. CRAB interacts with the local user environment, the CMS Data Management services and with the Grid middleware. It is able to use WLCG, gLite and OSG middleware. CRAB has been in production and in routine use by end-users since Spring 2004. It has been extensively used in studies to prepare the Physics Technical Design Report (PTDR) and in the analysis of reconstructed event samples generated during the Computing Software and Analysis Challenge (CSA06). This involved generating thousands of jobs per day at peak rates. In this paper we discuss the current implementation of CRAB, the experience with using it in production and the plans to improve it in the immediate future.

  13. Interactive effects of elevation, species richness and extreme climatic events on plant-pollinator networks.

    PubMed

    Hoiss, Bernhard; Krauss, Jochen; Steffan-Dewenter, Ingolf

    2015-11-01

    Plant-pollinator interactions are essential for the functioning of terrestrial ecosystems, but are increasingly affected by global change. The risks to such mutualistic interactions from increasing temperature and more frequent extreme climatic events such as drought or advanced snow melt are assumed to depend on network specialization, species richness, local climate and associated parameters such as the amplitude of extreme events. Even though elevational gradients provide valuable model systems for climate change and are accompanied by changes in species richness, responses of plant-pollinator networks to climatic extreme events under different environmental and biotic conditions are currently unknown. Here, we show that elevational climatic gradients, species richness and experimentally simulated extreme events interactively change the structure of mutualistic networks in alpine grasslands. We found that the degree of specialization in plant-pollinator networks (H2') decreased with elevation. Nonetheless, network specialization increased after advanced snow melt at high elevations, whereas changes in network specialization after drought were most pronounced at sites with low species richness. Thus, changes in network specialization after extreme climatic events depended on climatic context and were buffered by high species richness. In our experiment, only generalized plant-pollinator networks changed in their degree of specialization after climatic extreme events. This indicates that contrary to our assumptions, network generalization may not always foster stability of mutualistic interaction networks. PMID:26332102

  14. Builders Challenge High Performance Builder Spotlight: David Weekley Homes, Houston, Texas

    SciTech Connect

    2009-12-22

    Building America Builders Challenge fact sheet on David Weekley Homes of Houston, Texas. The builder plans homes as a "system," with features such as wood-framed walls that are air-sealed then insulated with R-13 unfaced fiberglass batts plus an external covering of R-2 polyisocyanurate rigid foam sheathing.

  15. Builders Challenge High Performance Builder Spotlight - Masco Environments for Living, Las Vegas, Nevada

    SciTech Connect

    2009-01-01

    Building America Builders Challenge fact sheet on Masco’s Environments for Living Certified Green demo home at the 2009 International Builders Show in Las Vegas. The home has a Home Energy Rating System (HERS) index score of 44, a right-sized air conditi

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

    ERIC Educational Resources Information Center

    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…

  17. Building America Best Practices Series Volume 8: Builders Challenge Quality Criteria Support Document

    SciTech Connect

    Baechler, Michael C.; Bartlett, Rosemarie; Gilbride, Theresa L.

    2010-11-01

    The U.S. Department of Energy (DOE) has posed a challenge to the homebuilding industry—to build 220,000 high-performance homes by 2012. Through the Builders Challenge, participating homebuilders will have an easy way to differentiate their best energy-performing homes from other products in the marketplace, and to make the benefits clear to buyers. This document was prepared by Pacific Northwest National Laboratory for DOE to provide guidance to U.S. home builders who want to accept the challenge. To qualify for the Builders Challenge, a home must score 70 or less on the EnergySmart Home Scale (E-Scale). The E-scale is based on the well-established Home Energy Rating System (HERS) index, developed by the Residential Energy Services Network (RESNET). The E-scale allows homebuyers to understand – at a glance – how the energy performance of a particular home compares with the performance of others. To learn more about the index and HERS Raters, visit www.natresnet.org. Homes also must meet the Builders Challenge criteria described in this document. To help builders meet the Challenge, guidance is provided in this report for each of the 29 criteria. Included with guidance for each criteria are resources for more information and references for relevant codes and standards. The Builders Challenge Quality Criteria were originally published in Dec. 2008. They were revised and published as PNNL-18009 Rev 1.2 in Nov. 2009. This is version 1.3, published Nov 2010. Changes from the Nov 2009 version include adding a title page and updating the Energy Star windows critiera to the Version 5.0 criteria approved April 2009 and effective January 4, 2010. This document and other information about the Builders Challenge is available on line at www.buildingamerica.gov/challenge.

  18. Impact assessment of extreme storm events using a Bayesian network

    USGS Publications Warehouse

    den Heijer, C.(Kees); Knipping, Dirk T.J.A.; Plant, Nathaniel G.; van Thiel de Vries, Jaap S. M.; Baart, Fedor; van Gelder, Pieter H. A. J. M.

    2012-01-01

    This paper describes an investigation on the usefulness of Bayesian Networks in the safety assessment of dune coasts. A network has been created that predicts the erosion volume based on hydraulic boundary conditions and a number of cross-shore profile indicators. Field measurement data along a large part of the Dutch coast has been used to train the network. Corresponding storm impact on the dunes was calculated with an empirical dune erosion model named duros+. Comparison between the Bayesian Network predictions and the original duros+ results, here considered as observations, results in a skill up to 0.88, provided that the training data covers the range of predictions. Hence, the predictions from a deterministic model (duros+) can be captured in a probabilistic model (Bayesian Network) such that both the process knowledge and uncertainties can be included in impact and vulnerability assessments.

  19. High Performance Builder Spotlight: Imagine Homes

    SciTech Connect

    2011-01-01

    Imagine Homes, working with the DOE's Building America research team member IBACOS, has developed a system that can be replicated by other contractors to build affordable, high-performance homes. Imagine Homes has used the system to produce more than 70 Builders Challenge-certified homes per year in San Antonio over the past five years.

  20. JOB BUILDER remote batch processing subsystem

    NASA Technical Reports Server (NTRS)

    Orlov, I. G.; Orlova, T. L.

    1980-01-01

    The functions of the JOB BUILDER remote batch processing subsystem are described. Instructions are given for using it as a component of a display system developed by personnel of the System Programming Laboratory, Institute of Space Research, USSR Academy of Sciences.

  1. High Performance Builder Spotlight: Cobblestone Homes

    SciTech Connect

    2011-01-01

    Cobblestone Homes of Freeland,MI quest to understand building science led to construction in 2010 of the "Vision Zero Project," a demonstration home that has earned a DOE Builders Challenge certification and achieved a HERS index of -4 with photovoltaics and 37 without PV.

  2. High Performance Builder Spotlight: Treasure Homes Inc.

    SciTech Connect

    2011-01-01

    Treasure Homes, Inc., achieved a HERS rating of 46 without PV on its prototype “Gem” home, located on the shores of Lake Michigan in northern Indiana, thanks in part to training received from a Building America partner, the National Association of Home Builders Research Center.

  3. Automatic Analysis of Radio Meteor Events Using Neural Networks

    NASA Astrophysics Data System (ADS)

    Roman, Victor Ştefan; Buiu, Cătălin

    2015-12-01

    Meteor Scanning Algorithms (MESCAL) is a software application for automatic meteor detection from radio recordings, which uses self-organizing maps and feedforward multi-layered perceptrons. This paper aims to present the theoretical concepts behind this application and the main features of MESCAL, showcasing how radio recordings are handled, prepared for analysis, and used to train the aforementioned neural networks. The neural networks trained using MESCAL allow for valuable detection results, such as high correct detection rates and low false-positive rates, and at the same time offer new possibilities for improving the results.

  4. Automatic Analysis of Radio Meteor Events Using Neural Networks

    NASA Astrophysics Data System (ADS)

    Roman, Victor Ştefan; Buiu, Cătălin

    2015-07-01

    Meteor Scanning Algorithms (MESCAL) is a software application for automatic meteor detection from radio recordings, which uses self-organizing maps and feedforward multi-layered perceptrons. This paper aims to present the theoretical concepts behind this application and the main features of MESCAL, showcasing how radio recordings are handled, prepared for analysis, and used to train the aforementioned neural networks. The neural networks trained using MESCAL allow for valuable detection results, such as high correct detection rates and low false-positive rates, and at the same time offer new possibilities for improving the results.

  5. Event-triggered synchronization strategy for complex dynamical networks with the Markovian switching topologies.

    PubMed

    Wang, Aijuan; Dong, Tao; Liao, Xiaofeng

    2016-02-01

    This paper concerns the synchronization problem of complex networks with the random switching topologies. By modeling the switching of network topologies as a Markov process, a novel event-triggered synchronization strategy is proposed. Unlike the existing strategies, the event detection of this strategy only works at the network topology switching time instant, which can significantly decrease the communication frequency between nodes and save the network resources. Under this strategy, the synchronization problem of complex network is equivalently converted to the stability of a class of Markovian jump systems with a time-varying delay. By using the Lyapunov-Krasovskii functional method and the weak infinitesimal operation, a sufficient condition for the mean square synchronization of the complex networks subject to Markovian switching topologies is established. Finally, a numerical simulation example is provided to demonstrate the theoretical results. PMID:26650712

  6. DISCRETE EVENT SIMULATION OF OPTICAL SWITCH MATRIX PERFORMANCE IN COMPUTER NETWORKS

    SciTech Connect

    Imam, Neena; Poole, Stephen W

    2013-01-01

    In this paper, we present application of a Discrete Event Simulator (DES) for performance modeling of optical switching devices in computer networks. Network simulators are valuable tools in situations where one cannot investigate the system directly. This situation may arise if the system under study does not exist yet or the cost of studying the system directly is prohibitive. Most available network simulators are based on the paradigm of discrete-event-based simulation. As computer networks become increasingly larger and more complex, sophisticated DES tool chains have become available for both commercial and academic research. Some well-known simulators are NS2, NS3, OPNET, and OMNEST. For this research, we have applied OMNEST for the purpose of simulating multi-wavelength performance of optical switch matrices in computer interconnection networks. Our results suggest that the application of DES to computer interconnection networks provides valuable insight in device performance and aids in topology and system optimization.

  7. Forecasting ENSO events: A neural network-extended EOF approach

    SciTech Connect

    Tangang, F.T.; Tang, B.; Monahan, A.H.; Hsieh, W.W.

    1998-01-01

    The authors constructed neural network models to forecast the sea surface temperature anomalies (SSTA) for three regions: Nino 4. Nino 3.5, and Nino 3, representing the western-central, the central, and the eastern-central parts of the equatorial Pacific Ocean, respectively. The inputs were the extended empirical orthogonal functions (EEOF) of the sea level pressure (SLP) field that covered the tropical Indian and Pacific Oceans and evolved for a duration of 1 yr. The EEOFs greatly reduced the size of the neural networks from those of the authors` earlier papers using EOFs. The Nino 4 region appeared to be the best forecasted region, with useful skills up to a year lead time for the 1982-93 forecast period. By network pruning analysis and spectral analysis, four important inputs were identified: modes 1, 2, and 6 of the SLP EEOFs and the SSTA persistence. Mode 1 characterized the low-frequency oscillation (LFO, with 4-5-yr period), and was seen as the typical ENSO signal, while mode 2, with a period of 2-5 yr, characterized the quasi-biennial oscillation (QBO) plus the LFO. Mode 6 was dominated by decadal and interdecadal variations. Thus, forecasting ENSO required information from the QBO, and the decadal-interdecadal oscillations. The nonlinearity of the networks tended to increase with lead time and to become stronger for the eastern regions of the equatorial Pacific Ocean. 35 refs., 14 figs., 4 tabs.

  8. Cough event classification by pretrained deep neural network

    PubMed Central

    2015-01-01

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

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

    PubMed

    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. PMID:25996752

  10. Network-based event-triggered filtering for Markovian jump systems

    NASA Astrophysics Data System (ADS)

    Wang, Huijiao; Shi, Peng; Agarwal, Ramesh K.

    2016-06-01

    The problem of event-triggered H∞ filtering for networked Markovian jump system is studied in this paper. A dynamic discrete event-triggered scheme is designed to choose the transmitted data for different Markovian jumping modes. The time-delay modelling method is employed to describe the event-triggered scheme and the network-related behaviour, such as transmission delay, data package dropout and disorder, into a networked Markovian time-delay jump system. Furthermore, a sufficient condition is derived to guarantee that the resulting filtering error system is stochastically stable with a prescribed performance index. A co-design method for the H∞ filter and the event-triggered scheme is then proposed. The effectiveness and potential of the theoretic results obtained are illustrated by a simulation example.

  11. Percolation Features on Climate Network under Attacks of El Niño Events

    NASA Astrophysics Data System (ADS)

    Lu, Z.

    2015-12-01

    Percolation theory under different attacks is one of the main research areas in complex networks but never be applied to investigate climate network. In this study, for the first time we construct a climate network of surface air temperature field to analyze its percolation features. Here, we regard El Niño event as a kind of naturally attacks generated from Pacific Ocean to attack its upper climate network. We find that El Niño event leads an abrupt percolation phase transition to the climate network which makes it splitting and unstable suddenly. Comparing the results of the climate network under three different forms of attacks, including most connected attack (MA), localized attack (LA) and random attack (RA) respectively, it is found that both MA and LA lead first-order transition and RA leads second-order transition to the climate network. Furthermore, we find that most real attacks consist of all these three forms of attacks. With El Niño event emerging, the ratios of LA and MA increase and dominate the style of attack while RA decreasing. It means the percolation phase transition due to El Niño events is close to first-order transition mostly affected by LA and MA. Our research may help us further understand two questions from perspective of percolation on network: (1) Why not all warming in Pacific Ocean but El Niño events could affect the climate. (2) Why the climate affected by El Niño events changes abruptly.

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

    PubMed

    Gigante, Guido; Deco, Gustavo; Marom, Shimon; Del Giudice, Paolo

    2015-11-01

    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. PMID:26558616

  13. A Fuzzy-Decision Based Approach for Composite Event Detection in Wireless Sensor Networks

    PubMed Central

    Zhang, Shukui; Chen, Hao; Zhu, Qiaoming

    2014-01-01

    The event detection is one of the fundamental researches in wireless sensor networks (WSNs). Due to the consideration of various properties that reflect events status, the Composite event is more consistent with the objective world. Thus, the research of the Composite event becomes more realistic. In this paper, we analyze the characteristics of the Composite event; then we propose a criterion to determine the area of the Composite event and put forward a dominating set based network topology construction algorithm under random deployment. For the unreliability of partial data in detection process and fuzziness of the event definitions in nature, we propose a cluster-based two-dimensional τ-GAS algorithm and fuzzy-decision based composite event decision mechanism. In the case that the sensory data of most nodes are normal, the two-dimensional τ-GAS algorithm can filter the fault node data effectively and reduce the influence of erroneous data on the event determination. The Composite event judgment mechanism which is based on fuzzy-decision holds the superiority of the fuzzy-logic based algorithm; moreover, it does not need the support of a huge rule base and its computational complexity is small. Compared to CollECT algorithm and CDS algorithm, this algorithm improves the detection accuracy and reduces the traffic. PMID:25136690

  14. Nonthreshold-based event detection for 3d environment monitoring in sensor networks

    SciTech Connect

    Li, M.; Liu, Y.H.; Chen, L.

    2008-12-15

    Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records.

  15. You Never Walk Alone: Recommending Academic Events Based on Social Network Analysis

    NASA Astrophysics Data System (ADS)

    Klamma, Ralf; Cuong, Pham Manh; Cao, Yiwei

    Combining Social Network Analysis and recommender systems is a challenging research field. In scientific communities, recommender systems have been applied to provide useful tools for papers, books as well as expert finding. However, academic events (conferences, workshops, international symposiums etc.) are an important driven forces to move forwards cooperation among research communities. We realize a SNA based approach for academic events recommendation problem. Scientific communities analysis and visualization are performed to provide an insight into the communities of event series. A prototype is implemented based on the data from DBLP and EventSeer.net, and the result is observed in order to prove the approach.

  16. WebDB Component Builder - Lessons Learned

    SciTech Connect

    Macedo, C.

    2000-02-15

    Oracle WebDB is the easiest way to produce web enabled lightweight and enterprise-centric applications. This concept from Oracle has tantalized our taste for simplistic web development by using a purely web based tool that lives nowhere else but in the database. The use of online wizards, templates, and query builders, which produces PL/SQL behind the curtains, can be used straight ''out of the box'' by both novice and seasoned developers. The topic of this presentation will introduce lessons learned by developing and deploying applications built using the WebDB Component Builder in conjunction with custom PL/SQL code to empower a hybrid application. There are two kinds of WebDB components: those that display data to end users via reporting, and those that let end users update data in the database via entry forms. The presentation will also discuss various methods within the Component Builder to enhance the applications pushed to the desktop. The demonstrated example is an application entitled HOME (Helping Other's More Effectively) that was built to manage a yearly United Way Campaign effort. Our task was to build an end to end application which could manage approximately 900 non-profit agencies, an average of 4,100 individual contributions, and $1.2 million dollars. Using WebDB, the shell of the application was put together in a matter of a few weeks. However, we did encounter some hurdles that WebDB, in it's stage of infancy (v2.0), could not solve for us directly. Together with custom PL/SQL, WebDB's Component Builder became a powerful tool that enabled us to produce a very flexible hybrid application.

  17. XAL Application Framework and Bricks GUI Builder

    SciTech Connect

    Pelaia II, Tom

    2007-01-01

    The XAL [1] Application Framework is a framework for rapidly developing document based Java applications with a common look and feel along with many built-in user interface behaviors. The Bricks GUI builder consists of a modern application and framework for rapidly building user interfaces in support of true Model-View-Controller (MVC) compliant Java applications. Bricks and the XAL Application Framework allow developers to rapidly create quality applications.

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

    PubMed Central

    Gigante, Guido; Deco, Gustavo; Marom, Shimon; Del Giudice, Paolo

    2015-01-01

    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. PMID:26558616

  19. Probabilistic approaches to fault detection in networked discrete event systems.

    PubMed

    Athanasopoulou, Eleftheria; Hadjicostis, Christoforos N

    2005-09-01

    In this paper, we consider distributed systems that can be modeled as finite state machines with known behavior under fault-free conditions, and we study the detection of a general class of faults that manifest themselves as permanent changes in the next-state transition functionality of the system. This scenario could arise in a variety of situations encountered in communication networks, including faults occurred due to design or implementation errors during the execution of communication protocols. In our approach, fault diagnosis is performed by an external observer/diagnoser that functions as a finite state machine and which has access to the input sequence applied to the system but has only limited access to the system state or output. In particular, we assume that the observer/diagnoser is only able to obtain partial information regarding the state of the given system at intermittent time intervals that are determined by certain synchronizing conditions between the system and the observer/diagnoser. By adopting a probabilistic framework, we analyze ways to optimally choose these synchronizing conditions and develop adaptive strategies that achieve a low probability of aliasing, i.e., a low probability that the external observer/diagnoser incorrectly declares the system as fault-free. An application of these ideas in the context of protocol testing/classification is provided as an example. PMID:16252815

  20. Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

    NASA Technical Reports Server (NTRS)

    Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

    2006-01-01

    Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

  1. Novel algorithms for improved pattern recognition using the US FDA Adverse Event Network Analyzer.

    PubMed

    Botsis, Taxiarchis; Scott, John; Goud, Ravi; Toman, Pamela; Sutherland, Andrea; Ball, Robert

    2014-01-01

    The medical review of adverse event reports for medical products requires the processing of "big data" stored in spontaneous reporting systems, such as the US Vaccine Adverse Event Reporting System (VAERS). VAERS data are not well suited to traditional statistical analyses so we developed the FDA Adverse Event Network Analyzer (AENA) and three novel network analysis approaches to extract information from these data. Our new approaches include a weighting scheme based on co-occurring triplets in reports, a visualization layout inspired by the islands algorithm, and a network growth methodology for the detection of outliers. We explored and verified these approaches by analysing the historical signal of Intussusception (IS) after the administration of RotaShield vaccine (RV) in 1999. We believe that our study supports the use of AENA for pattern recognition in medical product safety and other clinical data. PMID:25160375

  2. Airway reopening through catastrophic events in a hierarchical network

    PubMed Central

    Baudoin, Michael; Song, Yu; Manneville, Paul; Baroud, Charles N.

    2013-01-01

    When you reach with your straw for the final drops of a milkshake, the liquid forms a train of plugs that flow slowly initially because of the high viscosity. They then suddenly rupture and are replaced with a rapid airflow with the characteristic slurping sound. Trains of liquid plugs also are observed in complex geometries, such as porous media during petroleum extraction, in microfluidic two-phase flows, or in flows in the pulmonary airway tree under pathological conditions. The dynamics of rupture events in these geometries play the dominant role in the spatial distribution of the flow and in determining how much of the medium remains occluded. Here we show that the flow of a train of plugs in a straight channel is always unstable to breaking through a cascade of ruptures. Collective effects considerably modify the rupture dynamics of plug trains: Interactions among nearest neighbors take place through the wetting films and slow down the cascade, whereas global interactions, through the total resistance to flow of the train, accelerate the dynamics after each plug rupture. In a branching tree of microchannels, similar cascades occur along paths that connect the input to a particular output. This divides the initial tree into several independent subnetworks, which then evolve independently of one another. The spatiotemporal distribution of the cascades is random, owing to strong sensitivity to the plug divisions at the bifurcations. PMID:23277557

  3. A hybrid adaptive routing algorithm for event-driven wireless sensor networks.

    PubMed

    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

  4. Covert Network Analysis for Key Player Detection and Event Prediction Using a Hybrid Classifier

    PubMed Central

    Akram, M. Usman; Khan, Shoab A.; Javed, Muhammad Younus

    2014-01-01

    National security has gained vital importance due to increasing number of suspicious and terrorist events across the globe. Use of different subfields of information technology has also gained much attraction of researchers and practitioners to design systems which can detect main members which are actually responsible for such kind of events. In this paper, we present a novel method to predict key players from a covert network by applying a hybrid framework. The proposed system calculates certain centrality measures for each node in the network and then applies novel hybrid classifier for detection of key players. Our system also applies anomaly detection to predict any terrorist activity in order to help law enforcement agencies to destabilize the involved network. As a proof of concept, the proposed framework has been implemented and tested using different case studies including two publicly available datasets and one local network. PMID:25136674

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

    PubMed

    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. PMID:21499739

  6. Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism.

    PubMed

    Li, Lulu; Ho, Daniel W C; Cao, Jinde; Lu, Jianquan

    2016-04-01

    Cluster synchronization is a typical collective behavior in coupled dynamical systems, where the synchronization occurs within one group, while there is no synchronization among different groups. In this paper, under event-based mechanism, pinning cluster synchronization in an array of coupled neural networks is studied. A new event-triggered sampled-data transmission strategy, where only local and event-triggering states are utilized to update the broadcasting state of each agent, is proposed to realize cluster synchronization of the coupled neural networks. Furthermore, a self-triggered pinning cluster synchronization algorithm is proposed, and a set of iterative procedures is given to compute the event-triggered time instants. Hence, this will reduce the computational load significantly. Finally, an example is given to demonstrate the effectiveness of the theoretical results. PMID:26829603

  7. Proton Single Event Effects (SEE) Testing of the Myrinet Crossbar Switch and Network Interface Card

    NASA Technical Reports Server (NTRS)

    Howard, James W., Jr.; LaBel, Kenneth A.; Carts, Martin A.; Stattel, Ronald; Irwin, Timothy L.; Day, John H. (Technical Monitor)

    2002-01-01

    As part of the Remote Exploration and Experimentation Project (REE), work was performed to do a proton SEE (Single Event Effect) evaluation of the Myricom network protocol system (Myrinet). This testing included the evaluation of the Myrinet crossbar switch and the Network Interface Card (NIC). To this end, two crossbar switch devices and five components in the NIC were exposed to the proton beam at the University of California at Davis Crocker Nuclear Laboratory (CNL).

  8. A network of discrete events for the representation and analysis of diffusion dynamics

    NASA Astrophysics Data System (ADS)

    Pintus, Alberto M.; Pazzona, Federico G.; Demontis, Pierfranco; Suffritti, Giuseppe B.

    2015-11-01

    We developed a coarse-grained description of the phenomenology of diffusive processes, in terms of a space of discrete events and its representation as a network. Once a proper classification of the discrete events underlying the diffusive process is carried out, their transition matrix is calculated on the basis of molecular dynamics data. This matrix can be represented as a directed, weighted network where nodes represent discrete events, and the weight of edges is given by the probability that one follows the other. The structure of this network reflects dynamical properties of the process of interest in such features as its modularity and the entropy rate of nodes. As an example of the applicability of this conceptual framework, we discuss here the physics of diffusion of small non-polar molecules in a microporous material, in terms of the structure of the corresponding network of events, and explain on this basis the diffusivity trends observed. A quantitative account of these trends is obtained by considering the contribution of the various events to the displacement autocorrelation function.

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

    NASA Astrophysics Data System (ADS)

    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

  10. Strain Rate by Geodetic Observations Associated with Seismic Events in the SIRGAS-CON Network Region.

    NASA Astrophysics Data System (ADS)

    Marotta, G. S.; Franca, G.; Galera Monico, J. F.; Fuck, R. A.

    2014-12-01

    This research investigates surface strains related to seismic events and their relationship with pre- and post-seismic events in South American, Antarctica, Nazca, Cocos, North American and Caribbean plates , by analyzing the variation of estimated earth coordinates, for the period 2000-2014, supplied by a geodetic network called SIRGAS-CON. Based on data provided by the USGS for the same period, and after the Global Congruency test, we selected the events associated with unstable geodetic network points. The resulting strains were estimated based on the finite element method. It was possible to determine the strains along with the resulting guidelines for pre- and post-seismic, considering each region formed for analysis as a homogeneous solid body. Later, a multi-year solution of the network was estimated and used to estimate the strain rates of the earth surface from the changing directions of the velocity vectors of 332 geodetic points located in the South American plate and surround plates. The strain rate was determined and, using Euler vector computed, it was possible to estimate the convergence and accommodation rates to each plate. The results showed that contraction regions coincide with locations with most of the high magnitude seismic events. It suggest that major movements detected on the surface occur in regions with more heterogeneous geological structures and multiple rupture events; significant amounts of elastic strain can be accumulated on geological structures away from the plate boundary faults; and, behavior of contractions and extensions is similar to what has been found in seismological studies. Despite the association between seismic events and the strain of geodetic network, some events of high magnitude were excluded because it does not show the surface strain, which is located at great depths. It was confirmed that events of greater magnitude provide increased surface strain rate when compared with other similar depths.

  11. Event-triggered H∞ reliable control for offshore structures in network environments

    NASA Astrophysics Data System (ADS)

    Zhang, Bao-Lin; Han, Qing-Long; Zhang, Xian-Ming

    2016-04-01

    This paper investigates the network-based modeling and event-triggered H∞ reliable control for an offshore structure. First, a network-based model of the offshore structure subject to external wave force and actuator faults is presented. Second, an event-triggering mechanism is proposed such that during the control implementation, only requisite sampled-data is transmitted over networks. Third, an event-triggered H∞ reliable control problem for the offshore structure is solved by employing the Lyapunov-Krasovskii functional approach, and the desired controller can be derived. It is shown through simulation results that for possible actuator failures, the networked controller is capable of guaranteeing the stability of the offshore structure. In addition, compared with the H∞ control scheme without network settings, the proposed controller can suppress the vibration of the offshore structure to almost the same level as the H∞ controller, while the former requires less control cost. Furthermore, under the network-based controller, the communication resources can be saved significantly.

  12. Non-linear time series analysis of precipitation events using regional climate networks for Germany

    NASA Astrophysics Data System (ADS)

    Rheinwalt, Aljoscha; Boers, Niklas; Marwan, Norbert; Kurths, Jürgen; Hoffmann, Peter; Gerstengarbe, Friedrich-Wilhelm; Werner, Peter

    2016-02-01

    Synchronous occurrences of heavy rainfall events and the study of their relation in time and space are of large socio-economical relevance, for instance for the agricultural and insurance sectors, but also for the general well-being of the population. In this study, the spatial synchronization structure is analyzed as a regional climate network constructed from precipitation event series. The similarity between event series is determined by the number of synchronous occurrences. We propose a novel standardization of this number that results in synchronization scores which are not biased by the number of events in the respective time series. Additionally, we introduce a new version of the network measure directionality that measures the spatial directionality of weighted links by also taking account of the effects of the spatial embedding of the network. This measure provides an estimate of heavy precipitation isochrones by pointing out directions along which rainfall events synchronize. We propose a climatological interpretation of this measure in terms of propagating fronts or event traces and confirm it for Germany by comparing our results to known atmospheric circulation patterns.

  13. 17. DETAIL OF BUILDER'S PLAQUE, LOOKING NORTH. Philadelphia & ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    17. DETAIL OF BUILDER'S PLAQUE, LOOKING NORTH. - Philadelphia & Reading Railroad, Wissahickon Creek Viaduct, Spanning Wissahickon Creek, north of Ridge Avenue Bridge, Philadelphia, Philadelphia County, PA

  14. 25. EAST KEYSTONE OF PORTE COCHERE INSCRIBED 'G. CAMERON. BUILDER.' ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    25. EAST KEYSTONE OF PORTE COCHERE INSCRIBED 'G. CAMERON. BUILDER.' - Smithsonian Institution Building, 1000 Jefferson Drive, between Ninth & Twelfth Streets, Southwest, Washington, District of Columbia, DC

  15. Detection of stick-slip events within the Whillans Ice Stream using an artificial neural network

    NASA Astrophysics Data System (ADS)

    Bernsen, S. P.

    2014-12-01

    Temporal changes in the periodic stick-slip events on the Whillans Ice Stream (WIS) help to understand the hydrosphere-cryosphere coupling in West Antarctica. Previous studies have shown that the periodic behavior has been ongoing for a number of years but the record of slip events is incomplete. Rayleigh waves from WIS grounding line events exhibit different patterns than events from the interior of the glacier. An algorithm using a backpropagation neural network is proposed to efficiently extract surface waves that are a result of stick slip events. A neural network approach has its advantages of machine learning, simplified mathematics, and eliminates the need for an analyst to correctly pick first arrivals. Training data has been assembled using 107 events occuring during the 2010 austral summer that were previously identified to correspond to stick slip events at the grounding line as well as the interior of the WIS. A 0.1 s moving window of 3 s of each of the preprocessed attributes is input into the neural network for automated surface wave detection. Following surface wave detection a much longer 30 minute sliding window is used to classify surface wave detections as grounding line, interior, or non-stick slip events. Similar to the automatic detection algorithms for body waves, preprocessing using STA/LTA ratio, degree of polarization, variance, and skewness exhibit obvious patterns during the onset of surface waves. The The automated event detection could lead to more cost effective means of data collection in future seismic experiments especially with an increase in array density in cold weather regions.

  16. Energy Conservation for the Home Builder: A Course for Residential Builders. Course Outline and Instructional Materials.

    ERIC Educational Resources Information Center

    Koenigshofer, Daniel R.

    Background information, handouts and related instructional materials comprise this manual for conducting a course on energy conservation for home builders. Information presented in the five- and ten-hour course is intended to help residential contractors make appropriate and cost-effective decisions in constructing energy-efficient dwellings.…

  17. Builders Challenge High Performance Builder Spotlight: Artistic Homes, Albuquerque, New Mexico

    SciTech Connect

    2009-12-22

    Building America Builders Challenge fact sheet on Artistic Homes of Albuquerque, New Mexico. Standard features of their homes include advanced framed 2x6 24-inch on center walls, R-21 blown insulation in the walls, and high-efficiency windows.

  18. Builders Challenge High Performance Builder Spotlight - NextGen Home, Las Vegas, Nevada

    SciTech Connect

    2009-01-01

    Building America Builders Challenge fact sheet on the NextGen demo home built in Las Vegas. The home has a Home Energy Rating System (HERS) index score of 44 with R-40 spray foam attic insulation, R-40 insulated concrete walls, and a 4kW DC solar laminate

  19. The magnetic network location of explosive events observed in the solar transition region

    NASA Technical Reports Server (NTRS)

    Porter, J. G.; Dere, K. P.

    1991-01-01

    Compact short-lived explosive events have been observed in solar transition region lines with the High-Resolution Telescope and Spectrograph (HRTS) flown by the Naval Research Laboratory on a series of rockets and on Spacelab 2. Data from Spacelab 2 are coaligned with a simultaneous magnetogram and near-simultaneous He I 10,380 -A spectroheliogram obtained at the National Solar Observatory at Kitt Peak. The comparison shows that the explosive events occur in the solar magnetic network lanes at the boundaries of supergranular convective cells. However, the events occur away from the larger concentrations of magnetic flux in the network, in contradiction to the observed tendency of the more energetic solar phenomena to be associated with the stronger magnetic fields.

  20. Event-driven model predictive control of sewage pumping stations for sulfide mitigation in sewer networks.

    PubMed

    Liu, Yiqi; Ganigué, Ramon; Sharma, Keshab; Yuan, Zhiguo

    2016-07-01

    Chemicals such as Mg(OH)2 and iron salts are widely dosed to sewage for mitigating sulfide-induced corrosion and odour problems in sewer networks. The chemical dosing rate is usually not automatically controlled but profiled based on experience of operators, often resulting in over- or under-dosing. Even though on-line control algorithms for chemical dosing in single pipes have been developed recently, network-wide control algorithms are currently not available. The key challenge is that a sewer network is typically wide-spread comprising many interconnected sewer pipes and pumping stations, making network-wide sulfide mitigation with a relatively limited number of dosing points challenging. In this paper, we propose and demonstrate an Event-driven Model Predictive Control (EMPC) methodology, which controls the flows of sewage streams containing the dosed chemical to ensure desirable distribution of the dosed chemical throughout the pipe sections of interests. First of all, a network-state model is proposed to predict the chemical concentration in a network. An EMPC algorithm is then designed to coordinate sewage pumping station operations to ensure desirable chemical distribution in the network. The performance of the proposed control methodology is demonstrated by applying the designed algorithm to a real sewer network simulated with the well-established SeweX model using real sewage flow and characteristics data. The EMPC strategy significantly improved the sulfide mitigation performance with the same chemical consumption, compared to the current practice. PMID:27124127

  1. Rare events statistics of random walks on networks: localisation and other dynamical phase transitions

    NASA Astrophysics Data System (ADS)

    De Bacco, Caterina; Guggiola, Alberto; Kühn, Reimer; Paga, Pierre

    2016-05-01

    Rare event statistics for random walks on complex networks are investigated using the large deviation formalism. Within this formalism, rare events are realised as typical events in a suitably deformed path-ensemble, and their statistics can be studied in terms of spectral properties of a deformed Markov transition matrix. We observe two different types of phase transition in such systems: (i) rare events which are singled out for sufficiently large values of the deformation parameter may correspond to localised modes of the deformed transition matrix; (ii) ‘mode-switching transitions’ may occur as the deformation parameter is varied. Details depend on the nature of the observable for which the rare event statistics is studied, as well as on the underlying graph ensemble. In the present paper we report results on rare events statistics for path averages of random walks in Erdős–Rényi and scale free networks. Large deviation rate functions and localisation properties are studied numerically. For observables of the type considered here, we also derive an analytical approximation for the Legendre transform of the large deviation rate function, which is valid in the large connectivity limit. It is found to agree well with simulations.

  2. Economic Comparison of On-Board Module Builder Harvest Methods

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Cotton pickers with on-board module builders (OBMB) eliminates the need for boll buggies, module builders, the tractors, and labor needed to operate this machinery. Additionally, field efficiency may be increased due to less stoppage for unloading and/or waiting to unload. This study estimates the ...

  3. OSCAR experiment high-density network data report: Event 4 - April 21-23, 1981

    SciTech Connect

    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 netwok, as well as airborne air chemistry and cloud chemistry mueasurements, 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 fourth storm event, April 21-23. The report contains the high-density network precipitation chemistry data, air and cloud chemistry data from the two PNL aircraft, and meteorological data for the event, including standard National Weather Service products and radar and rawindsonde data from the event. 3 references, 80 figures, 11 tables.

  4. A Climate Network Based Index to Distinguish Sub- and Supercritical ENSO Events

    NASA Astrophysics Data System (ADS)

    Feng, Qingyi; Dijkstra, Henk

    2015-04-01

    The Bjerknes stability (BJ) index has frequently been used to measure the stability of the Pacific climate state with respect to the occurrence of El Niño-Southern Oscillation (ENSO) events. Although it has been recently criticized for not always reflecting the heat budget accurately, the BJ index nicely distinguishes the effects of different feedbacks on the growth of the ENSO mode of variability. Its main disadvantage is, however, that it has been determined from reanalysis products but not from available observations. This work proposes a similar stability index which is easier to evaluate. Tools of complex network theory are used to reconstruct a climate network from available sea surface temperature data. The new stability index Sd is derived from one of the topological properties (connectedness) of this network. By using output from the Cane-Zebiak model, we demonstrate that Sd provides similar information as the BJ index and can monitor whether an ENSO event is sub- or supercritical. By considering observed temperature data, we show that the 1972 and 1982 events were subcritical (excited by stochastic noise) while the 1997 and 2009 events were supercritical (sustained oscillation).

  5. Sequence-of-events-driven automation of the deep space network

    NASA Technical Reports Server (NTRS)

    Hill, R., Jr.; Fayyad, K.; Smyth, C.; Santos, T.; Chen, R.; Chien, S.; Bevan, R.

    1996-01-01

    In February 1995, sequence-of-events (SOE)-driven automation technology was demonstrated for a Voyager telemetry downlink track at DSS 13. This demonstration entailed automated generation of an operations procedure (in the form of a temporal dependency network) from project SOE information using artificial intelligence planning technology and automated execution of the temporal dependency network using the link monitor and control operator assistant system. This article describes the overall approach to SOE-driven automation that was demonstrated, identifies gaps in SOE definitions and project profiles that hamper automation, and provides detailed measurements of the knowledge engineering effort required for automation.

  6. Seismic network detection probability assessment using waveforms and accounting to event association logic

    NASA Astrophysics Data System (ADS)

    Pinsky, Vladimir; Shapira, Avi

    2016-05-01

    The geographical area where a seismic event of magnitude M ≥ M t is detected by a seismic station network, for a defined probability is derived from a station probability of detection estimated as a function of epicentral distance. The latter is determined from both the bulletin data and the waveforms recorded by the station during the occurrence of the event with and without band-pass filtering. For simulating the real detection process, the waveforms are processed using the conventional Carl Johnson detection and association algorithm. The attempt is presented to account for the association time criterion in addition to the conventional approach adopted by the known PMC method.

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

    PubMed Central

    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

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

    PubMed

    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. PMID:27367610

  9. Identifying positions from affiliation networks: Preserving the duality of people and events

    PubMed Central

    Field, Sam; Frank, Kenneth A.; Schiller, Kathryn; Riegle-Crumb, Catherine; Muller, Chandra

    2010-01-01

    Frank’s [Frank, K.A., 1995. Identifying cohesive subgroups. Social Networks 17, 27–56] clustering technique for one-mode social network data is adapted to identify positions in affiliation networks by drawing on recent extensions of p* models to two-mode data. The algorithm is applied to the classic Deep South data on southern women and the social events in which they participated with results comparable to other algorithms. Monte Carlo simulations are used to generate sampling distributions to test for the presence of clustering in new data sets and to evaluate the performance of the algorithm. The algorithm and simulation results are then applied to high school students’ transcripts from one school from the Adolescent Health and Academic Achievement (AHAA) extension of the National Longitudinal Study of Adolescent Health. PMID:20354579

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

    PubMed Central

    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. PMID:27367610

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

    PubMed Central

    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

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

    PubMed

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

    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

  13. Discrete-event simulation of a wide-area health care network.

    PubMed Central

    McDaniel, J G

    1995-01-01

    OBJECTIVE: Predict the behavior and estimate the telecommunication cost of a wide-area message store-and-forward network for health care providers that uses the telephone system. DESIGN: A tool with which to perform large-scale discrete-event simulations was developed. Network models for star and mesh topologies were constructed to analyze the differences in performances and telecommunication costs. The distribution of nodes in the network models approximates the distribution of physicians, hospitals, medical labs, and insurers in the Province of Saskatchewan, Canada. Modeling parameters were based on measurements taken from a prototype telephone network and a survey conducted at two medical clinics. Simulation studies were conducted for both topologies. RESULTS: For either topology, the telecommunication cost of a network in Saskatchewan is projected to be less than $100 (Canadian) per month per node. The estimated telecommunication cost of the star topology is approximately half that of the mesh. Simulations predict that a mean end-to-end message delivery time of two hours or less is achievable at this cost. A doubling of the data volume results in an increase of less than 50% in the mean end-to-end message transfer time. CONCLUSION: The simulation models provided an estimate of network performance and telecommunication cost in a specific Canadian province. At the expected operating point, network performance appeared to be relatively insensitive to increases in data volume. Similar results might be anticipated in other rural states and provinces in North America where a telephone-based network is desired. PMID:7583646

  14. A Tool for Modelling the Impact of Triggered Landslide Events on Road Networks

    NASA Astrophysics Data System (ADS)

    Taylor, F. E.; Santangelo, M.; Marchesini, I.; Malamud, B. D.; Guzzetti, F.

    2014-12-01

    In the minutes to weeks after a landslide trigger such as an earthquake or heavy rain, tens to thousands of landslides may occur across a region, resulting in simultaneous blockages across the road network, which can impact recovery efforts. In this paper, we show the development, application and confrontation with observed data, of a model to semi-stochastically simulate triggered landslide events and their impact on road network topologies. In this model, "synthetic" triggered landslide event inventories are created by randomly selecting landslide sizes and shapes from already established statistical distributions. The landslides are then semi-randomly distributed over the region's road network, where they are more or less likely to land based on a landslide susceptibility map. The number, size and network impact of the road blockages is then calculated. This process is repeated in a Monte Carlo type simulation to assess a range of scenarios. Due to the generally applicable statistical distributions used to create the synthetic triggered landslide event inventories and the relatively minimal data requirements to run the model, the model is theoretically applicable to many regions of the world where triggered landslide events occur. Current work focuses on applying the model to two regions: (i) the Collazzone basin (79 km2) in Central Italy where 422 landslides were triggered by rapid snowmelt in January 1997, (ii) the Oat Mountain quadrangle (155 km2) in California, USA, where 1,350 landslides were triggered by the Northridge Earthquake (M = 6.7) in January 1994. When appropriate adjustments are made to susceptibility in the immediate vicinity of the roads, model results match reasonably well observations. In Collazzone (length of road = 153 km, landslide density = 5.2 landslides km-2), the median number of road blockages over 100 model runs was 5 (±2.5 s.d.), compared to the observed number of 5. In Northridge (length of road = 780 km, landslide density = 8

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

    PubMed Central

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

    2015-01-01

    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. PMID:26190856

  16. First-break refraction event picking and seismic data trace editing using neural networks

    SciTech Connect

    McCormack, M.D.; Zaucha, D.E.; Dushek, D.W. )

    1993-01-01

    Interactive seismic processing systems for editing noisy seismic traces and picking the first-break refraction events have been developed using a neural network learning algorithm. The authors employ a back propagation neural network (BNN) paradigm modified to improve the convergence rate of the BNN. The BNN is interactively trained'' to edit seismic data or pick first breaks by a human processor who judiciously selects and presents to the network examples of trace edits or refraction picks. The network then iteratively adjusts a set of internal weights until it can accurately duplicate the examples provided by the user. After the training session is completed, the BNN system an then process new data sets in a manner that mimics the human processor. Synthetic modeling studies indicated that the BNN uses many of the same subjective criteria that humans employ in editing and picking seismic data sets. Automated trace editing and first-break picking based on the modified BNN paradigm achieve 90 to 98 percent agreement with manual methods for seismic data of moderate to good quality. Productivity increases over manual editing, and picking techniques range from 60 percent for two-dimensional (2-D) data sets and up to 800 percent for three-dimensional (3-D) data sets. Neural network-based seismic processing can provide consistent and high quality results with substantial improvements in processing efficiency.

  17. 8. DETAIL OF BUILDER'S PLATE, PROCLAIMING THE INVENTOR OF THIS ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    8. DETAIL OF BUILDER'S PLATE, PROCLAIMING THE INVENTOR OF THIS BRIDGE TYPE, WILLIAM SCHERZER. - Pennsylvania Railroad, "Eight-track" Bascule Bridge, Spanning Sanitary & Ship Canal, west of Western Avenue, Chicago, Cook County, IL

  18. 45. VIEW OF BRONZE BUILDERS PLATE LOCATED ON NORTH SIDE ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    45. VIEW OF BRONZE BUILDERS PLATE LOCATED ON NORTH SIDE AT OUTERMOST END OF WESTERN APPROACH WALL - Tomlinson Bridge, Spanning Quinnipiac River at Forbes Street (U.S. Route 1), New Haven, New Haven County, CT

  19. Detail of builder's plate at northeast end. Waterville Bridge, ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Detail of builder's plate at northeast end. - Waterville Bridge, Spanning Swatara Creek at Appalachian Trail (moved from Little Pine Creek at State Route 44, Waterville, Lycoming County), Green Point, Lebanon County, PA

  20. Words Analysis of Online Chinese News Headlines about Trending Events: A Complex Network Perspective

    PubMed Central

    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. PMID:25807376

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

    PubMed

    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. PMID:25807376

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

    NASA Astrophysics Data System (ADS)

    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

  3. Social network, presence of cardiovascular events and mortality in hypertensive patients.

    PubMed

    Menéndez-Villalva, C; Gamarra-Mondelo, M T; Alonso-Fachado, A; Naveira-Castelo, A; Montes-Martínez, A

    2015-07-01

    The aim of this study was to ascertain the relationship between social network and the appearance of mortality (cardiovascular events (CVEs)) in patients with arterial hypertension (AHT). This is a cohort study of 236 patients with a 9-year follow-up. Measurements included age, sex, blood pressure (BP), diabetes, hypercholesterolemia, marital status, social network, social support, stage of family life cycle (FLC), mortality and CVEs. Patients with a low social network registered higher global mortality (hazards ratio (HR) 2.6 (95% confidence interval (CI) 1.3; 5.5)) as did the oldest patients (HR 5.6 (1.9; 16.8)), men (HR 3.5 (95% CI 1.3; 9.3)) and subjects in the last FLC stages (HR 4.3 (95% CI 1.3;14.1)). Patients with low social support registered higher cardiovascular mortality (HR 2.6 (95% CI 1.1; 6.1)) as did the oldest patients (HR 12.4 (95% CI 2.8; 55.2)) and those with diabetes (HR 3.00 (95% CI 1.2; 7.6)). Patients with a low social network registered more CVEs (HR 2.1 (95% CI 1.1; 4.1)) than patients with an adequate network, as did the oldest patients (HR 3.1 (95% CI 1.4; 6.9)), subjects who presented with a higher grade of severity of AHT (HR 2.7 (1.3; 5.5)) and those in the last FLC stages (HR 2.5 (95% CI 1.0; 6.2)). A low social network is associated with mortality and the appearance of CVEs in patients with AHT. Low functional social support is associated with the appearance of cardiovascular mortality. PMID:25500900

  4. The Waveform Correlation Event Detection System project, Phase II: Testing with the IDC primary network

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Moore, S.G.

    1998-04-01

    Further improvements to the Waveform Correlation Event Detection System (WCEDS) developed by Sandia Laboratory have made it possible to test the system on the accepted Comprehensive Test Ban Treaty (CTBT) seismic monitoring network. For our test interval we selected a 24-hour period from December 1996, and chose to use the Reviewed Event Bulletin (REB) produced by the Prototype International Data Center (PIDC) as ground truth for evaluating the results. The network is heterogeneous, consisting of array and three-component sites, and as a result requires more flexible waveform processing algorithms than were available in the first version of the system. For simplicity and superior performance, we opted to use the spatial coherency algorithm of Wagner and Owens (1996) for both types of sites. Preliminary tests indicated that the existing version of WCEDS, which ignored directional information, could not achieve satisfactory detection or location performance for many of the smaller events in the REB, particularly those in the south Pacific where the network coverage is unusually sparse. To achieve an acceptable level of performance, we made modifications to include directional consistency checks for the correlations, making the regions of high correlation much less ambiguous. These checks require the production of continuous azimuth and slowness streams for each station, which is accomplished by means of FK processing for the arrays and power polarization processing for the three-component sites. In addition, we added the capability to use multiple frequency-banded data streams for each site to increase sensitivity to phases whose frequency content changes as a function of distance.

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

    NASA Astrophysics Data System (ADS)

    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.

  6. The Next Generation of NASA Night Sky Network: A Searchable Nationwide Database of Astronomy Events

    NASA Astrophysics Data System (ADS)

    Ames, Z.; Berendsen, M.; White, V.

    2010-08-01

    With support from NASA, the Astronomical Society of the Pacific (ASP) first developed the Night Sky Network (NSN) in 2004. The NSN was created in response to research conducted by the Institute for Learning Innovation (ILI) to determine what type of support amateur astronomers could use to increase the efficiency and extent of their educational outreach programs. Since its creation, the NSN has grown to include an online searchable database of toolkit resources, Presentation Skills Videos covering topics such as working with kids and how to answer difficult questions, and a searchable nationwide calendar of astronomy events that supports club organization. The features of the NSN have allowed the ASP to create a template that amateur science organizations might use to create a similar support network for their members and the public.

  7. HOS network-based classification of power quality events via regression algorithms

    NASA Astrophysics Data System (ADS)

    Palomares Salas, José Carlos; González de la Rosa, Juan José; Sierra Fernández, José María; Pérez, Agustín Agüera

    2015-12-01

    This work compares seven regression algorithms implemented in artificial neural networks (ANNs) supported by 14 power-quality features, which are based in higher-order statistics. Combining time and frequency domain estimators to deal with non-stationary measurement sequences, the final goal of the system is the implementation in the future smart grid to guarantee compatibility between all equipment connected. The principal results are based in spectral kurtosis measurements, which easily adapt to the impulsive nature of the power quality events. These results verify that the proposed technique is capable of offering interesting results for power quality (PQ) disturbance classification. The best results are obtained using radial basis networks, generalized regression, and multilayer perceptron, mainly due to the non-linear nature of data.

  8. Feedback between Accelerator Physicists and magnet builders

    SciTech Connect

    Peggs, S.

    1995-12-31

    Our task is not to record history but to change it. (K. Marx (paraphrased)) How should Accelerator Physicists set magnet error specifications? In a crude social model, they place tolerance limits on undesirable nonlinearities and errors (higher order harmonics, component alignments, etc.). The Magnet Division then goes away for a suitably lengthy period of time, and comes back with a working magnet prototype that is reproduced in industry. A better solution is to set no specifications. Accelerator Physicists begin by evaluating expected values of harmonics, generated by the Magnet Division, before and during prototype construction. Damaging harmonics are traded off against innocuous harmonics as the prototype design evolves, lagging one generation behind the evolution of expected harmonics. Finally, the real harmonics are quickly evaluated during early industrial production, allowing a final round of performance trade-offs, using contingency scenarios prepared earlier. This solution assumes a close relationship and rapid feedback between the Accelerator Physicists and the magnet builders. What follows is one perspective of the way that rapid feedback was used to `change history` (improve linear and dynamic aperture) at RHIC, to great benefit.

  9. The Real Time Display Builder (RTDB)

    NASA Technical Reports Server (NTRS)

    Kindred, Erick D.; Bailey, Samuel A., Jr.

    1989-01-01

    The Real Time Display Builder (RTDB) is a prototype interactive graphics tool that builds logic-driven displays. These displays reflect current system status, implement fault detection algorithms in real time, and incorporate the operational knowledge of experienced flight controllers. RTDB utilizes an object-oriented approach that integrates the display symbols with the underlying operational logic. This approach allows the user to specify the screen layout and the driving logic as the display is being built. RTDB is being developed under UNIX in C utilizing the MASSCOMP graphics environment with appropriate functional separation to ease portability to other graphics environments. RTDB grew from the need to develop customized real-time data-driven Space Shuttle systems displays. One display, using initial functionality of the tool, was operational during the orbit phase of STS-26 Discovery. RTDB is being used to produce subsequent displays for the Real Time Data System project currently under development within the Mission Operations Directorate at NASA/JSC. The features of the tool, its current state of development, and its applications are discussed.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. How events determine spreading patterns: information transmission via internal and external influences on social networks

    NASA Astrophysics Data System (ADS)

    Liu, Chuang; Zhan, Xiu-Xiu; Zhang, Zi-Ke; Sun, Gui-Quan; Hui, Pak Ming

    2015-11-01

    Recently, information transmission models motivated by the classical epidemic propagation, have been applied to a wide-range of social systems, generally assume that information mainly transmits among individuals via peer-to-peer interactions on social networks. In this paper, we consider one more approach for users to get information: the out-of-social-network influence. Empirical analyzes of eight typical events’ diffusion on a very large micro-blogging system, Sina Weibo, show that the external influence has significant impact on information spreading along with social activities. In addition, we propose a theoretical model to interpret the spreading process via both internal and external channels, considering three essential properties: (i) memory effect; (ii) role of spreaders; and (iii) non-redundancy of contacts. Experimental and mathematical results indicate that the information indeed spreads much quicker and broader with mutual effects of the internal and external influences. More importantly, the present model reveals that the event characteristic would highly determine the essential spreading patterns once the network structure is established. The results may shed some light on the in-depth understanding of the underlying dynamics of information transmission on real social networks.

  12. Adaptive Routing Protocol with Energy Efficiency and Event Clustering for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Tran Quang, Vinh; Miyoshi, Takumi

    Wireless sensor network (WSN) is a promising approach for a variety of applications. Routing protocol for WSNs is very challenging because it should be simple, scalable, energy-efficient, and robust to deal with a very large number of nodes, and also self-configurable to node failures and changes of the network topology dynamically. Recently, many researchers have focused on developing hierarchical protocols for WSNs. However, most protocols in the literatures cannot scale well to large sensor networks and difficult to apply in the real applications. In this paper, we propose a novel adaptive routing protocol for WSNs called ARPEES. The main design features of the proposed method are: energy efficiency, dynamic event clustering, and multi-hop relay considering the trade-off relationship between the residual energy available of relay nodes and distance from the relay node to the base station. With a distributed and light overhead traffic approach, we spread energy consumption required for aggregating data and relaying them to different sensor nodes to prolong the lifetime of the whole network. In this method, we consider energy and distance as the parameters in the proposed function to select relay nodes and finally select the optimal path among cluster heads, relay nodes and the base station. The simulation results show that our routing protocol achieves better performance than other previous routing protocols.

  13. Characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts

    NASA Astrophysics Data System (ADS)

    Chen, Siyue; Leung, Henry; Dondo, Maxwell

    2014-05-01

    As computer network security threats increase, many organizations implement multiple Network Intrusion Detection Systems (NIDS) to maximize the likelihood of intrusion detection and provide a comprehensive understanding of intrusion activities. However, NIDS trigger a massive number of alerts on a daily basis. This can be overwhelming for computer network security analysts since it is a slow and tedious process to manually analyse each alert produced. Thus, automated and intelligent clustering of alerts is important to reveal the structural correlation of events by grouping alerts with common features. As the nature of computer network attacks, and therefore alerts, is not known in advance, unsupervised alert clustering is a promising approach to achieve this goal. We propose a joint optimization technique for feature selection and clustering to aggregate similar alerts and to reduce the number of alerts that analysts have to handle individually. More precisely, each identified feature is assigned a binary value, which reflects the feature's saliency. This value is treated as a hidden variable and incorporated into a likelihood function for clustering. Since computing the optimal solution of the likelihood function directly is analytically intractable, we use the Expectation-Maximisation (EM) algorithm to iteratively update the hidden variable and use it to maximize the expected likelihood. Our empirical results, using a labelled Defense Advanced Research Projects Agency (DARPA) 2000 reference dataset, show that the proposed method gives better results than the EM clustering without feature selection in terms of the clustering accuracy.

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

    NASA Technical Reports Server (NTRS)

    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.

  15. Cluster synchronization of complex networks via event-triggered strategy under stochastic sampling

    NASA Astrophysics Data System (ADS)

    Hu, Aihua; Cao, Jinde; Hu, Manfeng; Guo, Liuxiao

    2015-09-01

    This paper is concerned with the issue of mean square cluster synchronization of non-identical nodes connected by a directed network. Suppose that the nodes possess nonlinear dynamics and split into several clusters, then an event-triggered control scheme is proposed for synchronization based on the information from stochastic sampling. Meanwhile, an equilibrium is considered to be the synchronization state or the virtual leader for each cluster, which can apply pinning control to the following nodes. Assume that a spanning tree exists in the subgraph consisting of the nodes belonging to the same cluster and the corresponding virtual leader, and the instants for updating controllers are determined by the given event-triggered strategy, then some sufficient conditions for cluster synchronization are presented according to the Lyapunov stability theory and linear matrix inequality technique. Finally, a specific numerical example is shown to demonstrate the effectiveness of the theoretical results.

  16. Event-train restoration via backpropagation neural networks. Interim report, January-July 1989

    SciTech Connect

    Raeth, P.G.

    1989-12-01

    This project is investigating backpropagation neural networks for specific applications in passive electronic warfare involving restoration of deinterleaved event trains to their original broadcast form. This is different from traditional bit-error detection/correction which relies on a prior knowledge of what the original bit stream looked liked. In electronic warfare it is unlikely that such prior knowledge will be available. Results of this research can be applied to 3 major problem areas: (1) pulse-train restoration, (2) communications signal compression, and (3) data compression.

  17. An event-based neural network architecture with an asynchronous programmable synaptic memory.

    PubMed

    Moradi, Saber; Indiveri, Giacomo

    2014-02-01

    We present a hybrid analog/digital very large scale integration (VLSI) implementation of a spiking neural network with programmable synaptic weights. The synaptic weight values are stored in an asynchronous Static Random Access Memory (SRAM) module, which is interfaced to a fast current-mode event-driven DAC for producing synaptic currents with the appropriate amplitude values. These currents are further integrated by current-mode integrator synapses to produce biophysically realistic temporal dynamics. The synapse output currents are then integrated by compact and efficient integrate and fire silicon neuron circuits with spike-frequency adaptation and adjustable refractory period and spike-reset voltage settings. The fabricated chip comprises a total of 32 × 32 SRAM cells, 4 × 32 synapse circuits and 32 × 1 silicon neurons. It acts as a transceiver, receiving asynchronous events in input, performing neural computation with hybrid analog/digital circuits on the input spikes, and eventually producing digital asynchronous events in output. Input, output, and synaptic weight values are transmitted to/from the chip using a common communication protocol based on the Address Event Representation (AER). Using this representation it is possible to interface the device to a workstation or a micro-controller and explore the effect of different types of Spike-Timing Dependent Plasticity (STDP) learning algorithms for updating the synaptic weights values in the SRAM module. We present experimental results demonstrating the correct operation of all the circuits present on the chip. PMID:24681923

  18. How activation, entanglement, and searching a semantic network contribute to event memory.

    PubMed

    Nelson, Douglas L; Kitto, Kirsty; Galea, David; McEvoy, Cathy L; Bruza, Peter D

    2013-08-01

    Free-association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long-lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist-cuing, primed free-association, intralist-cuing, and single-item recognition tasks. The findings also show that when a related word is presented in order to cue the recall of a studied word, the cue activates the target in an array of related words that distract and reduce the probability of the target's selection. The activation of the semantic network produces priming benefits during encoding, and search costs during retrieval. In extralist cuing, recall is a negative function of cue-to-distractor strength, and a positive function of neighborhood density, cue-to-target strength, and target-to-cue strength. We show how these four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks, indicating that the contribution of the semantic network varies with the context provided by the task. Finally, we evaluate spreading-activation and quantum-like entanglement explanations for the priming effects produced by neighborhood density. PMID:23645391

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

    NASA Technical Reports Server (NTRS)

    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.

  20. Building Air Monitoring Networks

    ERIC Educational Resources Information Center

    Environmental Science and Technology, 1977

    1977-01-01

    The different components of air monitoring networks, the status of air monitoring in the United States, and the services and activities of the three major American network builders are detailed. International air monitoring networks and alert systems are identified, with emphasis on the Dutch air monitoring network. (BT)

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

    PubMed

    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. PMID:23097678

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

    PubMed Central

    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. PMID:23097678

  3. EVENT84 user's manual: a computer code for analyzing explosion-induced gas-dynamic transients in flow networks

    SciTech Connect

    Martin, R.A.; Wilson, T.L.

    1984-12-01

    This manual supports the computer code EVENT84, which can predict explosion-induced gas-dynamic transients in flow networks. The code can model transients in any arbitrarily designated network of building rooms and ventilation systems. A lumped-parameter formulation is used. EVENT84 was designed to provide a safety analysis tool for he nuclear, chemical, and mining industries. It is particularly suitable for calculating the detailed effects of explosions in the far field using a parametric representation of the explosive event. The code input and a sample problem that illustrates its capabilities are provided.

  4. Statistical Patterns of Triggered Landslide Events and their Application to Road Networks

    NASA Astrophysics Data System (ADS)

    Taylor, Faith E.; Malamud, Bruce D.; Santangelo, Michele; Marchesini, Ivan; Guzzetti, Fausto

    2015-04-01

    In the minutes to weeks after a landslide trigger such as an earthquake or heavy rainfall, as part of a triggered landslide event, one individual to tens of thousands of landslides may occur across a region. If in the region, one or more roads become blocked by landslides, this can cause extensive detours and delay rescue and recovery operations. In this paper, we show the development, application and confrontation with real data of a model to simulate triggered landslide events and their impacts upon road networks. This is done by creating a 'synthetic' triggered landslide event inventory by randomly sampling landslide areas and shapes from already established statistical distributions. These landslides are then semi-randomly dropped across a given study region, conditioned by that region's landslide susceptibility. The resulting synthetic triggered landslide event inventory is overlaid with the region's road network map and the number, size, location and network impact of road blockages and landslides near roads calculated. This process is repeated hundreds of times in a Monte Carlo type simulation. The statistical distributions and approaches used in the model are thought to be generally applicable for low-mobility triggered landslides in many medium to high-topography regions throughout the world. The only local data required to run the model are a road network map, a landslide susceptibility map, a map of the study area boundary and a digital elevation model. Coupled with an Open Source modelling approach (in GRASS-GIS), this model may be applied to many regions where triggered landslide events are an issue. We present model results and confrontation with observed data for two study regions where the model has been applied: Collazzone (Central Italy) where rapid snowmelt triggered 413 landslides in January 1997 and Oat Mountain (Northridge, USA), where the Northridge Earthquake triggered 1,356 landslides in January 1994. We find that when the landslide

  5. Impacts of the January 2014 extreme rainfall event on transportation network in the Alps Maritimes (France)

    NASA Astrophysics Data System (ADS)

    Voumard, Jeremie; Penna, Ivanna; Jaboyedoff, Michel; Derron, Marc-Henri

    2014-05-01

    Road networks in mountain areas are highly inter-dependent systems, and hillslope processes such as landslides are main drivers of infrastructure detriment and transportation disruptions. Besides the structural damages, economic losses are also related to road and surrounding slope maintenance, as well as due to the disruption of transportation of goods, inaccessibility of tourist resorts, etc. 16-17th January 2014, an intense rainfall event was recorded in the Alpes Maritimes from the southern part of France. According to meteorological data, it was the highest since the 70's. This rainfall triggered numerous landslides (rockfalls, earth flows and debris flows), mostly on January 17th. There were no casualties registered due to hillslope processes, but several houses were damaged, some populations living in the Var valley along the RM 2205 road were isolated, and several roads were partially and totally blocked. 1.5 km upstream the village of Saint-Sauveur-sur-Tinée, 150 m3 of rock detached from the slope and blocked the road, after which temporary traffic interruptions due to road works lasted around one week. In the Menton area, where hillslopes are highly urbanized, the volume of rocks involved in slope failures was so large that materials removed to reestablish the traffic had to be placed in transitory storage sites. The average landslide volume was estimated at around 100 m3. Most of the landslides occurred in slopes cut during road and houses constructions. Several trucks were needed to clean up materials, giving place to traffic jams, etc. (some single events reached around 400 m3). The aim of this study is to document the impact on transportation networks caused by this rainfall event. Damages and consequences for the traffic were documented during a field visit, obtained from secondary information, as well as by the aid of a drone in the case of inaccessible areas.

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

    PubMed Central

    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

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

    NASA Technical Reports Server (NTRS)

    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.

  8. A polar cap absorption event observed using the Southern Hemisphere SuperDARN radar network.

    NASA Astrophysics Data System (ADS)

    Breed, A.; Morris, R.; Parkinson, M.; Duldig, M.; Dyson, P.

    A large X5 class solar flare and coronal mass ejection were observed emanating from the sun on July 14, 2000. Approximately 10 minutes later a large cosmic ray ground level enhancement was observed using neutron monitors located at Mawson station (70.5°S CGM), Antarctica; Large increases in proton flux were also observed using satellites during this time. This marked the start of a large polar cap absorption event with cosmic noise absorption peaking at 30 dB, as measured by a 30 MHz riometer located at Casey station (80.4°S CGM), Antarctica. The spatial evolution of this event and its subsequent recovery were studied using the Southern Hemisphere SuperDARN radar network, including the relatively low latitude observation provided by the Tasman International Geospace Environment Radar (TIGER) located on Bruny Island (54.6°S GGM), Tasmania. When the bulk of the CME arrived at the Earth two days later it triggered an intense geomagnetic storm. This paper presents observations of the dramatic sequence of events.

  9. Diet Segregation between Cohabiting Builder and Inquiline Termite Species

    PubMed Central

    Florencio, Daniela Faria; Marins, Alessandra; Rosa, Cassiano Sousa; Cristaldo, Paulo Fellipe; Araújo, Ana Paula Albano; Silva, Ivo Ribeiro; DeSouza, Og

    2013-01-01

    How do termite inquilines manage to cohabit termitaria along with the termite builder species? With this in mind, we analysed one of the several strategies that inquilines could use to circumvent conflicts with their hosts, namely, the use of distinct diets. We inspected overlapping patterns for the diets of several cohabiting Neotropical termite species, as inferred from carbon and nitrogen isotopic signatures for termite individuals. Cohabitant communities from distinct termitaria presented overlapping diet spaces, indicating that they exploited similar diets at the regional scale. When such communities were split into their components, full diet segregation could be observed between builders and inquilines, at regional (environment-wide) and local (termitarium) scales. Additionally, diet segregation among inquilines themselves was also observed in the vast majority of inspected termitaria. Inquiline species distribution among termitaria was not random. Environmental-wide diet similarity, coupled with local diet segregation and deterministic inquiline distribution, could denounce interactions for feeding resources. However, inquilines and builders not sharing the same termitarium, and thus not subject to potential conflicts, still exhibited distinct diets. Moreover, the areas of the builder’s diet space and that of its inquilines did not correlate negatively. Accordingly, the diet areas of builders which hosted inquilines were in average as large as the areas of builders hosting no inquilines. Such results indicate the possibility that dietary partitioning by these cohabiting termites was not majorly driven by current interactive constraints. Rather, it seems to be a result of traits previously fixed in the evolutionary past of cohabitants. PMID:23805229

  10. EEG-based event detection using optimized echo state networks with leaky integrator neurons.

    PubMed

    Ayyagari, Sudhanshu S D P; Jones, Richard D; Weddell, Stephen J

    2014-01-01

    This study investigates the classification ability of linear and nonlinear classifiers on biological signals using the electroencephalogram (EEG) and examines the impact of architectural changes within the classifier in order to enhance the classification. Consequently, artificial events were used to validate a prototype EEG-based microsleep detection system based around an echo state network (ESN) and a linear discriminant analysis (LDA) classifier. The artificial events comprised infrequent 2-s long bursts of 15 Hz sinusoids superimposed on prerecorded 16-channel EEG data which provided a means of determining and optimizing the accuracy of overall classifier on `gold standard' events. The performance of this system was tested on different signal-to-noise amplitude ratios (SNRs) ranging from 16 down to 0.03. Results from several feature selection/reduction and pattern classification modules indicated that training the classifier using a leaky-integrator neuron ESN structure yielded highest classification accuracy. For datasets with a low SNR of 0.3, training the leaky-neuron ESN using only those features which directly correspond to the underlying event, resulted in a phi correlation of 0.92 compared to 0.37 that employed principal component analysis (PCA). On the same datasets, other classifiers such as LDA and simple ESNs using PCA performed weakly with a correlation of 0.05 and 0 respectively. These results suggest that ESNs with leaky neuron architectures have superior pattern recognition properties. This, in turn, may reflect their superior ability to exploit differences in state dynamics and, hence, provide superior temporal characteristics in learning. PMID:25571328

  11. Muon physics and neural network event classifier for the Sudbury Neutrino Observatory

    NASA Astrophysics Data System (ADS)

    Chon, Myung Chol

    1998-12-01

    The Sudbury Neutrino Observatory (SNO) has been designed principally to study solar neutrinos and other sources of neutrinos such as supernova neutrinos and atmospheric neutrinos. The SNO heavy water Cerenkov detector will be able to observe all three flavors of neutrinos and allow us to determine the probability of neutrino flavor oscillation. It is hoped that SNO will provide answers to the questions posed by the solar neutrino problem and the atmospheric neutrino anomaly. In order for the experiment to be successful, it is important to fully understand muon interactions. First, muons may produce an important source of background for solar neutrino detection. Secondly, the detection of high-energy atmospheric neutrinos depends on detection of muons produced by the neutrino interaction either inside the detector or in the material surrounding the detector. The processes induced by stopping muons and muon-nucleus interaction are of great importance in a water Cerenkov detector as they produce secondary particles. Muon capture and muon decay processes have been studied in detail. The routines describing theses processes have been implemented in the SNOMAN code to study the detector response. A model to describe muon-nucleus deep inelastic scattering is proposed. In particular, the attempts to parameterize the secondary hadron multiplicity due to deep inelastic scattering are made. In addition, the hadron transport code has been added to SNOMAN for the simulation of the secondary hadron transport and subsequent Cerenkov photon production. Full Monte Carlo simulation of muon transport down to the SNO detector depth has been performed to understand the kinematic properties of cosmic-ray muons entering the SNO detector. Based on the results of the simulations, a simplified method to generate muon flux deep underground has been developed. The usage of pattern recognition techniques with Artificial Neural Networks has been investigated for the event-type classification

  12. Complex networks identify spatial patterns of extreme rainfall events of the South American Monsoon System

    NASA Astrophysics Data System (ADS)

    Boers, Niklas; Bookhagen, Bodo; Marwan, Norbert; Kurths, Jürgen; Marengo, José

    2013-08-01

    We investigate the spatial characteristics of extreme rainfall synchronicity of the South American Monsoon System (SAMS) by means of Complex Networks (CN). By introducing a new combination of CN measures and interpreting it in a climatic context, we investigate climatic linkages and classify the spatial characteristics of extreme rainfall synchronicity. Although our approach is based on only one variable (rainfall), it reveals the most important features of the SAMS, such as the main moisture pathways, areas with frequent development of Mesoscale Convective Systems (MCS), and the major convergence zones. In addition, our results reveal substantial differences between the spatial structures of rainfall synchronicity above the 90th and above the 95th percentiles. Most notably, events above the 95th percentile contribute stronger to MCS in the La Plata Basin.

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

    PubMed Central

    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

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

    PubMed

    Hao, Xiaoqing; An, Haizhong; Zhang, Lijia; Li, Huajiao; Wei, Guannan

    2015-01-01

    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. PMID:26462230

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

    PubMed Central

    Hao, Xiaoqing; An, Haizhong; Zhang, Lijia; Li, Huajiao; Wei, Guannan

    2015-01-01

    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. PMID:26462230

  16. Collaborative-Comparison Learning for Complex Event Detection Using Distributed Hierarchical Graph Neuron (DHGN) Approach in Wireless Sensor Network

    NASA Astrophysics Data System (ADS)

    Muhamad Amin, Anang Hudaya; Khan, Asad I.

    Research trends in existing event detection schemes using Wireless Sensor Network (WSN) have mainly focused on routing and localisation of nodes for optimum coordination when retrieving sensory information. Efforts have also been put in place to create schemes that are able to provide learning mechanisms for event detection using classification or clustering approaches. These schemes entail substantial communication and computational overheads owing to the event-oblivious nature of data transmissions. In this paper, we present an event detection scheme that has the ability to distribute detection processes over the resource-constrained wireless sensor nodes and is suitable for events with spatio-temporal characteristics. We adopt a pattern recognition algorithm known as Distributed Hierarchical Graph Neuron (DHGN) with collaborative-comparison learning for detecting critical events in WSN. The scheme demonstrates good accuracy for binary classification and offers low-complexity and high-scalability in terms of its processing requirements.

  17. Building America Top Innovations 2012: Reduced Call-Backs with High-Performance Production Builders

    SciTech Connect

    none,

    2013-01-01

    This Building America Top Innovations profile describes ways Building America teams have helped builders cut call-backs. Harvard University study found builders who worked with Building America had a 50% drop in call-backs. One builder reported a 50-fold reduction in the incidence of pipe freezing, a 50% reduction in drywall cracking, and a 60% decline in call-backs.

  18. 78 FR 42122 - Bridge Builder Trust and Olive Street Investment Advisers, LLC; Notice of Application

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-07-15

    ... COMMISSION Bridge Builder Trust and Olive Street Investment Advisers, LLC; Notice of Application July 9, 2013... requirements. APPLICANTS: Bridge Builder Trust (the ``Trust'') and Olive Street Investment Advisers (the... currently intends to rely on the requested order as a Fund is the Bridge Builder Bond Fund. For purposes...

  19. Builder 1 & C: Naval Training Command Rate Training Manual. Revised 1973.

    ERIC Educational Resources Information Center

    Naval Training Command, Pensacola, FL.

    The training manual is designed to help Navy personnel meet the occupational qualifications for advancement to Builder First Class and Chief Builder. The introductory chapter provides information to aid personnel in their preparation for advancement and outlines the scope of the Builder rating and the types of billets to which he can be assigned.…

  20. Children's E-Book Technology: Devices, Books, and Book Builder

    ERIC Educational Resources Information Center

    Shiratuddin, Norshuhada; Landoni, Monica

    2003-01-01

    This article describes a study of children's electronic books (e-books) technology. In particular, the focus is on devices used to access children's e-books, current available e-books and an e-book builder specifically for children. Three small case studies were conducted: two to evaluate how children accept the devices and one to test the ease of…

  1. 4. DETAIL OF BUILDER'S PLATES: '1901, CARTER H. HARRISON, COMMISSIONER ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    4. DETAIL OF BUILDER'S PLATES: '1901, CARTER H. HARRISON, COMMISSIONER OF PUBLIC WORKS, MAYOR F.W. BLOCKI, JOHN ERICSON, CITY ENGINEER'; 'FITZSIMONS AND CONNELL CO. SUBSTRUCTURE'; 'AMERICAN BRIDGE COMPANY, LASSIG PLANT, CONTRACTOR FOR SUPERSTRUCTURE' - Chicago River Bascule Bridge, West Cortland Street, Spanning North Branch of Chicago River at West Cortland Street, Chicago, Cook County, IL

  2. E-Classical Fairy Tales: Multimedia Builder as a Tool

    ERIC Educational Resources Information Center

    Eteokleous, Nikleia; Ktoridou, Despo; Tsolakidis, Symeon

    2011-01-01

    The study examines pre-service teachers' experiences in delivering a traditional-classical fairy tale using the Multimedia Builder software, in other words an e-fairy tale. A case study approach was employed, collecting qualitative data through classroom observations and focus groups. The results focus on pre-service teachers' reactions, opinions,…

  3. 2. DETAIL OF BUILDER'S PLATE: 'SUPERSTRUCTURE BUILT BY STROBEL STEEL ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    2. DETAIL OF BUILDER'S PLATE: 'SUPERSTRUCTURE BUILT BY STROBEL STEEL CONSTRUCTION CO., CHICAGO, ILL., 1913, SUBSTRUCTURE BUILT BY FITZSIMONS & CONNELL D&D CO., CHICAGO, ILL.' - Chicago River Bascule Bridge, Grand Avenue, Spanning North Branch Chicago River at Grand Avenue, Chicago, Cook County, IL

  4. 5. DETAIL OF BUILDER'S PLATE, WHICH READS '1898, THE SANITARY ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    5. DETAIL OF BUILDER'S PLATE, WHICH READS '1898, THE SANITARY DISTRICT OF CHICAGO, BOARD OF TRUSTEES, WILLIAM BOLDENWECK, JOSEPH C. BRADEN, ZINA R. CARTER, BERNARD A. ECKART, ALEXANDER J. JONES, THOMAS KELLY, JAMES P. MALLETTE, THOMAS SMYTHE, FRANK WINTER; ISHAM RANDOLPH, CHIEF ENGINEER.' - Santa Fe Railroad, Sanitary & Ship Canal Bridge, Spanning Sanitary & Ship Canal east of Harlem Avenue, Chicago, Cook County, IL

  5. 4. DETAIL OF BUILDER'S PLATE WHICH READS 'BUILT 1906 BY ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    4. DETAIL OF BUILDER'S PLATE WHICH READS 'BUILT 1906 BY THE CHICAGO AND ALTON RY. CO.; G.H. KIMBALL CHIEF ENGINEER; W.M. HUGHES CONSULTING ENG'R; PAGE & SHNABLE PATENTEES' - Chicago & Alton Railroad Bridge, Spanning South Branch of Chicago River, Chicago, Cook County, IL

  6. New Whole-House Solutions Case Study: Pine Mountain Builders

    SciTech Connect

    none,

    2013-02-01

    Pine Mountain Builders achieved HERS scores as low as 59 and electric bills as low as $50/month with extensive air sealing (blower door tests = 1.0 to 1.8 ACH 50), R-3 XPS sheathing instead of OSB, and higher efficiency heat pumps.

  7. 10. DETAIL OF BUILDER'S PLATE AT NORTH PORTAL. PLATE READS: ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    10. DETAIL OF BUILDER'S PLATE AT NORTH PORTAL. PLATE READS: 1889, BUILT BY THE BERLIN IRON BRIDGE CO. EAST BERLIN CONN. DOUGLAS & JARVIS PAT. APT. 16, 1878, AP'L 17, 1885. A.P. FORESMAN, WM. S. STARR, T.J. STREBEIGH, COMMISSIONERS. - Pine Creek Bridge, River Road spanning Pine Creek, Jersey Shore, Lycoming County, PA

  8. Polyol and Amino Acid-Based Biosurfactants, Builders, and Hydrogels

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This chapter reviews different detergent materials which have been synthesized from natural agricultural commodities. Background information, which gives reasons why the use of biobased materials may be advantageous, is presented. Detergent builders from L-aspartic acid, citric acid and D-sorbitol...

  9. SDMProjectBuilder: SWAT Setup for Nutrient Fate and Transport

    EPA Science Inventory

    This tutorial reviews some of the screens, icons, and basic functions of the SDMProjectBuilder (SDMPB) and explains how one uses SDMPB output to populate the Soil and Water Assessment Tool (SWAT) input files for nutrient fate and transport modeling in the Salt River Basin. It dem...

  10. Marketing and promoting solar water heaters to home builders

    SciTech Connect

    Keller, C.; Ghent, P.

    1999-12-06

    This is the final report of a four-task project to develop a marketing plan designed for businesses interested in marketing solar water heaters in the new home industry. This report outlines suggested marketing communication materials and other promotional tools focused on selling products to the new home builder. Information relevant to promoting products to the new home buyer is also included.

  11. Mining induced seismic event on an inactive fault in view of local surface and in mine underground networksS

    NASA Astrophysics Data System (ADS)

    Rudzinski, Lukasz; Lizurek, Grzegorz; Plesiewicz, Beata

    2014-05-01

    On 19th March 2013 tremor shook the surface of Polkowice town were "Rudna" mine is located. This event of ML=4.2 was third most powerful seismic event recorded in Legnica Głogów Copper District (LGCD). Citizens of the area reported that felt tremors were bigger and last longer than any other ones felt in last couple years. The event was studied with use of two different networks: underground network of "Rudna" mine and surface local network run by IGF PAS (LUMINEOS network). The first one is composed of 32 vertical seismometers at mining level, except 5 sensors placed in elevator shafts, seismometers location depth varies from 300 down to 1000 meters below surface. The seismometers used in this network are vertical short period Willmore MkII and MkIII sensors, with the frequency band from 1Hz to 100Hz. At the beginning of 2013th the local surface network of the Institute of Geophysics Polish Academy of Sciences (IGF PAS) with acronym LUMINEOS was installed under agreement with KGHM SA and "Rudna" mine officials. This network at the moment of the March 19th 2013 event was composed of 4 short-period one-second triaxial seismometers LE-3D/1s manufactured by Lenartz Electronics. Analysis of spectral parameters of the records from in mine seismic system and surface LUMINEOS network along with broadband station KSP record were carried out. Location of the event was close to the Rudna Główna fault zone, the nodal planes orientations determined with two different approaches were almost parallel to the strike of the fault. The mechanism solutions were also obtained in form of Full Moment Tensor inversion from P wave amplitude pulses of underground records and waveform inversion of surface network seismograms. Final results of the seismic analysis along with macroseismic survey and observed effects from the destroyed part of the mining panel indicate that the mechanism of the event was thrust faulting on inactive tectonic fault. The results confirm that the fault zones

  12. FormBuilder/FBGraphics programmer`s reference manual

    SciTech Connect

    Goetsch, J.A.

    1994-09-01

    A primary concern in most modern software applications is the development of an attractive, ``friendly`` Graphical User Interface (GUI). Increasingly, that concern is being met through the use of the OSF/Motif widget set. While this software toolset is extremely powerful, the vast knowledge and attention to detail required by the programmer tend to be nearly unmanageable. This translates into an extended learning curve and a large investment of time and effort before the programmer reaches a desirable level of productivity. Even then, developing anything but the most basic GUI often proves to be a tedious and costly undertaking. FormBuilder is an application programmers interface (API) that provides the programmer with a high-level interface to a subset of the ``X`` Window System and the OSF/Motif widget set. Through the use of the FormBuilder data types and procedure calls, the GUI programmer is afforded several distinct advantages over coding directly at the Motif, Xt, and Xlib layers. Among these advantages are a substantially reduced learning curve, more readable/maintainable/modifiable code, smaller, more efficient binaries, and reduced compile/link/debug time during development. Working in concert with the FormBuilder library is the FBGraphics library, a 2-dimensional graphics library that allows the programmer to perform graphical operations within certain FormBuilder ``windows``. The FBGraphics library is based on the Xlib drawing routines, and much like FormBuilder, its purpose is to provide the programmers with a simpler, more productive mechanism for producing the desired graphical output on the screen.

  13. Real-time Monitoring Network to Characterize Anthropogenic and Natural Events Affecting the Hudson River, NY

    NASA Astrophysics Data System (ADS)

    Islam, M. S.; Bonner, J. S.; Fuller, C.; Kirkey, W.; Ojo, T.

    2011-12-01

    The Hudson River watershed spans 34,700 km2 predominantly in New York State, including agricultural, wilderness, and urban areas. The Hudson River supports many activities including shipping, supplies water for municipal, commercial, and agricultural uses, and is an important recreational resource. As the population increases within this watershed, so does the anthropogenic impact on this natural system. To address the impacts of anthropogenic and natural activities on this ecosystem, the River and Estuary Observatory Network (REON) is being developed through a joint venture between the Beacon Institute, Clarkson University, General Electric Inc. and IBM Inc. to monitor New York's Hudson and Mohawk Rivers in real-time. REON uses four sensor platform types with multiple nodes within the network to capture environmentally relevant episodic events. Sensor platform types include: 1) fixed robotic vertical profiler (FRVP); 2) mobile robotic undulating platform (MRUP); 3) fixed acoustic Doppler current profiler (FADCP) and 4) Autonomous Underwater Vehicle (AUV). The FRVP periodically generates a vertical profile with respect to water temperature, salinity, dissolved oxygen, particle concentration and size distribution, and fluorescence. The MRUP utilizes an undulating tow-body tethered behind a research vessel to measure the same set of water parameters as the FRVP, but does so 'synchronically' over a highly-resolved spatial regime. The fixed ADCP provides continuous water current profiles. The AUV maps four-dimensional (time, latitude, longitude, depth) variation of water quality, water currents and bathymetry along a pre-determined transect route. REON data can be used to identify episodic events, both anthropogenic and natural, that impact the Hudson River. For example, a strong heat signature associated with cooling water discharge from the Indian Point nuclear power plant was detected with the MRUP. The FRVP monitoring platform at Beacon, NY, located in the

  14. Application of Parallel Discrete Event Simulation to the Space Surveillance Network

    NASA Astrophysics Data System (ADS)

    Jefferson, D.; Leek, J.

    2010-09-01

    In this paper we describe how and why we chose parallel discrete event simulation (PDES) as the paradigm for modeling the Space Surveillance Network (SSN) in our modeling framework, TESSA (Testbed Environment for Space Situational Awareness). DES is a simulation paradigm appropriate for systems dominated by discontinuous state changes at times that must be calculated dynamically. It is used primarily for complex man-made systems like telecommunications, vehicular traffic, computer networks, economic models etc., although it is also useful for natural systems that are not described by equations, such as particle systems, population dynamics, epidemics, and combat models. It is much less well known than simple time-stepped simulation methods, but has the great advantage of being time scale independent, so that one can freely mix processes that operate at time scales over many orders of magnitude with no runtime performance penalty. In simulating the SSN we model in some detail: (a) the orbital dynamics of up to 105 objects, (b) their reflective properties, (c) the ground- and space-based sensor systems in the SSN, (d) the recognition of orbiting objects and determination of their orbits, (e) the cueing and scheduling of sensor observations, (f) the 3-d structure of satellites, and (g) the generation of collision debris. TESSA is thus a mixed continuous-discrete model. But because many different types of discrete objects are involved with such a wide variation in time scale (milliseconds for collisions, hours for orbital periods) it is suitably described using discrete events. The PDES paradigm is surprising and unusual. In any instantaneous runtime snapshot some parts my be far ahead in simulation time while others lag behind, yet the required causal relationships are always maintained and synchronized correctly, exactly as if the simulation were executed sequentially. The TESSA simulator is custom-built, conservatively synchronized, and designed to scale to

  15. Simulation and Performance evaluation of ZigBee for wireless sensor networks having multiple events occurring simultaneously at a time

    NASA Astrophysics Data System (ADS)

    Dhama, Nitin; Minal, Kaur, Prabhjot; Kumar, Neelu

    2010-11-01

    ZigBee is an emerging standard for Wireless Sensor Networks (WSNs). It targets low distance, low data rate, low power consumption and low cost applications. According to standard nomenclature, it implements a Low Rate-Wireless Personal Area Network (LR-WPAN). ZigBee defines upper layers (network and application) of the ISO protocol reference model. On the contrary, in regards to the physical and data link ones, it relies over another standard, the well accepted IEEE802.15.4, which offers a gross transfer rate of 250 kbps in the 2.4 GHz ISM unlicensed band. Although ZigBee is designed for event-based applications, ZigBee is designed as a low-cost, low-power, low-data rate wireless mesh technology. There are many wireless sensor networks in which it is required to send information to the pan coordinator continuously and simultaneously. Our purpose here in this paper is to test zigbee for such kind of networks where multiple events take place simultaneously. Also we want to see the effect of increasing the number of events in a scenario, so that we can find out its effect.

  16. Molecular Insights into Reprogramming-Initiation Events Mediated by the OSKM Gene Regulatory Network

    PubMed Central

    Liao, Mei-Chih; Prigione, Alessandro; Jozefczuk, Justyna; Lichtner, Björn; Wolfrum, Katharina; Haltmeier, Manuela; Flöttmann, Max; Schaefer, Martin; Hahn, Alexander; Mrowka, Ralf; Klipp, Edda; Andrade-Navarro, Miguel A.; Adjaye, James

    2011-01-01

    Somatic cells can be reprogrammed to induced pluripotent stem cells by over-expression of OCT4, SOX2, KLF4 and c-MYC (OSKM). With the aim of unveiling the early mechanisms underlying the induction of pluripotency, we have analyzed transcriptional profiles at 24, 48 and 72 hours post-transduction of OSKM into human foreskin fibroblasts. Experiments confirmed that upon viral transduction, the immediate response is innate immunity, which induces free radical generation, oxidative DNA damage, p53 activation, senescence, and apoptosis, ultimately leading to a reduction in the reprogramming efficiency. Conversely, nucleofection of OSKM plasmids does not elicit the same cellular stress, suggesting viral response as an early reprogramming roadblock. Additional initiation events include the activation of surface markers associated with pluripotency and the suppression of epithelial-to-mesenchymal transition. Furthermore, reconstruction of an OSKM interaction network highlights intermediate path nodes as candidates for improvement intervention. Overall, the results suggest three strategies to improve reprogramming efficiency employing: 1) anti-inflammatory modulation of innate immune response, 2) pre-selection of cells expressing pluripotency-associated surface antigens, 3) activation of specific interaction paths that amplify the pluripotency signal. PMID:21909390

  17. Adaptive Multi-Path Routing with Guaranteed Target-Delivery Ratio of Critical Events in Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Baek, Jang Woon; Nam, Young Jin; Seo, Dae-Wha

    Wireless sensor networks are subject to node and link failures for a variety of reasons. This paper proposes a k-disjoint-path routing algorithm that varies the number of disjoint paths (k) in order to meet a target-delivery ratio of critical events and to reduce energy consumption. The proposed algorithm sends packets to the base station through a single path without the occurrence of critical events, however, it sends packets to the base station through k disjoint paths (k > 1) under the occurrence of critical events, where k is computed from a well-defined fault model. The proposed algorithm detects the occurrence of critical events by monitoring collected data patterns. The simulation results reveal that the proposed algorithm is more resilient to random node failure and patterned failure than other routing algorithms, and it also decreases energy consumption much more than the multi-path and path-repair algorithms.

  18. Best Practices Case Study: Pine Mountain Builders - Pine Mountain, GA

    SciTech Connect

    2011-09-01

    Case study of Pine Mountain Builders who worked with DOE’s IBACOS team to achieve HERS scores of 59 on 140 homes built around a wetlands in Georgia. The team used taped rigid foam exterior sheathing and spray foam insulation in the walls and on the underside of the attic for a very tight 1.0 to 1.8 ACH 50 building shell.

  19. HOT METAL BRIDGE (NOTE: BUILDERS: JONES AND LAUGHLIN STEEL CA. ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    HOT METAL BRIDGE (NOTE: BUILDERS: JONES AND LAUGHLIN STEEL CA. 1890), SOUTH PORTAL. THREE PIN CONNECTED CAMELBACK TRUSS SPANS, ONE SKEWED THROUGH TRUSS SPAN ON NORTH SIDE TRUSS BRIDGE, EAST OF HOT METAL BRIDGE BUILT BY AMERICAN BRIDGE COMPANY CA. 1910. (RIVETED MULTI-SPAN TRUSS). - Jones & Laughlin Steel Corporation, Pittsburgh Works, Morgan Billet Mill Engine, 550 feet north of East Carson Street, opposite South Twenty-seventh Street, Pittsburgh, Allegheny County, PA

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  1. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations.

    PubMed

    Wu, Emilia L; Cheng, Xi; Jo, Sunhwan; Rui, Huan; Song, Kevin C; Dávila-Contreras, Eder M; Qi, Yifei; Lee, Jumin; Monje-Galvan, Viviana; Venable, Richard M; Klauda, Jeffery B; Im, Wonpil

    2014-10-15

    CHARMM-GUI Membrane Builder, http://www.charmm-gui.org/input/membrane, is a web-based user interface designed to interactively build all-atom protein/membrane or membrane-only systems for molecular dynamics simulations through an automated optimized process. In this work, we describe the new features and major improvements in Membrane Builder that allow users to robustly build realistic biological membrane systems, including (1) addition of new lipid types, such as phosphoinositides, cardiolipin (CL), sphingolipids, bacterial lipids, and ergosterol, yielding more than 180 lipid types, (2) enhanced building procedure for lipid packing around protein, (3) reliable algorithm to detect lipid tail penetration to ring structures and protein surface, (4) distance-based algorithm for faster initial ion displacement, (5) CHARMM inputs for P21 image transformation, and (6) NAMD equilibration and production inputs. The robustness of these new features is illustrated by building and simulating a membrane model of the polar and septal regions of E. coli membrane, which contains five lipid types: CL lipids with two types of acyl chains and phosphatidylethanolamine lipids with three types of acyl chains. It is our hope that CHARMM-GUI Membrane Builder becomes a useful tool for simulation studies to better understand the structure and dynamics of proteins and lipids in realistic biological membrane environments. PMID:25130509

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

    NASA Astrophysics Data System (ADS)

    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 (a more distributed gauge network) will produce interpolation errors by reduced resolution of the precipitation field and 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

  3. Prediction of the most extreme rainfall events in the South American Andes: A statistical forecast based on complex networks

    NASA Astrophysics Data System (ADS)

    Boers, Niklas; Bookhagen, Bodo; Barbosa, Henrique; Marwan, Norbert; Kurths, Jürgen; Marengo, Jose

    2015-04-01

    During the monsoon season, the subtropical Andes in South America are exposed to spatially extensive extreme rainfall events that frequently lead to flashfloods and landslides with severe socio-economic impacts. Since dynamical weather forecast has substantial problems with predicting the most extreme events (above the 99th percentile), alternative forecast methods are called for. Based on complex network theory, we developed a general mathematical framework for statistical prediction of extreme events in significantly interrelated time series. The key idea of our approach is to make the internal synchronization structure of extreme events mathematically accessible in terms of the topology of a network which is constructed from measuring the synchronization of extreme events at different locations. The application of our method to high-spatiotemporal resolution rainfall data (TRMM 3B42) reveals a migration pattern of large convective systems from southeastern South America towards the Argentinean and Bolivian Andes, against the direction of the northwesterly low-level moisture flow from the Amazon Basin. Once these systems reach the Andes, they lead to spatially extensive extreme events up to elevations above 4000m, leading to substantial risks of associated natural hazards. Based on atmospheric composites, we could identify an intricate interplay of frontal systems approaching from the South, low-level moisture flow from the Amazon Basin to the North, and the Andean orography as responsible climatic mechanism. These insights allow to formulate a simple forecast rule predicting 60% (90% during El Niño conditions) of extreme rainfall events at the eastern slopes of the subtropical Andes. The rule can be computed from readily available rainfall and pressure data and is already being tested by local institutions for disaster preparation.

  4. Development of an event search and download system for analyzing waveform data observed at seafloor seismic network, DONET

    NASA Astrophysics Data System (ADS)

    Takaesu, M.; Horikawa, H.; Sueki, K.; Kamiya, S.; Nakamura, T.; Nakano, M.; Takahashi, N.; Sonoda, A.; Tsuboi, S.

    2014-12-01

    Mega-thrust earthquakes are anticipated to occur in the Nankai Trough in southwest Japan. In the source areas, we installed seafloor seismic network, DONET (Dense Ocean-floor Network System for Earthquake and Tsunamis), in 2010 in order to monitor seismicity, crustal deformations, and tsunamis. DONET system consists of totally 20 stations, which is composed of six kinds of sensors; strong-motion and broadband seismometers, quartz and differential pressure gauges, hydrophone, and thermometer. The stations are densely distributed with an average spatial interval of 15-20 km and cover near coastal areas to the trench axis. Observed data are transferred to a land station through a fiber-optical cable and then to JAMSTEC (Japan Agency for Marine-Earth Science and Technology) data management center through a private network in real time. The data are based on WIN32 format in the private network and finally archived in SEED format in the management center to combine waveform data with related metadata. We are developing a web-based application system to easily download seismic waveform data of DONET. In this system, users can select 20 Hz broadband (BH type) and 200 Hz strong-motion (EH type) data and download them in SEED. Users can also search events from the options of time periods, magnitude, source area and depth in a GUI platform. Event data are produced referring to event catalogues from USGS and JMA (Japan Meteorological Agency). The thresholds of magnitudes for the production are M6 for far-field and M4 for local events using the USGS and JMA lists, respectively. Available data lengths depend on magnitudes and epicentral distances. In this presentation, we briefly introduce DONET stations and then show our developed application system. We open DONET data through the system and want them to be widely recognized so that many users analyze. We also discuss next plans for further developments of the system.

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

    SciTech Connect

    AllamehZadeh, Mostafa

    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.

  6. Adaptive and context-aware detection and classification of potential QoS degradation events in biomedical wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Abreu, Carlos; Miranda, Francisco; Mendes, Paulo M.

    2016-06-01

    The use of wireless sensor networks in healthcare has the potential to enhance the services provided to citizens. In particular, they play an important role in the development of state-of-the-art patient monitoring applications. Nevertheless, due to the critical nature of the data conveyed by such patient monitoring applications, they have to fulfil high standards of quality of service in order to obtain the confidence of all players in the healthcare industry. In such context, vis-à-vis the quality of service being provided by the wireless sensor network, this work presents an adaptive and context-aware method to detect and classify performance degradation events. The proposed method has the ability to catch the most significant and damaging variations on the metrics being used to quantify the quality of service provided by the network without overreacting to small and innocuous variations on the metric's value.

  7. Evaluation of the U.S. Department of Energy Challenge Home Program Certification of Production Builders

    SciTech Connect

    Kerrigan, P.; Loomis, H.

    2014-09-01

    The purpose of this project was to evaluate integrated packages of advanced measures in individual test homes to assess their performance with respect to Building America Program goals, specifically compliance with the DOE Challenge Home Program. BSC consulted on the construction of five test houses by three Cold Climate production builders in three separate US cities. BSC worked with the builders to develop a design package tailored to the cost-related impacts for each builder. Therefore, the resulting design packages do vary from builder to builder. BSC provided support through this research project on the design, construction and performance testing of the five test homes. Overall, the builders have concluded that the energy related upgrades (either through the prescriptive or performance path) represent reasonable upgrades. The builders commented that while not every improvement in specification was cost effective (as in a reasonable payback period), many were improvements that could improve the marketability of the homes and serve to attract more energy efficiency discerning prospective homeowners. However, the builders did express reservations on the associated checklists and added certifications. An increase in administrative time was observed with all builders. The checklists and certifications also inherently increase cost due to: 1. Adding services to the scope of work for various trades, such as HERS Rater, HVAC contractor; 2. Increased material costs related to the checklists, especially the EPA Indoor airPLUS and EPA WaterSense(R) Efficient Hot Water Distribution requirement.

  8. What would you do? Managing a metro network during mass crowd events.

    PubMed

    Barr, Andy C; Lau, Raymond C M; Ng, Nelson W H; da Silva, Marco Antônio; Baptista, Marcia; Oliveira, Vinícius Floriano; Barbosa, Maria Beatriz; Batistini, Estela; de Toledo Ramos, Nancy

    2010-03-01

    Major public events, such as sporting events, carnivals and festivals, are common occurrences in urban and city environments. They are characterised by the mass movement of people in relatively small areas, far in excess of normal daily activity. This section reviews how different metro systems across the globe respond to such peaks of activity, ensuring that people are moved swiftly, efficiently and safely. To this end, representatives from four major public metro systems (London, Hong Kong, Rio de Janeiro and São Paulo) describe how their respective metro systems respond to the capacity demands of a major annual event. PMID:20494882

  9. Detecting and mitigating abnormal events in large scale networks: budget constrained placement on smart grids

    SciTech Connect

    Santhi, Nandakishore; Pan, Feng

    2010-10-19

    Several scenarios exist in the modern interconnected world which call for an efficient network interdiction algorithm. Applications are varied, including various monitoring and load shedding applications on large smart energy grids, computer network security, preventing the spread of Internet worms and malware, policing international smuggling networks, and controlling the spread of diseases. In this paper we consider some natural network optimization questions related to the budget constrained interdiction problem over general graphs, specifically focusing on the sensor/switch placement problem for large-scale energy grids. Many of these questions turn out to be computationally hard to tackle. We present a particular form of the interdiction question which is practically relevant and which we show as computationally tractable. A polynomial-time algorithm will be presented for solving this problem.

  10. Whole-House Approach Benefits Builders, Buyers, and the Environment

    SciTech Connect

    Not Available

    2001-05-01

    This document provides an overview of the U.S. Department of Energy's Building America program. Building America works with the residential building industry to develop and implement innovative building processes and technologies-innovations that save builders and homeowners millions of dollars in construction and energy costs. This industry-led, cost-shared partnership program aims to reduce energy use by 50% and reduce construction time and waste, improve indoor air quality and comfort, encourage a systems engineering approach for design and construction of new homes, and accelerate the development and adoption of high performance in production housing.

  11. Complex network analysis of high rainfall events during the northeast monsoon over south peninsular India and Sri Lanka

    NASA Astrophysics Data System (ADS)

    Martin, P.; Malik, N.; Marwan, N.; Kurths, J.

    2012-04-01

    The Indian Summer monsoon (ISM) accounts for a large part of the annual rainfall budget across most of the Indian peninsula; however, the coastal regions along the southeast Indian peninsula, as well as Sri Lanka, receive 50% or more of their annual rainfall budget during the northeast monsoon (NEM), or winter monsoon, during the months from October through December. In this study, we investigate the behavior of the NEM over the last 60 years using complex network theory. The network is constructed according to a method previously developed for the ISM, using event synchronization of extreme rainfall events as a correlation measure to create directed and undirected links between geographical locations, which represent potential pathways of moisture transport. Network measures, such as degree centrality and closeness centrality, are then used to illuminate the dynamics of the NEM rainfall over the relevant regions, and to examine the spatial distribution and temporal evolution of the rainfall. Understanding the circulation of the monsoon cycle as a whole, i.e. the NEM together with the ISM, is vital for the agricultural industry and thus the population of the affected areas.

  12. Co-design of H∞ jump observers for event-based measurements over networks

    NASA Astrophysics Data System (ADS)

    Peñarrocha, Ignacio; Dolz, Daniel; Romero, Julio Ariel; Sanchis, Roberto

    2016-01-01

    This work presents a strategy to minimise the network usage and the energy consumption of wireless battery-powered sensors in the observer problem over networks. The sensor nodes implement a periodic send-on-delta approach, sending new measurements when a measure deviates considerably from the previous sent one. The estimator node implements a jump observer whose gains are computed offline and depend on the combination of available new measurements. We bound the estimator performance as a function of the sending policies and then state the design procedure of the observer under fixed sending thresholds as a semidefinite programming problem. We address this problem first in a deterministic way and, to reduce conservativeness, in a stochastic one after obtaining bounds on the probabilities of having new measurements and applying robust optimisation problem over the possible probabilities using sum of squares decomposition. We relate the network usage with the sending thresholds and propose an iterative procedure for the design of those thresholds, minimising the network usage while guaranteeing a prescribed estimation performance. Simulation results and experimental analysis show the validity of the proposal and the reduction of network resources that can be achieved with the stochastic approach.

  13. Storm Event Variability in Particulate Organic Matter Source, Size, and Carbon and Nitrogen Content Along a Forested Drainage Network

    NASA Astrophysics Data System (ADS)

    Rowland, R. D.; Inamdar, S. P.; Parr, T. B.

    2015-12-01

    Coupled inputs of carbon and nitrogen comprise an important energy and nutrient subsidy for aquatic ecosystems. Large storm events can mobilize substantial amounts of these elements, especially in particulate form. While the role of storms in mobilizing allochthonous particulate organic matter (POM) is well recognized, less is known about the changes in source, particle size, and composition of POM as it is routed through the fluvial network. Questions we addressed include- (a) How does source, size, and C and N content of suspended POM vary with storm magnitude and intensity? (b) How does POM size and C and N content evolve along the drainage network? (c) How accurate are high-frequency, in-situ sensors in characterizing POM? We conducted this study in a 79 ha, forested catchment in the Piedmont region of Maryland. Event sampling for suspended POM was performed using automated stream water samplers and in-situ, high-frequency sensors (s::can specto::lyser and YSI EXO 2; 30 minute intervals) at 12 and 79 ha drainage locations. Composite storm-event sediment samples were also collected using passive samplers at five catchment drainage scales. Data is available for multiple storms since August 2014. Samples were partitioned into three discrete particle size classes (coarse: 1000-2000 µm, medium: 250-1000 µm, fine: < 250 µm) for organic C and N determination. Suspended sediments and seven soil end members were also analyzed for stable 13C and 15N isotopes ratios to characterize the evolution in sediment sources through the drainage network. Contrary to our expectations, preliminary results suggest finer suspended sediments in the upstream portion of the catchment, and that these may contain more POM. Unsurprisingly, sensors' ability to estimate the coarser particle classes via turbidity are weak compared to the finer class, but this is less pronounced in organic-rich sediments. Distinct patterns in in-situ absorbance spectra may suggest an ability to discern

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

  15. A pair of RNA binding proteins controls networks of splicing events contributing to specialization of neural cell types

    PubMed Central

    Norris, Adam D.; Gao, Shangbang; Norris, Megan L.; Ray, Debashish; Ramani, Arun K.; Fraser, Andrew G.; Morris, Quaid; Hughes, Timothy R.; Zhen, Mei; Calarco, John A.

    2014-01-01

    SUMMARY Alternative splicing is important for the development and function of the nervous system, but little is known about the differences in alternative splicing between distinct types of neurons. Furthermore, the factors that control cell-type-specific splicing and the physiological roles of these alternative isoforms are unclear. By monitoring alternative splicing at single cell resolution in Caenorhabditis elegans, we demonstrate that splicing patterns in different neurons are often distinct and highly regulated. We identify two conserved RNA binding proteins, UNC-75/CELF and EXC-7/Hu/ELAV, which regulate overlapping networks of splicing events in GABAergic and cholinergic neurons. We use the UNC-75 exon network to discover regulators of synaptic transmission and to identify unique roles for isoforms of UNC-64/Syntaxin, a protein required for synaptic vesicle fusion. Our results indicate that combinatorial regulation of alternative splicing in distinct neurons provides a mechanism to specialize metazoan nervous systems. PMID:24910101

  16. Reward and Novelty Enhance Imagination of Future Events in a Motivational-Episodic Network

    PubMed Central

    Bulganin, Lisa; Wittmann, Bianca C.

    2015-01-01

    Thinking about personal future events is a fundamental cognitive process that helps us make choices in daily life. We investigated how the imagination of episodic future events is influenced by implicit motivational factors known to guide decision making. In a two-day functional magnetic resonance imaging (fMRI) study, we controlled learned reward association and stimulus novelty by pre-familiarizing participants with two sets of words in a reward learning task. Words were repeatedly presented and consistently followed by monetary reward or no monetary outcome. One day later, participants imagined personal future events based on previously rewarded, unrewarded and novel words. Reward association enhanced the perceived vividness of the imagined scenes. Reward and novelty-based construction of future events were associated with higher activation of the motivational system (striatum and substantia nigra/ ventral tegmental area) and hippocampus, and functional connectivity between these areas increased during imagination of events based on reward-associated and novel words. These data indicate that implicit past motivational experience contributes to our expectation of what the future holds in store. PMID:26599537

  17. Time-to-event analysis with artificial neural networks: an integrated analytical and rule-based study for breast cancer.

    PubMed

    Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Hane Aung, M S; Chabaud, Sylvie; Bachelot, Thomas; Perol, David; Gargi, Thérèse; Bourdès, Valérie; Bonnevay, Stéphane; Négrier, Sylvie

    2008-01-01

    This paper presents an analysis of censored survival data for breast cancer specific mortality and disease-free survival. There are three stages to the process, namely time-to-event modelling, risk stratification by predicted outcome and model interpretation using rule extraction. Model selection was carried out using the benchmark linear model, Cox regression but risk staging was derived with Cox regression and with Partial Logistic Regression Artificial Neural Networks regularised with Automatic Relevance Determination (PLANN-ARD). This analysis compares the two approaches showing the benefit of using the neural network framework especially for patients at high risk. The neural network model also has results in a smooth model of the hazard without the need for limiting assumptions of proportionality. The model predictions were verified using out-of-sample testing with the mortality model also compared with two other prognostic models called TNG and the NPI rule model. Further verification was carried out by comparing marginal estimates of the predicted and actual cumulative hazards. It was also observed that doctors seem to treat mortality and disease-free models as equivalent, so a further analysis was performed to observe if this was the case. The analysis was extended with automatic rule generation using Orthogonal Search Rule Extraction (OSRE). This methodology translates analytical risk scores into the language of the clinical domain, enabling direct validation of the operation of the Cox or neural network model. This paper extends the existing OSRE methodology to data sets that include continuous-valued variables. PMID:18304780

  18. Assessing the Influence of an Individual Event in Complex Fault Spreading Network Based on Dynamic Uncertain Causality Graph.

    PubMed

    Dong, Chunling; Zhao, Yue; Zhang, Qin

    2016-08-01

    Identifying the pivotal causes and highly influential spreaders in fault propagation processes is crucial for improving the maintenance decision making for complex systems under abnormal and emergency situations. A dynamic uncertain causality graph-based method is introduced in this paper to explicitly model the uncertain causalities among system components, identify fault conditions, locate the fault origins, and predict the spreading tendency by means of probabilistic reasoning. A new algorithm is proposed to assess the impacts of an individual event by investigating the corresponding node's time-variant betweenness centrality and the strength of global causal influence in the fault propagation network. The algorithm does not depend on the whole original and static network but on the real-time spreading behaviors and dynamics, which makes the algorithm to be specifically targeted and more efficient. Experiments on both simulated networks and real-world systems demonstrate the accuracy, effectiveness, and comprehensibility of the proposed method for the fault management of power grids and other complex networked systems. PMID:27101619

  19. Solar installer training: Home Builders Institute Job Corps

    SciTech Connect

    Hansen, K.; Mann, R.

    1996-10-01

    The instructors describe the solar installation training program operated since 1979 by the Home Builders Institute, the Educational Arm of the National Association of Home Builders for the US Department of Labor, Job Corps in San Diego, CA. The authors are the original instructors and have developed the program since its inception by a co-operative effort between the Solar Energy Industries Association, NAHB and US DOL. Case studies of a few of the 605 students who have gone to work over the years after the training are included. It is one of the most successful programs under the elaborate Student Performance Monitoring Information System used by all Job Corps programs. Job Corps is a federally funded residential job training program for low income persons 16--24 years of age. Discussion details the curriculum and methods used in the program including classroom, shop and community service projects. Solar technologies including all types of hot water heating, swimming pool and spa as well as photovoltaics are included.

  20. DOE Zero Energy Ready Home Case Study: New Town Builders, Denver, Colorado

    SciTech Connect

    none,

    2013-09-01

    All homes in the Stapleton community must be ENERGY STAR certified; New Town Builders has announced that it will build 250–300 new homes over the next 7–10 years, all of which will be Challenge Homes. New Town received a 2013 Housing Innovation Award in the production builder category.

  1. Practices and Processes of Leading High Performance Home Builders in the Upper Midwest

    SciTech Connect

    Von Thoma, E.; Ojczyk, C.

    2012-12-01

    The NorthernSTAR Building America Partnership team proposed this study to gain insight into the business, sales, and construction processes of successful high performance builders. The knowledge gained by understanding the high performance strategies used by individual builders, as well as the process each followed to move from traditional builder to high performance builder, will be beneficial in proposing more in-depth research to yield specific action items to assist the industry at large transform to high performance new home construction. This investigation identified the best practices of three successful high performance builders in the upper Midwest. In-depth field analysis of the performance levels of their homes, their business models, and their strategies for market acceptance were explored. All three builders commonly seek ENERGY STAR certification on their homes and implement strategies that would allow them to meet the requirements for the Building America Builders Challenge program. Their desire for continuous improvement, willingness to seek outside assistance, and ambition to be leaders in their field are common themes. Problem solving to overcome challenges was accepted as part of doing business. It was concluded that crossing the gap from code-based building to high performance based building was a natural evolution for these leading builders.

  2. Evaluation of the Bridge Builders Program: Students Involved in Multicultural Activities.

    ERIC Educational Resources Information Center

    Petry, John R.; McCree, Herbert L.

    Bridge Builders is a 2-year program intended to develop leadership in high school students. Programmatic goals include enhancing the participants' understanding of other racial and ethnic groups, socioeconomic groups, gender awareness, social responsibility, and the value of community service. Bridge Builders participants confronted community…

  3. Wildlife Scenario Builder and User's Guide (Version 1.0, Beta Test)

    EPA Science Inventory

    Cover of the Wildlife Scenario <span class=Builder User's Manual" vspace = "5" hspace="5" align="right" border="1" /> The Wildlife Scenario Builder (WSB) was developed to improve the quality of wildlif...

  4. Aeolian dust event in Korea observed by an EZ Lidar in the frame of global lidar networks.

    NASA Astrophysics Data System (ADS)

    Lolli, Simone

    2010-05-01

    Duststorms and sandstorms regularly devastate Northeast Asia and cause considerable damage to transportation system and public health; further, these events are conceived to be one of the very important indices for estimating the global warming and desertification. Previously, yellow sand events were considered natural phenomena that originate in deserts and arid areas. However, the greater scale and frequency of these events in recent years are considered to be the result of human activities such as overgrazing and over-cultivation. Japan, Korea, Cina and Mongolia are directly concerned to prevent and control these storms and have been able to some extent to provide forecasts and early warnings. In this framework, to improve the accuracy of forecasting , a compact and rugged eye safe lidar, the EZ LIDAR™, developed together by Laboratoire des Sciences du Climat et l'Environnement (LSCE) (CEA-CNRS) and LEOSPHERE (France) to study and investigate structural and optical properties of clouds and aerosols, thanks to the strong know-how of CEA and CNRS in the field of air quality measurements and cloud observation and analysis, was deployed in Seoul, Korea in order to detect and study yellow sand events, thanks to its depolarization channel and scan capabilities. The preliminary results, showed in this paper, of this measurement campaign put in evidence that EZ Lidar, for its capabilities of operating unattended day and night under each atmospheric condition, is mature to be deployed in a global network to study long-range transport, crucial in the forecasting model.

  5. Establishing relationships with Artificial Neural Networks between geopotential height patterns and heavy rainfall events

    NASA Astrophysics Data System (ADS)

    Michaelides, Silas; Tymvios, Filippos

    2010-05-01

    Dynamically induced rainfall is strongly connected with synoptic atmospheric circulation patterns at the upper levels. This study investigates the relationship between days of high precipitation volume events in the eastern Mediterranean and the associated geopotential height patterns at 500hPa. To reduce the number of different patterns and to simplify the statistical processing, the input days were classified into clusters of synoptic cases having similar characteristics, by utilizing Kohonen' Self Organizing Maps (SOM) architecture. Using this architecture, synoptic patterns were grouped into 9, 18, 27 and 36 clusters which were subsequently used in the analysis. The classification performance was tested by applying the method to extreme rainfall events in the eastern Mediterranean. The relationship of the synoptic upper air patterns (500hPa geopotential height) and surface features (heavy rainfall events) was established. The 36 member classification was proven to be the most efficient system.

  6. Characterization and Analysis of Networked Array of Sensors for Event Detection (CANARY-EDS)

    Energy Science and Technology Software Center (ESTSC)

    2011-05-27

    CANARY -EDS provides probabilistic event detection based on analysis of time-series data from water quality or other sensors. CANARY also can compare patterns against a library of previously seen data to indicate that a certain pattern has reoccurred, suppressing what would otherwise be considered an event. CANARY can be configured to analyze previously recorded data from files or databases, or it can be configured to run in real-time mode directory from a database, or throughmore » the US EPA EDDIES software.« less

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

    ERIC Educational Resources Information Center

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

    2013-01-01

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

  8. Age differences in the Attention Network Test: Evidence from behavior and event-related potentials.

    PubMed

    Williams, Ryan S; Biel, Anna Lena; Wegier, Pete; Lapp, Leann K; Dyson, Benjamin J; Spaniol, Julia

    2016-02-01

    The Attention Network Test (ANT) is widely used to capture group and individual differences in selective attention. Prior behavioral studies with younger and older adults have yielded mixed findings with respect to age differences in three putative attention networks (alerting, orienting, and executive control). To overcome the limitations of behavioral data, the current study combined behavioral and electrophysiological measures. Twenty-four healthy younger adults (aged 18-29years) and 24 healthy older adults (aged 60-76years) completed the ANT while EEG data were recorded. Behaviorally, older adults showed reduced alerting, but did not differ from younger adults in orienting or executive control. Electrophysiological components related to alerting and orienting (P1, N1, and CNV) were similar in both age groups, whereas components related to executive control (N2 and P3) showed age-related differences. Together these results suggest that comparisons of network effects between age groups using behavioral data alone may not offer a complete picture of age differences in selective attention, especially for alerting and executive control networks. PMID:26760449

  9. Building America Case Study: New Town Builders' Power of Zero Energy Center, Denver, Colorado (Brochure)

    SciTech Connect

    Not Available

    2014-10-01

    New Town Builders, a builder of energy efficient homes in Denver, Colorado, offers a zero energy option for all the homes it builds. To attract a wide range of potential homebuyers to its energy efficient homes, New Town Builders created a 'Power of Zero Energy Center' linked to its model home in the Stapleton community of Denver. This case study presents New Town Builders' marketing approach, which is targeted to appeal to homebuyers' emotions rather than overwhelming homebuyers with scientific details about the technology. The exhibits in the Power of Zero Energy Center focus on reduced energy expenses for the homeowner, improved occupant comfort, the reputation of the builder, and the lack of sacrificing the homebuyers' desired design features to achieve zero net energy in the home. The case study also contains customer and realtor testimonials related to the effectiveness of the Center in influencing homebuyers to purchase a zero energy home.

  10. Practices and Processes of Leading High Performance Home Builders in the Upper Midwest

    SciTech Connect

    Von Thoma, Ed; Ojzcyk, Cindy

    2012-12-01

    The NorthernSTAR Building America Partnership team proposed this study to gain insight into the business, sales, and construction processes of successful high performance builders. The knowledge gained by understanding the high performance strategies used by individual builders, as well as the process each followed to move from traditional builder to high performance builder, will be beneficial in proposing more in-depth research to yield specific action items to assist the industry at large transform to high performance new home construction. This investigation identified the best practices of three successful high performance builders in the upper Midwest. In-depth field analysis of the performance levels of their homes, their business models, and their strategies for market acceptance were explored.

  11. DEVELOPMENT, EVALUATION AND APPLICATION OF AN AUTOMATED EVENT PRECIPITATION SAMPLER FOR NETWORK OPERATION

    EPA Science Inventory

    In 1993, the University of Michigan Air Quality Laboratory (UMAQL) designed a new wet-only precipitation collection system that was utilized in the Lake Michigan Loading Study. The collection system was designed to collect discrete mercury and trace element samples on an event b...

  12. Event-Related fMRI of Category Learning: Differences in Classification and Feedback Networks

    ERIC Educational Resources Information Center

    Little, Deborah M.; Shin, Silvia S.; Sisco, Shannon M.; Thulborn, Keith R.

    2006-01-01

    Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification…

  13. 46 CFR 308.409 - Standard form of War Risk Builder's Risk Insurance Policy, Form MA-283.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Standard form of War Risk Builder's Risk Insurance... TRANSPORTATION EMERGENCY OPERATIONS WAR RISK INSURANCE War Risk Builder's Risk Insurance § 308.409 Standard form of War Risk Builder's Risk Insurance Policy, Form MA-283. The standard form of War Risk...

  14. Systematic observations of long-range transport events and climatological backscatter profiles with the DWD ceilometer network

    NASA Astrophysics Data System (ADS)

    Mattis, Ina; Müller, Gerhard; Wagner, Frank; Hervo, Maxime

    2015-04-01

    The German Meteorological Service (DWD) operates a network of about 60 CHM15K-Nimbus ceilometers for cloud base height observations. Those very powerful ceilometers allow for the detection and characterization of aerosol layers. Raw data of all network ceilometers are transferred online to DWD's data analysis center at the Hohenpeißenberg Meteorological Observatory. There, the occurrence of aerosol layers from long-range transport events in the free troposphere is systematically monitored on daily basis for each single station. If possible, the origin of the aerosol layers is determined manually from the analysis of the meteorological situation and model output. We use backward trajectories as well as the output of the MACC and DREAM models for the decision, whether the observed layer originated in the Sahara region, from forest fires in North America or from another, unknown source. Further, the magnitude of the observed layers is qualitatively estimated taking into account the geometrical layer depth, signal intensity, model output and nearby sun photometer or lidar observations (where available). All observed layers are attributed to one of the categories 'faint', 'weak', 'medium', 'strong', or 'extreme'. We started this kind of analysis in August 2013 and plan to continue this systematic documentation of long-range transport events of aerosol layers to Germany on long-term base in the framework of our GAW activities. Most of the observed aerosol layers have been advected from the Sahara region to Germany. In the 15 months between August 2013 and November 2014 we observed on average 46 days with Sahara dust layers per station, but only 16 days with aerosol layers from forest fires. The occurrence of Sahara dust layers vary with latitude. We observed only 28 dusty days in the north, close to the coasts of North Sea and Baltic Sea. In contrast, in southern Germany, in Bavarian Pre-Alps and in the Black Forest mountains, we observed up to 59 days with dust. At

  15. Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events

    PubMed Central

    2015-01-01

    Background Biomedical studies need assistance from automated tools and easily accessible data to address the problem of the rapidly accumulating literature. Text-mining tools and curated databases have been developed to address such needs and they can be applied to improve the understanding of molecular pathogenesis of complex diseases like thyroid cancer. Results We have developed a system, PWTEES, which extracts pathway interactions from the literature utilizing an existing event extraction tool (TEES) and pathway named entity recognition (PathNER). We then applied the system on a thyroid cancer corpus and systematically extracted molecular interactions involving either genes or pathways. With the extracted information, we constructed a molecular interaction network taking genes and pathways as nodes. Using curated pathway information and network topological analyses, we highlight key genes and pathways involved in thyroid carcinogenesis. Conclusions Mining events involving genes and pathways from the literature and integrating curated pathway knowledge can help improve the understanding of molecular interactions of complex diseases. The system developed for this study can be applied in studies other than thyroid cancer. The source code is freely available online at https://github.com/chengkun-wu/PWTEES. PMID:26679379

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

    PubMed

    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. PMID:26456181

  17. Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis

    PubMed Central

    2015-01-01

    Background Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems. In this paper, we describe our participation in the latest BioNLP Shared Task using the large-scale text mining resource EVEX. We participated in the Genia Event Extraction (GE) and Gene Regulation Network (GRN) tasks with two separate systems. In the GE task, we implemented a re-ranking approach to improve the precision of an existing event extraction system, incorporating features from the EVEX resource. In the GRN task, our system relied solely on the EVEX resource and utilized a rule-based conversion algorithm between the EVEX and GRN formats. Results In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge. In the GRN task, we ranked fifth in the official results with a strict/relaxed SER score of 0.92/0.81 respectively. To try and improve upon these results, we have implemented a novel machine learning based conversion system and benchmarked its performance against the original rule-based system. Conclusions For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates. In the GE task we

  18. Response control networks are selectively modulated by attention to rare events and memory load regardless of the need for inhibition.

    PubMed

    Wijeakumar, Sobanawartiny; Magnotta, Vincent A; Buss, Aaron T; Ambrose, Joseph P; Wifall, Timothy A; Hazeltine, Eliot; Spencer, John P

    2015-10-15

    Recent evidence has sparked debate about the neural bases of response selection and inhibition. In the current study, we employed two reactive inhibition tasks, the Go/Nogo (GnG) and Simon tasks, to examine questions central to these debates. First, we investigated whether a fronto-cortical-striatal system was sensitive to the need for inhibition per se or the presentation of infrequent stimuli, by manipulating the proportion of trials that do not require inhibition (Go/Compatible trials) relative to trials that require inhibition (Nogo/Incompatible trials). A cortico-subcortical network composed of insula, putamen, and thalamus showed greater activation on salient and infrequent events, regardless of the need for inhibition. Thus, consistent with recent findings, key parts of the fronto-cortical-striatal system are engaged by salient events and do not appear to play a selective role in response inhibition. Second, we examined how the fronto-cortical-striatal system is modulated by working memory demands by varying the number of stimulus-response (SR) mappings. Right inferior parietal lobule showed decreasing activation as the number of SR mappings increased, suggesting that a form of associative memory - rather than working memory - might underlie performance in these tasks. A broad motor planning and control network showed similar trends that were also modulated by the number of motor responses required in each task. Finally, bilateral lingual gyri were more robustly engaged in the Simon task, consistent with the role of this area in shifts of visuo-spatial attention. The current study sheds light on how the fronto-cortical-striatal network is selectively engaged in reactive control tasks and how control is modulated by manipulations of attention and memory load. PMID:26190403

  19. Differential Network Analyses of Alzheimer’s Disease Identify Early Events in Alzheimer’s Disease Pathology

    DOE PAGESBeta

    Xia, Jing; Rocke, David M.; Perry, George; Ray, Monika

    2014-01-01

    In late-onset Alzheimer’s disease (AD), multiple brain regions are not affected simultaneously. Comparing the gene expression of the affected regions to identify the differences in the biological processes perturbed can lead to greater insight into AD pathogenesis and early characteristics. We identified differentially expressed (DE) genes from single cell microarray data of four AD affected brain regions: entorhinal cortex (EC), hippocampus (HIP), posterior cingulate cortex (PCC), and middle temporal gyrus (MTG). We organized the DE genes in the four brain regions into region-specific gene coexpression networks. Differential neighborhood analyses in the coexpression networks were performed to identify genes with lowmore » topological overlap (TO) of their direct neighbors. The low TO genes were used to characterize the biological differences between two regions. Our analyses show that increased oxidative stress, along with alterations in lipid metabolism in neurons, may be some of the very early events occurring in AD pathology. Cellular defense mechanisms try to intervene but fail, finally resulting in AD pathology as the disease progresses. Furthermore, disease annotation of the low TO genes in two independent protein interaction networks has resulted in association between cancer, diabetes, renal diseases, and cardiovascular diseases.« less

  20. Network Systems Technician.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. Center on Education and Training for Employment.

    This publication contains 17 subjects appropriate for use in a competency list for the occupation of network systems technician, 1 of 12 occupations within the business/computer technologies cluster. Each unit consists of a number of competencies; a list of competency builders is provided for each competency. Titles of the 17 units are as follows:…

  1. Stochastic switching in gene networks can occur by a single-molecule event or many molecular steps.

    PubMed

    Choi, Paul J; Xie, X Sunney; Shakhnovich, Eugene I

    2010-02-12

    Due to regulatory feedback, biological networks can exist stably in multiple states, leading to heterogeneous phenotypes among genetically identical cells. Random fluctuations in protein numbers, tuned by specific molecular mechanisms, have been hypothesized to drive transitions between these different states. We develop a minimal theoretical framework to analyze the limits of switching in terms of simple experimental parameters. Our model identifies and distinguishes between two distinct molecular mechanisms for generating stochastic switches. In one class of switches, the stochasticity of a single-molecule event, a specific and rare molecular reaction, directly controls the macroscopic change in a cell's state. In the second class, no individual molecular event is significant, and stochasticity arises from the propagation of biochemical noise through many molecular pathways and steps. As an example, we explore switches based on protein-DNA binding fluctuations and predict relations between transcription factor kinetics, absolute switching rate, robustness, and efficiency that differentiate between switching by single-molecule events or many molecular steps. Finally, we apply our methods to recent experimental data on switching in Escherichia coli lactose metabolism, providing quantitative interpretations of a single-molecule switching mechanism. PMID:19931280

  2. Uncertainty of precipitation estimates in convective events by the Meteorological Service of Catalonia radar network

    NASA Astrophysics Data System (ADS)

    Trapero, Laura; Bech, Joan; Rigo, Tomeu; Pineda, Nicolau; Forcadell, David

    In order to quantify the uncertainty of the radar-derived surface point quantitative precipitation estimates (QPE) from a regional radar network, a comparison has been made with a network of rain gauges. Three C-band Doppler radars and 161 telemetered gauges have been used. Both networks cover the area of Catalonia (NE Spain). Hourly accumulations integrated in daily amounts are studied. For each radar, three different precipitation products are obtained: short range, long range, and short range corrected radar QPE. The corrected product is generated by the Hydrometeorological Integrated Forecasting Tool (EHIMI), a software package designed to correct radar observations in real time for its use in hydrometeorological applications. Among other features, EHIMI includes a topographical beam blockage correction procedure. The first part of the analysis examines the bias found in the radar. The three radars generally underestimate precipitation, an effect increased with range from the radar and beam blockage, which is examined in detail in this study. Moreover, corrected QPEs systematically improve the BIAS (2 dB) and RMSf for high blockages (50-70%). The second part of the analysis illustrates the temporal evolution of the daily mean bias. Finally, the uncertainty of each rain gauge has been compared to each rainfall radar product. Geographic distribution of daily BIAS is consistent with slight under-estimation at short range and substantial at long range, especially in the north of Catalonia, which is an area with important beam blockage (> 40%). These results contribute to improve the knowledge about the spatial distribution of the QPE error benefiting a number of applications including verification of high-resolution NWP precipitation forecasts and use of advanced hydrometeorological models.

  3. CONNJUR Workflow Builder: A software integration environment for spectral reconstruction

    PubMed Central

    Fenwick, Matthew; Weatherby, Gerard; Vyas, Jay; Sesanker, Colbert; Martyn, Timothy O.; Ellis, Heidi J.C.; Gryk, Michael R.

    2015-01-01

    CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses. PMID:26066803

  4. Space fabrication demonstration system. [beam builder and induction fastening

    NASA Technical Reports Server (NTRS)

    1980-01-01

    The development effort on the composite beam cap fabricator was completed within cost and close to abbreviated goals. The design and analysis of flight weight primary and secondary beam builder structures proceeded satisfactorily but remains curtailed until further funding is made available to complete the work. The induction fastening effort remains within cost and schedule constraints. Tests of the LARC prototype induction welder is continuing in an instrumented test stand comprised of a Dumore drill press (air over oil feed for variable applied loads) and a dynamometer to measure actual welding loads. Continued testing shows that the interface screening must be well impregnated with resin to ensure proper flow when bonding graphite-acrylic lap shear samples. Specimens prepared from 0.030 inch thick graphite-polyethersulfone are also available for future induction fastening evaluation.

  5. Using neural networks as an event trigger in elementary particle physics experiments

    SciTech Connect

    Neis, E.; Starr, F.W.; Handler, T.; Gabriel, T.; Glover, C.; Saini, S.

    1994-02-01

    Elementary particle physics experiments often have to deal with high data rates. In order to avoid having to write out all data that is occurring online processors, triggers, are used to cull out the uninteresting data. These triggers are based on some particular aspect of the physics being examined. At times these aspects are often equivalent to simple pattern recognition problems. The reliability of artificial neural networks(ANNs) in pattern recognition problems in many fields has been well demonstrated. We present here the results of a study on the feasibility of using ANNs as an online trigger for high energy physics experiments.

  6. Evaluation of the U.S. Department of Energy Challenge Home Program Certification of Production Builders

    SciTech Connect

    Kerrigan, P.; Loomis, H.

    2014-09-01

    The purpose of this project was to evaluate integrated packages of advanced measures in individual test homes to assess their performance with respect to Building America program goals, specifically compliance with the DOE Challenge Home Program. BSC consulted on the construction of five test houses by three cold climate production builders in three U.S. cities and worked with the builders to develop a design package tailored to the cost-related impacts for each builder. Also, BSC provided support through performance testing of the five test homes. Overall, the builders have concluded that the energy related upgrades (either through the prescriptive or performance path) represent reasonable upgrades. The builders commented that while not every improvement in specification was cost effective (as in a reasonable payback period), many were improvements that could improve the marketability of the homes and serve to attract more energy efficiency discerning prospective homeowners. However, the builders did express reservations on the associated checklists and added certifications. An increase in administrative time was observed with all builders. The checklists and certifications also inherently increase cost due to: adding services to the scope of work for various trades, such as HERS Rater, HVAC contractor; and increased material costs related to the checklists, especially the EPA Indoor airPLUS and EPA WaterSense® Efficient Hot Water Distribution requirement.

  7. Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks.

    PubMed

    Acir, Nurettin; Oztura, Ibrahim; Kuntalp, Mehmet; Baklan, Bariş; Güzeliş, Cüneyt

    2005-01-01

    This paper introduces a three-stage procedure based on artificial neural networks for the automatic detection of epileptiform events (EVs) in a multichannel electroencephalogram (EEG) signal. In the first stage, two discrete perceptrons fed by six features are used to classify EEG peaks into three subgroups: 1) definite epileptiform transients (ETs); 2) definite non-ETs; and 3) possible ETs and possible non-ETs. The pre-classification done in the first stage not only reduces the computation time but also increases the overall detection performance of the procedure. In the second stage, the peaks falling into the third group are aimed to be separated from each other by a nonlinear artificial neural network that would function as a postclassifier whose input is a vector of 41 consecutive sample values obtained from each peak. Different networks, i.e., a backpropagation multilayer perceptron and two radial basis function networks trained by a hybrid method and a support vector method, respectively, are constructed as the postclassifier and then compared in terms of their classification performances. In the third stage, multichannel information is integrated into the system for contributing to the process of identifying an EV by the electroencephalographers (EEGers). After the integration of multichannel information, the overall performance of the system is determined with respect to EVs. Visual evaluation, by two EEGers, of 19 channel EEG records of 10 epileptic patients showed that the best performance is obtained with a radial basis support vector machine providing an average sensitivity of 89.1%, an average selectivity of 85.9%, and a false detection rate (per hour) of 7.5. PMID:15651562

  8. CTBT infrasound network performance to detect the 2013 Russian fireball event

    NASA Astrophysics Data System (ADS)

    Pilger, Christoph; Ceranna, Lars; Ross, J. Ole; Le Pichon, Alexis; Mialle, Pierrick; Garcés, Milton A.

    2015-04-01

    The explosive fragmentation of the 2013 Chelyabinsk meteorite generated a large airburst with an equivalent yield of 500 kT TNT. It is the most energetic event recorded by the infrasound component of the Comprehensive Nuclear-Test-Ban Treaty-International Monitoring System (CTBT-IMS), globally detected by 20 out of 42 operational stations. This study performs a station-by-station estimation of the IMS detection capability to explain infrasound detections and nondetections from short to long distances, using the Chelyabinsk meteorite as global reference event. Investigated parameters influencing the detection capability are the directivity of the line source signal, the ducting of acoustic energy, and the individual noise conditions at each station. Findings include a clear detection preference for stations perpendicular to the meteorite trajectory, even over large distances. Only a weak influence of stratospheric ducting is observed for this low-frequency case. Furthermore, a strong dependence on the diurnal variability of background noise levels at each station is observed, favoring nocturnal detections.

  9. PAnnBuilder: an R package for assembling proteomic annotation data.

    PubMed

    Li, Hong; Ding, Guohui; Xie, Lu; Li, Yixue

    2009-04-15

    PAnnBuilder is an R package to automatically assemble protein annotation information from public resources to provide uniform annotation data for large-scale proteomic studies. Sixteen public databases have been parsed and 54 annotation packages have been constructed based on R environment or SQLite database. These ready-to-use packages cover most frequently needed protein annotation for three model species including human, mouse and rat. Several extended applications such as annotation based on protein sequence similarity are also provided. Sophisticated users can develop their own packages using PAnnBuilder. PAnnBuilder may become an important tool for proteomic research. PMID:19237448

  10. Design of simulation builder software to support the enterprise modeling and simulation task of the AMTEX program

    SciTech Connect

    Nolan, M.; Lamont, A.; Chang, L.

    1995-12-12

    This document describes the implementation of the Simulation Builder developed as part of the Enterprise Modeling and Simulation (EM&S) portion of the Demand Activated Manufacturing Architecture (DAMA) project. The Simulation Builder software allows users to develop simulation models using pre-defined modules from a library. The Simulation Builder provides the machinery to allow the modules to link together and communicate information during the simulation run. This report describes the basic capabilities and structure of the Simulation Builder to assist a user in reviewing and using the code. It also describes the basic steps to follow when developing modules to take advantage of the capabilities provided by the Simulation Builder. The Simulation Builder software is written in C++. The discussion in this report assumes a sound understanding of the C++ language. Although this report describes the steps to follow when using the Simulation Builder, it is not intended to be a tutorial for a user unfamiliar with C++.